Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate 9811539766, 9789811539763
This book presents the proceedings of CRIOCM2018, 23rd International Symposium on Advancement of Construction Management
120 61 112MB
English Pages 1418 [1416] Year 2021
Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate
Editorial Board
Acknowledgements
Conference Organizer
Co-organizers
Advisory Committee (In Alphabetical Order by Last Name)
Organizing Committee
Chairman
Executive Chairman
Secretary-General
Executive Secretary-General
Members (In Alphabetical Order by Last Name)
International Academic Committee
Chairman
Members (In Alphabetical Order by Last Name)
Conference Secretariat
Contents
How Efficient is the Urbanization Process in China?
Abstract
1 Introduction
2 Research Method
3 Research Data
3.1 Establish of Input-Output Dimensional Indicators
3.2 Data Processing
4 Data Analysis
5 Discussion
5.1 The Performance of Urbanization Efficiency at National Level in China
5.2 Comparisons Between Provinces on Urbanization Efficiency Performance
6 Conclusion
Acknowledgement
References
Empirical Study on the Performance of Environmental Efficiency in the Chinese Provincial Capital Cities
Abstract
1 Introduction
2 Literature Review
3 Methodology
3.1 The Super-SBM Model with Undesirable Outputs
4 Data Source and Statistics
4.1 Selection of Indicators and Data Source
5 Results and Discussion
5.1 The Best and Worst EE Analysis
5.2 A Regional Level of EE Analysis
6 Conclusions
References
Re-Assessing Sustainable Urban Development from the Resident Perspective: A Case Study of Shanghai
Abstract
1 Introduction
2 Literature Review
2.1 Evaluation Method of Sustainable Urban Development
2.2 The Research Necessity of Resident Perception
3 Index System Construction and Data Collection
3.1 Index Selection
3.2 Data Collection
3.2.1 Questionnaire Design
3.2.2 Data Collection
4 Integrated Measurement Method and Process
4.1 Entropy Weight Method
4.2 Multi-regional and Multi-dimensional Sustainability Levels Measured
4.2.1 The Concept of Cloud Model
4.2.2 The Cloud Generator
4.3 Integrated Sustainability Assessment of Urban Development Based on Entropy Weight-Cloud Model
4.3.1 The Determination of Qualitative Criteria for Cloud Model
4.3.2 Determine the Cloud Model Eigenvalue of the Evaluation Index
4.3.3 Establishment of a Cloud Model to Comprehensively Evaluate the SUD Level
5 Measuring the Sustainable Development Level in Shanghai
5.1 Data Validity Test
5.2 Multi-regional Sustainability Level Measurement
5.2.1 Determine the Weight and Cloud Model Parameters
5.2.2 Regional Comprehensive Evaluation of Sustainable Development Level in Shanghai
5.2.3 Dimensional Comprehensive Evaluation of Sustainable Development Level in Shanghai
6 Conclusions
References
Rethinking “New Countryside Construction”: Lessons Learnt from the Guangzhou Luogang District, China
Abstract
1 Introduction
2 From an Industrial Zone Manager to a District Government: Local Governance Restructuring in the GLD Since the 1980s
2.1 Pragmatic Pursuit of Industrial Development
2.2 Land Requisition and Regional Disparities
2.3 New Countryside Construction as a Vehicle for Change
2.4 The Struggle for Welfare Services Provisions
3 Restructuring of Power Dynamics Between the State and Villages
3.1 Collaboration with Villagers and Village Organizations
3.2 Shareholding Reforms, Social Control and Institutional Capacity Building
3.3 New (Old) Power Dynamics Among Local State, Village Collective and Villagers
4 Implications of the GLD Experience
5 Conclusions
Acknowledgement
References
Study on the Development Mode and Promotion Strategy of Tourism-Oriented Characteristic Small Town in Jiangxi Province
Abstract
1 Introduction
2 Necessity and Present Situation of the Development of Tourism-Oriented Characteristic Small Town in Jiangxi Province
2.1 The Necessity of the Development of Tourist-Oriented Characteristic Small Town in Jiangxi Province
2.1.1 The Development Speed of Urban Economy in Jiangxi Province is Down
2.1.2 The Industrial Structure of Jiangxi Province is Adjusted and the Service Industry Develops Rapidly
2.2 The Development Status of Tourism-Oriented Characteristic Small Town in Jiangxi
2.2.1 The Tourism-Oriented Characteristic Small Towns Occupy a Large Proportion and Their Distribution is Relatively Concentrated
2.2.2 Imbalance Development of the Tourism-Oriented Characteristic Small Town
3 The Development Pattern Selection of the Tourism-Oriented Characteristic Small Town in Jiangxi Province
3.1 The Development Pattern Based on the Featured Resources
3.2 The Service-Led Development Pattern
3.3 Comprehensive Development Pattern
4 Problems Existing in the Development of Tourism-Oriented Characteristic Small Town in Jiangxi Province
4.1 Ignoring the Development of Supporting Industries
4.2 The Tourism Industry is not in Harmony with the Life of Residents
4.3 The Homogenization of Tourism Product is Serious and the Concentration of Tourism Region is Strong
5 Optimization of the Development Mode of Tourism-Oriented Small Town in Jiangxi Province
5.1 Perfecting the Industrial System
5.2 Reasonable Allocation of Functions
5.3 Enriching Tourism Products and Realizing the Tourism in Whole Region
6 Conclusions
References
Temporal-Spatial Evolution Patterns of Population Urbanization and Land Urbanization in China
Abstract
1 Introduction
2 Methods and Data
2.1 Kernel Density Estimation
2.2 Standard Deviational Ellipse
2.3 Indicator Selection and Data Source
3 Results
3.1 The Time Series Dynamic Evolution Characteristics in China’s Urbanization
3.2 The Evolution Characteristics of Spatial Pattern in China’s Urbanization
3.2.1 Center of Gravity Position and Migration Path
3.2.2 Spatial Distribution Direction
3.2.3 Spatial Clustering Characteristics
3.2.4 Spatial Distribution Pattern
4 Conclusions and Discussion
References
Dynamic Causal Linkages Among Urbanization, Energy Consumption, Pollutant Emissions and Economic Growth in China
Abstract
1 Introduction
2 Theoretical Model and Econometric Method
2.1 Extended Growth Model
2.2 Theoretical Underpinnings and Hypotheses Formulation
2.3 Estimation Methodology
3 Data and Analysis
3.1 Data
3.2 Empirical Analysis
3.2.1 Model 1
3.2.2 Model 2
3.2.3 Model 3
3.2.4 Model 4
3.2.5 Empirical Summary and Discussion
4 Conclusions and Policy Recommendations
4.1 Major Conclusions
4.2 Policy Recommendations
References
Study on Competitiveness Evaluation of the Intangible Cultural Heritage Town Based on Porter Diamond Model
Abstract
1 Introduction
2 The Connotation of Intangible Cultural Heritage Town
3 Research on the Competitiveness of Intangible Cultural Heritage Town
3.1 The Theory of Porter Diamond Model
3.2 Analysis on the Competitiveness of Intangible Cultural Heritage Towns and Its Index System Construction
3.2.1 Production Factors
3.2.2 Demand Conditions
3.2.3 Related and Supporting Industries
3.2.4 Business Competition
3.2.5 Government Action
4 The Weight Analysis of Evaluation Index of Intangible Cultural Heritage Town Competitiveness
5 Illustration Analysis
6 Conclusion
Acknowledgements
References
The Thinking on Spatial Management and Control of “Urban Growth Boundaries” from the Perspective of Natural Resources
Abstract
1 Introduction
2 The Discussion of Several Modes of Urban Development Boundaries
2.1 The Two-Way Control Between Government and Civil Society Mode to Develop the Boundaries in the West Coast of the United States
2.2 Shanghai: Cross Compound Utilization Mode of “Three Areas, Four Lines”
2.3 Xiamen: “The Combination of Rigidity and Flexibility” - the Spatial Management and Control Mode of the Urban Growth Boundaries
3 Question and Discussion
3.1 How Can We Change the Thinking of Spatial Management and Control of the Urban Growth Boundaries?
3.2 Can the Urban Growth Boundaries Guarantee the Quantity and Quality of Agricultural Land and Ecological Land?
3.3 At What Level and Scope Do We Define the Urban Growth Boundaries?
4 Conclusion
References
Evaluation on Performance of Ecological Welfare of Characteristic Small Town——A Case in Chongqing
Abstract
1 Introduction
2 Summary of Studies on Evaluation of Sustainable Development of Characteristic Small Towns
2.1 Construction Evaluation of Characteristic Small Town
2.2 The Concept of Ecological Welfare
2.3 Evaluation of Characteristic Small Towns from the Perspective of Ecological Welfare
3 Indicator System, Research Methods and Data Sources
3.1 Construction of Evaluation Index System
3.2 Research Methods
3.2.1 Entropy Method
3.2.2 Improved DEA - Super-SBM Model
3.3 Data Collection and Processing
4 Calculation Results and Analysis
4.1 Evaluation of Ecological Environment
4.2 Analysis of Residents’ Welfare Output Evaluation
4.3 Measurement and Evaluation of Performance of Ecological Welfare of Characteristic Small Towns in Chongqing
5 Conclusion
References
Problems and Countermeasures of Characteristic Development of Small Towns in Qiannan Prefecture
Abstract
1 Introduction
2 Construction Business Environments in China
3 Restrictive Factors in the Construction
4 Analyzing Countermeasures
4.1 Scientific Planning and Highlighting Local Ethnic Features
4.2 Improving the Functions of Small Towns and Taking the Road of Sustainable Development
4.3 Giving Full Play to the Advantages of Regional Resources and Cultivate Special Industries
4.4 Establishing a Diversified Investment and Financing System
5 Conclusion
Acknowledgement
References
How Weather Retain Migrants? Evidence from Floating Population Dynamic Monitoring Data
Abstract
1 Introduction
2 Literature Review
2.1 Long-Term Residence Tendency
2.2 Weather Attributes
3 Data and Empirical Model
3.1 Data Sources
3.2 Variables Settings
3.3 Logit Model
4 Empirical Evidence
4.1 Correlation Analysis
4.2 Logit Regression Analysis
4.3 Heterogeneous Effects
5 Conclusion and Discussion
References
Measurement of New Urbanization Construction Level and Diagnosis of Obstacle Factors——A Case of Urban Cluster in the Central Plains
Abstract
1 Question Raised
2 Study Area and Data
2.1 Overview of the Study Area
2.2 Index System Construction
2.3 Data Sources and Processing
3 Research Methods
3.1 Principal Component Analysis
3.2 Obstacles Diagnosis
4 Analysis Results
4.1 Time Dimension Analysis of New Urbanization Construction
4.2 Spatial Dimension Analysis of New Urbanization Construction
4.3 Obstacles to New Urbanization Construction
4.3.1 Sub-Target Obstacles
4.3.2 Indicator Layer Obstacle
5 Conclusion and Discussion
References
Study on the Impact Between Rapid Urbanization and Fire Safety Management——A China Perspective
Abstract
1 Introduction
2 Literature Review
3 Research Design
3.1 Research Measurements
3.1.1 Variables for Indicating Fire Safety Management Performance
3.1.2 Variables for Measuring the Level of Urbanization
3.2 Research Methods
3.2.1 Independence Verification
3.2.2 Correlation Analysis
3.3 Data Sources
4 Data Analysis
4.1 The Independence Test of Urbanization Index
4.2 Correlation Between Urbanization and Fire Safety Management
5 Discussion
5.1 Discussion Based on Dimension of the Number of Fires (Y1)
5.2 Discussion Based on the Dimension of Direct Economic Loss of Fires (Y2)
6 Conclusions
Acknowledgement
References
Study on Land-Use Efficiency Evaluation of Development Zones Based on DEA—Take Hi-Tech Zones as an Example
Abstract
1 Introduction
2 Methodology and Data
2.1 Data Envelopment Analysis
2.2 Index selection and data processing
3 Results and Analysis
3.1 Analysis of Overall Land-Use Efficiency
3.2 Regional Difference Analysis of Land-Use Efficiency
3.3 Comparative Analysis with Different Land Efficiency
3.4 Analysis of Optimization of Land-Use Efficiency
4 Measures and Suggestions
References
The Evaluation of Land Development and Utilization Based on 11 Prefecture-Level Cities in Hebei Province
Abstract
1 Introduction
2 Background
3 Data and Methods
3.1 Data Source
3.2 Research Method
4 Static Comparison of Land Utilization in All Cities
4.1 Population Density
4.2 Per Capita Living Space
4.3 Per Capita Area of Land Used for Construction
4.4 Built-Up Area/Urban Area
5 The Similarity Evaluation of Land Utilization in All Cities
5.1 Population Density
5.2 Per Capita Living Space
5.3 Per Capita Area of Land Used for Construction
5.4 Built-Up Area/Urban Area
6 Conclusion
References
The Study of the Expansion of Urban Functional Land in Ganzhou
Abstract
1 Introduction
2 Research Methods and Data Sources
2.1 Data Sources
2.2 Study Area
2.3 Research Methods
2.3.1 Expansion Intensity
2.3.2 Expansion Rate
3 Pattern Analysis of Expanding Process of Construction Land
3.1 The Expansion Intensity and Rate of Construction Land
3.2 The Direction of Functional Land Expansion
3.2.1 The Expansion of Residential Land
3.2.2 The Expansion of Industrial Land
3.2.3 Expansion of Commercial Land
4 Analysis of Factors of Construction Land Expansion
4.1 Natural Conditions
4.2 Economy and People
4.3 Traffic Location
4.4 Policy and Urban Planning
5 Conclusions and Discussion
References
Temporal-Spatial Evolution Characteristics of Economic Development of Hangzhou Bay Area and Its Influencing Factors
Abstract
1 Introduction
2 Research Area, Research Method and Data Sources
2.1 Research Area
2.2 Research Method
2.2.1 Building a Comprehensive Development Index System for Economic Development
2.2.2 Entropy Method
2.2.3 Evaluation Model of Comprehensive Level of Economic Development
2.2.4 Relative Rate of Development
2.2.5 Standard Deviation and Coefficient of Variation
2.3 Research Data
3 Temporal and Spatial Evolution of Economic Development in Hangzhou Bay Area
3.1 Overall Economic Development Level Shows Rapid Growth
3.1.1 Slow Growth Phase of Economic Development (1997–2000)
3.1.2 Accelerated Economic Growth (2001–2007)
3.1.3 The Turbulent Phase of Economic Development (2008–2013)
3.1.4 Rapid Economic Development (2014–2016)
3.2 Overall Economic Development Level Shows Rapid Growth
3.3 The Economic Index of Shanghai Ranks the Highest in the Bay Area
3.4 Absolute Differences in Regional Economies Increase and Relative Differences Decrease
3.5 The Economic Spatial Pattern of the Hangzhou Bay Area Presents a Pattern of “1 + 2 + 3 + X”
4 Factors Influencing the Spatial-Temporal Evolution of Economic Development in the Hangzhou Bay Area
4.1 Location Characteristics
4.2 Regional Development Policy
4.3 Changes in the External Environment
4.4 Other Factors
4.4.1 Traffic Factors
4.4.2 Development Path
4.4.3 Resource Endowment
5 Conclusion
References
Impacts of Land Expropriation on the Entrepreneurial Decision-Making Behavior of Land-Lost Peasants: An Agent-Based Simulation
Abstract
1 Introduction
2 Research Method
2.1 Revised Todaro Model for Explaining Entrepreneurial Behavior of Land-Lost Peasants
2.2 Multi-agent Simulation of the Entrepreneurial Behavior of Land-Lost Peasants
2.2.1 Modeling of Entrepreneurial Behavior of Land-Lost Peasants Within Land Expropriation Scenarios
2.2.2 Simulation
2.2.3 Parameter Description
3 Simulation Result Analysis
3.1 Compensation for Land Acquisition
3.2 Social Security
3.3 Land Location
4 Discussion
5 Conclusion
Acknowledgements
References
Analysis of the Land Use Situation of China in the Last Decade
Abstract
1 Construction Land Supply
1.1 Area of Construction Land Supplied by Government
1.2 The Structure of Land Supplied by the Government
2 The Efficiency of Land Use
2.1 GDP Per Hectares
2.2 The Proportion of Cultivated Land Occupied by Construction
3 The Distribution of Commercial Land
4 Land Price
5 Land Revenue and Land Finance
6 Forecast of the Near Future
6.1 Land Supply
6.2 Land Market and Land Price
6.3 Land Revenue and Risk Brought Land Mortgage
Acknowledgements
References
Research on the Governance Modality of Village-in-City Based on Mitchell Score-Based Approach
Abstract
1 Introduction
2 Research Methods and Study Area Overview
2.1 Research Methods
2.2 Study Area Overview
3 Case Study
3.1 Demolition and Reconstruction (M1)
3.1.1 Typical Village Survey of Longshun Village
3.1.2 Stakeholders and Their Importance
3.1.3 SCM Analysis of Governance Modality in Village-in-City
3.2 Partial Demolition and Space Optimization (M2)
3.2.1 Typical Village Survey of Datong Village
3.2.2 Stakeholders and Their Importance
3.2.3 SCM Analysis of Governance Modality in Village-in-City
3.3 Facilities and Landscape Comprehensive Consolidation (M3)
3.3.1 Typical Village Survey of Xiangjia Village
3.3.2 Stakeholders and Their Importance
3.3.3 SCM Analysis of Governance Modality in Village-in-City
4 Investigation of the Governance Modality of Village-in-City Based on Mitchell Score-Based Approach
4.1 Demolition and Reconstruction (M1)
4.1.1 Urban Village and Its Governance Features
4.1.2 Analysis of the Advantages and Disadvantages of the Governance Modality
4.2 Partial Demolition and Space Optimization (M2)
4.2.1 Urban Village and Its Governance Features
4.2.2 Analysis of the Advantages and Disadvantages of the Governance Modality
4.3 Facilities and Landscape Comprehensive Consolidation (M3)
4.3.1 Urban Village and Its Governance Features
4.3.2 Analysis of the Advantages and Disadvantages of the Governance Modality
5 Policy Suggestions
5.1 Housing: Build Low-Cost Housing for Floating Population and Include It in USB
5.2 Employment: Provide Employment Skills Training Services to Promote Population Urbanization
5.3 Planning: Combine Governance of the Village-in-City with the Overall Planning of the City
5.4 Government: Departmental Collaboration Reform
References
The Legislation of Transfer of the Right to Use Homestead
Abstract
1 Introduction
2 The Problem of the Transfer of the Right to Use the Homestead
2.1 Poor Transfer Channels Lead to Idleness
2.2 The Lack of Transfer Mechanism Leads to the Continuous Dispute of the Sale and Purchase Contract
2.3 The Subject Restriction Causes Property Defects
2.4 The Property Right of the Homestead Is Defective
2.5 The Homestead Transfer Property Registration Is Insufficient
2.6 The Regulation of the Right to Use Homestead Is Insufficient
3 The Necessity of the Reform of the Right to Use Homestead
3.1 In Favor of “Farmers”
3.2 In Favor of “Government”
4 Specific Advice
4.1 The Transfer Subject of the Right to Use the Homestead
4.2 The Transfer Object of the Right to Use the Homestead
4.3 The Homestead Had a Certain Year and Need to Pay Rent
5 Legislative Proposals for the Transfer of Homestead
5.1 Suggestions for Improvement of Homestead Laws and Regulations
5.2 Proposal on the Transfer of Homestead Legislation
6 Conclusion
7 Acknowledgement
References
Measures of Fire Protection Design for Embedded Substations
Abstract
1 Introduction
2 The Problems and Solutions of Fire Protection Design for Embedded Substation
2.1 Fire Problems in Embedded Substations
2.2 Control of Fire Hazard Level in Embedded Substation Equipment
2.3 Fire-Resistant Rating of Embedded Substation Enclosure Structure
3 Conclusions
Acknowledgement
References
The Conceptual Model of Belt and Road Infrastructure Projects
Abstract
1 Introduction
2 The Conceptual Model of B&R Projects
3 Opportunities in B&R Infrastructure Projects
4 Risk in B&R Infrastructure Projects
4.1 Risk Related to B&R Policy
4.2 Risk Related to Construction Market
4.3 Risk Related to Project Environment
4.4 Risk Related to Design Process
4.5 Risk Related to Construction Process
4.6 Risk Related to Staff and Management of the Project
5 Conclusion
Acknowledgment
References
Developing a Fuzzy Evaluation Model of Safety Management for Urban Water Environment Rehabilitation Project
Abstract
1 Introduction
2 Safety Fuzzy Comprehensive Evaluation Model
2.1 Defining the Evaluation Index Set
2.2 Determining the Weight Set
2.2.1 Determining the Weight by AHP
2.2.2 Determining the Weight by Entropy Weight Method
2.2.3 Determining the Combination Weight by AHP-Entropy Weight Method
2.3 Fuzzy Comprehensive Evaluation
2.3.1 Defining the Evaluation Scale Set
2.3.2 Fuzzy Comprehensive Evaluation of Safety Status
3 Model Application
3.1 Project Overview
3.2 Indicator Weight Determination
3.3 Fuzzy Operation and Fuzzy Comprehensive Evaluation
3.4 Result Analysis and Discussion
4 Conclusions
Acknowledgments
References
Total Safety Management Practice in an Urban Water Environment Rehabilitation Project
Abstract
1 Introduction
2 The Maozhou River Rehabilitation Project
3 Search-Tell-Check-Control
3.1 Concept of STCC
3.2 Steps of STCC Cycle
3.2.1 Search: Actively Collect Safety Management Information
3.2.2 Tell: Conduct Safety Education and Training
3.2.3 Check: Inspection of On-Site Production Activities
3.2.4 Control: Keep Security Issues Under Control
4 Hazards Risk Assessment and Accident Prediction Model
4.1 Causes of Accidents on the Construction Site
4.2 Safety Evaluation on the Construction Site
4.2.1 Evaluation Factors System
4.2.2 Results and Discussion
4.3 Accident Prediction Model Based on BP Neural Network
4.4 Pre-control Measures for Security Accidents
4.4.1 QR Code Security Management System
4.4.2 Video Surveillance System
4.4.3 Building an Information Management Platform
4.4.4 Strengthening Safety Education and Training
5 Conclusions
Acknowledgments
References
Application of Causal Analysis Method in Quality Management of the Maozhou River Rehabilitation Project
Abstract
1 Introduction
2 Quality Management of the Maozhou River Rehabilitation Project
3 Application of Causal Analysis Method
3.1 Personnel Management
3.2 Establish a Sound Post Responsibility System
3.3 Staff Education and Training
3.4 Personnel Qualification Management
3.5 Construction Machinery Management
3.6 Material Management
3.6.1 Material Selection
3.6.2 Factory Supervision System
3.6.3 Material Storage
3.7 Construction Methods and Management Measures
3.7.1 Construction Method
3.7.2 Management Measures
3.8 Environmental Management
3.9 Test and Inspection
3.9.1 Establish “Three-Level Inspection System”
3.9.2 Raw Material Detection
3.9.3 Spot Inspection
3.9.4 Pipeline Inspection
4 Conclusions
5 Acknowledgments
References
Environmental Management Scheme of EPC Model for Water Environmental Treatment Project
Abstract
1 Introduction
2 The Object, Method and Content of Field Investigation
3 Analysis of the Environmental Management Model of Present Project
3.1 Characteristic of ISO14001 in Application of Project Management
3.2 Analysis of Environmental Management Model Related to the Project
4 Environmental Management Scheme Process System Based on ISO14001
4.1 Determine the Type of Construction Project
4.2 Identification of Environmental Impact Factors
4.3 Prevention and Control Scheme of Environmental Contamination
4.4 Implementation and Evaluation of the Scheme
5 An Example of Quantitative Evaluation Scheme Based on AHP
5.1 Description of AHP Model
5.1.1 Establishment of Evaluation Index System
5.1.2 Weight Determination
5.2 Quantitative Evaluation Index System Based on AHP
6 Conclusion
Acknowledgements
References
Innovative Bioretention Facility for Siphonic Drainage System
Abstract
1 Introduction
2 Outline of Changzhen Depot
3 Innovative Bioretention Parterre
4 Conclusions
Acknowledgments
References
Estimating the Redistribution Effect of Affordable Housing on Income Distribution: Case Study of Nanjing
Abstract
1 Introduction
2 Literature Review
3 Theoretical Framework
4 Methodology of Estimating Housing Benefits
5 Empirical Analysis
5.1 The Data
5.2 Distribution of Benefits
5.3 The Change of Gini Coefficient
5.4 The Results
6 Conclusion
Acknowledgement
References
Research on Relationship Between the Real Estate Prices and Technological Innovation Through Human Capital in China
Abstract
1 Introduction
2 Research Method
3 Theoretical Analysis
3.1 Relevance Analysis
3.2 Relevance Analysis
4 Model Building
4.1 Derivation of Transmission Path
4.2 Model Design
4.3 Variable Design
5 Empirical Analysis
6 Conclusions
References
Research on the Commercial House Price of Supply and Demand Elasticity Based on the Panel Data of China’s Four Municipalities
Abstract
1 Introduction
2 Model Construction
2.1 Dynamic Cobweb Model
2.2 Variable Description
2.2.1 Supply Variable Description
2.2.2 Demand Variable Description
3 Data Description
3.1 Sources of Data
3.2 Data Processing
4 Regression Analysis
5 Conclusions and Discussion
5.1 Conclusion
5.2 Discussion
References
Capitalization of Urban Public Service Based on Urban Administrative Hierarchy: Evidence of Housing Prices from 281 Cities of China
Abstract
1 Introduction
2 Related Literature
3 Data and Methodology
4 Results and Analysis
4.1 Analysis of All 281 Cities
4.2 Analysis of Regression Results by Group
4.2.1 Sub-provincial Cities and Above
4.2.2 Provincial Capital Cities Except for Sub-provincial Cities
4.2.3 General Prefecture-Level Cities
4.3 Horizontal Comparison Analysis of Regression Results
5 Conclusions and Implications
References
Overseas Social Security Housing Construction Pattern and Its Enlightenment to China
Abstract
1 Introduction
2 Model of Affordable Housing Construction Abroad
2.1 Government-Led Model
2.2 Market-Oriented Model
3 Characteristics of Social Security Housing Construction in Developed Countries
3.1 Financial Support for Social Security Housing Construction
3.2 Relevant Legislation of Social Security Housing
3.3 Diversification of Affordable Housing Construction and Supply
4 Inspiration for the Construction of Social Security Housing in China
4.1 Establishing an Executable Housing Security Agency
4.2 Perfecting Laws and Regulations System
4.3 Provisions for the Construction of Social Security Housing
5 Conclusion
Acknowledgement
References
Research on Demand Forecast of Social Pension Facilities: A Case Study of Chongqing
Abstract
1 Introduction
2 Research Review
3 Current Situation of Population Aging and Pension Institutions in Chongqing
3.1 Current Situation of Population Aging
3.1.1 The Aging Degree Deepens, the Population of the Old Age Is Increasing Every Year
3.1.2 The Aging of Population and the Coexistence of Old Age
3.1.3 The Difference in the Number of Elderly Population Is Obvious
3.2 Spatial Distribution and Existing Problems of Elderly Care Institutions in Chongqing
3.2.1 Spatial Distribution of Pension Facilities in Chongqing
3.2.2 The Spatial Distribution of Endowment Facilities Are Different
3.2.3 The Imbalance Between Supply and Demand of the Pension Institutions and the Small Size of Pension Facilities
4 Study and Application of Forecasting Method for Elderly People in Chongqing
4.1 Research Methods
4.2 Model Establishment
4.3 Result Analysis
5 Forecast on the Demand for Elderly Care Facilities in Chongqing
5.1 Demand Forecast of the Number of Old-Age Beds Based on the Total Population
5.2 Forecast of the Number of Nursing Staff Based on the Total Number of Elderly Population
6 Conclusions and Discussion
6.1 Main Conclusions
6.2 Research Prospects
References
An Evolutionary Game Analysis on the Choice of Urban Housing Purchase Restriction Policy
Abstract
1 Introduction
2 Research Methodology
2.1 Problem Description
2.2 The Construction of Evolutionary Game Model of Housing Purchase Restriction Policies
2.3 Symbol Description
3 The Evolutionary Game Analysis of the Housing Purchase Restriction Policies in Central Cities and Sub-centers
3.1 Game Model Replication Dynamic Equation
3.2 Equilibrium Point and Stability Analysis of Game Model
4 Analysis and Discussion of Influencing Factors of Evolutionary Stability Strategies
5 Conclusions and Policy Recommendations
References
Multi-objective Optimization for the Portfolio Selection on Economic Prefabricated Component
Abstract
1 Introduction
2 Multi-objective Optimization Methodology
2.1 Multi-objective Optimization Problem
2.2 Design Variables
2.3 Objective Function
2.4 Objective Constraints
2.5 Model Summary and Solution Techniques
3 Case Study
4 Results and Discussions
5 Conclusion
Acknowledgements
References
Exploration on the Path of Integrating State-Owned Public Housing into the Housing System—Based on the Perspective of Social Network Analysis
Abstract
1 Introduction
2 Social Network Construction of Public Housing
2.1 Social Network
2.2 The Network Relationship of Public Housing
2.2.1 The Lessee
2.2.2 Lessee’s Immediate Family
2.2.3 Subtenant
2.2.4 Municipal Government Administration Department
2.2.5 District Government Administration Department
2.2.6 Street Office
2.2.7 News Media
3 Network Relationship Analysis of Direct Public Housing Problem
4 Problem Solving and Reform Path of Direct Management of Public Housing
4.1 Construction of Reform Thinking with the Goal of Clearing Away from the Exit
4.2 The Reform Idea of the Target of Rents Adjustment
5 Conclusion
References
Household Registration Discrimination and Housing Choice for Migrant Workers
Abstract
1 Introduction
2 Literature Review
3 Model Selection and Data Description
4 Policy Suggestions on Solving the Housing Problem of Migrant Workers
References
Study on the Relationship Between Housing Land Supply and Housing Price in Cities with Different Economic Development Levels
Abstract
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Sources
3.2 Economic Development Level
3.2.1 Per Capita GDP as the Standard——Chenery Industrialization Stage Theory
3.2.2 Urbanization Rate as the Standard – the National New-Type Urbanization Planning
3.3 Division Result
4 The Relationship Between Housing Land Supply and Housing Price in Cities with Different Economic Development Levels
4.1 Economic Development Level I——Shanghai
4.2 Economic Development Level II——Xi’an
4.3 Economic Development Level III——Xining
5 Conclusion
References
The Impact of Demographic Structure on Housing Price in Beijing Based on System Dynamics
Abstract
1 Introduction
2 Literature Review
3 The System Dynamics Model of the Influence of Demographic Structure on Housing Price in Beijing
3.1 Introduction to System Dynamics
3.2 The Cause-and-Effect Diagram of the Influence of Demographic Structure on Housing Price in Beijing
3.3 The Stock-and-Flow Diagram of the Influence of Demographic Structure on Housing Price in Beijing
3.4 Parameter Estimation of the Model
4 Simulating the Effect of Demographic Structure on House Prices in Beijing
4.1 Data Sources and Simulation Credibility
4.2 Simulation of House Price in Beijing
4.3 The Change of House Prices in Beijing Under the Change of Demographic Structure
5 Conclusions and Policy Recommendations
Acknowledgement
References
A Review of the Application of Hedonic Pricing Model in the Nigerian Real Estate Market
Abstract
1 Introduction
2 Hedonic Pricing Model: Brief Origin
3 Research Method
4 Results and Discussion
4.1 Affiliations of Contributors
5 Active Contributors to the Publications
6 Annual Trend of Research Output
7 Case Study Areas
8 Conclusion and Further Research
Acknowledgements
References
Research on the Large-Scale Development of Prefabricated Buildings Using System Dynamics
Abstract
1 Introduction
2 Research Method
3 Analysis of the Large-Scale Development of Prefabricated Buildings
3.1 Analysis of the Prefabricated Building Market System
3.2 Analysis of the Prefabricated Building Policy System
3.3 Analysis of the Prefabricated Building Economy System
3.4 Analysis of the Prefabricated Building Technology System
3.5 The Establishment and Analysis of System Dynamics Model
4 Suggestions
5 Conclusions
References
Study on the Policy Efficiency of Real Estate Tax Reform to Local Real Estate Market Regulation
Abstract
1 Introduction
2 Materials and Methods
2.1 Land-Transferring Fee and Real Estate Tax
2.2 Literature Review
2.3 Theory and Research Method
2.3.1 Wealth Theory
2.3.2 Income Theory and New Theory
2.3.3 Data Envelopment Analysis (DEA)
2.4 Index Selection and Data Sources
3 Results
4 Conclusion
References
Research on the Allocation of Excess Revenue Between Public and Private Sectors in Mega Construction Projects
Abstract
1 Introduction
2 Model Description and Analysis
2.1 Emergence Mechanism of Game Behavior Between Public and Private Sectors
2.2 A Game Model of Public and Private Sectors
3 Solution and Discussion
3.1 Strategy 1: Priority Strategy Model of Private Sector
3.2 Strategy 2: Priority Strategy Model of Public Sector
3.3 Comparative Analysis of Total Revenue of PPP Construction Project in Two Strategies
4 Numerical Example
5 Conclusions
Acknowledgments
References
A Conceptual Framework for Identifying Performance Indicators of PPP Urbanization Projects Based on Sustainability Goals
Abstract
1 Introduction
2 Literature Review
3 Research Methodology
4 Establishment of the Conceptual Framework for Identifying KPIs
4.1 The Dimension of Sustainability Goals
4.2 The Dimension of Process of PPP Urbanization Projects
4.3 The Proposed Conceptual Framework for Identifying KPIs
5 Summary
References
The Risk Sharing Mechanism of Developing Characteristic Town in PPP Mode
Abstract
1 Introduction
2 Relevant Theoretical Basis
3 Theoretical Model of Risk Sharing of Developing Characteristic Town in PPP Mode
3.1 Investment and Financing Features of Characteristic Town in PPP Mode
3.2 Utility of Combining PPP Mode and Characteristic Town
3.3 The Risk Sharing Model of Developing Characteristic Town in PPP Mode
4 Risk Sharing Framework of Developing Characteristic Town in PPP Mode
4.1 Division of Risk Sharing Subjects
4.2 Project Risks and Its Arrangement
5 The Risk Sharing Game Model for the Development of Characteristic Town in PPP Mode
5.1 Basic Elements and Assumptions of Game Analysis
5.2 Game Model of Risk Sharing
5.3 Discussion
6 Conclusion
References
Research on the Development of Green Real Estate Finance in Guizhou Province
Abstract
1 Introduction
2 Literature Review
2.1 Green Finance
2.2 Real Estate Finance
3 Research Methodology
3.1 Literature Research Method
3.2 Macroscopic and Microscopic Method
4 Background and Status of Developing Green Real Estate Finance in Guizhou Province
4.1 Development Background of Green Real Estate Finance
4.2 Status of Green Real Estate Finance Development in Guizhou Province
4.2.1 Paying Great Attention to the Development of Green Finance
4.2.2 Be the First to Introduce a Green Financial Development Support Policy
4.2.3 Issued a Number of Green Ecological Community and Green Building Evaluation Standards
4.2.4 Further Promote the Construction and Innovation of Green Real Estate Finance
5 Problems in the Development of Green Real Estate Finance in Guizhou Province
5.1 Green Real Estate Finance Business is Relatively Low in Green Finance Business
5.2 Limited Use of Financial Resources by Financial Institutions
5.2.1 A Huge Financing Gap for Green Development
5.2.2 Over-Reliance on Indirect Financing
5.2.3 The Awareness of Developing Green Finance Business is not Strong
5.2.4 Environmental and Social Risk Management is Not in Place
5.2.5 Partial Loss of Financial Functions Other Than Financing
6 Policy Suggestions on the Development of Green Real Estate Finance in Guizhou Province
6.1 Vigorously Increase the Proportion of Green Real Estate Finance Business
6.2 Improve the Green Real Estate Financial System
6.3 Strengthening Financial Infrastructure Construction
6.4 Establish a Green Financial Risk Prevention Mechanism
6.5 Establish a Green Financial Talent Cultivation Environment
6.6 Establish a Green Real Estate Financial Synergy Development Mechanism
7 Conclusion
References
3D Point Cloud Data Enabled Facility Management: A Critical Review
Abstract
1 Introduction
2 Research Method
3 PCD-Enabled FM Research
3.1 Object Properties
3.2 PCD Sensing and Processing
3.3 PCD Output and Decision Support
4 Discussion and Conclusion
References
Assessing Performance Characteristics of Concreting Equipment: Reliability Engineering Approach
Abstract
1 Introduction
2 Brief Literature Review
3 Research Methodology
4 Regression Analysis of Concreting Equipment
5 Conclusion
References
Social Impacts of Adopting Robotics in the Construction Industry: A Systematic Literature Review
Abstract
1 Introduction
2 Methodology
2.1 Three Stages Search
3 Result and Discussion
3.1 Competencies of Employees
3.2 Occupational Health and Safety
3.2.1 Psychosocial Stressors from Robotics
3.2.2 Job Control
3.2.3 Social Isolation
3.2.4 Cognitive Demand
3.2.5 Skill Discretion
3.3 Management Skills
3.3.1 Social Skills
3.3.2 Technological Skills
3.3.3 Economic and Managerial Skills
3.4 Organizational Structure
3.5 Roboethics and Liability Issues
4 Conclusion
References
Prefabricated Construction: A Bibliometric Analysis
Abstract
1 Introduction
2 Method
2.1 Defining Keywords
2.2 Data Acquisition
2.3 Refinement of Data
2.4 Citation Analysis
2.5 Co-citation Analysis
3 Findings
3.1 The Changing Pattern of Publications
3.2 Author Influence
3.3 Affiliation Statistics
3.4 Journal Statistics
3.5 Network Analysis
3.5.1 Citation Analysis
3.5.2 Co-citation Analysis
4 Conclusions
References
Text Mining Based Exploration of Smart City Building Development
Abstract
1 Introduction
2 Research Method
2.1 Text Mining
2.2 Data Collection
2.3 Pro-Processing
2.4 Information Extraction
2.5 Software Implementation
3 Results and Discussions
3.1 Top Words in Terms of TF-IDF
4 Topic Model
4.1 Topic Model Visualization
5 Result Analysis
5.1 Research Focus
5.2 Trend Analysis
6 Conclusion
Acknowledgement
References
BIM Research Progress in Chinese Construction Industry: Based on Chinese First-Tier Literature Statistical Analysis
Abstract
1 Introduction
2 BIM Publication Statistical Analysis
2.1 The Change of Number of BIM Publications in China
2.2 Research Methods Adopted by BIM Researchers in China
2.3 The Stage of Life-Cycle Construction Projects Studied by the BIM Research in China
2.4 The Type of Projects Studied by BIM Researchers in China
3 Conclusions and Future Research Directions
Acknowledgement
References
Visualization Analyses Using Citespace on Researches of BIM Development from 2003 to 2017
Abstract
1 Introduction
2 The Concept and Development of BIM
3 Visual Analysis on BIM Research Using CiteSpace
3.1 Time Distribution of Literature
3.2 Representative Articles and Authors
3.3 Key Words and Terms
3.4 Research Trend
4 Research Focus Based on Periods of BIM Development
4.1 Education of BIM
4.2 Features of BIM
4.3 Interdisciplinary Application of BIM
5 Conclusion
References
The Integrated Technology of BIM5D and VR is Applied in the Construction Management of Building Engineering
Abstract
1 Introduction
2 Literature Review
2.1 In the Field of Architectural Design
2.2 In the Field of Construction Management
3 Integrated Application Technology of BIM5D and VR
3.1 Application of BIM5D Platform
3.2 VR System Application Research
3.3 Research on Integrated Application Platform of BIM5D and VR
3.3.1 Software Development
3.3.2 Building\,5D\,Information\,Data\,Conversion Docking Based on P-BIM
3.3.3 Research on Integrated Application Platform of BIM5D and VR
4 Integration Technology of BIM5D and VR
4.1 Optimization of Construction Plan
4.2 Virtual Bottom
4.3 Construction Quality Management
4.3.1 Traditional Mode for Construction Quality Management
4.3.2 BIM5D and VR Integration Technology for Construction Quality Management
5 Conclusion
References
Research on the Efficiency of 3D Collaborative Design Based on P-BIM Cloud Platform
Abstract
1 Introduction
2 Literature Review
2.1 Information Exchange Based on BIM
2.2 Architectural Design Efficiency
3 Analysis of the Current Status of Collaborative Design
3.1 Collaborative Design Platform Application Status
3.2 Analysis of the Reasons for the Less Application of 3D Collaborative Platform
4 3D Collaborative Design P-BIM Cloud Platform Introduction
4.1 Related Theories of Building a 3D Collaborative Design Platform
4.2 The Composition of P-BIM Cloud Platform
4.3 Characteristics of Information Exchange Based on P-BIM Cloud Platform
5 Case Study
5.1 Experiment Procedure
5.2 Results and Discussions
6 Conclusions
References
Research on the Whole Life Cycle Information Management System of Prefabricated Building Based on BIM+
Abstract
1 Introduction
2 Literature Review
3 Research Methodology
4 Design of Information Management System Platform
4.1 The Collaborative Design Stage
4.2 The Prefabricated Components Manufacturing Stage
4.3 The Logistics Transportation Stage
4.4 The On-site Assembly Stage
4.5 The Operation and Maintenance Stage
5 Case Analysis
6 Conclusion
References
Constructing a Building Information Modelling (BIM) Execution Plan for Quantity Surveying Practice
Abstract
1 Introduction
2 Execution Plans for BIM Use in Quantity Survey (QS-BIM)
2.1 Preliminary Cost Estimate Process in the Context of BIM
2.2 Design-Stage Cost Plan in the Context of BIM
2.3 Tendering in the Context of BIM
2.4 Cost Control in the Context of BIM
2.5 Variations and Final Accounts in the Context of BIM
3 Case Study
3.1 Overview of the Adopted BIM Software
3.2 BIM-Based Quantity Take-off
3.3 Quantities Extraction
3.4 Findings
4 Conclusions
References
The Management of Full Life Cycle for Architecture Based on BT and BIM Technology
Abstract
1 Introduction
2 Using BIM and BT Technology to Solve the “Pain” of Construction Project Management and Quality
2.1 BIM Technology Ensures Complete and Intuitive Information of Architectural Design
2.2 Engineering Supervision and Project Management Apply BT Technology to Manage Supply Chain Information Flow, Improve Construction Project Management Technology, Reduce Man-Made Quality and Safety Risks
2.3 Intelligent Contract System of BIM + BT Technology Mobilizes the Enthusiasm of Construction Companies
2.4 The Digitization of BT Assets and Property Management After Construction Is Completed to Ensure the Efficient Circulation of Assets and the Improvement of Property Management
3 Conclusions
References
A Framework of BIM-Based Value for Money (VFM) Evaluation Methods of PPP Projects at Decision-Making Stages
Abstract
1 Introduction
2 Conventional VFM Evaluation Method
3 VFM Evaluation Method Based on BIM
4 Comparative Analysis of VFM Evaluation Method Between BIM Based and Conventional VFM Evaluation
5 Conclusion and Limitations
References
Research on the Connection of Big Data and Construction Management Based on Histcite
Abstract
1 Introduction
2 Research Methodology
3 Research Findings
3.1 Research Status
3.2 Core Articles Analysis
3.3 Big Data Analysis
3.4 Our Opportunity
4 Technology Support and Category
5 Conclusion
Acknowledgments
References
A Holistic Evaluation of Low Carbon City Performance in the Context of Low Carbon Pilot Cities in China
Abstract
1 Introduction
2 Research Methodology
2.1 An Indicator Evaluation Framework Evaluates the Low-Carbon Development Performance of Low-Carbon Cities from the Overall Evaluation Perspective
2.2 Creation of Global Priority Indicators by Applying Entropy Method
2.3 A TOPSIS Method for Evaluating the Low Carbon City Performance
3 Selection of Low Carbon City Indicators
3.1 Target Recognition of Low Carbon Construction in Low Carbon Pilot Cities
3.2 Establishment of Evaluation Index of Low Carbon City Construction Level
4 Practice of Low Carbon City in China
4.1 Data Collection
4.2 Evaluation Results of the Low Carbon City Performance Between Low Carbon Pilot City
5 Discussion
5.1 Low Carbon City Performance Overall Low Carbon Pilot Cities
5.2 Low Carbon City Performance Across Five Different Dimensions
6 Conclusions
Acknowledgement
References
Analysis on the Influence Factors of the Inert Construction Waste Recycling in Chongqing
Abstract
1 Introduction
2 Influence Factors of Inert Construction Waste Recycling
2.1 Production Stage
3 Transportation Stage
3.1 Disposal Stage
3.2 Sales Stage
3.3 Factors Summary
4 Key Influence Factors Identification and Analysis
4.1 Modeling
4.2 Extraction of Influencing Factors
4.3 Extraction of the First-Class Key Factors
4.4 Identification of Key Factors
5 Analysis of Key Influencing Factors
5.1 Analysis of Policy Factors
5.2 Analysis of Market Factors
5.3 Analysis of Cost Factors
6 Countermeasures and Suggestions
7 Improving the Market Competitiveness of Recycling Products
8 Improving the Management Ability of Building Garbage Classification
9 Conclusion
Acknowledgement
References
Comprehensive Evaluation of Urban Ecological Carrying Capacity ——A Case Study of Chongqing
Abstract
1 Introduction
1.1 Study Area and Data
1.2 Methods
1.2.1 The Establishment and Standardization of the Index System
1.2.2 The Weighting of Evaluation Indicators
1.2.3 Construction of Evaluation Model of Ecological Carrying Capacity
1.2.4 The Determination of the Evaluation Criteria for the Analysis of Ecological Carrying Capacity
2 Results and Analysis
2.1 Results
2.1.1 The Evaluation of Support Subsystem
2.1.2 The Evaluation of Pressure Subsystem
2.1.3 The Evaluation of the Load Pressure Index
2.1.4 The Comprehensive Evaluation of Ecological Carrying Capacity
2.2 Analysis
3 Conclusion
Acknowledgment
References
Overview and Analysis on the Effectiveness of Indicator Systems for Evaluating Urban Carrying Capacity
Abstract
1 Introduction
2 Literature Review
3 Methodology
4 Data Collection
5 Data Analysis
5.1 Overview of the Literatures on Urban Carrying Capacity Evaluation
5.2 The Analysis on the Methodology of Selected Indicator Systems
5.3 Comparison Between Selected Indicator Systems
6 Discussion
7 Conclusion
Acknowledgements
References
Prediction on the Contribution of Green Building Development to Carbon Emissions Reduction: A Case Study of Chongqing
Abstract
1 Introduction
2 Literature Review
3 Research Methodologies
4 Empirical Analysis
5 Results and Discussions
6 Conclusion
Acknowledgement
References
Evaluation of Low-Carbon City Construction Maturity—A Case Study of Chongqing
Abstract
1 Introduction
2 Methodology
2.1 CMM
2.2 FAHP
3 The Construction of Low-Carbon City Construction Maturity Evaluation Index System
3.1 The Principles of the Construction of the Evaluation Index System
3.2 Construction of Low-Carbon City Construction Maturity Evaluation Index System
3.3 Weighting Each Index Based on FAHP
3.3.1 Development of a Judgment Matrix Using Pair-Wise Comparisons
3.3.2 Construction of Fuzzy Consistency Matrices
3.3.3 Calculation of Weights
4 Empirical Study of Evaluating Chongqing’s Low-Carbon Construction Maturity
4.1 Study Area
4.2 Data Sources and Numerical Standardization
4.3 Scales of R-Score for Each Maturity Level of Chongqing
4.4 Results and Discussion
5 Conclusion
Acknowledgements
References
Study on Evolution of Urban Carrying Capacity of Resources and Environment Under the Background of Big Data
Abstract
1 Introduction
2 Research Method
3 Research Problems
3.1 Definition on Urban Resource System and Environmental System
3.2 Relationship Among the Elements of Urban Carrying Capacity
3.3 Evolution of Urban Carrying Capacity
4 Definition of Large-Scale Cities
4.1 The Dimension of the City Scale
4.2 The Benchmarks of the City Scale
4.3 Definition of Large-Scale Cities
5 Definition of Urban Resource System and Environmental System
5.1 Definition of Urban System Based on System Theory
5.2 Establishment of System Dependencies
6 Analysis on the Relationship Among Components of UCC
6.1 Gaining Insights into the Trend of Changing Elements on UCC
6.2 Covering the Changing Small Probability of the Element
6.3 Establishing the Correlation Among the Components of UCC
7 Evolution of Urban Carrying Capacity
7.1 Historical Evolution of Urban Carrying Capacity
7.2 Regional Differences in Urban Carrying Capacity
8 Conclusion
Acknowledgment
References
Comparison of Evaluation Standards for Green Building
Abstract
1 Introduction
2 Green Building Rating System Description
2.1 ASGB
2.2 LEED
2.3 BREEAM
2.4 Green Mark
2.5 G-SEED
2.6 CASBEE
3 Comparison
3.1 Assessment Index
3.2 Evaluation Weightings
3.3 Evaluation Approach
3.4 Evaluation Rank
4 Conclusion
References
When to Maximize Green Benefits in the Construction and Engineering Industry? Perspectives from Risk Modifying Factors
Abstract
1 Introduction
2 Literature Review and Hypothesis
3 Empirical Design and Methodology
3.1 Data Collection
3.2 Difference-in-Difference Analysis
3.3 Risk – Adjusted Rate of Return
3.4 Credit Risk-Rating Model
4 Results and Discussion
4.1 DID Analysis and Risk Adjusted Return
4.2 Results of Credit Risk Rating Comparison
5 Conclusion
References
Characterizing the Flows of Construction and Demolition Waste in China
Abstract
1 Introduction
2 Methodology
2.1 Investigation Method
2.2 Distributions and Material Flows
3 Results and Discussion
3.1 Distributions
3.2 Material Flows
3.2.1 Material Flows in China
3.2.2 Material Flows in Other Countries
3.3 Cause of Low Recycling Rate
4 Conclusions and Suggestions
Acknowledgement
References
Innovative Design of the Sponge City Facilities in Changzhen Depot
Abstract
1 Introduction
2 Outline of Changzhen Depot
3 Innovation Design of the Sponge City Facilities
3.1 Design Goals
3.2 Layout Principles
3.3 Innovation Design
3.4 Layout Schemes
4 Innovative Sponge City Facilities
4.1 Biological Wastewater Treatment System
4.2 Bioretention Parterre
5 Evaluation and Cost Estimation
6 Conclusions
Acknowledgments
References
Carbon Emission of on Site Logistics for Tall Buildings
Abstract
1 Introduction
2 Review of Relevant Research Works
2.1 Carbon Emissions During Construction
2.2 Carbon Emissions from Transportation and Logistics of High-Rise Buildings
3 Methods
3.1 Purpose
3.2 Range and System Boundaries
3.3 Methods
4 Case Study
4.1 The Description of the Buildings
4.2 The Scope of the Account
4.3 The Data Collection
5 Analysis of the Emissions in This Case
5.1 Analysis of Horizontal Transportation Carbon Emission and Vertical Transportation Carbon Emission During Construction
5.2 Analysis of Carbon Emission from Logistics in Civil Construction and Installation Sites
5.3 Analysis of Carbon Emission Per Unit Area of Civil Engineering and Installation Engineering
5.4 Sensitivity Analysis
6 Conclusions
Acknowledgments
References
A Queuing Model to Improve the Utilization of Concreting Equipment
Abstract
1 Introduction
2 Brief Literature Review
3 Queuing Model to Optimize the Concreting Equipment Utilization
3.1 Concreting as a Queuing Process
3.2 Optimum Fleet Cost Analysis
3.3 Concreting Operation Modelling
4 Case Studies and Discussion
5 Conclusion
References
A Paradigm Shift from Green Buildings to Sustainable Cities: Concept and Future Direction
Abstract
1 Introduction
2 Green Buildings
2.1 Origin and Concept
2.2 Standards and Guideline
3 Sustainable Cities and Communities
3.1 Origin and Concepts
3.2 Standards and Guideline
4 Transition from Green Buildings to Sustainable Cities
4.1 Why Does the Transition Matter?
5 Conclusion
Acknowledgement
References
A Model for Predicting the Generation of Demolition Waste During the Urban Renewal Process
Abstract
1 Introduction
2 Literature Review
2.1 Methods of Estimation on DW Quantity
2.2 Methods of Prediction on DW Generation Time
2.3 Methods of Prediction on DW Generation Location
3 Methods
3.1 GOOGLE EARTH for Calculating the Lag Time of Demolition Waste Generation
3.2 BIGEMAP for Calculating the Gross Floor Area of Urban Renewal Projects
3.3 Model for Estimating the Quantity of Demolition Waste Generation
3.4 Model for Predicting the Time of Demolition Waste Generation
4 Case Study
4.1 Case Description
4.2 Predicted Results
4.2.1 The Quantity of Demolition Waste
4.2.2 The Generation Time and Location of Demolition Waste
5 Conclusion
References
Research on Forecast of Economic Benefits of Reduction Management of Construction Waste
Abstract
1 Introduction
2 Literature Review of Reduction of Construction Waste
2.1 Waste Reduction Studies at the Design Phase
2.2 Waste Reduction Studies at the Construction Phase
2.3 Waste Reduction Studies at the Waste Processing Phase
3 Economic Benefit Model of Reduction Management of Construction Waste
3.1 Critical Factors of the Economic Benefits of the Reduction of Construction Waste
3.2 Construction Waste Management Economic Efficiency System
4 Model Test
4.1 Case Study
4.2 Determination of Model Parameters
4.3 Model Test
5 Analysis of Simulation Results
6 Conclusion
References
Occupant Behavior in Energy Efficiency: A Case Study in Sydney
Abstract
1 Introduction
2 Description of the Building
3 Building Simulation
3.1 Software Used During the Simulation and 3D Model
3.2 Construction Types
3.3 Thermal Zones, Internal Loads and Infiltration Rates
3.4 Schedules
3.5 Dynamic Simulations
4 Results and Discussions
5 Conclusion
Acknowledgement
References
Gaps Between Supply and Demand of Recycled Aggregate: A Sydney Metropolitan Case Study
Abstract
1 Introduction
1.1 Energy Consumption and Carbon Footprint Considerations
1.2 Financial Viability
2 Recycled Aggregate Demand
3 Recycled Aggregate Supply
4 Discussions
5 Conclusion
References
How Does China’s Low Carbon Pilot Program Perform? Evidence from the First Batch of Low-Carbon Pilot Provinces
Abstract
1 Introduction
2 Research Methods
2.1 Calculation for Carbon Emission
2.2 Driving Force Analysis
2.3 Data Sources
3 Results and Discussion
3.1 An Overview of Carbon Emission Performance for the Five Pilot Low Carbon Provinces
3.2 Driving Forces of Carbon Emission for the Five Province
4 Conclusions and Police Implications
4.1 Main Findings
4.2 Policy Implications
4.3 Further Study
Acknowledgments
References
Mechanical Lasting Effectiveness of Carbon-Conditioning on Mixed Recycled Aggregate
Abstract
1 Introduction
2 Aim
3 Research Methodologies
3.1 Material
3.2 Carbon-Conditioning Chamber
3.3 Experimental Procedures
4 Carbon-Conditioned Recycled Aggregate Weight Characteristics
4.1 Mixed Recycled Aggregate
5 Conclusion
Acknowledgements
References
Life-Cycle Assessment of Economic and Environmental Benefits of Green Residential Buildings
Abstract
1 Introduction
2 Literature Review
2.1 Definition of Green Building
2.2 Green Building Assessment Standards
2.3 LCA in Green Building Construction
3 Framework of Evaluating the Benefits
3.1 Economic Benefits
3.2 Environmental Benefits
4 Case Studies
4.1 Case 1: Jindongfang Project
4.2 Case 2: Lakeshore Wooden Villa
4.3 Comparison Analysis
5 Conclusion
References
A Practical Model to Assess Life-Cycle Greenhouse-Gas Emissions for Australian Commercial Buildings
Abstract
1 Introduction
2 Research Methodologies
2.1 Life-Cycle GHG-Emission Assessment
2.2 Model Development
3 Results and Discussions
4 Conclusion
Acknowledgements
References
Optimum Solutions for Green Buildings: A Life-Cycle Cost Perspective Considering Transport and Land Use and Ecology Credits
Abstract
1 Introduction
2 Transport Key Criterion in Green Star Rating Tool
3 Land Use and Ecology Key Criterion
4 Research Methodologies
5 Analysis on Transport Credits
5.1 Optimum Solutions for Transport Credits
6 Analysis on Land Use and Ecology Credits
7 Optimum Solutions for Land Use and Ecology Credits
8 Conclusions
Acknowledgement
References
Preferences and Willingness-to-Pay for Vertical Greenery Systems in Singapore
Abstract
1 Introduction
2 Literature Review
2.1 Benefits of VGS
2.2 Willingness-To-Pay
2.3 Research Gap
3 Methodology
3.1 Questionnaire Design
3.2 Data Collection
3.3 Sampling
3.4 Methods of Analysis
4 Analysis of Survey Results
4.1 Section 1: Awareness and Understanding of VGS
4.2 Section 2: Willingness-To-Pay Results for VGS
5 Conclusion
5.1 Summary Findings
5.2 Contributions to Existing Knowledge
5.3 Limitation and Recommendations
Acknowledgement.
Appendix
References
Methods to Mitigate the Negative Effects on Durability of Recycled Aggregate Concrete
Abstract
1 Introduction
2 Aims and Objectives
3 Mitigation Methods
3.1 Permeability
3.1.1 Effect of TSMA on Permeability
3.1.2 Effect of Superplasticisers on Permeability
3.1.3 Effect of Metakaolin, Flyash and Blast-Furnace Slag on Permeability
3.2 Carbonation
3.2.1 Effect of Superplasticisers on Carbonation
3.2.2 Effect of Metakaolin, Flyash and Blast-Furnace Slag on Carbonation
3.3 Chloride Ingress
3.3.1 Effect of TSMA on Chloride Ingress
3.3.2 Effect of Superplasticisers on Chloride Ingress
3.3.3 Effect of SCM (Metakaolin, Flyash, Blast-Furnace Slag) on Chloride Ingress
3.4 Sulfate Attack
3.4.1 Effect of TSMA on Sulfate Attack
3.4.2 Effect of SCM (Metakaolin, Flyash, Blast-Furnace Slag) on Sulfate Attack
4 Conclusions
References
Study on Countermeasures of Rural Living Environment Improvement
Abstract
1 Introduction
2 The Present Situation of Rural Human Settlement Environment
2.1 Environmental Health Condition
2.2 Installation of Rural Environmental Infrastructure
2.3 Capital Investment Status
2.4 Construction of Comprehensive Renovation Project of Rural Environment
3 Measures for the Renovation of Rural Living Environment
3.1 Promoting the Disposal of Rural Domestic Waste
3.1.1 Cleaning Up History and Accumulate Rubbish
3.1.2 Rational Selection of Waste Disposal Methods
3.1.3 Establishing and Improving the Management Mechanism of Waste Disposal
3.2 Promoting Rural Toilet Revolution
3.2.1 Reasonable Choice of Changing Toilet Mode
3.2.2 Implementation of Toilet Excrement and Sewage Treatment
3.3 Treatment of Rural Domestic Sewage
3.3.1 Advancing the Sewage Treatment in Echelon
3.3.2 Strengthening Sewage Control
3.3.3 Adopting Scientific Sewage Treatment Methods and Technology
3.4 Promoting the Appearance of Village
3.4.1 Advancing Village Street Hardening
3.4.2 Promoting Village Greening
3.4.3 Promoting Village Lighting
3.4.4 Promoting Village Beautification
3.5 Strengthening the Management of Village Planning
3.5.1 Scientific Programming
3.5.2 Strengthening Planning Control
3.6 Perfecting Construction and Manage-Protect Mechanism
3.6.1 Establishing and Perfecting the Investment and Financing Mechanism
3.6.2 Promoting Specialized and Market-Oriented Construction and Running Manage-Protecting
3.6.3 Perfecting Financial Subsidy and Reasonable Sharing Mechanism of Farmer’s Payment
4 Conclusion
Acknowledgments
References
Sustainability Assessment for Rural Community Generated from Land Consolidation: A Case Study in China
Abstract
1 Introduction
2 Research Methods
2.1 Critical Factors (CFs) for Assessing Sustainability
2.2 Evaluation Model
3 Case Study
4 Discussion
5 Conclusion
Acknowledgements
References
Thinking on Spatial Restructuring of Traditional Villages in the Ancient Miao Territory Corridor Under the Ground of Rural Revitalization
Abstract
1 Introduction
2 Literature Review
2.1 Introduction of “The Ancient Miao Territory Corridor” and Traditional Villages
2.2 Value of Space Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor”
2.2.1 Need for Theory Construction for Boosting Rural Revitalization Strategy
2.2.2 Realistic Need for Boosting the Implementation of Rural Revitalization and Application for Listing as World Cultural Route Heritage
2.3 Review on Researches on Space System of Traditional Villages in “The Ancient Miao Territory Corridor”
2.3.1 Research Status
2.3.2 Review and Analysis on the Status
3 Research Content
3.1 Research Orientation of Space Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor”
3.1.1 Interpretation of Relationship Between the General Requirements of Rural Revitalization Strategy and Traditional Village Space
3.1.2 Contents of Space System Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor”
3.2 Innovation of Research on Space Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor”
3.2.1 Innovation of Research Model
3.2.2 Innovation of Research Content
3.2.3 Innovation of Research Method
4 Research Method
5 Conclusion
Acknowledgements
References
Investigation, Development and Application of Wood Structure Dwellings in Qiannan
Abstract
1 Introduction
2 Qiannan Traditional Wood Structure Dwellings
3 Defects of Traditional Wood Structure Dwellings
3.1 Randomness of Wood
3.2 Poor Corrosion Resistance of Wood
3.3 Poor Connectivity of Components
3.4 Poor Fire Resistance of Wood
3.5 High Costs of Wood Construction
4 Renovation of Modern Wood Structure
4.1 Deep Processing Technology of Raw Material
4.2 Transformation of Traditional Structure
4.3 Improvement of Connection Style
4.4 Simple and Unpolluted Construction
5 Construction Proposal of Wood Structure Residential Building
5.1 Realizing the Industrialization of Wood and Reducing Cost
5.2 Building Green Residential Architecture and Cultural Tradition Village
5.3 Cultivating Local Ethnic Construction Engineer
References
Research on Renewable Energy Utilization in the New Countryside in Qinba Mountain: A Case Study in Bazhong, Sichuan Province
Abstract
1 Introduction
2 Current Situation of Rural Energy Development in Qinba Mountain
2.1 Rural Natural Conditions
2.2 Current of Rural Energy Consumption
2.3 Research on Rural Energy Problems
3 Research on Traditional Household Biogas
4 Solar Energy Centralized Biogas System
4.1 Application of Solar Energy in Biogas Digesters
4.2 Fermentation Materials
4.3 Structure of Solar Centralized Biogas Digester
4.4 Advantages of Solar Energy Centralized Biogas Digester
5 Feasibility Analysis
5.1 Technical Feasibility Analysis
5.2 Economic Feasibility Analysis
5.3 Environmental Feasibility Analysis
5.4 Social Feasibility Analysis
6 Conclusion
References
Research on the Welfare of Homestead Transfer Under the Background of Targeted Poverty Alleviation—Based on Sen’s Feasibility Analysis
Abstract
1 Introduction
2 Problems and Countermeasures in the Circulation of Homestead
2.1 Current Situation and Problems of Homestead Circulation
2.2 Sen’s Theory and Analytical Framework
2.3 Utility Analysis of Welfare Based on Feasible Capability Framework
3 Empirical Analysis
3.1 Poverty Phenomenon of Peasant Households in Yongshun County
3.2 Analysis of Welfare Utility of Homestead Circulation in Poor Area
4 Conclusions and Recommendations
References
Optimising Facilities Provision in Retirement Villages - A Case Study in Australia
Abstract
1 Introduction
2 Literature Review
3 Research Methods
4 Results and Analysis
5 Discussion and Conclusions
References
Design of “Point Spirit” Cultural Heritage Protection Mobile Platform Based on LIDAR
Abstract
1 Introduction
2 Research on the Application of Lidar in Cultural Heritage Protection
2.1 Application of Ground Lidar in Cultural Heritage Protection
2.2 Application of Airborne LIDAR in Cultural Heritage Protection
2.3 Application of Other LIDAR in Cultural Heritage Protection
3 Methods
4 “Point Spirit” Cultural Heritage Protection Mobile Software Design
4.1 “Point Spirit” Software Principles
4.2 “Point Spirit” Software Function
4.3 “Point Spirit” Software Advantages
5 Conclusions and Discussions
Acknowledgments
References
Discovering Spatial Interdependencies from Mobile Phone Data and Transportation Data: Evidence from Guizhou Province
Abstract
1 Introduction
2 Data and Methods
2.1 Data Description and Data Processing
2.1.1 Mobile Phone Data
2.1.2 Transportation Data
2.1.3 Data Processing
2.2 Study Methods
2.2.1 The Complex Network Theory
2.2.2 Quadratic Assignment Procedure
2.2.3 Quantitative Analysis
3 Results and Discussion
3.1 Network Establishment
3.2 Centrality Calculation
3.3 Community Detection
3.4 The Correlation Between the Two Kinds of Flow
3.5 Attenuation Rule of the Two Kinds of Flow
4 Conclusion
Acknowledgement
References
Research Trends of Information Technology Application in Construction Workers’ Behavior Monitoring
Abstract
1 Introduction
2 Overall Research Analysis
2.1 Year Profile of Publications
2.2 Research Author
2.3 Countries
2.4 Journal
3 Classification of Research on Information Technology Based Workers’ Behavior Safety Monitoring
3.1 Vision-Based Technology for Behavior Safety Monitoring
3.1.1 Surveillance Cameras
3.1.2 Portable Cameras
3.1.3 RGB-D Sensors
3.1.4 Stereo Vision Camera
3.2 Radio Frequency Based Technology for Behavior Safety Monitoring
3.2.1 RFID
3.2.2 UWB
3.2.3 Other Radio Frequency Based Technology
3.3 Fusion Technology for Behavior Safety Monitoring
4 Discussion and Future Research
4.1 Discussion
4.2 Future Research Direction
5 Conclusion
Acknowledgments
References
The Visualization Analysis of Organizational Information Ecosystem Development Based on Social Networks
Abstract
1 Introduction
2 Data Collection and Research Methods
3 Research Hotspots and Development Structure Analysis
3.1 Co-occurring Subject Category Network
3.2 Journal Co-citation Network
3.3 Co-occurring Keywords Network
4 Knowledge Base Analysis
4.1 Author Co-citation Network
4.2 Document Co-citation Network
4.3 Structural Variation Analysis
5 Conclusion
References
Research on the Mechanism of the Economic Compensation to Prefabricated Building Based on the Loss of Developers’ Revenue
Abstract
1 Introduction
2 Theoretical Analysis of Loss of Revenue
2.1 Analysis of Source of Loss of Revenue
2.2 Determination of Compensation for Loss of Revenue
3 Apportionment Model Based on Revenue Loss
3.1 Apportionment Ideas
3.2 The Rationality of Compensation
4 The Establishment of Apportionment Model
4.1 The Establishment of the Model
4.2 Comprehensive Benefit Calculation
4.2.1 Economic Benefits
4.2.2 Environmental Benefits
4.2.3 Social Benefits
5 Conclusion
References
The Correlation Between Intangible Assets and Business Performance of Listed Construction Enterprises in China
Abstract
1 Introduction
2 Literature Review
2.1 Definition and Classification of Intangible Assets
2.2 Value Relevance of Intangible Assets
3 Research Hypothesis and Model Establishment
3.1 Research Hypothesis
3.2 Model Establishment
3.3 Variable Definition
3.3.1 Dependent Variable
3.3.2 Independent Variable
3.3.3 Control Variable
4 Sample Selection and Data Statistics
4.1 Sample Selection
4.2 Data Statistics
4.2.1 Overall Situation of Intangible Assets
4.2.2 Composition of Intangible Assets
5 Empirical Test and Regression Analysis
5.1 Unit Root Testing
5.2 Model Testing
5.3 Results Analysis
5.3.1 Overall Intangible Assets and Business Performance
5.3.2 Different Types of Intangible Assets and Business Performance
6 Conclusions
References
Structure Analysis of Information Flow in Project Design Stage Based on Information Theory
Abstract
1 Introduction
2 Project Design Phase in PLC
2.1 Construction Unit Demand Structure
2.2 Building Functional Structure
2.3 Architectural Physical Structure
3 Information Status of the Building
3.1 The Complexity of Information Flow During Project Design Stage
3.2 Entropy Model of Information Flow in Product Design Stage
3.3 The Information Distance of the State of the Project Design Stage in PLC
4 Product Model Establishment and Model Application Based on TBS Method
4.1 The Concept of TBS
4.2 Project Design Process Analysis
4.3 Information Status of Architectural Design Process in Project Design
4.4 Information Status Analysis of Project Design Process
5 Discussion
6 Conclusion
References
The Influence of Culture Value of Civil Engineering Projects on Their Life-Span
Abstract
1 Introduction
2 The Problems of Civil Engineering Projects in China
3 The Research Hypothesis and Methods
3.1 The Hypothesis on the Cause of Short Life of Engineering Projects in China
3.2 Research Methods
4 Case Studies of the Longevous Projects
4.1 The Suzhou Garden
4.2 Dujiang Dam
4.3 City Wall of Ming Dynasty in Nanjing
4.4 Yinyu Hall
4.5 Mustang Ridge
4.6 Analysis on Longevous Engineering Projects
5 Case Studies on Short-Lived Engineering Projects
5.1 China Sports Museum
5.2 Shenyang Summer Palace
5.3 West Nanjing Viaduct
5.4 Tianzi Hotel
5.5 “White Houses”
5.6 Analysis of the Short-Lived Projects
6 Concluding Marks and Research Prospect
6.1 Concluding Marks
6.2 Research Prospects
References
Typhoon Risk Perception and Positive Coping Behaviors of Middle School Students in Ningbo City
Abstract
1 Introduction
2 Research Method
2.1 Variables and Measurements
2.1.1 PCB
2.1.2 Risk Perception
2.2 Control Variables
2.2.1 Gender
2.2.2 Year Grade
2.2.3 Discipline Preferences
2.2.4 Geography Knowledge Preferences
2.2.5 Parental Education Level
2.2.6 Annual Household Income
2.2.7 Typhoon Experience
2.3 Data Collection
3 Findings
3.1 Primary Analysis
3.2 Regression Results
4 Discussions
5 Conclusion
Acknowledgments
References
Research on the Mechanism of Influencing Factors of Construction Workers’ Unsafe Behavior Based on DEMATEL and ISM
Abstract
1 Introduction
2 Factors Affecting Unsafe Behavior
3 Method
3.1 Measures
3.2 Analysis of Influences
3.2.1 Direct Influence Matrix
3.2.2 Comprehensive Influence Matrix
3.2.3 Influence Degree, Center Degree and Cause Degree
3.2.4 Integrated DEMATEL/ISM Method Calculation
3.2.5 Multi-Level Hierarchical Interpretation Structure Model
4 Results
5 Discussion
6 Conclusion
Acknowledgments
References
Study on the Information Flow for Construction Project Safety Management
Abstract
1 Introduction
2 Literature Review
3 Research Approach
3.1 Framework of the Safety Information Flow Model
3.2 Data Collection for Metadata and Flowing Pattern of Information
3.3 Data Collection for Right and Responsibility to Handle Safety Information
3.3.1 Allocating Right and Responsibility to Handle Safety Information
4 The Safety Information Flow Model
4.1 Overview of the Safety Information Flow Model
4.1.1 Overview of Module 1: Outline of Information Flow
4.1.2 Overview of Module 2: Right and Responsibility in Handling the Data
5 Discussion and Result Analysis
6 Conclusion
Acknowledgment
References
Factors Influencing Construction Workers’ Safety Behaviours in the Off-Site Manufacturing Plants: A Conceptual Framework
Abstract
1 Introduction
2 Literature Review
2.1 Theory of Planned Behaviour
2.2 Model Modification and Extension
2.3 Concepts
2.3.1 Attitude Toward the Behaviour
2.3.2 Subjective Norm
2.3.3 Perceived Behavioural Control
2.3.4 Intention to Work Safely
2.3.5 Safety Behaviour
2.3.6 Situation Awareness
2.3.7 Behavioural Habit
3 Innovations of the Conceptual Model
4 Conclusions and Directions for Future Research
Acknowledgment
References
Author Index
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Fenjie Long · Sheng Zheng · Yuzhe Wu · Gangying Yang · Yan Yang Editors
Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate
Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate
Fenjie Long Sheng Zheng Yuzhe Wu Gangying Yang Yan Yang •
•
•
•
Editors
Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate
123
Editors Fenjie Long Guizhou Institute of Technology Guiyang, Guizhou, China Yuzhe Wu Department of Land Management Zhejiang University Hangzhou, Zhejiang, China
Sheng Zheng Department of Land Management Zhejiang University Hangzhou, Zhejiang, China Gangying Yang Guizhou Institute of Technology Guiyang, Guizhou, China
Yan Yang College of Economics and Management Guizhou Institute of Technology Guiyang, Guizhou, China
ISBN 978-981-15-3976-3 ISBN 978-981-15-3977-0 https://doi.org/10.1007/978-981-15-3977-0
(eBook)
© Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate
Editorial Board Fenjie Long Sheng Zheng Yuzhe Wu Gangying Yang Yan Yang Jiaming Shan Yuxuan Chen Xiaofeng Sun Zhiyi Xu Hui Tang Kai Wang Liang Long Xiongjin Wang Qun Du Xinyi Yang
Guizhou Institute of Technology Department of Land Management, Zhejiang University Department of Land Management, Zhejiang University Guizhou Institute of Technology College of Economics and Management, Guizhou Institute of Technology Department of Land Management, Zhejiang University Department of Land Management, Zhejiang University Department of Land Management, Zhejiang University Department of Land Management, Zhejiang University College of Economics and Management, Guizhou Institute of Technology College of Economics and Management, Guizhou Institute of Technology College of Economics and Management, Guizhou Institute of Technology College of Economics and Management, Guizhou Institute of Technology College of Economics and Management, Guizhou Institute of Technology College of Economics and Management, Guizhou Institute of Technology
Acknowledgements The symposium gratefully acknowledges the support of the organizations below.
v
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Proceedings of the 23rd International Symposium
Conference Organizer The Chinese Research Institute of Construction Management (CRIOCM) Guizhou Institute of Technology (GIT)
Co-organizers College of Urban and Environmental Sciences, Peking University Research Center of Urbanization and Industrial Development, School of Civil Engineering, Tsinghua University Hang Lung Center for Real Estate, Tsinghua University School of Public Affairs, Zhejiang University Real Estate Research Institute, Xi’an Jiaotong University International Research Center for Sustainable Built Environment, Chongqing University Department of Real Estate and Construction, The University of Hong Kong Department of Building and Real Estate, The Hong Kong Polytechnic University Institute of Public Project and Engineering Cost, Tianjin University of Technology Real Estate Research Institute, Guizhou University of Finance and Economics Guangdong Zhongjianpulian co., LTD Department of Land Economy, University of Cambridge China Future City Lab, Massachusetts Institute of Technology International Journal of Construction Management Journal of Urban Management
Advisory Committee (In Alphabetical Order by Last Name) Changhong Bai K. W. Chau Abdol R. Chini Zuoji Dong Changchun Feng Roger Flanagan Kemei Hu Hongyu Liu Roger-Bruno Richard Geoffrey Shen Weiguo Song Cifang Wu Zhangping Xin Guohua Zhang Yiming Zhao
Nankai University The University of Hong Kong University of Florida, USA Ministry of Land and Resources of China Peking University University of Reading, UK Ministry of Ecology and Environment of China Tsinghua University Université de Montréal, CAN The Hong Kong Polytechnic University Ministry of Science and Technology of China Zhejiang University Urban Problems Journal National Development and Reform Commission Ministry of Housing and Urban-Rural Development of China
Proceedings of the 23rd International Symposium
vii
Organizing Committee Chairman Fenjie Long Yuzhe Wu
Guizhou Institute of Technology Zhejiang University
Executive Chairman Gangying Yang
Guizhou Institute of Technology
Secretary-General Wilson W. S. Lu Yan Yang
The University of Hong Kong Guizhou Institute of Technology
Executive Secretary-General Jing Qiao Li Zhou Sheng Zheng
Guizhou Institute of Technology Guizhou Institute of Technology Zhejiang University
Members (In Alphabetical Order by Last Name) Helen X. H. Bao Lin Chen Jianqun Chu Zhikun Ding Shan Hai Rowson K. H. Lee Dezhi Li Weidong Xinhai Lu Yi Peng Zhejiang Chengshuang Sun Yongtao Tan Siu Wai Wong Jing Wu Zhigang Wu Donglang Yang Gui Ye Kunhui Ye Yilin Yin Mingxuan Yu Hongping Yuan Xiaoling Zhang
University of Cambridge, UK Guangzhou University Peking University Shenzhen University Construction Engineering Quality Supervision in Shenzhen Hong Kong Continuing Professional Education Centre Southeast University Liu Zhejiang University Central China Normal University University of Finance and Economics Harbin Institute of Technology The Hong Kong Polytechnic University The Hong Kong Polytechnic University Tsinghua University South China Normal University Xi’an Jiaotong University Chongqing University Chongqing University Tianjin University of Technology Renmin University of China Southwest Jiaotong University City University of Hong Kong
viii
Zhenyu Zhao Vivian W.Y. Tam Bo Xia Siqi Zheng Jian Zuo
Proceedings of the 23rd International Symposium
North China Electric Power University University of Western Sydney, Australia Queensland University of Technology, Australia Massachusetts Institute of Technology, USA The University of Adelaide, Australia
International Academic Committee Chairman Liyinn Shen Martin Skitmore
Chongqing University Queensland University of Technology, Australia
Members (In Alphabetical Order by Last Name) Haijun Bao Edwin Hon-wan Chan Stuart Green Miklos Hajdu Xianjin Huang Xiaohui Huang Heng Li Qiming Li Anita M. W. Liu Jian Lin Guiwen Liu S. P. Low Wilson W. S. Lu Ping Lv Mona Shah Jonathan Shi Miroslaw J. Skibniewski Michael C. H. Yam Jiayuan Wang Jianping Wang Shouqing Wang Tingfang Wu Xiaolong Xue Hongping Yuan Gui Ye Hong Zhang Hong Zhang George Zillante Saixing Zeng
Zhejiang University of Finance and Economics The Hong Kong Polytechnic University University of Reading, UK Szent Istvan University, Hungary Nanjing University The Hong Kong Polytechnic University The Hong Kong Polytechnic University Southeast University The University of Hong Kong Peking University Chongqing University National University of Singapore, Singapore The University of Hong Kong Renmin University of China National Institute of Construction M&R, India Louisiana State University, USA The University of Maryland, USA The Hong Kong Polytechnic University Shenzhen University Guizhou Institute of Technology Tsinghua University Guizhou University of Finance and Economics Guangzhou University Southwest Jiaotong University Chongqing University Tsinghua University Zhejiang University The University of Adelaide, Australia Shanghai Jiaotong University
Proceedings of the 23rd International Symposium
Patrick X. W. Zou Jian Zuo
ix
Swinburne University of Technology, Australia The University of Adelaide, Australia
Conference Secretariat Xiongjing Wang Hui Tang Xiaoji Zhang Xinyi Yang
Guizhou Guizhou Guizhou Guizhou
Institute Institute Institute Institute
of of of of
Technology Technology Technology Technology
Contents
How Efficient is the Urbanization Process in China? . . . . . . . . . . . . . . . Yitian Ren, Weisheng Lu, Liyin Shen, Yu Zhang, and Zhi Liu
1
Empirical Study on the Performance of Environmental Efficiency in the Chinese Provincial Capital Cities . . . . . . . . . . . . . . . . . . . . . . . . . Yu Zhang, Jindao Chen, Yitian Ren, and Ya Wu
16
Re-Assessing Sustainable Urban Development from the Resident Perspective: A Case Study of Shanghai . . . . . . . . . . . . . . . . . . . . . . . . . Hongyun Si, Daizhong Tang, Quanwei Xu, and Guangdong Wu
29
Rethinking “New Countryside Construction”: Lessons Learnt from the Guangzhou Luogang District, China . . . . . . . . . . . . . . . . . . . . Yao Dai, Siu Wai Wong, Bo-Sin Tang, and Jinlong Liu
53
Study on the Development Mode and Promotion Strategy of Tourism-Oriented Characteristic Small Town in Jiangxi Province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qunhong Liu and Shuoyang Li Temporal-Spatial Evolution Patterns of Population Urbanization and Land Urbanization in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xi Yang, Xinhai Lu, Ruihong Liu, Zexiu Chen, Nan Ke, and Weichen Shen Dynamic Causal Linkages Among Urbanization, Energy Consumption, Pollutant Emissions and Economic Growth in China . . . Munir Ahmad, Zhen-Yu Zhao, Marie Claire Mukeshimana, and Muhammad Irfan
66
77
90
Study on Competitiveness Evaluation of the Intangible Cultural Heritage Town Based on Porter Diamond Model . . . . . . . . . . . . . . . . . . 106 Mei Lu, Xingdi Tong, and Qi Li
xi
xii
Contents
The Thinking on Spatial Management and Control of “Urban Growth Boundaries” from the Perspective of Natural Resources . . . . . . . . . . . . 122 Zhiyi Xu and Yuzhe Wu Evaluation on Performance of Ecological Welfare of Characteristic Small Town——A Case in Chongqing . . . . . . . . . . . . . . . . . . . . . . . . . . 136 Jiuxia Tan, Yu Zhao, and Hao Wu Problems and Countermeasures of Characteristic Development of Small Towns in Qiannan Prefecture . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Tong Yuesong and Wang Chao How Weather Retain Migrants? Evidence from Floating Population Dynamic Monitoring Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Chengen Wu and Xiaonan Zhang Measurement of New Urbanization Construction Level and Diagnosis of Obstacle Factors——A Case of Urban Cluster in the Central Plains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Han Jing, Yang Chun, Ke Nan, and Lu Xin-hai Study on the Impact Between Rapid Urbanization and Fire Safety Management——A China Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Ying Zhang Study on Land-Use Efficiency Evaluation of Development Zones Based on DEA—Take Hi-Tech Zones as an Example . . . . . . . . . . . . . . . . . . . . 198 Yi Li and YuZhe Wu The Evaluation of Land Development and Utilization Based on 11 Prefecture-Level Cities in Hebei Province . . . . . . . . . . . . . . . . . . . 214 Yongsheng Wang, Yuan Zhang, Yulong Li, and Guijun Li The Study of the Expansion of Urban Functional Land in Ganzhou . . . 226 Xiying Hu, Cuiping Huang, and Wei Wu Temporal-Spatial Evolution Characteristics of Economic Development of Hangzhou Bay Area and Its Influencing Factors . . . . . 235 Na Liu and Yuzhe Wu Impacts of Land Expropriation on the Entrepreneurial Decision-Making Behavior of Land-Lost Peasants: An Agent-Based Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251 Haijun Bao, Hao Dong, Jinshui Jia, Yi Peng, and Qiuxiang Li Analysis of the Land Use Situation of China in the Last Decade . . . . . . 269 Juan-er Zheng, Ling-xia Cao, Wen-bin Tan, and Feng Deng Research on the Governance Modality of Village-in-City Based on Mitchell Score-Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 Qin Wang and Yuzhe Wu
Contents
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The Legislation of Transfer of the Right to Use Homestead . . . . . . . . . . 305 Jianfeng Ye and Yuzhe Wu Measures of Fire Protection Design for Embedded Substations . . . . . . . 317 Xiner Luo, Hong Yang, Peng Yu, and Changfu Sun The Conceptual Model of Belt and Road Infrastructure Projects . . . . . 325 Jelena M. Andrić, Jiayuan Wang, Patrick X. W. Zou, and Ruyou Zhong Developing a Fuzzy Evaluation Model of Safety Management for Urban Water Environment Rehabilitation Project . . . . . . . . . . . . . . . . . 341 Xingxiu Wang, Zhengqiang Yu, Tinglin Wang, Jian Liu, Zengwen Bu, and Liu Ru Total Safety Management Practice in an Urban Water Environment Rehabilitation Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353 Na Li, Weidong Huang, Jian Liu, Yunchu Chen, Zengwen Bu, Kejun Luo, and Shujie Guan Application of Causal Analysis Method in Quality Management of the Maozhou River Rehabilitation Project . . . . . . . . . . . . . . . . . . . . . 365 Min Dong, Huaxiang Zhao, Kejun Chen, Xiaoling Qin, Jian Liu, Gang Wang, and Jun Wang Environmental Management Scheme of EPC Model for Water Environmental Treatment Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 Dongjie Chen, Yunchu Chen, Ningkang Li, Hui Zhang, Huabo Duan, Jian Liu, and Peiwen Sun Innovative Bioretention Facility for Siphonic Drainage System . . . . . . . 390 Zhan Yuan, Jianying Pan, Jian Liu, Xiaolei Wang, Zengwen Bu, and Lingyi Wu Estimating the Redistribution Effect of Affordable Housing on Income Distribution: Case Study of Nanjing . . . . . . . . . . . . . . . . . . . 397 Junjie Li Research on Relationship Between the Real Estate Prices and Technological Innovation Through Human Capital in China . . . . . . . . . 412 Zhang Hong, Chen Yingying, and Li Vera Research on the Commercial House Price of Supply and Demand Elasticity Based on the Panel Data of China’s Four Municipalities . . . . 426 Yanming Lyu and Mengxue Chen Capitalization of Urban Public Service Based on Urban Administrative Hierarchy: Evidence of Housing Prices from 281 Cities of China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 Junhua Chen, Siyu Chen, Dingwen Zheng, and Yanhui Hao
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Contents
Overseas Social Security Housing Construction Pattern and Its Enlightenment to China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 Zou Run-yan, Huang He, Wen Jia-ming, Ying Qian-liang, Li Hong-yi, and Dan Cheng-long Research on Demand Forecast of Social Pension Facilities: A Case Study of Chongqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457 Yu Zhao, Jiuxia Tan, and Yang Chen An Evolutionary Game Analysis on the Choice of Urban Housing Purchase Restriction Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 Guancen Wu, Shanshan Xi, and Huan Chen Multi-objective Optimization for the Portfolio Selection on Economic Prefabricated Component . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493 Y. H. Gao and C. Mao Exploration on the Path of Integrating State-Owned Public Housing into the Housing System—Based on the Perspective of Social Network Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503 Wenyue Ma, Ping Lyu, Miao Yu, and Bowen Yang Household Registration Discrimination and Housing Choice for Migrant Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516 Wei Wei Study on the Relationship Between Housing Land Supply and Housing Price in Cities with Different Economic Development Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529 Yuxuan Chen and Yuzhe Wu The Impact of Demographic Structure on Housing Price in Beijing Based on System Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 546 Zhang Hong, Gao Wen, and Li Vera A Review of the Application of Hedonic Pricing Model in the Nigerian Real Estate Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 Rotimi B. Abidoye and Albert P. C. Chan Research on the Large-Scale Development of Prefabricated Buildings Using System Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 570 Yu Bian, Clyde Zhengdao Li, and Ru Sun Study on the Policy Efficiency of Real Estate Tax Reform to Local Real Estate Market Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 580 J. M. Shan, X. P. Chen, and Y. Z. Wu Research on the Allocation of Excess Revenue Between Public and Private Sectors in Mega Construction Projects . . . . . . . . . . . . . . . . 591 Qinghua He, Ting Wang, Daoan Fan, and Dongqi Wang
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A Conceptual Framework for Identifying Performance Indicators of PPP Urbanization Projects Based on Sustainability Goals . . . . . . . . . 604 Juankun Li, Wei Xiong, and Shiquan Wang The Risk Sharing Mechanism of Developing Characteristic Town in PPP Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617 Huang Yanqing, Yang Jianlin, and Zhou Hongji Research on the Development of Green Real Estate Finance in Guizhou Province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629 Kewen Zhang 3D Point Cloud Data Enabled Facility Management: A Critical Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641 Jinying Xu, Ke Chen, Fan Xue, and Weisheng Lu Assessing Performance Characteristics of Concreting Equipment: Reliability Engineering Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 658 A. Ghosh, A. Hasan, and K. N. Jha Social Impacts of Adopting Robotics in the Construction Industry: A Systematic Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 668 Bashir Tijani and Yingbin Feng Prefabricated Construction: A Bibliometric Analysis . . . . . . . . . . . . . . . 681 Yulun Pan, Huanyu Wu, Jiguo Wang, Jingru Ll, and Jian Zuo Text Mining Based Exploration of Smart City Building Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 694 Zhikun Ding, Zongjie Li, and Ting Hu BIM Research Progress in Chinese Construction Industry: Based on Chinese First-Tier Literature Statistical Analysis . . . . . . . . . . . . . . . 710 Zhang Shang, Liang Yehua, and Shane Galvin Visualization Analyses Using Citespace on Researches of BIM Development from 2003 to 2017 . . . . . . . . . . . . . . . . . . . . . . . . 720 R. B. Wang, P. Mao, J. Li, and Q. Wang The Integrated Technology of BIM5D and VR is Applied in the Construction Management of Building Engineering . . . . . . . . . . . 732 Min Zhou and Jiayuan Wang Research on the Efficiency of 3D Collaborative Design Based on P-BIM Cloud Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 747 Fuping Zhou, Jiayuan Wang, Gejing Shang, and Jingya Li Research on the Whole Life Cycle Information Management System of Prefabricated Building Based on BIM+ . . . . . . . . . . . . . . . . . . . . . . . 763 Xingchong Wang, Bo Yu, and Jiayuan Wang
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Constructing a Building Information Modelling (BIM) Execution Plan for Quantity Surveying Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 778 Jing Wang, Anna Zetkulic, and Weisheng Lu The Management of Full Life Cycle for Architecture Based on BT and BIM Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 791 Zengwen Bu, Hong Yang, and Xingxiu Wang A Framework of BIM-Based Value for Money (VFM) Evaluation Methods of PPP Projects at Decision-Making Stages . . . . . . . . . . . . . . . 797 Xiaoyan Jiang, Wenfeng Ouyang, Xiaoya Dai, Kang Hu, Yong Liu, and Bo Xia Research on the Connection of Big Data and Construction Management Based on Histcite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 808 Hongyang Li, Yousong Wang, Nanxi Ouyang, Yuyan Lin, and Cheng Wen A Holistic Evaluation of Low Carbon City Performance in the Context of Low Carbon Pilot Cities in China . . . . . . . . . . . . . . . . . . . . . . . . . . . 819 Xiaoyun Du and CongHui Meng Analysis on the Influence Factors of the Inert Construction Waste Recycling in Chongqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 839 S. Y. Sun Comprehensive Evaluation of Urban Ecological Carrying Capacity ——A Case Study of Chongqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 854 Li Qiulin Overview and Analysis on the Effectiveness of Indicator Systems for Evaluating Urban Carrying Capacity . . . . . . . . . . . . . . . . . . . . . . . . 869 Zhi Liu, Yitian Ren, and Liyin Shen Prediction on the Contribution of Green Building Development to Carbon Emissions Reduction: A Case Study of Chongqing . . . . . . . . 888 Mengcheng Zhu, Vivian W. Y. Tam, Liyin Shen, and Yu Zhang Evaluation of Low-Carbon City Construction Maturity—A Case Study of Chongqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 900 Linyan Luo, Qingqing Wang, and Xiaoyun Du Study on Evolution of Urban Carrying Capacity of Resources and Environment Under the Background of Big Data . . . . . . . . . . . . . . 918 Jinhuan Wang Comparison of Evaluation Standards for Green Building . . . . . . . . . . . 931 Wenjing Cui, Lin Zhang, and Jianghong Cao
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When to Maximize Green Benefits in the Construction and Engineering Industry? Perspectives from Risk Modifying Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 945 Qian Xu and Yujie Lu Characterizing the Flows of Construction and Demolition Waste in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 956 N. Zhang, H. B. Duan, P. S. Huo, L. N. Zheng, and H. Zhang Innovative Design of the Sponge City Facilities in Changzhen Depot . . . 965 Yan Liu, Xiaolei Wang, Jian Liu, Jianying Pan, Zengwen Bu, and Lingyi Wu Carbon Emission of on Site Logistics for Tall Buildings . . . . . . . . . . . . 979 Xiaoqing Lu, Yuan Fang, and Yanjing Zeng A Queuing Model to Improve the Utilization of Concreting Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 992 A. Hasan, N. R. Sahoo, A. Ghosh, and K. N. Jha A Paradigm Shift from Green Buildings to Sustainable Cities: Concept and Future Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1003 Cheng Siew Goh, Steve Rowlinson, and Chen Wang A Model for Predicting the Generation of Demolition Waste During the Urban Renewal Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1014 Bo Yu, Jiayuan Wang, Zhengdao Li, Huanyu Wu, Yani Lai, and Jie Li Research on Forecast of Economic Benefits of Reduction Management of Construction Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1028 Jingrong Zhang, Jiayuan Wang, and Bo Yu Occupant Behavior in Energy Efficiency: A Case Study in Sydney . . . . 1040 Vivian W. Y. Tam, Laura M. M. C. E. Almeida, and Khoa N. Le Gaps Between Supply and Demand of Recycled Aggregate: A Sydney Metropolitan Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1050 Vivian W. Y. Tam, Farid Sartipi, and Khoa N. Le How Does China’s Low Carbon Pilot Program Perform? Evidence from the First Batch of Low-Carbon Pilot Provinces . . . . . . . 1060 Wu Ya, Shuai Chenyang, Zhang Yu, Chen Jindao, and Song Xiangnan Mechanical Lasting Effectiveness of Carbon-Conditioning on Mixed Recycled Aggregate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1074 Vivian W. Y. Tam, Anthony Butera, and Khoa N. Le Life-Cycle Assessment of Economic and Environmental Benefits of Green Residential Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1081 Zhikang Bao, Yuzhe Li, Jianli Hao, Weisheng Lu, and Chee Seong Chin
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A Practical Model to Assess Life-Cycle Greenhouse-Gas Emissions for Australian Commercial Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . 1097 Cuong N. N. Tran, Vivian W. Y. Tam, Khoa N. Le, and I. M. Chethana S. Illankoon Optimum Solutions for Green Buildings: A Life-Cycle Cost Perspective Considering Transport and Land Use and Ecology Credits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1106 Illankoon M. Chethana S. Illankoon, Vivian W. Y. Tam, Khoa N. Le, and Cuong N. N. Tran Preferences and Willingness-to-Pay for Vertical Greenery Systems in Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1118 Ziyou Huang, Yujie Lu, and Xiangnan Song Methods to Mitigate the Negative Effects on Durability of Recycled Aggregate Concrete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1132 Vivian W. Y. Tam and Mahfooz Soomro Study on Countermeasures of Rural Living Environment Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1145 Gui Ye, Siyu Luo, Yi Chen, and Yuhe Wang Sustainability Assessment for Rural Community Generated from Land Consolidation: A Case Study in China . . . . . . . . . . . . . . . . . 1157 Yi Peng, Xinbing Gu, Xiaodong Zhang, and Zhimin Wang Thinking on Spatial Restructuring of Traditional Villages in the Ancient Miao Territory Corridor Under the Ground of Rural Revitalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1172 Dong Wang, Geng Ma, and Heng Liu Investigation, Development and Application of Wood Structure Dwellings in Qiannan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1185 Guiman Xu and Haiya Han Research on Renewable Energy Utilization in the New Countryside in Qinba Mountain: A Case Study in Bazhong, Sichuan Province . . . . . 1194 Zhuoling Zhong, Jiayuan Wang, and Cheng Fan Research on the Welfare of Homestead Transfer Under the Background of Targeted Poverty Alleviation—Based on Sen’s Feasibility Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1212 Ping Lv and Yuewen Gu Optimising Facilities Provision in Retirement Villages - A Case Study in Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1225 Bo Xia, Ayokunle Olanipekun, Xin Hu, Qing Chen, Xiaoyan Jiang, and Yong Liu
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Design of “Point Spirit” Cultural Heritage Protection Mobile Platform Based on LIDAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1237 Jie Zhao, Mengtian Cao, Shufang Wu, and Zhigang Wu Discovering Spatial Interdependencies from Mobile Phone Data and Transportation Data: Evidence from Guizhou Province . . . . . . . . . 1246 F. J. Long, L. F. Zheng, and L. Shi Research Trends of Information Technology Application in Construction Workers’ Behavior Monitoring . . . . . . . . . . . . . . . . . . . 1256 Gui Ye, Ran Lu, Jingjing Yang, and Xiaoyu Tang The Visualization Analysis of Organizational Information Ecosystem Development Based on Social Networks . . . . . . . . . . . . . . . . . . . . . . . . . 1269 Wenjia Guo, Junwei Zheng, and Hongtao Xie Research on the Mechanism of the Economic Compensation to Prefabricated Building Based on the Loss of Developers’ Revenue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1282 Yang Chen, Hao Wu, and Jiuxia Tan The Correlation Between Intangible Assets and Business Performance of Listed Construction Enterprises in China . . . . . . . . . . . . . . . . . . . . . 1295 Yousong Wang, Jing Huang, and Hongyang Li Structure Analysis of Information Flow in Project Design Stage Based on Information Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1309 Yunshan Jiang, Pengpeng Xu, Chao Mao, and Yan Fu The Influence of Culture Value of Civil Engineering Projects on Their Life-Span . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1325 Zhuxin Tang, Xinyuan Wang, Xumeng Zhang, Bingbing Hu, Yunyi Wang, and Jie Li Typhoon Risk Perception and Positive Coping Behaviors of Middle School Students in Ningbo City . . . . . . . . . . . . . . . . . . . . . . . 1347 Yi Peng and Fuying Zhang Research on the Mechanism of Influencing Factors of Construction Workers’ Unsafe Behavior Based on DEMATEL and ISM . . . . . . . . . . 1361 Gui Ye, Lijuan Yang, Jing Liu, and Yuan Fu Study on the Information Flow for Construction Project Safety Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1373 Yee Sun Hung, Jinjing Ke, and Xiaowei Luo
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Factors Influencing Construction Workers’ Safety Behaviours in the Off-Site Manufacturing Plants: A Conceptual Framework . . . . . . 1383 Qinjun Liu, Gui Ye, Yingbin Feng, and Minh Tri Trinh Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1395
How Efficient is the Urbanization Process in China? Yitian Ren1,2(&), Weisheng Lu3, Liyin Shen1,2, Yu Zhang4, and Zhi Liu4 1
2
School of Management Science and Real Estate, Chongqing University, Chongqing, China [email protected] IRCSBE (International Research Centre for Sustainable Built Environment), Chongqing University, Chongqing, China 3 Department of Real Estate and Construction, University of Hong Kong, Pokfulam, Hong Kong, China 4 Chongqing University, Chongqing, China
Abstract. China has been witnessing an unprecedented urbanization process since the implementation of reform and opening policy in 1980s. And the blueprint of Chinese urbanization program will continue for the coming future. Nevertheless, the rapid urbanization progress in China has been consuming vast amount of resources, and the conflicts between limited resources and rapid urbanization development has become much more intensified. It is therefore essential to pursue and improve efficiency during the urbanization construction in order to save resources and achieve urbanization sustainability. This study investigates the efficiency of Chinese urbanization construction by employing “I-O” (input-output) indicators with considering not only desirable output also the undesirable outputs of urbanization construction. The Super-efficiency SBM (Slack-based Measure) model is adopted for conducting the analysis, and the research data are collected from 30 Chinese provinces during 2008–2015. The analysis results tell that the average performance of urbanization efficiency at national level in China is relatively low, though an improvement has been achieved during this surveyed period (2008–2015). There is significant variation between top performers and bottom players, and the results suggest that those socially and economically advanced provinces are found to be more efficient in the process of urbanization construction. It is also discovered that East China is much more advanced on the efficiency performance during the urbanization process, however Southwest region presents the lowest urbanization efficiency performance during the time period of 2008–2015. Keywords: Urbanization efficiency “I-O” (Input-output) dimensional indicators Desirable and undesirable output Super efficiency-SBM model China
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1–15, 2021. https://doi.org/10.1007/978-981-15-3977-0_1
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Y. Ren et al.
1 Introduction Urbanization epitomizes the development of human society and is an important social process in developing countries. And this is particularly the case in China [1, 2]. Since early 1980s, China has witnessed a dramatic and unprecedented urbanization process, the national urbanization level increased from 17% to 58% during the year 1978–2017, with an average increase rate of more than 1% annually [2]. Comparatively, the average annual increase rate of urbanization development worldwide is only less than 0.5% [3]. Whilst the urbanization progress in China has been consuming huge amount of resources, for example, water, timber, coal, other natural resources and labor forces [4]. For example, it is reported that more than 400 Chines cities are facing the problem of water shortage, and among these cities, more than 200 are under severe shortage or water resources, which jeopardizes the urbanization development in these cities [4, 5]. However, resources particularly those non-renewable resources are of limitation, especially for the country such as China which carries on large scale of population. The conflicts between limited resources and urbanization development in developing countries have been widely appreciated [4], this is particularly the case in large developing countries like China. With the aim of saving resources and achieving the sustainability of urbanization process, it is important to pursue and improve efficiency during the urbanization construction. Furthermore, a proper and adequate understanding about whether the resources are utilized efficiently is considered as a helpful approach not only for evaluating the quality of urbanization development but also for assessing the level of resource waste during urbanization construction process. Urbanization can be appreciated as a complex “input-output” systematic development process, and the efficiency of urbanization process can be assessed by examining and comparing the benefits or outputs to the resources consumed (inputs) [6]. An urbanization process with high efficiency is defined that the process generates more benefits whilst consumes less resources. Different types of economic development mode and different industrial structures will lead to different urbanization efficiency performance [7]. By evaluating scientifically the urbanization efficiency of individual provinces and regions, the experience from top performers and the lessons from bottom players can be mined and shared, which can further enable the efficiency improvement across the whole country of China. And the urbanization efficiency improvement can also provide valuable references for the efficiency upgrading in other developing countries worldwide. Based on the above information, this study aims to examine holistically and properly the efficiency of current urbanization construction in China, and analyze the experiences and lesson in terms of efficiency performance from different provinces and regions during its urbanization practice. Measures for improving urbanization efficiency will also be investigated to promote the sustainable urbanization development.
How Efficient Is the Urbanization Process in China?
3
2 Research Method Super-efficiency SBM (Slack-based Measure) model is employed in this study to investigate the efficiency performance of urbanization construction process in China. Based on the studies of Tone and Li et al. [8–11]. The applying procedures of Superefficiency SBM model (with incorporating not only desirable outputs also undesirable outputs) are presented as follows. Assume that an urbanization development system owns n independent and homogeneous decision-making units (DMUs). And each DMU includes three elements, namely, consuming m types of inputs, generating s1 types of desirable outputs, and producing s2 types of undesirable outputs (such as pollutant discharge). The above explanation of parameters is accordingly denoted in details by three independent vectors, namely, vector of input elements, x 2 Rm ; vector of desirable output, yd 2 Rs1 ; and undesirable output vector, yud 2 Rs2 . As assumed above, there are n independent and homogeneous DMUs in an system of urbanization construction, then three matrices: X, Y d and Y ud can be obtained: X ¼ ½x1 ; x2 ; . . .; xn 2 Rmn ; Y d ¼ yd1 ; yd2 ; . . .; ydn 2 Rs1 n ; ud ud 2 Rs2 n ; Y ud ¼ yud 1 ; y2 ; . . .; yn In line with the establish of above three vectors, a production possibility set (P) is then described by the Eq. (1) below: P ¼ f x; yd ; yud jx Xk; yd Yd k; yud Y ud kg
ð1Þ
In Eq. (1), k is the non-negative intensity vector, indicating that above Eq. (1) is under the condition of constant returns to scale (CRS). And the inequality “x Xk” indicates that the actual level of input elements in the urbanization practice is greater than the input level of production frontier. yd Yd k indicates that actual level of desirable output elements is below the desirable output level of production frontier. And yud Y ud k indicates that the actual level of undesirable output elements is greater than the undesirable output level of production frontier. A DMU to be measured is denoted as x0 ; yd0 ; yud 0 , its efficiency to be measured by the Slack-based Measure (SBM) model is described by using the Eq. (2): q ¼ min
1þ
1 s1 þ s2
Pm
s i i¼1 xi0 Ps2 sudr sdr þ d r¼1 y r¼1 yud r0 r0
1 m1 P s1
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Y. Ren et al.
8 > > < Subject to > > :
x0 ¼ Xk þ S yd0 ¼ Y d k Sd ud y0 ¼ Y ud k þ Sud S 0; Sd 0; Sud 0; k 0
ð2Þ
Where S means the redundancy of inputs, Sd refersto the desirable outputs shortage, ud d ud S refers to the undesirable outputs shortage, S ¼ S ; S ; S is called slacks. The efficiency q assumes the values in the range ½0; 1: Only if q ¼ 1, and d ud S ¼d0; Sud ¼ 0; S ¼ 0, then the urbanization construction process of DMU x0 ; y0 ; y0 is appreciated as SBM-efficient. However, if the efficiency value q\1, then the urbanization construction of DMU x0 ; yd0 ; yud is considered not efficient [8, 10]. 0 In most conditions of the efficiency analysis, when the amount of DMU become large, it happens that the q value of some DMUs becomes 1 at the same time, then it will be difficult to further distinguish DMUs by its SBM-efficiency value q, which is obtained by model (2). Thus, in order to further discriminate and rank the DMUs according to their efficiency values, the Super-efficiency SBM model is used as follows. Then, we assume that the DMU x0 ; yd0 ; yud is efficient according to Slack-based 0 Measurement (SBM) model, i.e. q ¼ 1 by employing the Eq. (2). Under this circumstance, to further discriminate the DMU x0 ; yd0 ; yud with other SBM-efficient DMUs 0 d ud and rank the DMU x0 ; y0 ; y0 by a specific efficiency value, which may be larger than 1, a production possibility set Pn x0 ; yd0 ; yud is defined, spanned by X; Y d ; Y ud 0 excluding x0 ; yd0 ; yud 0 , and this production possibility set is described in the following Eq. (3). Xn Xn Pn x0 ; yd0 ; yud k x ; yd k yd ; yud ¼ f x; yd ; yud jx 0 j¼1;6¼0 j j j¼1;6¼0 j j Xn k yud ; yd 0; k 0g j¼1;6¼0 j j
ð3Þ
Then the efficiency performance value of the concerned DMU x0 ; yd0 ; yud 0 , measured by Super-SBM model, which can be larger than 1, denoted as q , is measured by the following Eq. (4): q ¼ min 8 > > >
yud nj¼1;6¼0 kj yud > j > : d x x0 ; yd yd0 ; yud yud ; y 0; k 0 0
ð4Þ
How Efficient Is the Urbanization Process in China?
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3 Research Data This paper investigates the urbanization efficiency of 30 provinces in Mainland China during the time period of 2008–2015, Tibet is excluded from the surveyed provinces because of the data unavailability. 3.1
Establish of Input-Output Dimensional Indicators
In order to employ the method established in Sect. 2 of this study, and measure properly the urbanization efficiency performance of 30 Chinese provinces during the time period of 2008–2015, the inputs and outputs of urbanization construction process should be comprehended and identified. By incorporating previous studies, this study establishes the input-output elements of urbanization construction system, as presented in Fig. 1. The inputs of urbanization construction system include capital, land, labor, water resource and energy. The outputs of urbanization construction system include both desirable outputs and undesirable outputs, for which desirable outputs include population aggregation, economic growth, urbanization habitation, urban living quality, urban landscaping and urban-rural integration, and undesirable outputs include greenhouse gas emission and water pollution.
Fig. 1. The input-output elements of urbanization construction system
In line with the established “input-output” elements of urbanization construction in Fig. 1, and in referring to existing literatures, the specific indicators for measuring urbanization inputs and outputs elements are determined. Table 1 shows the input indicators of urbanization construction process: Urban total investment in fixed assets (I1) for measuring the capital level [12–15]; number of urban employed persons (I2) for the labor level [15–18]; urban construction land area (I3) for measuring the consumption of land [17, 19]; total water consumption (I4) for measuring the water resources consumed [20–24]; and total energy consumption (I5) for measuring the energy invested in the urbanization construction process [21, 25, 26].
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Y. Ren et al. Table 1. Indicators for measuring the input elements of urbanization construction system Input indicator Elements Measuring indicator Capital Urban total investment in fixed assets (I1) Labor Urban employed persons (I2) Land Urban construction land area (I3) Water Total water consumption (I4) energy Total energy consymption (I5)
Table 2 further presents the output indicators of urbanization construction system: Table 2. Indicators for measuring the output dimensions in urbanization process Output indicator Type of outputs Desirabel outputs
Undesirable outputs
Dimension • Population aggregation • Economic increment • Urbanization habitation • Urban living quality • Urban landscaping • Urban-rural integration • Greenhouse gas emission • Water pollution
Indicator Urbanization rate (O1) Non-agricultural GDP (O2) Urban built-up area (O3) Total retail sales of social consumer goods (O4) Green coverage in built-up area (O5) Income ratio of rural to urban residents (O6) CO2 emission (O7) Discharge of wastewater (O8)
The desirable output of population aggregation is assessed by the indicator O1 (urbanization rate) [27, 28], economic increment is assessed by the indicator O2 (nonagricultural) [12, 27, 29], urbanization habitation is measured by the indicator O3 (urban built-up area) [30, 31], urban living quality is measured by the indicator O4 (total urban retails sales of social consumer goods) [32–34], urban landscaping is measured by the indicator O5 (green coverage in urban built-up area) [35, 36], and urban-rural integration is measured by the indicator O6 (income ratio of rural- urban residents [30, 31]. In terms of those undesirable outputs of the urbanization construction process defined in Fig. 1, greenhouse gases emission and water pollution are two most significant undesirable output brought in the urbanization construction process. Accordingly, indicator O7 (CO2 emission) is used to assess the emission level of greenhouse gases, indicator O8 (discharge of wastewater) is used to assess the level of water pollution [37, 38].
How Efficient Is the Urbanization Process in China?
3.2
7
Data Processing
In referring to the established input-output indicators listed in above Table 1 and Table 2, the indicator data of 30 surveyed Chinese provinces during the time period of 2008–2015 are collected respectively from various official statistical publications, including China Statistical Yearbook (2009–2016) and China Energy Statistical Yearbook (2009–2016). Furthermore, in order to ensure the accuracy of analysis result, the monetary variables are converted into the constant prices in the year 2007. Specifically, variable I1 is deflated with the price index of investment in fixed assets, variable O2 is deflated with GDP deflators, and variable O4 is deflated with consumer price index (CPI). In terms of the indicator O7 (CO2 emissions), there is no official statistical publication about the carbon emission at provincial level in China. With this background, in referring to previous study, this research uses the calculation guideline of CO2 emission published by the IPCC (Intergovernmental Panel on Climate Change) [39]. Thus, carbon emission can be calculated by using the Eq. (5) as follows. ECt ¼ 44=12
Xn i¼1
Eti LCVi CFi Oi
ð5Þ
Where ECt refers the total carbon emissions for an individual province from the consumption of n types of fossil fuel in year t. In this study, 8 types of fossil fuel are concerned, namely, natural gas, raw coal, kerosene, fuel oil, gasoline, rude oil, liquefied petroleum gases and diesel oil. And number (44/12) in Eq. (5) indicates the ratio of molecular weight of CO2 (44) to the molecular weight of carbon (12). And Eti denotes the total consumption amount of fossil fuel i in the year t, LCVi refers the lower calorific value of the concerned fuel i, CFi indicates the carbon emission factor of the concerned fossil fuel i, and Oi refers to the oxidation rate of the carbonaceous fuel i. And the above coefficient values of eight types of fossil fuels in China can be obtained from official guideline [40]. Thus the indicator data of O7 of 30 surveyed Chinese provinces during the year 2008–2015 can be calculated accordingly.
4 Data Analysis In line with the research method established in Sect. 2, by employing the empirical research data processed in Sect. 3, the performance value of urbanization efficiency in 30 surveyed Chinese provinces during the year 2008–2015 can be obtained, as shown below in the Table 3.
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Y. Ren et al. Table 3. The analysis results of urbanization efficiency ( q )
Surveyed Provinces
2008
2009
2010
2011
2012
2013
2014
2015
Average Rank of average value
Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shannxi Gansu Qinghai Ningxia Xinjiang Annual average
1.1641 1.2803 1.0032 1.0021 1.0202 1.0015 1.0208 1.0332 1.0228 1.0264 1.0159 0.6236 1.0508 0.6442 1.0128 0.6408 0.5673 0.5250 1.1299 0.4480 1.3835 0.6607 0.4851 0.4954 0.4269 0.5137 1.0116 1.3099 1.0902 0.5562 0.8722
1.1774 1.2686 1.0034 0.5259 1.0202 1.0029 1.0215 1.0347 1.0225 1.0408 1.0185 0.5781 1.0452 0.6805 1.0106 1.0007 1.0008 0.4319 1.1320 0.5319 1.3674 0.5715 0.5561 0.4528 0.3990 1.0002 1.0108 1.1441 1.1024 0.5707 0.8908
1.1791 1.2950 1.0031 0.5819 1.0148 1.0104 1.0243 1.0325 1.0235 1.0364 1.0186 0.5949 1.0266 0.6548 1.0087 0.4381 0.5323 0.4658 1.1355 0.5820 1.3490 0.6578 0.5002 0.4980 0.4381 1.0064 1.0098 1.2162 1.1066 0.5620 0.8667
1.1901 1.2809 0.6669 1.0013 1.0345 1.0122 1.0407 1.0208 1.0193 1.0485 1.0172 0.6055 1.0197 0.6354 1.0241 0.4019 0.5240 0.4655 1.1388 0.5482 1.3442 1.0011 0.4684 0.4994 0.3989 1.0173 1.0056 1.2186 1.1164 0.7198 0.8828
1.1993 1.2436 0.5962 0.6017 1.0482 1.0134 1.0429 1.0192 1.0142 1.0576 1.0142 0.5601 1.0110 0.5839 1.0244 0.3778 0.5947 0.4759 1.1317 0.4367 1.3481 1.0104 0.4672 0.4673 0.3987 1.0018 1.0067 1.2223 1.1019 0.4998 0.8524
1.2006 1.2648 1.0082 0.5693 1.0474 1.0095 1.0357 1.0315 1.0172 1.0089 1.0091 0.5060 1.0130 0.5205 1.0284 0.4022 1.0033 0.5947 1.1213 0.4913 1.3694 1.0065 0.3663 0.5881 0.5395 0.5345 1.0072 1.1798 1.0913 0.4620 0.8676
1.2043 1.2707 1.0106 0.5361 1.0375 1.0053 1.0345 1.0348 1.0152 1.0157 1.0105 0.5018 1.0212 0.4883 1.0296 0.4867 1.0014 0.6786 1.1154 0.4847 1.3646 1.0100 0.3678 0.4715 0.4008 0.5102 1.0044 1.1574 1.0814 0.4401 0.8597
1.1922 1.2818 1.0087 0.5422 1.0377 1.0082 1.0406 1.0322 1.0160 1.0482 1.0197 0.5234 1.0042 0.6295 1.0290 0.5105 1.0001 1.0003 1.1117 0.5773 1.3628 1.0128 0.4311 0.6030 0.5544 0.5277 1.0093 1.2254 1.0803 0.4248 0.8948
1.1884 1.2732 0.9125 0.6701 1.0326 1.0079 1.0326 1.0299 1.0188 1.0353 1.0155 0.5617 1.0240 0.6046 1.0209 0.5323 0.7780 0.5797 1.1270 0.5125 1.3611 0.8664 0.4553 0.5094 0.4445 0.7640 1.0082 1.2092 1.0963 0.5294 0.8734
4 2 17 21 9 16 8 10 13 7 14 24 11 22 12 25 19 23 5 27 1 18 29 28 30 20 15 3 6 26
5 Discussion 5.1
The Performance of Urbanization Efficiency at National Level in China
It can be seen from the analysis result in Table 3 that the urbanization efficiency performance is relatively low during the surveyed period (2008–2015) across the whole country in China, with the evidence that: For each surveyed year, the average urbanization efficiency performance of 30 provinces in China is less than 1, and this average value is only 0.8734 for the whole surveyed time period. Furthermore, the information in Table 3 tells that in 2008, 18 surveyed provinces presented the performance of urbanization efficiency larger than 1, and this figure becomes 20 by the year 2015. This growth indicates that the efficiency performance in China has improved significantly during the surveyed time period.
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In fact, this improvement of Chines national urbanization efficiency is attributed to multiple aspects, for example, the innovation of technology, which enables less carbon emission and wastewater pollution in line with the improvement of productivity. According to the empirical research data processed in Sect. 3 of this study, the annual increase rate of carbon emission at national level decreased significantly from 5.71% during 2008–2009 to only 0.97% during 2014–2015. And the annual increase of wastewater emission has also decreased from 3.05% (2008–2009) to 2.67% (2014– 2015). The analysis result information in Table 3 can also be presented by a graphical approach, as shown in the following Fig. 2. The figure indicates that the performance values of urbanization efficiency present significant variations between both provinces and the surveyed years. And those provinces in the East China region perform better efficiency during the urbanization construction process in the surveyed time period.
Fig. 2. Urbanization efficiency (q ) between individual provinces in China during 2008–2015
And China can also be divided into eight economic zones in terms of economic performance perspective, including Northeast, North Coast, South Coast, East Coast, Middle Yangtze River, Middle Yellow River, Northwest and Southwest, which can be illustrated in Fig. 3.
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Fig. 3. Geographic division of the eight economic regions in China
The analysis result in Table 3 can be further processed to show the average performance value of urbanization efficiency of above eight economic regions in China during surveyed time period. The regional urbanization efficiency performance is described in Fig. 4. The figure further indicates that South Coast region has performed best in terms of urbanization efficiency during surveyed time period (2008–2015). In fact, it is widely appreciated that this region has been devoting great efforts in many aspects to enhance the overall quality of the urbanization development. For example, it was widely reported that the provinces of Guangdong and Fujian, two typical provinces belong to the South Coast region, have been promoting the development of energy saving innovation during the Chinese Eleventh and Twelfth 5-year plans. Figure 4 further tells that the development of urbanization in the regions of North Coast, East Coast and Northeast present relatively good efficiency during the surveyed period, evidenced by the average efficiency performance values of 1.10, 1.02 and 1.02. Nevertheless, the average urbanization efficiency performance in Southwest China is very poor during the surveyed period. Actually the lagged behind condition of urbanization development in Southwest China has also been echoed in previous studies [1, 7, 36], locating at interior China and being at a disadvantage by China’s long term unbalanced development strategies which focus more on the development of East part of the country. Actually, in referring to the research data processed in Sect. 3, the energy consumption and the carbon emission per unit GDP in the Southwest China is much higher than the average level.
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Fig. 4. Average urbanization efficiency performance of eight economic zones in China
5.2
Comparisons Between Provinces on Urbanization Efficiency Performance
Top Performers of Urbanization Efficiency in China. It can be seen from Table 3 that the top 5 urbanization efficiency performers include Hainan, Tianjin, Qinghai, Beijing and Guangdong. This section will take Guangdong as an example to investigate why it can achieve relatively high performance in terms of urbanization efficiency during surveyed period (2008–2015). Guangdong ranked 5th in terms of the performance of urbanization efficiency during surveyed period (2008–2015). In fact, Guangdong has devoted great efforts in promoting energy conservation and improvement of resource utilization during its urbanization construction practice. For example, the implementation of “Green Building Action Implementation Plan”, and a series of policy instruments to conduct green building standards in the aspects of government investment, public rental housing, etc. Driven by the above policy forces, Guangdong has increased green building of more than 8100 104 square meters, and conducted the energy-saving renovation work towards more than 2050 104 square meters in the existing buildings. These measures have helped effectively reduce the undesirable outputs such as carbon mission and wastewater pollution during the urbanization construction process. According to the empirical data described in the Sect. 2 of this study, the annual increase of carbon emission in Guangdong has decreased significantly from 8.7% (2007–2008) to 3.5% (2014–2015).
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Bottom Players of Urbanization Efficiency in China. Table 3 further tells that the provinces of Yunnan, Guangxi, Sichuan, Guizhou, and Shannxi have poorest efficiency performance during the urbanization construction in the surveyed period. These provinces dominantly have weaker economic force, weaker construction foundation, and also lack of sustainable development consciousness. Taking Shannxi as an example, there are lots of resource-dominated towns in Shannxi province, and the industry structures of these townships are overwhelmingly single with the extensive development pattern. Furthermore, the energy consumption amount of Shannxi is huge, which presents great pressure on the mission of carbon reduction. Similarly, the urbanization construction in Guizhou is driven by the extensive development pattern, and overwhelmingly relying on the heavy industry. According to the research data in the Sect. 3 of this study, the energy consumption per unit GDP was 0.95 tce/104 RMB and the carbon emission per unit GDP was 1.15 ton/RMB in Guizhou in the year 2015, whist these two figures are only 0.29 tce/104 RMB and 0.27 ton/RMB in Beijing at the same year.
6 Conclusion This study considers urbanization development as an “I-O (input-output)” systematic process, and points out that an input-output dimensional indicator system (incorporating not only desirable outputs but also undesirable outputs) should be employed to examine effectively the efficiency performance of urbanization process. With adopting the Super-efficiency SBM (Slack-based Measure) model, the research findings indicate that the overall performance of the urbanization construction efficiency in China in the surveyed period (2008–2015) is relatively poor although an overall increment has been made. And the results also indicate that those provinces socially and economically advanced are found to be more efficient in urbanization process. It is also found that significant variations exist on the efficiency performance of urbanization construction between different regions in China. The efficiency performance of East part in China is much more advanced, and Southwest China received the poorest performance of urbanization efficiency during surveyed time period (2008–2015). The findings from this research provide essential references for investigating the quality of current quick urbanization process in the context of China. With receiving the assessment of efficiency performance of individual provinces and analyzing the policy instruments, those poor urbanization efficiency performers can learn from the top performers by implementing various effective measures to transform industry structure, promote innovation in energy saving, and also enhance the quality of public infrastructure and social service, etc. Furthermore, this research also contributes to enriching the literature in the research discipline of urbanization efficiency. And the research framework adopted for examining the holistic perspective in examining the efficiency performance of Chinese urbanization development can also be employed for examining the efficiency performance of urban-rural development in the context of other developing countries internationally.
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Acknowledgement. The research of this conference paper is financially supported by two research funding, namely, National Social Science Foundation of China (Grant No. 17ZDA062), and National Social Science Foundation of China (15BJY038).
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Empirical Study on the Performance of Environmental Efficiency in the Chinese Provincial Capital Cities Yu Zhang1(&), Jindao Chen2, Yitian Ren1, and Ya Wu1 1
2
Faculty of Construction Management and Real Estate, Chongqing University, Shapingba District, Chongqing 400045, China [email protected] Department of Construction Management and Real Estate, Tongji University, Shanghai, China
Abstract. Environmental problem produced by energy consumption in China is the issue that immediately needs to be resolved. City is the economic and social center, which is the main machine for the social economic development. Therefore, Environmental protection is the responsibility of every city. Many cities have started the transformation from extensive economic development mode to the sustainable development mode in order to contribute to the environmental-friendly society. Devoting abundant endeavor and resources to environmental protection, yet, it seems that little is known whether the development is effective. This paper estimates the environmental efficiency (EE) of the 30 Chinese provincial capital cities. Based on the Super-slack-based measure (Super-SBM) model with both undesirable and desirable outputs, we adopted to analyze the environmental efficiency performance of 30 provincial capital cities in 2016. The practical results from this research suggest that there are 13 cities were attained to have achieved ideal whole efficiency, giving the environmental efficiency values of larger than 1. The top environmental efficiency performers are Haikou, Guangzhou and Beijing, indicating that the environmental efficiency performance is commonly better located in eastern China. The worst three are Lanzhou, Taiyuan and Xining mainly located in western China. The results from this study provide valuable references to policy-makers and administrators for designing and adopting effective methods to develop the sustainable development in the Chinese cities. Keywords: Super-SBM model Environmental efficiency Undesirable outputs Sustainable development Provincial capital cities
1 Introduction Since China implemented the economic reform policy and opening up to the world in 1978, the economic development in this country have made extraordinary achievements [1–3]. For instance, China’s economy ranks second in the world since 2010 and over the Japan [4]. City is the economic and social center, which is the main machine for the social economic development [5, 6]. There are 657 cities in 2017 in China, © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 16–28, 2021. https://doi.org/10.1007/978-981-15-3977-0_2
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which is the largest number of cities in the world. Among them, 14 cities has the GDP more than trillions Yuan such as Guangzhou and Shenzhen [7]. The urban economic progress has brought many benefits, such as more job opportunities, increase of income and technologic development. Nevertheless, the economic development mode is widely considered as extensive growth pattern in China, which stands for ineffective in utilizing nature resources [8–10]. The extensive development mode has caused many issues in the country. It was reported that CO2 emissions increased by 2.7 times during the period of 2000 to 2015, volumes of solid wastes augmented by 4.0 times, and wastewater discharged increased by 1.8 times for the same period [11]. Previous studies suggest that the air pollution problem affected by the unparalleled urbanization and economic development in China has turn into one of the dilemmas for the past few years [12, 13]. The study by Yan, et al. [14] shows that many cities in China have suffered water pollution from the dramatic economic development process. In fact, the problem of water pollution is considered as a main risk to health in the country [15, 16]. And soil pollution over the past years was also a serious problem in line with the urbanization progress in China [17]. More seriously, China has experienced an unparalleled pace and scale of urbanization, which is well considered as the major contributor to environmental pollution. The urbanization rate has reached 58.5% in 2017. [18] and is currently estimated to increase to 75% by 2050 [19] which indicates the environmental protection in the urban district will face great challenges. Realizing the extensive development models brought these problems, the Chinese government has been working to resolve these issues by presenting and implementing many laws and policies. For example, Environmental Protection Law [20]. The Chinese government promises to implement the ecological, green and low-carbon development concept strategy in the “13th Five-Year Plan” economic and social development plan [21]. Furthermore, for implementing these laws, policies and strategies, China has been devoting a huge amount of efforts and resources on annual basis. In 2000, the government invested RMB 100 billion to various environmental protection programs [11]. This figure increased by 9 times in 2015. Whereas it is significant to implement these environmental protection initiatives and devote resources for addressing the problems caused. It is also important to understand what efficiency has been received from these efforts, which cities are good performers can share the experience. In other words, resources may be wasted in the process of implementing environmental protection progress. Thus, it is important to examine the EE in the current urbanization practice, thus proper measures can be take to correct or improve the current practice where necessary. And it will also make a great contribution to global environmental protection.
2 Literature Review In the literature, it is essential to use a multi-factor model to properly evaluate environmental efficiency. Data envelopment analysis (DEA) is the usual method to evaluate the efficiency of a production in previous studies. DEA was initially suggested by Charnes, et al. [22] to assessing the comparative efficiency of decision-making units
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(DMUs) in 1978. Later, DEA has been commonly used to evaluate the efficiency between inputs and outputs in numerous different areas such as agriculture, industry and service industry. [23–26]. According to the above researches, DEA method is a useful method to calculate the efficiency of a system in numerous different areas. With regard to environmental efficiency researches, many research results has been done. There are some previous researches using DEA method (as shown in Table 1). The DEA method is generally applicable to measuring the environmental efficiency in many previous studies at industrial and regional levels. For instance, by using DEA, Chang, et al. [23] evaluated the EE of 30 Chinese transportation sectors. Zhou, et al. [27] adopted entropy-DEA model in evaluating the EE of 30 Chinese provincial power industries during the period of 2005 to 2010. Based on DEA model, Wu, et al. [28] evaluated the environmental efficiencies of 30 Chinese provincial industries during 2007–2011. He et al. [29] measured the EE of the socioeconomic sectors at the provincial level in China in 2010 by using DEA method. Lee et al. [30] measured EE of 11 port cities across the word, which shows that the best performance city is Singapore, while Tianjin is the worst. The above results propose that the DEA method has been usually engaged to estimate the environmental efficiency at industrial and regional levels, few of them focus on the Chinese provincial capital city. Therefore, this study aims to measure value of EE in different provincial capital cities in China. Policy implications of the research results will be discussed. These results are estimated to provide the government and managers with a policy development reference to further improve environmental quality based on the ambitious economic development plan promoted by urbanization. The rest of this article is structured as follows. Literature review was provided in Sect. 2. Section 3 introduces the principle of undesirable outputs Super-SBM model. Data source and statistics are presented in Sect. 4. The results and discussion are showed in Sect. 5. Section 6 presented the conclusions.
3 Methodology This paper uses a method to explore the environmental efficiency of Chinese 30 provincial capital cities in 2016, namely, Super-SBM with undesirable outputs. SuperSBM model is an improvement of the traditional DEA method. It is commonly appreciated that there are weighty limits to use the traditional DEA model. According to the research by Tone [42], the traditional DEA method does not consider the excesses in inputs and shortages in outputs (called slacks) in a Decision-Making Unit (DMU). In addition, the traditional DEA method does not consider the undesirable outputs (e.g., environmental pollutes), though the environmental pollutes in a DMU do exist and have important impact on the efficiency of DMU. To surmount the above discussion, the undesirable outputs Super-SBM model is uses in this study [37, 42–44].
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Table 1. The application researches of EE. Researcher Zhang et al. [8] Oggioni et al. [31] Zhou et al. [27] Chang et al. [23] Wu et al. [28] Chang et al. [24] Liu et al. [32] Chen and Jia [33] He et al. [29] Bian and Yang [34] Song et al. [35] Wang et al. [36] Li et al. [37] Yang et al. [38] Chen et al. [39] Zhang et al. [40] Li et al. [41] Lee et al. [30]
3.1
Main concept Eco-efficiency
Method DEA
Eco-efficiency
DEA
Objective area Chinese 30 provincial industrial systems 21 countries’ cement industry
Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency Environmental efficiency
EntropySBM SBMDEA DEA
Chinese 30 provincial power industries Chinese 30 provincial transportation sectors Chinese 31 provincial industries
SBMDEA SBMDEA SBMDEA SBMDEA EntropyDEA SBMDEA DEA
global 27 airlines
SuperSBM SuperDEA DEA SBMDEA DEA SBMDEA
Chinese 30 provincial land transportation sectors Chinese 30 provincial industries Chinese 30 provincial socioeconomic sectors Chinese 30 provinces Chinese 30 provinces Chinese 29 provinces Chinese 29 provinces Chinese 30 provinces Chinese 30 provinces Chinese 30 provinces Beijing 11 port cities in the world
Period 2008 2005 to 2008 2001 to 2010 2010 2007 to 2010 2010 2009 to 2012 2008 to 2012 2010 2006 2002 2010 2000 2008 1991 2010 2000 2010 2001 2010 2005 2011 2005 2009 2011
to to to to to to to
The Super-SBM Model with Undesirable Outputs
Considering the researches by Tone [42–44] and Li et al. [37], the Super-SBM model with undesirable outputs to evaluate EE in a DMU includes the next procedures:
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First, there are n DMUs, which has n m input factors and n s1 desirable outputs and n s2 undesirable outputs. Thus, there are three vectors: x 2 Rm , yd 2 Rs1 , and yud 2 Rs2 . The definition of matrices X, Y d and Y ud as follows: X ¼ ½x1 ; x2 ; ; xn 2 Rmn [ 0; Y d ¼ yd1 ; yd2 ; ydn 2 Rs1 n [ 0; ud ud Y ud ¼ yud 2 Rs2 n [ 0: 1 ; y2 ; yn Now, the production possibility set (P) can be described: P¼
x; yd ; yud jx [ Xk; yd Y d k; yud Y ud k; k 0 :
Where the P is under the condition of constant returns to scale (CRS). According to SBM model proposed by Tone’s theoretical and combined the production possibility set (P), the undesirable outputs SBM model can be measured as follows [44]: Undesirable outputs SBM q ¼ min
P
Þ x0 ¼ Xk þ S yd0 ¼ Y0d Sd Subject to ud y0 ¼ Y0ud þ Sud > > : S 0; Sd 0; Sud 0; k 0 1þs
8 > >
ik ij j i > Pj¼1;6¼k > > > ydrk nj¼1;6¼k ydrj kj þ sdr > > Pn < ud yud kj þ sud tk t j¼1;6¼k ytjP Subject to P s s2 1 1 d d ud ud > 1 s =y þ s > rk r¼1 r k¼1 k =ytk [ 0 s1 þ s2 > > > > S 0; Sd 0; Sud 0; k 0 > : i ¼ 1; 2; . . .; m; j ¼ 1; 2; . . .; nðj 6¼ kÞ; r ¼ 1; 2; . . .; s1 ; t ¼ 1; 2; . . .; s2 ð2Þ In the model (2), the value q can be larger than 1, which is the objective funtion. Therefore, comparing with other DEA models, the undesirable outputs Super-SBM model is more suitable to assess the EE.
4 Data Source and Statistics 4.1
Selection of Indicators and Data Source
Labor force and capital are usually as the basic input indicators [23]. Considering that the sustainable development is indicated by effective use of energy and water [36]. Therefore, labor force and employment of total city, fixed investment, electricity consumption and water consumption are selected as the input indicators for evaluating environmental efficiency. In referring to output indicators, a production process produces have the desirable outputs and undesirable outputs. And, the desirable output is commonly used to measure GDP. Also, urban area of green land is the standard to measure the environmental quality. This study also adopts urban area of green land as desirable output. Environmental pollutants are usually undesirable outputs, which include wastewater, waste gas and waste residue. In this study, volume of industrial wastewater discharged, SO2 (sulphur dioxide emission) and soot/dust emission is the representative undesirable output. DMU is considered to be more efficient if it gets better desirable output with both less input and less undesirable output. All data are from China city statistical yearbook, China environmental statistical yearbook. Appendix 1 shows the input and output indicators of 30 provincial capital cities. Table 2 shows the descriptive statistics of each indicator. Table 3 shows the data of input and output indicators.
5 Results and Discussion 5.1
The Best and Worst EE Analysis
According to the undesirable outputs Super-SBM model in Eq. (2) and the data in Sect. 4, the results of environmental efficiency between Chinese provincial capital cities in 2016 are shown in Table 3. According to the Table 3, the top 3 best performance cities in environmental efficiency are Haikou, Guangzhou and Beijing. The three
22
Y. Zhang et al. Table 2. Input and output indicators for analysis.
Input indicators Labor force Fixed assets investment Energy consumption Water consumption Output indicators GDP Area of Green land Wastewater SO2 Soot (dust)
Unit
Minimum Maximum
Median
Mean
Std.dev
104 persons 104 Yuan 104 kwh 104 ton
34.21
132.00
200.73
180.83
Unit
791.52
8481120.4 115011503.2
33801873.1 34679513.2
22904926.2
580836.00 14860200.00
2203278.00 3493773.03
3360796.77
11445.00
320385.00
46429.5
73333.03
68589.19
Minimum Maximum
Median
Mean
Std.dev
8323994.0 187922597.21 41011667.2 55955162.24 46911106.7 104 Yuan Hectare 3872.00 144524.00 17906.5 32218.97 35373.04 104 ton 507.00 Ton 593.0 Ton 156.0
36599.00 174048.0 83787.0
5244.5 27337.5 24819.5
9339.3 35921.9 32490.9
8930.3 33932.4 24474.2
cities are deliberated the model cities for improving environmental efficiency, which are the model to get win-win balance between the economic development and environmental protection. Thus, the other inefficient Chinese cities are able to learn from their experience for integrated environmental efficiency improvement. On the whole, Guangzhou’s environmental efficiency is higher than others. The reason may be due to the great development of economy, technical innovation and environmental protection in Guangzhou. In the economic part, Guangzhou, China’s first special economic zone, has accomplished impressive achievements in recent years. In the industrial part, environmentally friendly industries are main industries in Guangzhou such as foreign trade export industry and electronic industry. In the environmental part, according to Guangzhou Environmental Status Bulletin in 2016, the government in Guangzhou has been implementing many policies and regulations for environmental protection, such as air quality management policy and soil environmental protection policy. Meanwhile, it also invests much capital and technology to deal with wastewater and solid waste. For another example, Haikou, renowned for its tourism, is also has very high environmental efficiency. The reason for the phenomenon is that the industrial structure in Haikou is dominated by tourism rather than other high pollution and high energy consumption industries. Furthermore, Table 3 indicates that the three worst environmental efficiency cities are Lanzhou, Taiyuan and Xining. The reasons of this phenomenon are in numerous factors. Lanzhou is located in Northwest China in Gansu province, and the economic development is relatively low. Meanwhile, according to Gansu Provincial Environmental Protection Agency, Lanzhou is a typical heavy industry and resource-exhausted
Empirical Study on the Performance of Environmental Efficiency
23
Table 3. Sample research data for the 30 surveyed Chinese provincial capital cities in the year 2016 City
Input indicators
Output indicators
Labor force
Fixed assets investment
Energy consumption
Water consumption
GDP
Area of green land
Wastewater
SO2
Soot (dust)
Beijing
791.52
52609510.84
164491.00
10202704.00
171186681.32
82113.00
8515.00
10257.00
7874.00
Tianjin
286.04
85071789.12
87040.00
8079297.00
119277145.67
33069.00
18022.00
54539.00
57280.00
Shijiazhuang
99.54
37869506.58
49410.00
2257985.00
39531854.28
12423.00
13022.00
85815.00
52705.00
Taiyuan
104.05
13522754.35
36499.00
2348433.00
19710840.44
12655.00
3879.00
15707.00
21897.00
Hohhot
41.14
12332060.94
14819.00
698443.00
21164579.40
14416.00
2339.00
52316.00
79103.00
Shenyang
129.26
10881234.32
71483.00
2714322.00
36989112.38
28724.00
5547.00
37530.00
30130.00
Changchun
125.88
31071016.25
38588.00
1551000.00
39923260.85
18581.00
2548.00
21893.00
24451.00
Harbin
130.40
33611977.53
39362.00
1745478.00
40691456.94
13797.00
4235.00
26217.00
21781.00
Shanghai
627.78
45026736.19
320385.00
14860200.00
187922597.21
131681.00
36599.00
67376.00
72782.00
Nanjing
205.19
36903179.36
132652.00
5247900.00
70044334.87
91674.00
21624.00
28639.00
48592.00
Hangzhou
290.13
38962925.04
65087.00
5839636.00
75450884.93
34211.00
28382.00
39499.00
20414.00
Hefei
148.02
43356108.96
47891.00
1555875.00
41843642.38
18185.00
5130.00
9011.00
11483.00
Fuzhou
156.83
34574346.71
40551.00
1712776.00
41331877.55
11661.00
3696.00
39196.00
67548.00
Nanchang
125.98
30278881.22
42753.00
1473811.00
29043319.64
12290.00
10258.00
13800.00
33926.00
Jinan
135.90
26504676.50
42327.00
2483158.00
43589170.82
15942.00
5993.00
28458.00
54677.00
Zhengzhou
200.85
46673751.93
37259.00
3739035.00
54111807.24
17628.00
7966.00
34898.00
28977.00
Wuhan
213.26
46948162.74
132833.00
4171334.00
79444849.58
23217.00
12623.00
17917.00
54089.00
Changsha
120.93
44637548.39
60558.00
1759889.00
62400952.62
11177.00
4287.00
6634.00
6890.00
Guangzhou
325.23
38037049.13
228850.00
8235701.00
130361322.11
144524.00
19326.00
20726.00
8951.00
Nanning
97.45
25067512.60
55445.00
1488748.00
24697400.05
39718.00
3834.00
9381.00
9693.00
Haikou
51.42
8481120.38
22786.00
703442.00
8387333.30
5665.00
507.00
593.00
156.00
Chongqing
412.88
115011503.15
139456.00
8260454.00
118311478.68
59758.00
25875.00
174048.00
83787.00
Chengdu
552.73
55702579.55
111813.00
3605032.00
81162933.21
31084.00
9262.00
17318.00
19407.00
Kunming
133.60
26142864.15
44968.00
1108310.00
28677095.10
15901.00
5359.00
80083.00
25188.00
Xi’an
199.20
33991768.75
57396.00
2731240.00
41728951.41
20945.00
4030.00
4914.00
2853.00
Lanzhou
68.57
13277614.98
24059.00
1195118.00
15100096.01
7734.00
3342.00
19192.00
15892.00
Xining
34.21
9177092.85
15780.00
769658.00
8323994.09
3872.00
2050.00
56796.00
60483.00
Yinchuan
35.46
11391857.42
11445.00
580836.00
10788441.59
9683.00
3672.00
24366.00
11220.00
Urumqi
72.67
10722266.73
29655.00
2148571.00
16398843.42
28258.00
4489.00
40166.00
34024.00
Guiyang
105.74
22545999.37
34350.00
1544805.00
21058610.12
15983.00
3768.00
40373.00
8475.00
city, which leads to it use more energy and produce more contaminants [45]. It can be found in Table 3 that the value of environmental efficiency only 0.3025 in Xining. Xining is located in western China in Qinghai province. It is not only slower economic development but also backward technology to reduce pollutant emissions. 5.2
A Regional Level of EE Analysis
By applying the Super-SBM model, this paper calculated the input-output environmental efficiency of Chinese provincial capital cities. This research also examined all efficiency characteristics in terms of their geographical distribution. According to the value of efficiency in Table 3, the cluster map of integrated efficiency of the Chinese provincial capital cities is demonstrated in Fig. 1.
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Y. Zhang et al. Table 4. Environmental efficiency value of Chinese provincial capital cities
City Haikou Guangzhou Beijing Changsha Nanning Yinchuan Urumqi Shanghai Changchun Tianjin Zhengzhou Hangzhou Nanjing Hefei Harbin
Environmental efficiency 1.3457 1.2672 1.1561 1.0921 1.0725 1.0547 1.0487 1.0371 1.0349 1.0296 1.0236 1.0086 1.0064 0.7283 0.6582
Rank
City
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Jinan Shenyang Xi’an Fuzhou Hohhot Chengdu Kunming Wuhan Chongqing Shijiazhuang Nanchang Guiyang Lanzhou Taiyuan Xining
Environmental efficiency 0.6515 0.6035 0.5945 0.5858 0.5608 0.5535 0.5350 0.5255 0.4985 0.4802 0.4380 0.4346 0.4090 0.3851 0.3025
Rank 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Fig. 1. A regional level of environmental efficiency in the Chinese provincial capital cities
Empirical Study on the Performance of Environmental Efficiency
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As it can be seen from Fig. 1, 13 cities achieved optimal overall efficiency, giving the environmental efficiency values of more than 1 such as Haikou, Guangzhou, Beijing, Changsha, Nanning, and Yinchuan. And, the environmental efficiency performances of many cities in China were lower than 0.6 such as Xi’an, Xining, Taiyuan, Lanzhou, Guiyang, Nanchang, and Shijiazhuang. It is indicated that these cities have 40% the potential to increase desirable outputs and reduce undesirable outputs. This finding is consistent with _ENREF_14 Li et al. [37] and Song et al. [35], which also suggested that the EE value in China is far from the SBM-efficient and relatively low. In recent years, the economic development in the Chinese cities is growing rapidly with the eco-environment is also deteriorated. Hence, it is widely considered that the intensive economic development is the main development pattern for China to pursue the sustainable. It is worthy noted that from the figure the cities located in the eastern area have better EE performance, which mainly relies on a good geographical position and advantageous policies. Meanwhile, these cities have sound economic foundation, advanced technique and talent resource foundation. Thus, they have the ability to adopt pollution control and energy conservation policies and measures, which contributes to a good environmental efficiency performance.
6 Conclusions By establishing Super-SBM model for assessing the environmental efficiency of the Chinese 30 provincial capital cities, this study suggested that 13 cities were found to have achieved ideal overall efficiency, giving the environmental efficiency values of larger than 1. The cities Haikou, Guangzhou and Beijing are the best environmental efficiency performers, and Lanzhou, Taiyuan and Xining are the worst three. In a word, these good environmental efficiency cities are located in eastern of China. Some western cities also have good environmental efficiency performance, such as Urumqi. The poor environmental efficiency performers are mainly located in western of China. According to the above results, there are important policy implications. Policies for the creation of both rapid economic development and environmental protection would be made through the following proposals based on the different characteristics of EE of the Chinese cities. (1) The best performance cities such as Guangzhou should be facilitated experience -sharing with other cities. The eastern cities should be as the model position, improving environmental efficiency through restructuring themselves industrial structure and upholding the development of innovation technique, improving the third industry’s proportion in the urban economy. (2) For the western cities, the governments should improve management skills and methods, communicating and cooperating more with other cities, which could be avoided secondary pollution. The research team will investigate other Chinese cities’ environmental efficiency such as prefecture-level cities in their further study.
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Re-Assessing Sustainable Urban Development from the Resident Perspective: A Case Study of Shanghai Hongyun Si1(&), Daizhong Tang2, Quanwei Xu2, and Guangdong Wu3 1 School of Public Administration and Policy, Shandong University of Finance and Economics, Jinan 250014, China [email protected] 2 School of Economics and Management, Tongji University, Shanghai 200092, China 3 School of Tourism and Urban Management, Jiangxi University of Finance & Economics, Nanchang 330013, China
Abstract. The measuring method of sustainable development level based on urban official statistics is relatively objective, and an increasing number of countries have used it to assess government performance and city ranking. However, there is still no effective measures to make urban development more resilient and sustainable. This paper investigates the limitations of the existing urban sustainable development assessing methods and reassesses urban sustainability from the perspective of resident perception. First, we refined a sixdimensional evaluation index system by expert interview and literature review. Then, we used the method combining the entropy weight and cloud model to comprehensively measure the sustainability level of different regions in Shanghai. We found that the sustainable development level of the center city, new town, and suburb areas were classified between “middle” and “good”, while the suburb areas were closer to the “middle” level, and the center city, new town areas were closer to the “good” level. The highest sustainable level was found in the center city areas, which exhibited obvious heterogeneity and robustness. The new town’s sustainability level is the second, while it experiences the fastest development speed. From the perspective of the whole city, the resident perceived sustainability of economic living, social security, public service, city environment, and infrastructure have reached the “middle” level and above, with the best assessment for infrastructure. The exception is the perception related to public traffic. This study contributes a new angle of resident perception and the “entropy weight-cloud model” method for conducting an integrated assessment of urban sustainability. While revealing sustainable development level of the whole city, it can also help making a detailed comparative analysis of the sustainability differences from different regions and different dimensions. Keywords: Urban sustainability Resident perception assessment Entropy weight-cloud model
Integrated
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 29–52, 2021. https://doi.org/10.1007/978-981-15-3977-0_3
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1 Introduction According to statistics, nearly 50% of the world’s population of 7.3 billion lived in cities in 2016 [1]; it is estimated that 66% of the world’s population will live in urban areas by 2050 [2]. This could cause widespread challenges for air pollution, traffic congestion, waste management and human health, etc. In 1987, the United Nations World Commission on Environment and Development (WCED) first published the “Our Common Future” report proposing the concept of sustainable development. Since then, the idea of sustainable development has been generally accepted, and sustainable development has become an important standard for countries to assess national, regional, and urban development levels [3]. China and the United States have promoted the behavior of low-carbon and green consumption, and scholars have begun to measure the level of sustainable urban development (SUD) [4–6]. Statistical analyses of urban populations, resources, economic and other official data indicators have been used to calculate and rank the sustainable development of neighboring cities of the same region or type through different types of weights and data standardization approaches [7]. The measuring method of sustainable development level based on official urban statistics is relatively objective, and countries increasingly use them to evaluate government performance and urban ranking. However, there is still no effective measures to make urban development more resilient and sustainable [8]. The essence of SUD is to promote the balance between the human living environment and economic development [9]. Different urban areas have different development states and sustainable contradictions. As such, using the same indicators to measure the sustainability of different cities could distort the conclusions, and more importantly, may lead to the wrong governance measures [10]. On the other hand, if the resident believe that when SUD indicators don’t match the indicators selected by city policy, there may be a tense state characterized in a top-down sustainable development model [11]. Through discussions with more than 60 experts in the field of sustainable development, and 130 residents residing in different United Kingdom (UK) cities, Catalina found that the indicators based on the official statistical yearbook, which have a certain interpretative delay, are generally a good reflection of the sustainable development of urban areas. However, people are more inclined to assign different levels of importance to different indicators to assess city sustainability, while few scholars have considered these in the existing measurement studies [12]. Perceptual cognition refers to the visual or psychological perception of residents as it relates to changes in something [13, 14]. It is considered as an indispensable element in assessing the sustainable urban carrying capacity [15], compared to previously observed significant improvements [16]. For example, economic development and institutional governance are at a high level in Shanghai, and the associated psychological response, desire, and the emotional depression of residents experiencing a fastpaced and high-expense life are important considerations for urban managers and planners. In terms of perceiving the sustainable development level, residents believe that the consensus on the environment includes human attitudes, values, behavior, and clear expectations of other forms of sustainability [17]. Data used to measure and evaluate these perceptions are collected primarily through social surveys [18].
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The above analysis shows that evaluating SUD from the angle of resident perception is a clear and important research gap. However, since multi-regional and multidimensional social surveys require significant energy, time and cost, there have not been further studies in this area. Based on previous studies and from the resident perspective, this study constructed a sustainable evaluation system of urban development. Combined with interviews with experts, residents, and managers, the research examined the city center, new towns, and suburbs with the help of the Shanghai Municipal People’s Government. We then used the “entropy weight-cloud model” method to evaluate the sustainable development level of Shanghai, and to reveal the regional differences and “urban pain” from the resident’s view. This provides a theoretical reference for the government-oriented urban sustainable governance.
2 Literature Review 2.1
Evaluation Method of Sustainable Urban Development
Assessing sustainable urban development is a complex system engineering involving multiple regional and dimensional spaces [19]. Domestic and foreign scholars have deployed many urban sustainable development assessment methods, mainly by establishing social, economic, environmental, and resource evaluation subsystems. After standardizing the official statistics, the analytic hierarchy process (AHP) [20], principal component analysis [21], gray relational analysis [22], clustering analysis [23], and entropy weight [24] methods were systematically used to evaluate, and their different advantages and disadvantages were described as follows. AHP approach quantifies the decision maker’s experience and is particularly applicable in situations where the target structure is complex and lacks data. Although the AHP method integrates both qualitative and quantitative information in the process of completing a comprehensive evaluation, it cannot avoid randomness, subjectivity, uncertainty and ambiguity in the evaluation process. And the judgment matrix is prone to significant inconsistencies [25]. The principal component analysis is applied more frequently and with better results to analyze social economic statistics. However, principal component analysis requires a large sample size, involves a cumbersome process, and assumes that the indicators are linear. In practical applications, if the relationship between the indicators is nonlinear, there may be deviations in the evaluation results [26]. Many mathematical methods are used for a comprehensive evaluation, but each method considers a different focal point for the problem. The different methods of selection may lead to differences in the evaluation results. As such, a multi-objective comprehensive evaluation should be based on the characteristics of the object itself; the appropriate method must be selected based on objectivity, operability, and effectiveness [27]. It needs to point out that a comprehensive evaluation method addresses only the data, while the effectiveness of the evaluation results ultimately depends on the design of the index system [28]. The construction of sustainable city is a complex system engineering, with double levels of uncertainties (i.e. randomness and ambiguity). The entropy weight method can measure the weight of the index based on the degree of data
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variation and has a strong objective advantage [29], thus reducing the subjectivity of survey data to some extent. The cloud model can transform qualitative evaluation information into quantitative evaluation data, and can express the evaluation result clearly and intuitively in the form of a cloud image. This provides guidance for managers and decision makers [30]. Combined with the use of related computing software, the model can reduce calculation complexity, while improving the efficiency and accuracy of the sustainable evaluation [31]. Therefore, the entropy weight method and the cloud model are very suitable for evaluating the SUD level. 2.2
The Research Necessity of Resident Perception
As the material living standard improves, the government, residents, and scholars have recently begun to address ways to improve the spiritual levels of happiness and prosperity, residents’ subjective well-being, and life satisfaction [32]. Resident perception mainly refers to the human brain’s reaction to objective things and feelings about the outside world. Perceptions provide a complex understanding of a system, building emotions and other psychological activities. Social psychology research generally considers both sensation and perception [33]. In studying evaluations of urban development, resident perception usually refers to a social perception of sustainable factors [34]. This kind of social perception includes a wide range of objects. From the micro perspective, it includes the perception of the individual and the perception of interpersonal relationships. While at a macro point of view, it includes perceptions of economic life, social culture and public environment [35] (see Fig. 1).
Economic life
Residents perceive sustainability Public environment
Social culture
Fig. 1. Resident perceived sustainable dimensions
The sustainable development of a city depends not only on resource supplies and the environment, but also local residential support [36]. The main body of urban construction and development is human; the fundamental purpose of sustainable development is to sustain residents. Statistical yearbook data are macro-level, and are published on a delay. For these and other reasons, evaluating the level of sustainable
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33
development does not fully represent the resident needs. Therefore, it is important to evaluate the sustainability of urban development based on resident perception. This evaluation can reflect sustainability problems existing in cities and help provide sustainable policy guidelines. Given this, this study established a sustainable evaluation index system based on urban economic development, social culture, public environment, and other life-related dimensions. Taking into account the case of cities to be representative, the Chinese large city of Shanghai was selected to conduct a resident survey. The measurement indicators were provided according to their characteristics, and the resident perceptions of sustainable urban development were evaluated.
3 Index System Construction and Data Collection 3.1
Index Selection
Establishing an indicator system can provide information about a state or a change in the evaluation system [37]. It intuitively describes the urban sustainable development level and plays an important role in comprehensively measuring the city sustainable development level. Economy, society, and environment are widely considered to be the three core dimensions of sustainable urban development in the existing researches. However, some scholars have proposed integrating dimensions of infrastructure and life quality into the evaluation system [38]. Therefore, this study defined indicators related to six dimensions of the economic living standard, public service level, social security level, city environment level, public traffic level, and other infrastructure level. These six dimensions were used to comprehensively evaluate the sustainable development level of the city. This study first involved the review of the relevant literature on evaluating urban sustainable development in both China and other countries. The research then extracted suitable indicators from several different dimensions, based on the development characteristics of Shanghai. To ensure comprehensiveness, a forum was conducted, consisting of 10 experts (including government administrators, research academics, and representatives of planning and design institutes) and 15 residents from different representative regions in Shanghai. Table 1 shows the resulting modified evaluation indicator system. 3.2
Data Collection
3.2.1 Questionnaire Design For the investigation of statistical evaluation problems, placing the indicator belonging to the same variable into the same group can improve the questionnaire’s efficiency [51]. In addition, to ensure reliable and valid data, the measurement index for the relevant research can be amended based on the literature review to match the study situation [52]. In this study, there are six evaluation dimensions and 36 measurement indicators. The questionnaire includes more detailed statement measurement indicators. For example, the questionnaire asks, “how do you evaluate water pollution control in your area of residence?” The questionnaire uses a 5-level Likert scale: the higher the score, the higher level of resident awareness. A score of 5 represents “very good”; a
34
H. Si et al. Table 1. The integrated evaluation system of SUD level
Evaluation Dimension Economic Living D1 Public Service D2
Social Security D3 City Environment D4 Public Traffic D5 Infrastructure D6
Indicator
Reference
development situation of industry I1, employment situation I2, housing situation I3, shopping situation I4, financial services I5, the food security situation I6 medical institutions number I7, medical technology level I8, primary and secondary education quality I9, public culture level I10, public pension service I11, public security level I12 unemployment insurance I13, pension security I14, medical security I15, housing security I16, maternity guarantee I17, industrial injury insurance I18 city regional layout I19, appearance of the city I20, historical building protection I21, environment protection I22, air pollution controlling I23, water pollution controlling I24 bus station I25, bus frequency I26, subway density I27, shared bike coverage I28, road congestion I29, parking space I30 garbage sorting and recycling I31, disaster prevention facilities I32, water supply facilities I33, power supply facilities I34, gas facilities I35, communication facilities I36
He [39], Rothrock [40] Marti [41], Sebhatu [42]
Perra [43], Ghellere [44] Baumgartner [45], Li [46] Bohne [47], Pupphachai [48] Affolderbach [49], Madu [50]
score of 1 represents “very bad”. Since potentially investigated groups come from different education backgrounds, the measurement items need to be easy to understand and answer. Ten questionnaires were pretested by experts in the field of urban sustainable development; a few items and their descriptions were modified to result in the formal questionnaire, based on expert feedback. 3.2.2 Data Collection Study data came from paper questionnaires and electronic questionnaires, collected in two ways. The questionnaire star platform was used as a tool to edit the electronic questionnaire and store collected data. The WeChat of Chinese APP was the platform used to forward electronic questionnaires. Research objects were selected based on the following two principles. The goal of SUD is to promote the coordinated development of rural and urban areas, suburbs and city center areas, and rural and urban residents in terms of population, economy, society, resources, and environment. The desired result is to change the world’s currently long-term unsustainable concept of development, production, and consumption [53]. This article argues that the survey area is a key factor in ensuring that the data is representative. As such, the survey area should cover, but not be limited to the city center, new towns, and suburbs. On the other hand, the sustainable development of a city is a long-term system engineering, bringing together natives and
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strangers in the development process. They personally experience and create a new sustainable city. Therefore, this study required that most study participants have lived in Shanghai for 5 years or more; participants should include, but are not limited to urban residents, foreign residents, rural farmers, and other household registrants. Based on the considerations above, the investigative team visited regions in 10 areas of the city center, 7 new towns, and 9 suburbs outside the outer ring road in Shanghai. Data were gathered from June to August in 2017 (the division of the regions is based on the “Shanghai Urban Master Plan (2016-2040) “, shown in Fig. 2). The team conducted a questionnaire survey with residents, assessing perceptions about the city’s level of sustainable development, and soliciting advice related to Shanghai’s urban sustainable development in the process. A total of 1576 questionnaires were collected. Of these, 1263 copies were electronic questionnaires and 313 copies were paper questionnaires. The results showed that answers to 113 questionnaires were selected with the same option, 16 questionnaires were not completed, and 1447 valid cases were retrieved. This resulted in an effective recovery rate of 91.8%; the number of samples was strongly representative. Table 2 provides the detailed descriptive statistics of the sample.
Fig. 2. The distribution of the research areas
36
H. Si et al. Table 2. The descriptive statistics of the samples Characteristic Age
Category Frequency Percentage(%) 18–25 231 15.96 25–40 853 58.95 40–55 278 19.22 Above 55 85 5.87 Household registration Native & urban 792 54.73 Native & rural 92 6.36 Stranger & urban 258 17.83 Stranger & rural 305 21.08 Region Suburb 840 58.05 New town 258 17.83 Center city 349 24.12 Living years Within 2 165 11.40 2–5 163 11.26 5–10 182 12.58 Above 10 937 64.76 Educational background Below junior school 127 8.78 High school 204 14.10 College or bachelor degree 1015 70.14 Above master degree 101 6.98
4 Integrated Measurement Method and Process 4.1
Entropy Weight Method
The entropy weight method is a method of calculating weights, according to the degree of the variant indices and the size of the information entropy [54]. The entropy method can reduce the interference of human factors in the indicator weights, making the evaluation results more realistic. By calculating the entropy of each index, we can measure the amount of index information, ensuring that the established indicators reflect most of the original information. There are m evaluation indexes and n evaluation objects, forming the original data matrix X ¼ ðxij Þmn . For some indicators i, the greater the difference of the index value xij, the greater the role of the index in the comprehensive evaluation. Three steps are used to obtain weights using the entropy weight method: Step 1: Normalization of raw data matrix. First, m evaluation indexes are established. The original data matrix obtained by n evaluation objects is as follows:
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x11 B .. X¼@ . xm1
1 x1n .. C .. . A . xmm
37
ð1Þ
The matrix can be standardized: R ¼ ðrij Þmn
ð2Þ
In formula (2), rij indicates the standard value of the j evaluation object on the i evaluation index, rij 2 [0,1]. For the benefit index: xij minfxij g rij ¼
j
maxfxij g minfxij g j
ð3Þ
j
For the cost index: maxfxij g xij rij ¼
j
maxfxij g minfxij g j
ð4Þ
j
Step 2: Define entropy. In the evaluation problem involving n evaluation objects with m evaluation indexes, the entropy of the index i is defined as: Hi ¼
In formula (5), fij ¼ rij =
n 1 X fij ln fij ; i ¼ 1; 2; 3. . .; m ln n j¼1
n P
ð5Þ
rij . When fij ¼ 0, make fij ln fij ¼ 0.
j¼1
Step 3: Define entropy weight. When the entropy of the i index is defined, the entropy weight of the i index is defined as: xi ¼
1 Hi m P m Hi i¼1
In the formula (6), 0 xi 1,
m P i¼1
xi ¼ 1
ð6Þ
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4.2
H. Si et al.
Multi-regional and Multi-dimensional Sustainability Levels Measured
The cloud model is a modern mathematical theory, designed to study complex uncertainty. Academician Deyi Li proposed the theory based on traditional fuzzy set theory and probability theory. It can describe the randomness, fuzziness, and relevance of variables, and realize the mapping and transformation of qualitative and quantitative uncertainties. It has been applied in state diagnosis and integrated evaluation in many fields [55]. This paper presents a series of indicators across different dimensions to improve the integrity of sustainable development coverage. Some quantitative indicators are easy to measure (for example, the number of medical institutions and the bus station). In contrast, some indicators are qualitative and difficult to measure (for example, medical level and regional planning layout), but are essential for sustainable urban development. These soft indicators are difficult to assess in the existing sustainability assessment systems and tools, because there is no corresponding reference standard. In general, language terms that contain important information are difficult to quantify, so evaluators often express their views in a vague way. The cloud model is able to address this problem [56]. Therefore, this paper applies the cloud model to measure the level of SUD. 4.2.1 The Concept of Cloud Model Let U be a quantitative domain of numerical representation, and C be a qualitative concept on U. If the quantitative value x 2 U is a stochastic realization of qualitative concept C, the degree of determination of x for lðxÞ 2[0,1] is a random number with a stable tendency, if [57]: l : U ! ½0; 1; 8 2 U; x ! uðxÞ The distribution of x on domain U is called the cloud model, denoted as C(x), and each x is called a cloud drop. The cloud model represents a concept with three numerical features: expected Ex, entropy En, and hyper-entropy He. The Ex is expected in the cloud domain distribution center, is the most representative point of qualitative concept. En entropy is a measure of qualitative concepts of uncertainty, is determined by the random and fuzzy concept. It not only reflects the degree of discrete droplets, but also reflects the fuzziness of qualitative concepts. Hyper-entropy He is the uncertainty measure of entropy, and is determined by the randomness and fuzziness of entropy. It mainly reflects the cohesiveness of uncertainty in a qualitative concept. 4.2.2 The Cloud Generator The cloud generator is a specific algorithm that converts between qualitative concepts and quantitative data in a cloud model. The positive cloud generator realizes the transition from qualitative concept to quantitative value, producing cloud droplets from the cloud’s digital signature (Ex, En, He). The reverse cloud generator converts terms from quantitative to qualitative concepts, transforming exact data into qualitative concepts for cloud digital features (Ex, En, He), shown in Fig. 3.
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Ex En
39
Ex
CG
CG-1
Drop xi,yi
He
En He
The positive cloud generator
The reverse cloud generator
Fig. 3. Cloud generator
In this paper, the inverse cloud generator is used to convert questionnaire data into cloud droplets. Therefore, we only introduce the process of the inverse cloud generator here. First, we enter the quantitative values of the N cloud droplets and the determinants (xi, yi) of each cloud droplet. Then, the output (Ex, En, He) of the qualitative concept A is expressed by a specific algorithm. The main algorithm for the inverse cloud generator is as follows [58]:
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi He ¼ S2 En2 ¼
Ex ¼ X
ð7Þ
rffiffiffi n p 1X En ¼ jxi Xj 2 n i¼1
ð8Þ
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi rffiffiffi n n X 1 X 2 2ð p1 ðxi XÞ jxi XjÞ n 1 i¼1 2 n i¼1
ð9Þ
indicates the mean value of N cloud drops; S2 indicates the In the formula (9), X variance. 4.3
Integrated Sustainability Assessment of Urban Development Based on Entropy Weight-Cloud Model
4.3.1 The Determination of Qualitative Criteria for Cloud Model Determine the evaluation of the language combination of V, using China’s evaluation criteria of “excellent, good, medium, and poor.” These correspond to the four grades: very good, good, middle, and bad. The symmetric cloud model is used to describe the numerical features of the cloud model, using the following formula [59]. 8 V min > < Ex ¼ V max þ 2 min En ¼ V maxV 6 > : He ¼ k
ð10Þ
In formula (10), k is a constant, and can be adjusted based on the uncertainty level of the variable itself [60]. Based on the questionnaire score (on a 5-level Likert scale), the corresponding remark set of the evaluation language was determined as [0,5], thus
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the corresponding variation range and corresponding parameters of each qualitative evaluation language can be obtained as shown in Table 3. Table 3. The variable range and cloud model parameters Evaluation language Bad (poor) Interval (0, 2.5] Ex 2.5 En 1/6 He k
Middle (medium) (2.5, 3.5] 3 1/6 k
Good (good) (3.5, 4.5] 4 1/6 k
Very good (excellent) (4.5, 5] 4.5 1/6 k
4.3.2 Determine the Cloud Model Eigenvalue of the Evaluation Index First, 1447 questionnaires were used to calculate the weight W and the cloud model digital feature (Exi, Eni, Hei) of each secondary index using the entropy weight method and the inverse cloud generator. Then we calculated the comprehensive cloud eigenvalues of primary index using the following formula [61]. 8 > > < > > :
Ex ¼ Ex1 x1xþ1 þExx2 2xþ2 þþþxnExn xn
En ¼
x21 1 x21 þ x22 þ þ x2n x21 x21 þ x22 þ þ x2n
He ¼
x22 x2 En2 þ þ x2 þ x2 þn þ x2 Enn x21 þ x22 þ þ x2n n 1 2 x2 x2 He1 þ x2 þ x2 þ2 þ x2 He2 þ x2 þ x2 þn þ x2 Hen n n 1 2 1 2
En þ
ð11Þ
In formula (11), xi is the weight of each secondary evaluation index; (Exi, Eni, Hei) is the cloud model digital characteristic parameter of each secondary index; and n is the number of the evaluation index, i = 1, 2, …, n. 4.3.3 Establishment of a Cloud Model to Comprehensively Evaluate the SUD Level The primary indicators are interrelated, affecting each other. For example, the sustainability of the infrastructure may impact the sustainability of the city environment, and the sustainability of social security could influence the sustainability of public service. A comprehensive cloud operation in the virtual cloud is needed to comprehensively evaluate the upper level index [62]. The cloud model of the five first-level evaluation indexes is calculated as a broader cloud, obtained by formula (12). 8 < Ex ¼ Ex1 En1 x1 þ Ex2 En2 x2 þ þ Exn Enn xn En ¼ En1 x1 þ En2 x2 þ Enn xn : 1 x1 þ He2 En2 x2 þ Hen Enn xn He ¼ He1 En En1 x1 þ En2 x2 þ þ Enn xn
ð12Þ
In formula (12), xi is the weight of each primary evaluation index; (Exi, Eni, Hei) is the cloud model digital characteristic parameter of each primary index; n is the number of evaluation index; and i = 1, 2, …, n. Figure 4 provides a detailed establishment of a cloud model allowing an integrated evaluation of a sustainable urban development level.
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Constructing index system of sustainable urban development level
Questionnaire design and data collection from the whole city
Determination of index weight by entropy weight method
Determination of cloud model classification standards
Calculate the characteristic value of the cloud model for the indicators
Building a cloud model of integrated evaluation for SUD level Fig. 4. The establishment process of cloud model for the integrated evaluation of SUD level
5 Measuring the Sustainable Development Level in Shanghai 5.1
Data Validity Test
Reliability refers to the degree of consistency in outcomes when the same object is measured using different test methods. The Cronbach’s alpha coefficient is often used to test reliability in the academic community. The closer the coefficient is to 1, the higher the degree of consistency between the item and the corresponding variable, indicating that the measurement is well designed. For this study, we first used SPSS 24.0 to conduct the reliability test. The overall Cronbach’s alpha coefficient of the questionnaire is 0.967; this indicates that the questionnaire’s reliability is high. Second, to measure whether the 36 indexes selected in advance correspond to the six dimensions designed in the index system, the study used the AMOS software to conduct a confirmatory factor analysis of the questionnaire data. The load of the six dimensions of the evaluation model is between 0.68 and 0.95; this indicates that the statistic of the model is significant. The statistical reliability is between 0.8 and 0.9, and the factor load of all the secondary indexes is between 0.56 and 0.81. The Model Fit shows RMR 0.028 < 0.05, and RMSEA is 0.047, less than 0.08. The GFI is 0.928; AGFI is 0.912, which is greater than 0.9; and PGFI is 0.760, > 0.5. All models result in suitable indexes, indicating that the 36 measurement indicators can be aggregated into 6
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H. Si et al.
effective factors. The constructed evaluation index system and the recovery questionnaire data match each other, and the evaluation index system has the ideal degree of fit, and so we can conduct the cloud model analysis. 5.2
Multi-regional Sustainability Level Measurement
5.2.1 Determine the Weight and Cloud Model Parameters The questionnaire data were converted into matrix input for MATLAB2014a; formulas (1)-(6) were programmed to calculate the weight of the city center, new towns, and suburbs for the 36 measurements and six dimensions. Then, the cloud model for the three regions was calculated by using the inverse cloud generator with the formulas (7)(9). This article expresses the summary features of the cloud model and the weight value of the Shanghai city center, shown in Table 4. Using formulas (11)-(12), we obtained the comprehensive eigenvalues of the cloud model in the city center using the integrated cloud computing (3.6318, 0.1460, 0.2716). This yields a comprehensive evaluation, using the cloud model of the whole city, suburb, and new town (3.5551, 0.1559, 0.2649), (3.41584, 0.1659, 0.2538), (3.5871, 0.1492, 0.244). Similarly, we can generate a cloud model of the digital features of the whole city, suburb, and new town (3.5551, 0.1559, 0.2649), (3.41584, 0.1659, 0.2538), (3.5871, 0.1492, 0.2415). 5.2.2 Regional Comprehensive Evaluation of Sustainable Development Level in Shanghai Because the hyper-entropy in the four-region cloud model feature is close to 0.3, k is defined as 0.3. In the process of calculating the reverse cloud generator, to more clearly and intuitively compare the comprehensive cloud model, the qualitative reviews can be correspondingly adjusted 2 to 3 times, based on each index’s comprehensive score [63]. The cloud model parameters of the regional comprehensive evaluation of Shanghai SUD and the cloud model parameters corresponding to each qualitative evaluation language are entered into the positive cloud generator. MATLAB software is then used to draw the cloud for the city center, new town, suburbs, and the entire city’s sustainable development level; these clouds are shown in Figs. 5, 6, 7, 8, 9. Figures 5, 6, 7, 8 shows that after several years of green and low-carbon development in Shanghai, the city center, new towns, suburbs, and the entire city’s sustainable development levels fall between “middle” and “good”. The suburbs’ sustainable development level is closer to the “middle” level, however, the development level of the center city, new towns, and the whole city is closer to “good”. This shows that the city center and the new town residents are more satisfied with the current sustainable development level; residents in the suburbs are satisfied with the development situation at the next highest level. The new towns’ sustainable development level is gradually approaching the development level of the city center while it is above the city’s overall average level. This demonstrates that the sustainable development level of Shanghai’s new towns have been increasing rapidly in recent years.
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Table 4. The weights and cloud model parameters of center urban evaluation index. Dimension (Ex, En, He)
Index
Economic Living D1 (3.6751,0.1409,0.2309)
Development Situation of Industry I1 Employment Situation I2 Housing Situation I3 Shopping Situation I4 Financial Services I5 Food Security Situation I6 Number of Medical Institutions I7 Medical Technology Level I8 Primary and Secondary Education I9 Public Culture Level I10 Public Pension Service I11 Public Security Level I12 Unemployment Insurance I13 Pension Security I14 Medical Security I15 Housing Security I16 Maternity Guarantee I17 Industrial Injury Insurance I18
Public Service D2 (3.6989,0.1455,0.2656)
Social Security D3 (3.5730,0.1481,0.2762)
Cloud model parameters (Ex, En, He)
Weight xi
xij
(3.8195,0.7467,0.1477)
0.1695
0.0281
(3.6361,0.8485,0.2824)
0.0280
(3.4298,0.8615,0.2557)
0.0287
(3.9226,0.8339,0.2882)
0.0285
(3.8338,0.8659,0.0994)
0.0281
(3.4556,0.9057,0.2980)
0.0281
(3.6590,0.9663,0.3057)
0.1672
0.0279
(3.7020,0.8868,0.2437)
0.0281
(3.6991,0.8783,0.1936)
0.0276
(3.6734,0.8465,0.2048)
0.0277
(3.5960,0.9667,0.3088)
0.0281
(3.9169,0.7070,0.3417)
0.0278
(3.4642,0.8425,0.2847)
0.1636
0.0278
(3.5989,0.9870,0.3268)
0.0277
(3.6246,0.9270,0.3270)
0.0263
(3.3496,0.8788,0.2236)
0.0269
(3.7994,0.8613,0.2020)
0.0276
(3.5960,0.8374,0.2836)
0.0273 (continued)
44
H. Si et al. Table 4. (continued)
Dimension (Ex, En, He)
Index
Cloud model parameters (Ex, En, He)
Weight xi
xij
City Environment D4 (3.5332,0.1512,0.2269)
City Regional Layout I19 Appearance of the City I20 Historical Building Protection I21 Environment Protection I22 Air Pollution Controlling I23 Water Pollution Controlling I24 Bus Station I25 Bus Frequency I26 Subway Density I27 Shared Bike Coverage I28 Road Congestion I29 Parking Space I30 Garbage Sorting and Recycling I31 Disaster Prevention Facilities I32 Water Supply Facilities I33 Power Supply Facilities I34 Gas Facilities I35 Communication Facilities I36
(3.6877,0.8136,0.1246)
0.1672
0.0280
Public Traffic D5 (3.5514,0.1527,0.3072)
Infrastructure D6 (3.7734,0.1378,0.3240)
(3.8310,0.8444,0.9209)
0.0280
(3.6934,0.9209,0.2210)
0.0281
(3.6762,0.9360,0.2652)
0.0275
(3.0860,0.9033,0.2705)
0.0273
(3.2837,1.0089,0.2696)
0.0281
(3.8596,0.7857,0.2473) (3.6447,0.9617,0.2932)
0.1666
0.0277 0.0276
(4.0029,0.7950,0.3977)
0.0278
(3.7335,0.9621,0.2931)
0.0278
(3.3095,1.0383,0.3242)
0.0278
(2.9800,1.0539,0.2952)
0.0279
(3.4269,1.0148,0.3432)
0.1663
0.0276
(3.5931,0.9463,0.3098)
0.0277
(3.8596,0.7702,0.3111)
0.0278
(4.0745,0.7312,0.2936)
0.0277
(3.9685,0.6276,0.3698)
0.0275
(3.9111,0.7922,0.3210)
0.0280
Figure 9 shows that Shanghai’s state of sustainable development is highest in the center city, at a level greater than in the new towns, whole city, and the suburbs. Within the same degree of membership, the level of sustainable development cloud entropy En (development level of uncertainty; the smaller the En, the more stable the development
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1 bad 0.9
middle good very good
0.8
Center city
Degree of membership
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
3
4
5
6
7 Expectation
8
10
9
11
Fig. 5. The SUD cloud chart of center city 1 bad 0.9
middle good very good
0.8
New town
Degree of membership
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
2
3
4
5
6
7 Expectation
8
9
10
11
12
Fig. 6. The SUD cloud chart of new town
level) ranks as follows: suburbs > the whole city > new towns > center city. The cloud hyper-entropy He (the thicker the cloud, the higher the dispersion of the sample) ranks as follows: center city > the whole city > suburbs > new towns. The sustainable development level of the city center is the highest; it also has a higher degree of dispersion than is seen for the city’s average discrete level. This shows that the development process and recent integration of urban and rural areas has resulted in many suburban and non-local residents moving into the city center city. This has formed a highly heterogeneous international city. At the same time, the hyper-entropy He in the center urban area is the smallest, shows that the development level is the most stable and robust. In addition, the stability of the new towns’ development is strong,
46
H. Si et al. 1 bad middle
0.9
good very good
0.8
Suburb
Degree of membership
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
3
4
5
6
7 Expectation
8
9
10
11
Fig. 7. The SUD cloud chart of suburb 1 bad
0.9
middle good
0.8
very good Whole city
Degree of membership
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
3
4
5
6
7 Expectation
8
9
10
11
Fig. 8. The SUD cloud chart of whole city
while the degree of dispersion is very small. This shows that steady development in recent years has mainly depended on local government and resident management. Suburbs are the regions with the strongest uncertainty in sustainable development level, and the degree of dispersion is very small, indicating room for future development. 5.2.3 Dimensional Comprehensive Evaluation of Sustainable Development Level in Shanghai We summarized the integrated sustainability score of the city center, suburbs, the new towns, and the entire city with respect to infrastructure, public service, social security, economic living, public traffic and city environment dimensions. Figure 10 shows the
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1 Center city Suburb
0.9
New town Whole city
0.8
Degree of membership
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
6
6.2
6.4
6.6
6.8
7 Expectation
7.2
7.4
7.6
7.8
8
Fig. 9. The SUD cloud chart of center city, new town, suburb and the whole city
associated radar map. The analysis shows that the economic living, infrastructure, and public service aspects of the city’s center are more sustainable and the residents are more satisfied with them. The new town area has higher sustainability with respect to city environment, social security, infrastructure, and economic living. The aspects of city environment and social security have sustainability levels that residents perceive as being beyond the center city, showing that Shanghai’s new town environment and social security level have greatly improved in recent years. Suburban economic living and infrastructure have given residents a higher level of perceived sustainability; while the rest of dimensions are slightly inferior. From the perspective of the entire city, in addition to higher infrastructure scores, the other aspects of the sustainable development level lay between the levels of the suburbs and new town, but closer to the latter. It shows that the entire city of Shanghai has developed faster in infrastructure construction, and residents are satisfied with it. The average score for public traffic in Shanghai is no more than seven, close to the general level. In contrast, the sustainability level of the city center’s public traffic development is highest, followed by the new town. Overall, the city center is leading in many aspects; however, the new town areas are approaching the center city and are developing rapidly. The sustainable development advantages in the city environment and social security are becoming increasingly prominent. Due to a lack of talent, industry, and policy support, suburban area development is relatively slow. As the last link to sustainable development in Shanghai, it is also the most arduous link, and needs strong support.
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Public Service
Infrastructure 7.6 7.4 7.2 7 6.8 6.6 6.4 6.2 6
City Environment
Social Security
Center city
Public Traffic
Economic Living New town
suburb
The whole city
Fig. 10. The dimensional SUD evaluation of center city, new town, suburb and the whole city
6 Conclusions Sustainable development is key to ensuring that a city’s living standard, environment, economy, and society are unaffected, especially considering the fact that 50 percent of the world’s population live in cities. As such, more and more countries are bringing SUD into a strategic development position. This study was conducted to improve the comprehensive evaluation method of urban sustainable development levels, and fill a research gap related to resident perception. The article’s contribution was to extract an evaluation index system of SUD from the perspective of resident perception. The study also proposed an evaluation method using an entropy weight-cloud model. The evaluation results were objective and reasonable, reflecting the problem intuitively and clearly. In contrast to previous evaluation methods, this study of resident perspectives analyzed sustainability differences across different regions and dimensions. This approach is more conducive to implementing governmental-specific measures, and more effectively enhancing the subjective resident well-being. This study was limited by some uncontrollable factors. First, this article uses an international, mature scale of measurement to conduct the questionnaire survey. Indicators were selected based on the international literature. On the basis of different cultural habits in different countries, the questionnaire responses may produce some measurement error. Further, urban sustainable management is a complex system
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engineering. As such, the evaluation model established in this paper assessed the sustainable development level of Shanghai, but may not be enough to identify the sustainable development direction for other Chinese cities. Subsequent studies will more deeply examine resident needs, and will focus on designing and conducting questionnaires from the perspective of government, society, and resident. Using urban agglomeration as the object of study to design a more complete assessment mechanism of urban sustainable development from a fair and efficient perspective could also be future research point.
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Rethinking “New Countryside Construction”: Lessons Learnt from the Guangzhou Luogang District, China Yao Dai1(&), Siu Wai Wong1, Bo-Sin Tang2, and Jinlong Liu3
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1 Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China [email protected] Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China 3 School of Agricultural Economics and Rural Development, Renmin University of China, Beijing, China
Abstract. China’s nationwide “New Countryside Construction” policy promotes integrated urban-rural development by spending public resources to improve infrastructure and social services in the rural areas. Although its primary aim is to revitalize agricultural production and enhance peasants’ livelihood, this policy has had many unexpected consequences for urban growth and local governance. This study examines the local implementation of this policy and its impact on urban transformation and local state building. Based on an indepth analysis of local governance restructuring in the Guangzhou Luogang District, the study explores how the local authority has shifted its strategy from a single-minded pursuit of industrial-led development to a full-fledged administrative agenda, through engaging the participation of village organizations and villagers in land management and social welfare provisions. Reflecting on the GLD experience, this study proposes a new perspective for interpreting the transformation of local governance under China’s new strategy for urbanizing the rural countryside. Keywords: China Urbanization
New Countryside Construction Local governance
1 Introduction The fast pace of industrialization and urbanization over the past three decades has created increasing divisions between urban and rural areas in China. In the UN-Habitat report for 2008/2009, China’s rural-urban disparities are highlighted as “one of the widest income gaps between rural and urban areas of any country in the world” [1]. These disparities, indicative of a dichotomous and exploitative relationship between urban and rural areas, have deep roots in China’s household registration (hukou) system. Established in the 1950s, the hukou system is an institution that separates the legal status of urban residents from that of rural residents. In the hukou system, all Chinese households are divided into two major categories: “non-agricultural (or urban) © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 53–65, 2021. https://doi.org/10.1007/978-981-15-3977-0_4
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hukou” and “agricultural hukou.” Only people who have urban hukou status can enjoy state welfare benefits such as subsidized education, medical care and pensions. People from agricultural hukou are excluded from state welfare benefits and their migration to urban areas is restricted. Although restrictions on urban-rural migrations were gradually loosened during the reform period, the hukou system still dominated China’s development throughout the 1990s. Alongside this unique system, both state and private investments in the past decades were highly concentrated in urban areas. Rural China supported the urban sector with cheap material inputs, which enables the state to achieve its objectives of industrialization and urbanization [2]. Lacking economic and social power, peasants became vulnerable during the mighty urbanization movement in the 1990s. In search of better living conditions, many peasants left their homes and streamed into cities looking for new living [3]. However, subject to the constraints of the hukou system, most of these rural migrant workers lacked veritable rights to the city. The discrimination against migrant workers is rooted in urban-rural dual system. For example, it was difficult for them to find high-wage jobs, and the labor rights of migrant workers were usually violated by employers, such as poor working conditions and wage arrears. They were excluded from social services, like housing and health care provided by local government. Health issues raised among them owing to poor living conditions. A growing number of rural people floating into cities also created negative effect on rural development. One of the consequences was an acute decline of agricultural production1. To cope with these social problems, the Chinese government shifted its attention to rural areas and sought to ameliorate the problem of rural-urban inequality. As an important part of this effort, the “Socialist New Countryside Construction” policy was napped out by the central state in 2005. As stated by the official documents, the socialist new countryside (shehuizhuyi Xinnongcun 社会主义新农村) is defined as modern villages with four standards- “advanced production, improved livelihood, clean and tidy villages, a civilized social atmosphere and efficient management.” Pursuant to these objectives, the Chinese government has taken unprecedented measures to revitalize the rural sector thought tax cuts and agricultural subsidies, and by diverting fiscal resources towards the provision of public services in village areas. As the Chinese government gradually shifts from pursuing urban-biased economic growth in favor of integrated rural-urban development, it is important to ask how this new development ideology has effectuated changes in China’s urbanization processes and its impact on the transformation of local governance. Socialist China’s marketoriented reforms have enabled the decentralization of administrative and fiscal powers from the central state to the local state, and this has led to the reinvention and consolidation of local organizations such as municipalities and urban district [4]. Such deliberate state-led market reforms, however, have allowed very limited changes in the 1
Some Chinese scholars describe the economic and social problems of rural China in 1990s as “Sannong Wenti,” which refer to three interlocked economic and social problems related to “the grief of peasants,” “the poverty of rural villages,” and ‘the decline of agricultural production.” For details about Sannong Wenti, see Tiejun Wen, Sannong Wenti Yu Shiji Fansi (Rural China’s Centenary Reflection) (Beijing: Sanlian Publishing House, 2005).
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political sphere. Because of this specific context, many pre-existing studies on China’s local governance tend to reject pluralism and clientelism as ways of explaining statesociety relationships in reform China and instead adopt the concept of “state corporatism”, which emphasizes the many informal links between multiple actors within the formal party-state organizations [5]. One of the most common models is the “local state corporatism” proposed by Jean Oi [6, 7]. The emergence of this model, the author argues, was because of the fiscal reforms implemented by the central government in the early 1980s, with the aim of making localities fiscally self-sufficient. Consequently, township governments became independent fiscal entities with both the responsibility for local expenditures and an unprecedented autonomy in using the revenue they captured. This change has spurred local governments to collude with local actors to promote the development of rural enterprises, whose operations were dominated by the Chinese central government [8]. Recently, the “local state corporatism” approach has been criticized for limiting its analysis to the interaction between the local state and the local rural enterprises, overlooking individual actors in the processes. In an explicit attempt to address this deficiency, the “village corporatism” model highlights the active role of the villagers in urban social transformation by suggesting that the villagers are not just passive participants in corporatism imposed by the state; they actively resist the local state’s land exploitation [9]. Using the Guangzhou Luogang District (GLD) as a case study, this article illustrates an example of a departure from the model of “local state corporatism” in characterizing China’s local governance. In the GLD, the local state moved away from its traditional role in promoting industrial development to engage with social welfare provisions for villagers. As an example of the local state consolidating its leadership role in development by getting village organizations and villagers involved in social welfare provisions, the GLD mode of local governance stands in stark contrast to the model of “village corporatism”, which describes a self-protective strategy of peasants and their village collectives against land appropriation by the exploitative local state.
2 From an Industrial Zone Manager to a District Government: Local Governance Restructuring in the GLD Since the 1980s The GLD is located in the eastern part of Guangzhou City. The total area of GLD was 393.22 square kilometers and a population of approximately 170,000 [10]. In 2005, the Guangzhou municipal government merged the Guangzhou Development District (GDD) with Luogang Town to form the GLD as a new administrative district [11]. After that, the existing GLD district government is actually the consortium of the GDD Administrative Committee (GDDAC) and the Lougang township government. As the GDDAC demonstrated a stronger capacity for public administration and management than the Lougang township government, the new district government adopted the organizational structure of the GDDAC in framing its administrative system.
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Pragmatic Pursuit of Industrial Development
Established in the early 1980s, the GDD was one of the first development zones at national level to experiment with China’s market reform and urban development policies. Over two decades of development, the GDD grew from an industrial zone of less than 7 square kilometers of labor-intensive manufacturing industries to, by the end of the 1990s, a hi-tech industrial area with a total area of approximately 190 square kilometers. As the local authority of a rapidly expanding development zone, the GDDAC primarily aimed to sustain a strong growth of tax revenue from industrial development. The local governance system of the GDD was largely dominated by the single-minded pursuit of industrial growth [12]. This policy, however, equipped the local state with abundant fiscal resources and impressive capacities in public administration. In ensuring efficient administrative services for foreign investors, the GDDAC kept its organizational structure lean and simple2. As early as the mid-1990s, massive land appropriations for the swift urban expansion of the GDD exposed the GDDAC to acute conflicts with local villagers [13]. More than 3,000 villagers from three villages were relocated just to construct the first phase of Guangzhou Science City. Land-centered conflicts between the GDDAC and local villagers kept growing in the early millennium when another mega-project called “Knowledge City” was launched in the northern part of the district. These conflicts resulted in increasing social tensions, and local officials realized that they should compromise with rural villagers in order to realize their pragmatic pursuit of industrial development. To ensure a sufficient land supply for investors to expand industrial investment, local officials recognized that acquiring arable land from the neighboring villages would remain an unavoidable part of the GDD’s future development. Worried that leaving villagers with the impression that they ‘bullied peasants” might cause more conflicts in future land requisition, local government intentionally minimized villagers’ dissatisfaction through actively respecting their needs. 2.2
Land Requisition and Regional Disparities
The GDDAC’s early engagement in land requisition and villager resettlement was mostly project-based. Consequently, villages within the district were divided into three categories: (1) new urban neighborhoods3 where all arable land was expropriated by the state; (2) new urban neighborhoods where partly arable land was expropriated by the state; and (3) rural villages where land use was not affected by urbanization. The villages in the first two categories became much wealthier than those in the third category for two reasons. First, the villages affected by land requisition usually held a large amount of collective land that could be used for non-agricultural purpose. As a part of land compensation, a certain percentage of land was returned to the affected
2
3
Compared with other district governments in Guangzhou City, the total numbers of departments and civil servants of the existing GLD government are lesser by about 33% and 50% respectively. Villagers’ Committees in these new urban neighbourhoods have been reorganized into Residents’ Committees.
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village collectives. These lands were called “reserved lands” (ziliu jinji yongdi自留经 济用地) and were legally zoned for non-farming uses4. Second, the GDDAC paid a certain amount of cash compensation to the villages. As a result, the villages could generate considerable income from two major sources to improve villagers’ livelihood and village public services: (1) interest from land compensation fees that were retained by the village collective and (2) rental income from “reserved land” that was returned by the state to the village collective for non-agricultural development after land requisition. Because of these revenue sources, the villages in the third category could only generate income from the remaining arable land, orchards and forests that had not been requisitioned for urban development. In this context, only villages directly affected by land requisitions were able to provide better welfare services. The poor villages, which were located at the outskirt of the Science City and the Knowledge City, were sealed off from the benefits. This phenomenon was incompatible with the GDDAC’s wholehearted pursuit of a world-class environment for investors. Not only had it created a growing income inequality among villagers, it also created a “chaotic landscape” that placed the GDD’s advanced industrial zones among shabby village settlements. 2.3
New Countryside Construction as a Vehicle for Change
Given these disparities, the GDDAC perceived that greater central management was essential in the system of villager resettlement. The policy of New Countryside Construction has further promoted the development of this direction. In response to the central government’s call for integrated rural-urban development, the Municipal government established the GLD as a new urban district in 2005 in order to show its endeavor to carry out the New Countryside Construction policy. At that moment, the GDD was already a well-developed industrial area while Luogang Town was a rural area where villagers mainly depended on agricultural production. As revealed by the official statistics, the net income per capita of the GDD was about 35,000 yuan in 2004, which was four times that of Luogang’s villages during the early years of the new millennium [14]. Taking GDD as a “growth pole” to promote the development of Luogang villages, the Guangzhou Municipality exhibited its promise to implement the principle of “cities support countryside (chengshi zhichi nongcun 城市支持农村), industries nurture agricultural production (gongye fanbu nongye工业反哺农村),” which had been encouraged by the central government as major part of the New Countryside Construction. By advocating a new planning ideology for lower administrative levels, the New Countryside Construction policy offered the GDDAC political and legal frameworks to map out a more comprehensive policy for rural development and villager resettlement. Before the formal establishment of the GLD, the GDDAC had gradually managed to change the hukou status of all local villagers from “agricultural” to “non-agricultural”
4
This policy was introduced by the Guangdong Province in the 1980 s. Its primary purpose was to help villagers in generating income from non-agricultural production after losing their arable land to urbanization.
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(nong zhuan fei 农转非). Between 2004 and 2006, 74,751 villagers from 12 villages became urban residents. At the same time, villagers of these villages (now urban neighborhoods) re-organized their Villagers’ Committees into Residents’ Committees [15]. According to Guangdong Land Consolidation Planning in 2011, land consolidation in the Guangzhou city is mainly oriented to the “Three Old” Transformation (sanjiu gaizao 三旧改造),which has played a leading part in building “clean and tidy villages”. The implementation of the “New Countryside Construction” strategy in the GLD was essentially a process of in-situ urbanization, under which many traditional villages were transformed into modern urban settlements. Consequently, how to provide social services (such as medical services and retirement pensions) for these new residents, who had long been excluded from welfare benefits funded by the state under the hukou system, constituted the core challenge for local governance in the GLD. 2.4
The Struggle for Welfare Services Provisions
The new GLD government struggled to engage the social welfare provisions, including providing medical services, retirement pensions and job opportunities. In urban China, social welfare programmes, such as pensions and medical insurance, are drawn partly from state subsidies and partly from employers. However, villagers depended heavily on the village collectives to acquire pubic goods and services and on collective land for their livelihood needs. The same was true for villagers living in GLD. To tackle these problems for these new residents, the district government established a new cooperative medical system in 2005. It raises funds through personal payments, collective support and government funding. The government continues to increase the level of subsidy. Offering job opportunities is another important constituent of welfare programmes in these new urban settlements. One year after the GLD was established, 40,000 labors become surplus and about 49,000 ex-villagers had to find new their jobs in nonagricultural sector. [16]. These ex-villages lacking special skills and working in the village collective enterprises find it difficult to find jobs in urban job marketplaces after losing their arable land to urbanization. To solve this problem, The GLD government attempted to create more jobs through collaborations with the factories. The district government also introduced a “Non-walled Factory Scheme,” which aimed at encouraging ex-villagers to participate in work. It was difficult to offer job opportunities, so the GLD government started an “Entrepreneurship Scheme” to assist exvillagers to create their own businesses. Apart from these immediate measures, the GLD government provided vocational trainings to improve job-seekers’ skills [17].
3 Restructuring of Power Dynamics Between the State and Villages 3.1
Collaboration with Villagers and Village Organizations
In the development of welfare services programs, the district government adopted a tripartite model involving village collectives (namely, Shareholding Cooperatives or Gufen jingji hezuoshe 股份经济合作社 in Chinese) and villagers. For instance, when
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constructing village clinics, the GLD government bore the construction costs and the village provided the land. Besides, the district government subsidized the training of village doctors and coordinated the central procurement of pharmaceuticals for neighborhood/village clinics with the aim of enhancing their bargaining power in price negotiation with pharmaceutical companies. Similar forms of collaboration also applied to the provision of pension schemes and even seemingly negligible issues such as property management fees. Initially, some villagers refused to pay management fees after they were relocated to new apartment buildings. They questioned why extra monthly fees were required for management, as this had not been necessary in their village. When the management company tried to explain that the fees were collected for cleaning and maintaining the common areas of the building, they further questioned whether it was necessary, as the existing building environment was much cleaner and tidier than that of their previous village. The local government took this dispute between ex-villagers and the property management company as an opportunity to help villagers adapt to the urban way of life, in which social integration is not governed by family ties, but by economic relations. It offered to pay one-third of the costs for those households that would take the initiative to pay management fees. To reward these advanced households for their compliance behavior, the collective unit concerned contributed equally to another one-third of the fees. 3.2
Shareholding Reforms, Social Control and Institutional Capacity Building
If this tri-partite model provides fiscal incentives for Shareholding Cooperatives (SCs) and villagers to participate in the development of social services, shareholding reforms can be seen as a “hard” approach adopted by the new district government to reshape SCs as a platform linking villagers to the authorities. SCs were previously known as “Bridges and Production Teams.” In the Maoist era, these village collectives organized peasants’ day-to-day production activities. Moreover, they assumed administrative responsibilities for a range of village affairs, such as fiscal management, public services, public order, social security, conscription, and conflict mediation. In the reform period, Bridges and Productions were gradually reorganized as village selfgoverning organizations, namely Villagers’ Committees and Rural Economic Cooperatives. The introduction of the Household Responsibility System consistently undermined the organizational capacities of these village organizations by allowing villagers more freedom to use their land for farming production. Under these circumstances, collective organizations in rural China experienced a severe organizational decline throughout the 1980s. In the Luogang area, the intensive land requisition programs provided opportunities for some village collective organizations to enjoy a renaissance from the 1990s onward. As discussed in the proceeding sections, land requisitions brought considerable income to many village collectives. Distribution issues raised due to the increasing collective incomes. To seeking a better distributive mechanism, village collectives were guided by the township government to implement shareholding reforms by converting villagers’ rights to collective assets into shares. As a consequence, villagers became shareholders who could receive dividends every year. The renaissance of these
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collective organizations has been seen as re-collectivization of rural society after the de-collectivization that resulted from the carrying out of the Household Responsibility System [18, 19]. During the 1990s, similar to SCs in other parts (such as Shenzhen and some counties of Guangzhou) of Pearl River Delta, the SCs in GLD developed their own mechanisms for defining shareholders’ rights and distributing collective profits5. This allows SCs to manage collective assets autonomously, but it can create loopholes that local cadres can use to redistribute shares. Their traditional business mode, grounded in the management of a village power bloc, had obviously limited their capacity to grow through pursuing economies of scale and efficiency. Moreover, the ambiguities with respect to collective ownership had created grey areas that allowed village cadres to manipulate the real operations of asset management. These emerging problems become the main cause of conflict between the village collectives and their villagers, generating opportunities for the district government to intervene in the SCs through shareholding reform. The first important step taken by the district government was requiring all SCs to reclassify their shares into two types: shequ shares(社区股)and shehui shares (社会股). In addition to the reclassification and redistribution of shares, the district government initiated organizational restructuring in all the SCs. In 2003, the district government required the village cadres to prepare a set of Articles of Association for the SC that they belonged to. Prepared by the village cadres, the Articles had to be endorsed by the Street Office and then presented to the Shareholders’ Meeting for final approval. By virtue of the Articles, each SC was required to form the Board of Directors and a Board of Supervisors by election. Through these reforms, the actual operation of SCs is subject to a series of rules and procedures of the “Articles of Association”. 3.3
New (Old) Power Dynamics Among Local State, Village Collective and Villagers
Shareholding reforms in GLD attempt to formalize the pre-existing practices by implementing a new regulatory framework to change the old system. This round of shareholding reforms equipped the SCs with company-like organizational structures, which have facilitated the pursuit of economic efficiency and greater accountability of local cadres. Simultaneously, these reforms interacted with other measures that allowed the local state to secure cooperative actions from both village cadres and villagers. Taking the shareholding reform as an opportunity, the district government has incorporated more compliance rules into villagers’ entitlement to share interests, including social welfare services and dividends, which are main resources of their livelihoods.
5
Starting from Shenzhen and some counties of Guangzhou City form the early, the shareholding reforms were underway throughout the Pearl River Delta Region during the 1990 s. The result has been the emergency of a variety of shareholding models was embedded within specific local contexts. See Shenglan Li, Institutional Property Reforms in Rural China and Urbanization (Woguo Nongcun Chanquan Zhidu Gaige Yu Nongcun Chengzhenghu Fazhan) (Guangzhou: Sun Yat-Sen University Press, 2004).
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Formal rules such as laws, regulations and policies are becoming increasingly vital in local governance. For example, villagers serving a prison sentence are entitled to lesser dividends [20]. In addition, village cadres can enjoy the legitimacy derived from formal rules and procedures of the Articles, which are similar to these modern companies. However, this was at the costs of more restrictions imposed by the local state. First, all the SCs are under the administration of the district government after these reforms. They are also under the leadership of the Party Secretaries. Consequently, the SCs still had to work with the government to provide social welfare. As a result, the village cadres are invariably responsible for carrying a dual role. They are monitored by their shareholders because they now need to demonstrate their efforts in acting for the benefits and interests of all shareholders. They also need to comply with the local state’s administration and guidance, by implementing state policies and monitoring the compliance behavior of their shareholders [21].
4 Implications of the GLD Experience The GLD experience exemplifies the local state managing the urban transformation of rural areas through the deliberate engagement of district government in social welfare providing. This study suggests that several key factors have interacted to determine the governance process and patterns in the GLD. There is no question that the GLD’s mode of governance is underpinned by the local government’s abundant financial resources, coupled with a strong capacity in public administration. This is an important precondition for the local state to expand its role in welfare service provisions, but insufficient to guarantee collaboration with the village collectives and villagers in promoting and implementing action-oriented proposals. In the case of the GLD, the separate interests of the district government, the village collectives and the villagers constitute another critical condition for its specific governance outcomes. The district government needs land resources for industrial development and urban expansion. However, this is not only for economic accumulation. It is also for the pursuit of greater fiscal capacity, with which the local state can engage in social welfare provisioning and thereby claim greater legitimacy in the course of local state building. The local government’s reliance on land to achieve the dual purposes of economic development and welfare service provisioning inevitably speeds up its land requisition programs, triggering land disputes between the district government and villagers. These conflicts, however, should not be regarded simply as villages’ resistance to the state’s land requisitions. Unlike their counterparts in some other peri-urban areas of China, villagers living in the GLD are not landless peasants displaced by urbanization. Rather, they co-own (through the SC) a certain amount of “reserved commercial land” after the state’s land requisition [22]. The handsome income derived from leasing out these commercial lands to investors has equipped village collectives with impressive financial capacities to provide improved village facilities and social security services for villagers. Under such circumstances, village collectives and villagers generally do not resist land requisitions. What village collectives are really concerned about is the
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amount of compensation and how to enhance the profit-making capacities of their “reserved land.” To villagers, what is important is how land compensation fees and land related incomes are distributed. In this context, the tension between villagers and their self-organizing village units constitutes another important and integral part of local land politics in GLD. This has especially been the case, when increasing revenuegenerating opportunities from the collective village land lured some village leaders to engage in corruption, fraudulent activities and illegal undertakings, which benefit their own wallets and sacrifice the villagers’ interest. These conflicts and tensions have created opportunities for the local government to extend power into villages and regain control over the widespread unrest surrounding land disputes [23]. Apparently, the experience of GLD is embedded in its local economic, social and political contexts. Whether the GLD mode of governance can be duplicated in other parts of China requires further research. Yet, the GLD experience and its locallyspecific lessons offer useful insights that can inform local governance reforms in different contexts, as they highlight the unexpected effects of the New Countryside Construction policy on rural-urban transition. Moreover, they demonstrate some issues in the relations between urbanization and local governance restructuring that have implications for both theory and policy. The central state’s policy shift towards integrated urban-rural development has spurred local governments to establish welfare services for villagers who have lost their arable land in the process of urbanization. However, it seems that the objective of the New Countryside Construction policy, to revitalize agriculture, is still hard to achieve. In responding to the central state’s call for ensuring rural-urban equality, local governments have been making every effort to eliminate the existing inequalities by turning peasants into urbanities and facilitating the transformation of rural villages to urban neighborhoods. There has been very little effort to offer technical support or direct subsidies for agricultural production and the marketing of agricultural products. Under such circumstances, the local implementation of the New Countryside Construction policy in many localities has essentially been an in-situ urbanization process. To survive this new round of urbanization, local governments have to respond to the rising demand for housing, pensions and medical services from rural peasants (now urban residents), who were previously excluded from the welfare benefits provided by the state under the hukou system. However, in the absence of stable revenue from goods and services taxes, property taxes and so on, local authorities have to rely on land as a major source of income for local public finance. In the case of GLD, the local government does not directly depend on revenue from the sale of public land but has to secure its tax revenue from business enterprises by expanding its industrial development zones into the neighboring village areas. As local politics try to balance land grabs for commercial projects with farmland conversion for social welfare provisions, new forms of conflict and collaboration between local governments and rural villagers have emerged, transforming the role of the local state and creating new institutional arenas for interaction among the state, village collectives and villagers.
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5 Conclusions Extending from the idea of “building a new countryside”, the Chinese central government recently mapped out an important strategy on “rural vitalization (zhenxing nongchun)” in 2018. It aims to build rural areas with thriving businesses, pleasant living environments, social etiquette and civility, effective governance, and prosperity. What can be learnt from the experience of Guangdong Luogang district? During the past decades, an urban-biased development strategy, supported by the rural-urban dualist system, has undoubtedly brought enormous economic success to China. Nonetheless, this strategy has also generated increasing rural-urban divisions, and generated resistance, opposition and confrontation from the rural villagers. Recognizing that these social tensions are undermining the legitimacy of the socialist ruling regime, the Chinese government intended to redress the widening rural-urban inequalities through the New Countryside Construction policy. This study argues that although the New Countryside Construction program is aimed at improving the rural peasants’ livelihood, it should also be seen as an attempt by Chinese state to build its governing capacity to retake its control over rural society These trends have brought about the appearance of new local governance modes that are not fully represented under the intellectual perspectives of “local state corporatism” and “village corporatism.” Using the GLD in Guangdong Province as a case study, this article identifies one of the new modes of local governance with the following distinguishable characteristics. First, the GLD model of governance reflects the transformation of local governance strategies, from taking industrial development as the sole and eventual goal of rural urbanization to providing comprehensive public goods and services to villagers (e.g. creating job opportunities). In collaboration with the local village organizations, the local government enhances the social well-being of the rural community, although the level of services is still far below that of the urban residents. Second, the implementation of shareholding reforms provides villagers with a better delineation of their rights to collective assets. This inspires villages to support the urban development, which can increase the values of their collectively owned land. However, we should note that these villages do not remain completely automatous from the local institutions and the local state’s supervision. Third, this new mode of governance represents a subtle extension and expansion of local state power into rural communities. During the Maoist period, the central state closely linked the Chinese rural societies, which were self-governing, to its state apparatus through an elaborate “Commune-Brigade-Production Team” administrative bureaucracy in the villages. In the reform era, however, the implementation of the Household Responsibility System, coupled with an urban-biased development strategy, consistently undermined the state’s regulatory functions in rural areas. In the new wave of urbanization driven by the New Countryside Construction movement, the GLD local government has sought to link village organizations and villagers to its regulatory framework through shareholding reforms. All in all, the case of GLD shows that the actual implementation of new countryside building has essentially been a process of urbanization, which is blurring the collective
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identity of villagers and leading to the disintegration of self-governing communities. Any attempt to revitalize the countryside requires a further examination of how to strengthen the linkage o villagers, solidify their collective identity and blind their common interests together in a locality. Acknowledgement. Research findings of this study come from a research grant from (Project No. PolyU 25203215) the Research Grants Council of the Hong Kong Special Administrative Region, China and an international grant (Grant No. 0175–1049) from the Ford Foundation.
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19. Po, L.: Redefining rural collectives in China: land conversion and the emergence of rural shareholding co-operatives. Urban Stud. 45(8), 1603–1623 (2008) 20. Wong, S.W.: Reconsolidation of state power into urbanising villages: shareholding reforms as a strategy for governance in the pearl river delta region. Urban Stud. 53(4), 689–704 (2016) 21. Wong, S.W.: Urbanization as a process of state building: local governance reforms in China. Int. J. Urban Region. Res. 39(5), 912–926 (2015) 22. Wong, S.W.: Land requisitions and state-village power restructuring in Southern China. China Q. 224, 888–908 (2015) 23. Tang, B.S., Wong, S.W., Liu, S.C.: Institutions, property taxation and local government finance in China. Urban Stud. 48(5), 847–875 (2011)
Study on the Development Mode and Promotion Strategy of Tourism-Oriented Characteristic Small Town in Jiangxi Province Qunhong Liu(&) and Shuoyang Li Institute of Urban Construction, Jiangxi Normal University, No. 99 Zi Yang Street, Nanchang 330022, Jiangxi, China [email protected]
Abstract. In the upsurge for construction of characteristic small town, as the main force, the tourism-oriented characteristic small town plays a significant role for the development of characteristic small town, all regions have tried to build the tourism-oriented characteristic small town to promote the development of the local economy, thus pushing forward the new type urbanization. This paper takes the tourism-oriented characteristic small town in Jiangxi Province as the research object, then, it analyzes the necessity and present situation of developing the tourism-oriented characteristic small town in Jiangxi Province, next, according to the guiding role of the development mode to the development of things, the paper analyzes the development mode of the tourism-oriented characteristic small town in Jiangxi Province, so as to find out the problems of neglecting the industrial development, the disharmony between the tourism industry and the residents' life as well as the strong centralization of the tourism regions that are existing in the development of the small town. Finally, relevant countermeasures are put forward form three aspects, which are the perfection of industrial system, reasonable allocation of functions and the development of tourism in the whole region. Keywords: Tourism-oriented characteristic small town Developing pattern Promotion strategy
1 Introduction Under the background of new urbanization, along with the requirement to promote the collaborative development of the urban and rural area, as the main force of promoting new urbanization, the characteristic small town has obtained significant attention of the state, it is planning to develop one thousand characteristic small towns by 2020 under the leadership of the ministry of housing and urban-rural development. In January 2016, the government of Jiangxi published the development scheme for characteristic small town of Jiangxi Province, with requirements to build a suitable sized populated area with urban functions as well as the rural culture. There are twelve towns in Jiangxi that have been selected as the national level characteristic small towns, however according to the development features of the twelve characteristic small towns, tourism-oriented © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 66–76, 2021. https://doi.org/10.1007/978-981-15-3977-0_5
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characteristic small town has taken the largest portion of 75%, therefore the analysis over the tourism-oriented characteristic small town is of great importance. The tourism-oriented characteristic small town refers to the development of the town which mainly relies on the tourist industry, with supplement of additional industries radiated by the tourist industry, of which the tourist industry can be classified by tourism, health and fitness industries, accommodation and catering industries, leisure entertainment industry etc., and the developing pattern is the general term for the orientation and path of the object development under a certain background, which possesses instructional function to the development of things. It is necessary to consider from multiple aspects of resource advantage, transportation factor and geological position, etc. while choosing the developing pattern for the tourist town, and make the correct choice over the developing pattern through analyzing multiple factors and continuously improving the development pattern. From the perspective of developing pattern for tourism-oriented characteristic small town in Jiangxi, the developing pattern of the town has not been completed yet and therefore would be necessary to be further improved. Based on the analysis of the development mode of tourism-oriented characteristic small town in Jiangxi Province, the problems existing in the development mode of the small town are found out and the relevant suggestions are put forward, so as to promote the construction of the tourism-oriented characteristic small town in Jiangxi Province.
2 Necessity and Present Situation of the Development of Tourism-Oriented Characteristic Small Town in Jiangxi Province 2.1
The Necessity of the Development of Tourist-Oriented Characteristic Small Town in Jiangxi Province
2.1.1 The Development Speed of Urban Economy in Jiangxi Province is Down The GDP of Jiangxi Province was 1.29 trillion yuan in 2012 and 2.08 trillion yuan in 2017. In the past five years, the GDP in Jiangxi Province had shown the increasing trend year by year (Fig. 1), but its growth rate was gradually slowing down. However, under the appearance of slow economic growth rate in urban area, there are a lot of problems hidden below, such as large proportion of fixed assets investment, the real economy is weak, low proportion of service industry, slow cultivation of new growth point, stagnant development of manufacturing industry and so on. The concrete reasons that lead to these problems are the insufficiency of effective supply, unreasonable industrial structure, unbalanced regional development, etc., which have hindered the development of economy. As an important grasp in promoting the new style of
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urbanization, the characteristic small town has great influence on the coordination of regional economic development and the improvement of industrial structure. Therefore, a series of urban economic development issues like this have promoted the development of tourism-oriented characteristic small town.
Fig. 1. 2012–2017 regional GDP and growth rate (Source of the data: Jiangxi Province Statistical Yearbook)
2.1.2 The Industrial Structure of Jiangxi Province is Adjusted and the Service Industry Develops Rapidly At present, industry is still a short board for the economic development of most cities in Jiangxi Province, especially the problems of small industrial scale, difficult transformation of traditional industries, industrial chain is relatively short and so on have not been fundamentally improved. At the same time, when the industrial development has been hindered, the service industry is quietly starting up. In 2015, the growth rate of service industry had surpassed the growth rates of GDP as well as the second industry for the first time, with the tax revenue of service industry accounted for 53.25% of the total tax revenue, which became the largest source of tax revenue. In 2017, growth rate of service industry in Jiangxi Province was 10.7%, which took on the third place around the China, in addition, the contribution rate of service industry was 1% higher than that of the second industry, so it has formally become the largest industry type in Jiangxi Province. What’s more, the industrial structure of Jiangxi Province is continuously to be optimized, the output growth of service industry is increasing continuously (Fig. 2), at the same time, the GDP of tourism industry in Jiangxi Province has been increased year by year in the past five years, whose proportion in gross domestic product of the tertiary industry is also rising year by year, which provides an opportunity for the development of the tourism-oriented characteristic small town.
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Fig. 2. Regional gross domestic product and the gross domestic product of primary, secondary and tertiary industries during 2012–2017 (Source of the data: Jiangxi Province Statistical Yearbook)
2.2
The Development Status of Tourism-Oriented Characteristic Small Town in Jiangxi
2.2.1 The Tourism-Oriented Characteristic Small Towns Occupy a Large Proportion and Their Distribution is Relatively Concentrated Currently, Jiangxi has twelve national level characteristic small towns, respectively as Wengang Town, Shangqing Town, Wentang Town, Jiangwan Town, Nanjing Town, Yonghe Town, Yiqian Town, Yaoli Town, Xiaobu Town, Haihui Town, Taiping Town and Geshan Town [1]. The construction types of characteristic small towns are mainly classified as industry oriented, technology oriented, agriculture oriented as well as tourist oriented. From the perspective of development features, the industry characteristic small towns are reflected with innovative industry, with the industry revenue taking the main portion the town’s revenue [2]; the technology characteristic small town has mainly focused on the emerging industries like technical intelligence, and this kind of towns are often located in the areas with high degree of economic development; the agriculture characteristic small town based on rural area and provides service to the rural area, which equals to the transaction platform of the agricultural products; the tourist characteristic small towns mainly manifest as towns with unique tourist resources, which concentrate on the tourist industry with supplement of additional industries radiated by the tourist industry. The construction type has been categorized by following the development features of the twelve characteristic small towns, the agriculture characteristic small towns include Nanjing Town in Quannan County, specialty industry towns contain Wengang Town in Jinxian County and the Geshan town in Zhangshu City, which are separately developing two characteristic industries of pen production and medical production industry. The remaining nine characteristic small towns are all tourist characteristic small towns which has reached a portion of 75%. In this paper, the locations 12 characteristic small towns are found out through Google earth, then, drawing the geographical location distribution map (Fig. 3) and the type distribution map (Fig. 4) of the characteristic small towns in Jiangxi Province by using Arcgis software [3].
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According to the figure, it can be analyzed and known that the distribution of characteristic small towns in Jiangxi Province is relatively scattered. However, the distribution of tourism-oriented characteristic small towns is relatively concentrated, which are mainly located in the northern and central regions of Jiangxi Province.
Fig. 3. Distribution of characteristic small town (Source of the figures: painted by the author)
Fig. 4. Type distribution of characteristic small town (Source of the figures: painted by the author)
2.2.2 Imbalance Development of the Tourism-Oriented Characteristic Small Town Among the construction types of characteristic small town in Jiangxi Province, the tourism-oriented characteristic small town has accounted for a great portion, from the perspective of developing features, the tourism-oriented characteristic small town has taken the tourist industry as the main body, and promoted the construction of the town through bringing forth the development of other relative industries. However according to the current developing status of the tourism-oriented characteristic small town of Jiangxi Province, imbalance problems exist in its developing process. The Shangqing Town, Wentang Town and Jiangwan Town which have a tourist industry basis are developing fairly well, they rely on the unique tourist resources and the original tourist basis, promote the construction of the characteristic small town with the basis of forming a certain degree of aggregation for the tourists and the completeness of supporting industries for the tourist industry. Nevertheless tourism-oriented characteristic small town without or with relatively weak tourist basis, it is unable to generate sufficient attraction to the visitors due to the insufficient of uniqueness for the tourist resources and less obvious of the tourist advantages, therefore hard for it to form aggregation for the tourist and push forward the development of the town. Taking Yiqian Town as an example, which develops the tourist industry mainly relies on the
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local historic culture, however, on account of lacking uniqueness and weak tourist basis for the tourist resources, the development and progress of the town has not been obvious.
3 The Development Pattern Selection of the TourismOriented Characteristic Small Town in Jiangxi Province The tourism-oriented characteristic small town refers to the characteristic small town which is dominated by the tourist industry. However, it will present various development patterns according to the different resources and distinct conditions of the small town. The development patterns of tourism-oriented characteristic small town in Jiangxi Province can be divided into three categories, please see Table 1 for the specific details. 3.1
The Development Pattern Based on the Featured Resources
The featured resources can be divided into natural tourism resources and historical and cultural resources [4]. The natural tourism resources refer to the natural landscape composed of geographical conditions or natural creatures. It is shown in a small town with unique scenic spots and superior natural environment. The scenic spot is the main attraction for the development pattern of the characteristic small town depending on the natural resources so as to make the formation of leisure matching facility and promote the development of the additional industry of tourism. It covers a wide range for the historical and cultural resources which mainly include historical sites, heritage buildings and religious culture etc. It is shown in a small town with a clear historical context for the historical sites or towns. The development pattern of characteristic small town relying on the historical and cultural resources regards the historic culture or cultural relics and traditional architecture as the tourism attractive point and takes the tourist industry as the leading position in order to promote the development of related industries. Shangqing Town, Wentang Town, Jiangwan Town and Yiqian Town are the characteristic small towns in Jiangxi Province relying on the development pattern of featured resources. Shangqing Town, located in the core scenic area of Long Hushan Mountain tourist attraction, is the birthplace of Chinese Taoism with unique and abundant natural tourism resources and historical and cultural resources. The development of the small town is mainly driven by the core of tourist industry. Wentang Town, located fifteen kilometers south of Yichun City, has the National 5A Tourist Attraction, Ming Yueshan Mountain and the rare selenium spa resource in the world, “The First Selenium Spring in China”, which improve the development of tourist industry and related industries on account of the peculiarity of tourism resources. Jiangwan Town, which is the few millennium ancient town in Wuyuan County, is the forerunner of the inheritance and protection of the Huizhou Culture with abundant
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historical and cultural resources. It mainly focuses on the development of the tourism industry by historical culture. Yiqian Town is one of the most complete and large residential buildings in Jiangxi province. It takes the residential architecture as the attraction point to develop the tourism industry. 3.2
The Service-Led Development Pattern
The service-led tourism-oriented characteristic small town which closes to the tourist attraction is the tourist reception place. As the distributing center of tourism, the development of small town mainly provides leisure and entertainment services for tourists through analyzing the consumption features and consumption preferences of tourists so that tourists can have different experiences compared with scenic spots. It is the development pattern which relies on tourism to develop related tourist industry, pays attention to the extension and service in the development of tourist industry, strengthens the complementation between the function of small town and scenic spot, and continuously consummates the service function of catering and accommodation in small town. Haihui Town, which is dominated by service in the tourism-oriented characteristic small town of Jiangxi Province, is located in the eastern suburb of Jiujiang City, Jiangxi Province. It is located on the east of Poyang Lake with vastness and the west of Five Old Men Peaks in Lushan Mountain. Based on the superior location which is close to the tourist attractions, Haihui Town creates a different area for leisure and entertainment services through the development of agricultural tourism and leisure vacation in order to make tourists experience different ways of amusement. 3.3
Comprehensive Development Pattern
The comprehensive development pattern refers to the integration of two or more development patterns for characteristic small town. Under this development pattern, the characteristic small town generally has unique tourist resources and good locational conditions [5]. From the current situation for development of the tourism-oriented characteristic small town in our country, most of the characteristic small towns in the comprehensive development pattern combine the development pattern based on the characteristic resources with that dominated by ecological leisure. The characteristic small town, which take the requirements for leisure and tourism in the big city as the motive force and featured resources as the development support, is generally located on the suburb of big city and takes the road of comprehensive development of leisure and vacation. Yonghe Town, Yaoli Town, Xiaobu Town and Taiping Town are the characteristic small towns under the comprehensive development pattern in Jiangxi Province. Among them, it is dominant for the comprehensive development mode based on featured resources and ecological recreation, such as Yaoli Town, Xiaobu Town and Taiping Town. Taiping Town is 30 km far from Nanchang City, and there are 4A scenic spots: Shenlong Lake and Lion Peak, with beautiful environment and high negative oxygen ion content. Taiping Town develops ecological leisure industry as well as tourist industry.
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Table 1. The development pattern of characteristic small town in Jiangxi Province Development pattern Development pattern based on the featured resources Development pattern dominated by the ecological leisure Development pattern with service-led Comprehensive development pattern
Characteristic small towns Shangqing Town, Wentang Town, Jiangwan Town, Yiqian Town None
Haihui Town Yonghe Town, Yaoli Town, Xiaobu Town, Taiping Town Data source: the author collects data to analyze and collate.
4 Problems Existing in the Development of Tourism-Oriented Characteristic Small Town in Jiangxi Province 4.1
Ignoring the Development of Supporting Industries
With the continuous expansion of the construction scale, the tourism-oriented characteristic small town requires more perfect supporting industries to meet the needs of local residents as well as the tourists [6]. However, the tourism-oriented characteristic small town in Jiangxi Province (especially the development model based on the characteristic resources) has overemphasized the development of tourism resources and the building of tourist attractions, thus neglecting the development of supporting industries. In addition to develop the tourism through relying on the characteristic resources, the tourism-oriented characteristic small town also needs to perfect the relevant supporting industries, such as catering industry, accommodation industry and so on. While the supporting industries of tourism in most small towns of Jiangxi Province are not perfect enough, the supporting industries are lack of a certain scale as well as the systematization, so that these small towns can not meet the needs of tourists. What’s more, there is also unreasonable phenomenon in the layout of supporting industries, most of the small towns arrange the supporting industries around the scenic spots, which leads to the phenomenon of uneven distribution of supporting industries. 4.2
The Tourism Industry is not in Harmony with the Life of Residents
At present, the construction of tourism-oriented characteristic small towns in Jiangxi Province focuse on the needs of tourism development and less attention is paid to the real ideas of the people. Therefore, conflicts between the aboriginal people and other stakeholders are easy to be generated during the construction process. For example, the employment of residents can not be solved practically, thus leading to a contrast between the hollowing of towns and villages and the strong seasonality of tourism; next, the incomes of local residents are unbalanced and uncoordinated, residents whose original address and location are better have gained more income through projects such as land rental or sales or developing happy farmhouse and so on, while the incomes of other residents are difficult to meet their expectations; facilities for leisure,
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entertainment and business services are mainly built for tourists, which are out of touch with the life of residents, etc. 4.3
The Homogenization of Tourism Product is Serious and the Concentration of Tourism Region is Strong
Tourism products is divided into core products, actual products and extended products [7]. In Jiangxi Province, the development mode of tourism-oriented characteristic small town is relatively concentrated, and there are some homogenization problems in the building of tourism products. For example, the characteristic small town which is developed by relying on the characteristic tourism resources only develops the sightseeing, traveling of scenic spots and so on, they do not develop the tourism resources in depth, which leads to the homogenization of tourism products. The strong concentration of tourism region also exists in most of the tourism-oriented small towns. Tourists often stay in the core tourism areas and can not form the traveling in the whole region. For example, the area where the tourists of Taiping Town mainly stay is the periphery with Xinjie Street as the core. The rest of the small town is less visited because of the tourism products lack of attraction and the tourism lacks of systematic planning.
5 Optimization of the Development Mode of TourismOriented Small Town in Jiangxi Province 5.1
Perfecting the Industrial System
The development of tourism-oriented characteristic small town needs to establish a systematic industrial system, the industry is the core of characteristic small town. The development of industry in tourism-oriented characteristic small town not only needs to build the tourism industry, but also to build the characteristic industry, so as to make the two major industries form the linkage effect. In the selection of characteristic industries, we should combine the development conditions of small towns, selecting the newly developed industries or traditional industries; in the positioning of tourism industry, in addition to the building by relying on the scenic spots, it is also necessary to build the extensive tourism industry cluster structure, in order to constantly improve tourism related supporting industries, so that tourism and catering, accommodation, entertainment, passenger transportation as well as the trade and commerce can be connected together organically [8]. When building an industry, it should be considered about the interests of local residents, through the development of industry to provide employment opportunities for local residents, such as the creation of happy farmhouse and hostel, thus increasing the income of local residents and relieving the contradiction between the development of tourism industry and local residents' life. The perfection of industrial system can provide a solid economic base and industrial foundation for the development of the tourism-oriented characteristic small town, and at the same time, it can promote the construction of tourism-oriented characteristic small town brand.
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Reasonable Allocation of Functions
The development of tourist tourism-oriented characteristic small town should be reasonably allocated based on the layout of industry and the need of tourism development. The functions of small town generally include the following several aspects: on the one hand, the allocation of function of the small town needs to meet the needs of local residents, on the other hand, it also needs to meet the requirements of outside tourists. When allocating the functions of small town, first of all, the core functional area should be arranged according to the town planning and the overall tourism planning. In general, the core functional area should be equipped with tourist center, parking lot and major tourism projects, etc. Secondly, relying on local unique resources to create the sub-projects of tourism, through the landing of sub-projects to achieve the coverage of project peripheral functions, in addition, according to the interaction between the functions as well as the topographical factor of the small town to divide the functional land, so as to realize the intensification of land use, at the same time to realize the mutual connection between the functions, so that meeting the life needs of the tourists and the local residents. 5.3
Enriching Tourism Products and Realizing the Tourism in Whole Region
The development in whole region of the tourism-oriented characteristic small town should take the characteristic of small town as the leading part from the perspective of the whole region, at the same time, strengthening the creation of tourism products and the finding of the tourism characteristics of small town, so as to solve the problems in homogenization of tourism products and the strong concentration of the tourism regions, thus realizing the tourism with full time as well as the space in whole region [9]. Full-time tourism in the whole region needs small town to rely on local tourism activities or folk customs to create festival activities, so that connecting the tourism activities with tourism areas in time; the full-space tourism in the whole region needs the small town to do a good tourism planning, so as to connect the different regions of the town through tourism activities and tourism regions, combining the different spaces of the small town into an organic whole and realizing the tourism in whole region.
6 Conclusions The tourism-oriented characteristic small town is the key point of developing the characteristic small town in Jiangxi Province. Optimizing the development mode of the characteristic small town becomes the important way to solve the problems existing in the tourism-oriented characteristic small town in Jiangxi Province, such as imperfection of the industrial system, the disharmony between tourism industry and the residents' life, serious homogenization of tourism products. According to the in-depth analysis of the development mode and problems of tourism-oriented characteristic small town in Jiangxi Province, the small town should be continuously optimized its development mode from the aspects of perfecting the industrial system, rationally allocating the
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functions and realizing the tourism in whole region, so as to promote the development of small town and to solve the problems existing in the development of tourismoriented characteristic small town in Jiangxi Province.
References 1. 44 towns listed in the list of the first feature towns in Jiangxi. Urban Plann. Commun. (16), 8 (2017) 2. Mo, Z., Wangdan, Q.: The road of industrial linkage development in characteristic small towns with historical classics – taking Xihu District Longwu tea town as an example. Huazhong Archit. 35(6), 84–90 (2017) 3. Wang, X., Hou, J., Han, X.: Spatial distribution characteristics and influencing factors of Chinese characteristics towns. Planner 34(01), 12–15+35 (2018) 4. Zhaojing. Analysis of the present situation, problems and patterns of the tourist characteristic small towns. Price China (05), 83–85 (2017) 5. Xu, Z.: The study on the development pattern of suburban tourism towns under the background of new urbanization. Zhenzhou University (2015) 6. Zhao, H.: Analysis on the innovation and development of tourism characteristic towns. Economic Issues (2017) 7. Wang, Y., Feng, W.: Further discussion on the concept and structure of tourist products. J. Taiyuan Teach. Coll. Nat. Sci. Ed. 6(3), 35–39 (2007) 8. Jiang, X., Lu, Y.: Analysis on sustainable development mode of Xizhou tourism town in Dali. China Bus. Trade (08), 176–178 (2011) 9. Zeng, X., Zheng, Y.: Discussion on the tourism development in Yongding county from the perspective of whole region tourism. J. Fujian Agric. Forestry Univ. (Philos. Sci. Ed.) 18(01), 86–91 (2015)
Temporal-Spatial Evolution Patterns of Population Urbanization and Land Urbanization in China Xi Yang, Xinhai Lu(&), Ruihong Liu, Zexiu Chen, Nan Ke, and Weichen Shen College of Public Administration, Central China Normal University, Wuhan, China [email protected]
Abstract. The purpose of this paper is tantamount to explore the dynamic evolution and spatial distribution pattern of urbanization in China from the perspectives of population urbanization and land urbanization. The methods used in this paper are the kernel density estimation and the standard deviations ellipse. The results of the study: 1) The general level of China’s population urbanization and land urbanization has been continuously improved. The interprovincial differences in population urbanization are gradually narrowing which land urbanization continue to increase. However, land urbanization is higher than population urbanization in terms of growth rate, the degree of polarization and inter-provincial differences. 2) The gravity center of China’s population urbanization is located in Henan province, the direction of movement is generally moving southward to southward;The gravity center of land urbanization is located in the junction of northeastern Anhui province and northwestern Jiangsu province, the direction of movement is generally moving eastward to westward. 3) The main trend of China’s population urbanization spatial distribution is roughly the same as that of “Hu Huanyong Line”, which is the dividing line of population density in China,the spatial differences are mainly reflected in the northwest-southeast direction, the spatial-temporal differences are more obviously driven by the population distribution. The main trend of spatial distribution of land urbanization is roughly the same as that of the developed eastern coastal economic belt, the spatial differences are mainly reflected in the eastwest direction, and the spatial-temporal differences are more obviously driven by the economic development level. 4) China’s land urbanization shows more obvious spatial agglomeration than population urbanization. The spatial development of population urbanization shows a trend of shrinkage and polarization, while the spatial development of land urbanization shows a trend of expansion and discretization. In conclusions, the development of China’s new-type urbanization should not only resolve the contradiction of imbalance between the population urbanization and land urbanization, but also resolve the contradiction of between regional development differences, to achieve the intrinsic coupling and spatial equilibrium between population urbanization and land urbanization. Keywords: Population urbanization Land urbanization New-type urbanization Kernel density estimation Standard deviations ellipse © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 77–89, 2021. https://doi.org/10.1007/978-981-15-3977-0_6
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1 Introduction Urbanization is an important driving force for the development and progress of human civilization. The core of urbanization is population urbanization, which is the process of rural population gathering in cities and the increase in urban population. The carrier of urbanization is land urbanization, which is the process of the transformation of rural land into urban land and the expansion of urban areas. In 2017, the 19th National Congress of the Communist Party of China proposed that “the main contradiction in Chinese society has been transformed into a contradiction between the growing needs of the people’s better life and the development of inadequate imbalances. “. However, the process of urbanization in China is not only facing the unbalanced and inadequate between the development of population urbanization and land urbanization, but also facing the unbalanced and inadequate between regional development, which has become a typical portrayal of unbalanced and inadequate development of China’s society. At present, the academic circles have carried out the relevant research on the definition of the urbanization of the population and the urbanization of the land [1], the coupling coordination [2, 3], the interaction [4], the spatial differences [5, 6], the reasons for the imbalance [7, 8], coordinated development policy [9], which lays a solid foundation for the research of this paper. Due to the difference in population and land factor endowment in different regions and the difference in the combination modes and optimization degree of various factors in the process of economic development. So, the regional differences in population urbanization and land urbanization have been widely recognized by scholars in the background of regional heterogeneity. Scholars synthesize the Gini coefficient [10], Coefficient of deviation [11], exploratory spatial data analysis [12], Geo-weighted regression model [13] and spatial econometric model [14] and other methods to analyze the regional difference and influence factors of population urbanization and land urbanization. The research areas are the Chinese national level [15], including Western region [16], Northeast region [17], Yangtze River Economic Belt [18] etc. and individual provincial and municipal levels of Sichuan province [19], Zhejiang province [20] and Lanzhou city [21]. The characteristics of temporal evolution and spatial pattern evolution of population urbanization and land urbanization are the important components of the temporal and regional differences of urbanization and the two key indexes of urbanization development. The current researches have made great contribution to China’s new-type urbanization theory research and practice development. However, most of the existing literature focuses on the study which is the spatial-temporal differences in one aspect of population urbanization or land urbanization. In a few literatures studies that combine population urbanization with land urban temporal evolution and spatial patterns are mostly studied from the perspective of local regions,the research on the long-time series and large-scale spaces of the combination of China’s population urbanization and land urbanization are relatively insufficient. While the traditional research methods used in the existing literature can reflect the differences in population urbanization and land urbanization to some extent, but it is difficult to effectively reveal the characteristics of temporal evolution and spatial distribution pattern of China’s population urbanization and land urbanization.
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This paper based on the existing research results. The data onto population urbanization and land urbanization supported by the provincial administrative units of the Chinese mainland in the period of 1996–2016. The integrated use of kernel density estimation and standard deviation ellipse method to study the dynamic evolution characteristics and spatial distribution patterns of China’s population urbanization and land urbanization, in order to provide reference for the policy formulation of China’s new-type urbanization strategy by revealing the historical evolution law of spatialtemporal pattern of China’s urbanization development.
2 Methods and Data 2.1
Kernel Density Estimation
Kernel density estimation (KDE)is a non-parametric method of estimating the probability density function. Its feature is that no assumption of parametric model is required to describe the distribution of random variables using a continuous density curve [22], which has become one of the important tools to study spatial distribution disequilibrium, can reveal the dynamic evolution of population urbanization and land urbanization development according to the kernel density estimation curve. The function formula is as follows: f ðxÞ ¼
n x x 1 X i k nh i¼1 h
ð1Þ
i is a kernel function; h is f ðxÞ is a density function, n is the sample quantity; k xx h bandwidth, x1 ; x2 ; . . .; xn is the sample observation value. The common kernel function has gauss kernel function, triangle kernel function, four-corner kernel function, Epanechnikov kernel function and so on, the choice of kernel function has little influence on the estimation result. In this paper, the common gaussian kernel function is used to estimate the distribution of China’s population urbanization and land urbanization. The curve distribution position reflects the level of urbanization development; The height of the main peak of the curve reflects the regional difference in urbanization development; The number of curve peaks reflects the degree of urbanization polarization; The ductility of the left and right tail of the curve reflects the difference between the urbanization level of the low value zone and the high value zone and the other regions, when the longer the trailing end means the differences are greater. 2.2
Standard Deviational Ellipse
Standard deviational ellipse (SDE) is used to reveal the spatial distribution characteristics of geographical elements which was first put forward by Lefever in 1926 [23], then widely used in the field of space statistics. Its constituent elements mainly include: center on gravity (mean center), rotation angle h, long axis and short axis. The center of gravity reflects the relative position of the element in the two-dimensional space.
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Rotation angle represents the angle formed by clockwise rotation of the north direction to the oval long axis. The long axis reflects the main trend direction of the factor space, which is reflected by rotation angle. The short axis reflects the trend direction of the spatial distribution of the elements. The ratio of the short axis to the long axis can reflect the shape of the spatial distributions of the elements, the ratio is closer to the 1, which indicates that the main factor space distribution is closer to the circle. A balanced urbanization development should be the situation where the population urbanization and the land urbanization have the similar spatial overall distribution characteristic, therefore both in the spatial distribution will show similar standard difference ellipse, otherwise the two-spatial distribution will have the difference. The standard deviation ellipse can clearly reflect the spatial distribution pattern and evolution law of China’s population urbanization and land urbanization. The formula is as follows: The center of gravity is calculated as: MðX; YÞ ¼
Pn Pn wi xi i¼1 wi yi Pi¼1 P ; n n i¼1 wi i¼1 wi
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MðX; YÞ represents the center of gravity of a region, n is total number of subregions, wi is the No. i’s sub-region property value; xi and yi represent the central coordinate of the No. i’s sub-region. The angle of rotation is calculated as: 8 AþB > > > tan h ¼ > > C > ! > > n n > X X > > > ~xi2 ~yi2 A¼ > > > > i¼1 i¼1 < vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi !2 !2 ð3Þ u n n n u X > X X > >B ¼ t 2 2 > ~xi ~yi ~xi~yi þ4 > > > > i¼1 i¼1 i¼1 > > > n > X > > > ~xi~yi C ¼ 2 > : i¼1
Where ex i and ey i are the deviations of the xy-coordinates from the mean center. The standard deviations from the x-axis and y-axis are: 8 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi rP n pffiffiffi > e ðe x cosh y sinh > i i i¼1 > rx ¼ 2 < n ð4Þ rP ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi n > p ffiffi ffi > e ðe x sinh y cosh i i > i¼1 : ry ¼ 2 n
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Indicator Selection and Data Source
The Research on the development of urbanization requires long time data to support, considering the reliability and availability of long-term data, in reference of existing research [24, 25], this article selects two dimensions of population urbanization and land urbanization to analyze the development of urbanization. Population urbanization is the core of urbanization, this paper uses the ratio of the urban resident population of the regional total population to characterize the urbanization level of population, which is used to reflect the process and agglomeration the degree of population of town agglomeration. Land urbanization is the carrier of urbanization, to keep consistent with the index of population urbanization, this paper adopts the ratio of built-up area to total area to characterize the urbanization level of land, which can reflect urban land expansion process and bearing space. Data onto National Bureau of Statistics of China and China’s Social and Economic Development Statistical Database, including China Statistical Yearbook, New China 60 Statistical Data Compiled, China City Statistical Yearbook and China Urban Construction Statistical Yearbook, finally sorted out the basic data onto population urbanization and land urbanization of the provincial administrative unit of the Chinese mainland from 1996 to 2016. Due to the lack of relevant data, China’s Hong Kong Special Administrative Region, Macao Special Administrative Region, Taiwan Province and the South China Sea Islands are not included in this article.
3 Results 3.1
The Time Series Dynamic Evolution Characteristics in China’s Urbanization
Use the calculates formulas for kernel density estimation and the EViews Software draws the map of China’s population urbanization and land urbanization kernel density of 1996, 2006 and 2016 (Fig. 1, Fig. 2), describing the dynamic evolution of the time series of China’s population urbanization and land urbanization during the research period.
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Fig. 2. The sequence evolution of China’s land urbanization
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The dynamic evolution characteristics of the time series of population urbanization (Fig. 1): (1) From the position of the kernel density curve in the research period shows a gradual shift to the right, which indicates that the urbanization level of the population is constantly improving. From 1996 to 2016, the total population of China increased from 1223.89 million to 1382.71 million, with the town population increasing from 373.04 million to 792.98 million. It’s increased by 2.13 times, the population urbanization rate has increased from 30.48% rose to 57.35%, an annual growth rate of 3.21%. (2) From the peak height of the curve crest, the main peak of the curve appears to fall first from 1996 to 2006, the main peak of the curve appears to rise from 2006 to 2016. It shows that the disparity between population urbanization level between provinces is enlarged before the trend is narrowed. (3) From the number of curve crest, in the study period, the kernel density curve shows the multimodal pattern of the main peak and the secondary peak, which indicates that the urbanization of the population of the research period is multipolar, among which, in 2016 the population urbanization level of Beijing, Tianjin and Shanghai is more than that of the 80%, which is much larger than the 57.35%of China’s population urbanization rate. (4) From the left and right side of the curve, the right trailing edge of the curve is larger than the left trailing end, the right trailing end appears the thickening trend, and shows the gradual overlapping trend, indicating that more and more middle and lower provinces population urbanization began to the high value area inflow, in the high value area province population town development speed began to slow down. The population urbanization of regional absolute difference has a decreasing trend, which shows that the potential for China’s population urbanization lies in some areas which are still in the middle and low value areas. The dynamic evolution characteristics of the time series of land urbanization (Fig. 2): (1) From the position of the kernel density curve, the curve position in the research period shows a gradual shift to the right, which indicates that the level of the urbanization of the land is continuously increasing. From 1996 to 2016, China’s built-up area was increased from 20660 square kilometers to 54331.47 square kilometers, it’s increased by 2.13 times, land urbanization rate from 0.22% rose to 0.57%, an annual growth is 4.95%. (2) From the peak height of the curve crest, the peak height of the curve is decreasing, showing the trend from “spike peak shape” to “wide peak shape”, which indicates that the disparity of land urbanization between provinces in China that shows a trend of continuous expansion. (3) From the number of curve crest, the kernel density curve shows the multimodal pattern of the main peak and the secondary peak, which indicates that the urbanization of land in China during the research period is more and more multipolar in the study period. (4) From the left and right side of the curve, the curve left trailing start to value changes in the range is small, the right trailing tail changes in the range of expansion trend, and the thickness of the end of the thickening trend, indicating that in the high value of the provinces land urbanization faster growth. There are more and more provinces where the level of land urbanization
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has gone to high value areas, but the development base and development speed of various regions are different. In some areas the level of land urbanization is much higher than that in other areas, and the absolute difference in the Land urbanization area has expanded. By comparing the graph of the kernel density curves of China’s population urbanization and land urbanization, it can be found that: (1) The position of the curve shows the right shift trend, which indicates that the level of population urbanization and the level of land urbanization both showed an increasing trend during the research period. However, during this period, China’s urban population increased by 2.13 times, the annual growth rate of population urbanization was 3.21%, but the built-up area grew by 2.63 times, and the average annual growth rate of land urbanization was 4.95%, the growth rate of land urbanization is faster than population urbanization. (2) On Curve Crest Peak Height. Population urbanization’s peak height of the main peak shows an increasing trend from 2006 to 2016. However, land urbanization from 1996 to 2016, the peak height of the main peak shows a continuous downward trend. It shows that the provincial differences in population urbanization are gradually decreasing, and the difference in land urbanization is increasing. (3) On Curve Crest Quantity, the phenomenon of multiple peaks of the main and sub-peaks has appeared, which indicates that polarization quadrants appeared in China’s population urbanization and land urbanization during the study period, but in the crest quantity the land urbanization is more than the population urbanization. It indicates that the polarization degree of the land urbanization is greater than the population urbanization polarization degree. (4) On the trailing end of the curve, both the right trailing end is larger than the left tail, and the thickness of the right trailing tail is increasing, indicating that more provinces population urbanization and land urbanization of China have begun to flow to high value areas over time. But the right trailing end of the land urbanization curve is more obvious than the population urbanization curve, and the urbanization of the land differs more than the urbanization of the population. 3.2
The Evolution Characteristics of Spatial Pattern in China’s Urbanization
By using the standard deviation ellipse formula, the center of gravity (GC) and the standard deviation ellipse (SDE) of population urbanization and land urbanization in 1996, 2006 and 2016 were calculated respectively (Table 1), by using ArcGIS software to achieve visual display (Fig. 3, Fig. 4), the main purpose is characterizing China’s population urbanization and land urbanization of the gravity of the transfer and spatial distribution pattern characteristics.
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Fig. 3. The standard deviation ellipse of China’s population urbanization
Fig. 4. The standard deviation ellipse of China’s land urbanization
Table 1. The parameters of standard deviation ellipse for China’s population urbanization and land urbanization Classification
Year Center of gravity coordinates
Population urbanization 1996 2006 2016 Land 1996 urbanization 2006 2016
113.26°E 113.16°E 112.40°E 117.33°E 117.45°E 117.15°E
35.33°N 34.38°N 34.21°N 34.12°N 34.9°N 34.8°N
Perimeter Area (km) (km2)
XStdDist YStdDist Rotation (km) (km) (/°)
7091.50 6879.60 6846.63 4789.93 4488.58 4623.33
1057.21 1014.94 1020.39 572.13 569.58 586.56
3978469.80 3737112.43 3708262.84 1673405.22 1513195.08 1605273.10
1197.92 1172.11 1156.85 931.08 845.71 871.19
49.99 36.21 40.82 7.62 1.64 6.60
3.2.1 Center of Gravity Position and Migration Path Population urbanization center on gravity and Migration path: (1) In general, the population urbanization center of gravity and moving range is located in Henan province from 1996 to 2016, the overall movement towards the direction of the first to the south (slightly westward) and then to the southwest migration trend, the moving speed shows the first fast after the slow trend. (2) The specific location of the population urbanization Center of gravity is located in Jiaozuo in 1996, then is located in Zhengzhou in 2006, now is located in Luoyang in 2016. (3) The specific migration trajectory and speed of the population urbanization center of gravity from 1996 to 2006: population urbanization center of gravity to the south (slightly westward) moves 105.43 km, the average annual mobile 10.54 km; from 2006 to 2016 population Urbanization center of gravity move to the west of the south of 59.34 km, the annual move 5.93 km. It shows that the population urbanization of South China was faster than that in the north from1996 to 2006, and the population of southwest China developed faster than the rest of the country from 2006 to 2016.
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Land urbanization center of gravity and Migration path: (1) In general, the center of gravity and movement of land urbanization from 1996 to 2016, it is located in the northeast of Anhui Province and the northwest of Jiangsu Province, the overall appearance of the first eastward and then westward migration trend, the moving speed showed a first slow and fast trend. (2) The specific location of the land urbanization Center of gravity is located in Xuzhou, Jiangsu Province in 1996; it is located in Suzhou of Anhui Province in 2006 and 2016. (3) The specific migration track and speed of the land urbanization center of gravity from1996 to 2006, the land Urbanization center of gravity moves to the East 23.43 km, the average annual mobile 2.34 km; the land urbanization move west 47.48 km from 2006 to 2016, the average annual mobile 4.75 km. It shows that land urbanization in eastern China grew faster than the rest of the country from 1996 to 2006, and the growth rate of land urbanization in central and western China began faster than in the east from 2006 to 2016. Generally speaking, the deviation from the center of gravity reflects the spatial nonequilibrium of China’s population urbanization and land urbanization. The distance and speed of the migration of the center of gravity of population urbanization have decreased trend, which indicates that the spatial fluctuation of the population’s urbanization center of gravity tends to moderate. The migration distance and speed of the center of gravity of the land urbanization have increased tendency, which indicates that the spatial fluctuation of the center of gravity movement of the land is tending to increase. At the same time, the distance between population urbanization and land urbanization is extended from the 399.44 km in 1996 to 420.42 km in 2016, which indicates that the spatial distribution of population urbanization and land urbanization has enlarged trend. 3.2.2 Spatial Distribution Direction Population urbanization: the rotation angle first decreased and then increased from 1996 to 2016. The overall trend shows a fluctuating trend. The main trend of China’s population urbanization spatial distribution are roughly the same as that of “Hu Huanyong Line”, which is the dividing line of population density of China. The standard deviation ellipse spatial distribution generally shows the northeast-southwest direction is the main trend, and the northwest-southeast direction is the auxiliary trend. It shows that the spatial pattern difference in northwest-southeast directions of China’s population urbanization is larger than that of northeast-southwest. Land urbanization: the rotation angle first decreased and then increased, which shows a general trend of fluctuation from 1996 to 2016. The major axis of the ellipse maintains the same trend as the eastern coastal developed economic belt, and the standard deviation ellipse spatial distribution is generally presented to the south-north direction are the main trend direction, and the east-west direction is the auxiliary trend direction. It shows that the spatial pattern difference in east-west directions of China’s land urbanization is larger than that of south-north. Generally speaking, the spatial distribution of China’s population urbanization is driven more by population density, the spatial difference in population urbanization is mainly reflected on the northwest-southeast direction. The spatial distribution of land urbanization is driven more by the level of economic development, the spatial differences in land urbanization are mainly reflected on the east-west direction.
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3.2.3 Spatial Clustering Characteristics Population urbanization: The population urbanization standard deviation ellipse perimeter and area overall appearance reduces the trend; the perimeter reduces 244.87 km and the area reduces the 270206.96 km2 from1996 to 2016. It indicated that the China’s population urbanization development presents the spatial contraction agglomeration situation during this period. Land urbanization: The land urbanization standard deviation ellipse perimeter and the area overall showed the first decrease and then expand the trend from1996 to 2016. The perimeter reduced 301.36 km and the area reduced the 160210.15 km2 from 1996 to 2006. The perimeter increased the 134.75 km and the area increased the 92078.02 km2 from 2006 to 2016. It shows that the development of land urbanization in China from 1996 to 2006 presents the trend of spatial contraction and agglomeration, the development of land urbanization in China from 2006 to 2016 presents a spatial expansion and discretization. Generally speaking, the standard deviation ellipse of land urbanization in the perimeter and area is less than that of population urbanization, which indicates that the urbanization of Chinese land has more obvious spatial agglomeration characteristics than population urbanization. At the same time, the standard deviation ellipse between population urbanization and land urbanization in China’s central and eastern coastal areas of overlapping quadrants, indicating that the central and east China’s coastal population urbanization and land urbanization general development level is higher, and the two imbalances less than other regions. 3.2.4 Spatial Distribution Pattern Population urbanization: Both of the long axes and the short axis showed a decreasing trend from 1996 to 2006. The short axis decreased by 42.26 km and the long axis decreased by 25.82 km, indicating that the short axis decreased more than the long axis. The ratio of the short axis to the long axis decreases from 0.883 to 0.866 and the ellipse has the tendency of flattening, which indicates that the urbanization rate of population in China slows down, but the growth rate of the short axis (northwestsoutheast) is more than that of the long axis (northeast-southwest) during this period. The short axis grew 5.45 km, the long axis decreased by 15.26 km, the ratio of the short axis to the long axis increased from 0.866 to 0.882, and the ellipse had a circularity trend from 2006 to 2016, indicating that the short axis (northwest-southeast) of the population urbanization growth rate in the accelerated stage, the long axis (northeast- Southwest) of population urbanization growth rate continues to slow down. Land urbanization: From 1996 to 2006, the short axis decreased by 2.55 km, the long axis decreased by 85.37 km, the ratio of the short axis to the long axis increased from 0.614 to 0.673,the ellipse has the tendency of roundness, indicating that the short axis (east-west) direction and the long axis (south- North) in the direction of land urbanization growth rate is in the deceleration stage, but the south-north to land urbanization growth rate slowed to a greater extent than the east-west to land urbanization growth rate slowed down from 2006 to 2016. The short axis grew 16.99 km, the long axis grew 25.48 km, and the ratio of the short axis to the long axis decreased from 0.6735 to 0.6733, the ellipse with slight flattening trend, indicating that the growth rate of land urbanization in the directions of the short-axis (east-west) and the long-axis
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(south-north) are at an accelerating stage from 2006 to 2016. However, the growth rate of land urbanization in the south-north is higher than that of east-west. In general, the ratio of short-axis to long-axis of China’s population urbanization was greater than 0.8, and the ratio of short-axis to long-axis of land urbanization was greater than 0.6 from 1996 to 2016. The spatial distribution pattern of population urbanization is more rounded than that of land urbanization. In additional, the standard deviation ellipse of population urbanization is larger than land urbanization in terms of perimeter and area. It shows that the spatial difference of China’s population urbanization is less than that of land urbanization, and the spatial heterogeneity of land urbanization is more prominent.
4 Conclusions and Discussion In this paper, the kernel density estimation and the standard deviation ellipse method are used to analyze the temporal evolution characteristics and spatial distribution pattern of China’s population urbanization and land urbanization from 1996 to 2016 from the timespace two-dimensional perspective. Finally, the following main conclusions are drawn: (1) The general development of population urbanization and land urbanization in China shows a trend of increasing. The urbanization of land is increasing faster than the urbanization of population, population urbanization and land urbanization have polarized phenomenon, but the degree of polarization of land urbanization is greater than that of population urbanization. At the same time, the provincial differences of land urbanization are greater than that of population urbanization. (2) China’s population urbanization center of gravity is located in Henan province, the general movement in the direction of the first to the south (slightly westward) and then to the southwest migration trend. And the movement speed shows that the first is fast then is slow trend. The gravity center of land urbanization is located in the junction of northeastern Anhui Province and northwestern Jiangsu province, the direction of movement is generally moving eastward first and then moving westward, the movement speed shows the first is fast then is slow trend. The distance between urbanization of population and urbanization of land has been enlarged, the non-equilibrium of the spatial distribution of the two has further aggravated the trend. (3) The main trend of China’s population urbanization spatial distribution is roughly the same as that of “Hu Huanyong Line”, which is the dividing line of population density in China; The main trend direction of the land urbanization spatial distribution is the south-north trend, which is roughly the same trend as the developed economic belt of China’s eastern coastal areas. The spatial pattern of China’s population urbanization exists in northwest-southeast direction, which is different from the northeast-southwest direction. The spatial pattern of land urbanization is different from that in the east-west to the south-north. The spatial-temporal difference of population urbanization is driven by the population distribution, and the spatial-temporal difference of land urbanization is more obvious than the driving effect of economic development level.
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(4) China’s urbanization of land has more obvious spatial agglomeration characteristics than population urbanization, and the development space of population urbanization in China is shrinking and agglomeration, and the development space of Chinese land urbanization presents the discretization trend of first contraction and then agglomeration. The general development level of population urbanization and land urbanization in the central and eastern coastal areas of China is higher than that in other regions. The spatial difference of Chinese population urbanization is less than that of land urbanization, and the spatial heterogeneity of land urbanization is more prominent. The core of urbanization is the urbanization of people, the carrier of urbanization is the urbanization of land, which is the two wheels of promoting the development of urbanization, only the double wheel drive together, urbanization can be coordinated development, in the past 20 years, China’s urbanization has made great achievements, but at the same time because there are some problems, in the process of urbanization in China, there are not enough contradictions between the urbanization of population and land urbanization, and the imbalance between the urbanization of population and the development of land urbanization areas. Therefore, the development of China’s new-type urbanization should not only resolve the contradiction of imbalance between the population urbanization and land urbanization, but also resolve the contradiction of between regional development differences, achieving the intrinsic coupling and spatial equilibrium between population urbanization and land urbanization.
References 1. Wang, X.F., Yang, H.P.: Review on the coordinated development of land urbanization and population urbanization in China. Enterp. Econ. 36(01), 166–173 (2017) 2. Sun, H.M., Wang, L.: Research on the coordination of population urbanization and land urbanization—based on the perspective of industrial support. Res. Financ. Econ. Issues 12, 31–36 (2017) 3. Chen, F.G., Zhang, H.O., Wu, Q.T., et al.: A study on coordinate development between population urbanization and land urbanization in china. Hum. Geogr. 25(05), 53–58 (2010) 4. Yang, S.Q., Wu, Q.: Incoordination between urban expansion and urban population growth and their interaction. China Popul. Resour. Environ. 26(11), 28–36 (2016) 5. Cui, X.F.: Population urbanization and land urbanization in ethnic minority areas: Disequilibrium and spatial heterogeneity. China Popul. Resour. Environ. 24(08), 63–72 (2014) 6. Yang, L.X., Yuan, S.F., Wang, X.C.: Spatial pattern disparity of coordinating the population urbanization and land urbanization in 69 counties of Zhejiang province. China Land Sci. 27 (11), 18–22+30 (2013) 7. Li, X.M., Chen, D.C.: An analysis on the reason of China’s population urbanization and land urbanization disorders. Reform. Strategy 30(12), 105–110 (2014) 8. Cao, J.M., Chen, S.Y.: Urbanization in China: from space to population. Contemp. Financ. Econ. 02, 78–83 (2016)
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9. Yuan, F.C., Kang, H.J.: The “Man-Land” imbalance and its breakthrough in the process of new urbanization. J. Chin. Acad. Governance 04, 47–52 (2016) 10. Chen, L., Zhu, X.G.: Regional disequilibrium and dynamic evolution of China’s urbanization: evidence from the Gini coefficient and kernel density estimation. Stat. Inf. Forum 32(05), 76–84 (2017) 11. Yin, H.L., Xu, T.: The mismatch between population urbanization and land urbanization in China. Urban Plann. Forum 02, 10–15 (2013) 12. Jin, H., Li, R.J., Li, Y.Y.: The Coordination of triple urbanization’s spatial differentiation and driving forces based on ESDA-GWR. Stat. Res. 35(01), 75–81 (2018) 13. Pan, J.H., Hu, Y.X., Liu, X., et al.: Spatial-temporal Pattern of the Coordinated development efficiency of the ‘four modernizations’ of prefecture level cities or above in China. Sci. Geogr. Sinica 36(04), 512–520 (2016) 14. Han, Z.L, Wen, X.L, Liu, T.B.: Analysis on spatial-temporal differentiation characteristics and influence factors of China’s population semi-urbanization rate. Econ. Geogr. 37(11), 52– 58+108 (2017) 15. Yang, Y., Ma, X.G., Wang, C.: The spatial-temporal dynamics of the land urbanization level in China base on nighttime light data. Hum. Geogr. 30(05), 91–98 (2017) 16. Sun, L.P, Yang, J.: Spatial and temporal analysis of the coordination between population urbanization and land urbanization in western China. Areal Res. Dev. 36(03), 55–58+65 (2017) 17. Guo, F.Y., Li, C.G., Chen, C., et al.: Spatial-temporal coupling characteristics of population urbanization and land urbanization in northeast China. Econ. Geogr. 35(09), 49–56 (2015) 18. Zhang, L.X., Zhu, D.L., Du, T., et al.: Spatial-temporal pattern evolvement and driving factors of land urbanization in Yangtze river economic belt. Resour. Environ. Yangtze Basin 26(09), 1295–1303 (2017) 19. Deng, Y.J., Pan, H.Y., Jiang, G., et al.: Research on the spatial and temporal evolution of coordinated development between population urbanization and land urbanization in Sichuan province. J. Sichuan Normal Univ. (Nat. Sci.) 40(03), 375–384 (2017) 20. Yu, Z.L., Wu, C.F.: Analysis on spatial characteristics and influence factors of land urbanization from the perspective of ESDA-GWR in Zhejiang province. China Land Sci. 30 (03), 29–36 (2016) 21. Guo, Y.Z., Sun, P.J., Liu, X.L., et al.: Analysis based on entropy weight method in Lanzhou city land urbanization space-time development. J. Gansu Agric. Univ. 51(01), 126–131 (2016) 22. Liu, H.J., Du, G.: Spatial-temporal pattern of China’s economic development and its dynamic evolution: Based on city level DMSP/OLS night-time lights data, Chinese J. Popul. Sci. 37(03), 17–29+126 (2017) 23. Lefever, D.W.: Measuring geographic concentration by means of the standard deviational ellipse. Am. J. Sociol. 32(1), 88–94 (1926) 24. Liu, Q., Du, X.H., Sheng, Y.X.: Study on the coordination relationship between population urbanization and land urbanization in China based on stage comparison. China Popul. Resour. Environ. 28(01), 26–34 (2018) 25. Tang, S.K., Song, H.P.: The matching of land urbanization and population urbanization in China. Urban Probl. 11, 2–6 (2013)
Dynamic Causal Linkages Among Urbanization, Energy Consumption, Pollutant Emissions and Economic Growth in China Munir Ahmad, Zhen-Yu Zhao(&), Marie Claire Mukeshimana, and Muhammad Irfan School of Economics and Management, North China Electric Power University, Beijing, China [email protected], [email protected], [email protected], [email protected]
Abstract. This study is an empirical attempt to explore the dynamic causal linkages among urbanization, energy consumption, pollutant emissions and economic growth, making use of simultaneous structural equations. A country panel of 30 Chinese provinces and cities, and three regional panels, for time span 2005 to 2014, have been estimated employing one-step System generalized method of moments (GMM) as well as one-step Difference GMM estimator. A unified model of economic growth, incorporating urbanization, energy consumption and pollutant emissions, has been developed. The empirics reveal that (1) urbanization positively drives energy consumption and pollutant emissions but is not driven by the same, (2) energy consumption positively drives pollutant emissions but is not driven by the same, (3) pollutant emissions negatively drives and is driven by economic growth, (4) economic growth positively drives and is driven by urbanization and energy consumption. These results are highly robust across all the panels. Based on these results, the policies proposed include (i) developing incentive/subsidy based urbanization mechanism supportive to induce more migration to western zone of China, (ii) developing rationing instrument concerning energy prices, setting the differentiated price structure based on urbanization level and type of fossil-fuels used, and (iii) directing further urbanization targeting less urbanized regions, like western zone, focusing low-emissions infrastructure and transport system to sustain high prospective growth rates. Keywords: Urbanization Energy consumption Pollutant emissions Economic growth Extended growth model China
1 Introduction Over the last few decades, global society has been transformed in terms of industrial development, urbanization, and environmental degradation. These transformations have close mutual linkages. The industrialization process is the core source of economic growth, which gives drift to accelerated urbanization in developed as well as rapidly developing nations. This phenomenon, in principal, works through the © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 90–105, 2021. https://doi.org/10.1007/978-981-15-3977-0_7
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development of non-agrarian sectors of these nations [15]. In this regard, the policies pursuing accelerated urbanization are popular in developing world, with aim of fostering economic growth [24]. Since, last four decades, China has undergone substantial urbanization from 19.4% in 1980 to 56.8% in 2016, along with enjoying incredibly high economic growth of approximately 10% on average [55]. This rapid urbanization rate and high economic growth rate were fueled with massive energy use, resulting in pronounced level of pollutant emissions and hence challenging the environmental sustainability. According to China Statistical Yearbook [43], the energy consumption met rapid increase from 146964 Mtce1 in 2000 to 436000 Mtce in 2016 out of which all sources of renewable energy consumption contributed merely minor portion (7.3% in 2000 to 13.3% in 2016). Consequently, the concentration of pollutant emissions reached a level 43% higher than the set national standards of China [16]. This issue has gained great attention and hence has become vital policy concern among economies around the world. In spirit of this scenario, there is a vast body of existing literature exploring the potential links among urbanization, energy consumption and economic growth. In this domain first strand of research emerged and composed energy-environment-economic growth nexus [4, 6, 14, 45, 48, 49] consisting of linkages among energy consumption, pollutant emissions and economic growth, finding mixed results on existence and direction of causality among these variables. Whereas, second research strand was based on urbanization-energy-economic growth nexus [1, 7, 25, 27, 28, 30, 33, 38, 56]. Based on empirical analysis, the research in this domain is further divided into two groups. The first group includes researches focusing on correlation analyses [21, 32, 45, 57, 58], while the focus of second one remained causal connections between energy use, urbanization and economic growth [19, 23, 34, 36, 39, 41, 49]. Among first group of researches, some of the studies found positive correlations between urbanization and energy consumption [32, 46] and some ended up with finding negative correlations between these variables [21, 45, 56]. The studies employing causality found existence of causal relationship between urbanization and energy consumption, but direction of causality and nature of relationship are still ambiguous. The third strand of research focused cointegrating analysis in energy-urbanization-economic growth domain [5, 9, 13, 29, 31, 51]. The results of these studies vary from no cointegrating relationship to long-run and short-run cointegration. The brief visit of existing literature it is concluded that the perplexity remains there about the nature of relationship among urbanization, energy consumption, and economic growth. Despite plethora of studies in this arena, the unanimous consensus about the nature of relationship among urbanization, energy consumption, pollutant emissions and economic growth is still lacking. Besides, no single study has been found simultaneously considering the dynamic relationship among variables of urbanization, energy consumption, pollutant emissions and economic growth. In view of the foretold scenario, the current study attempts to contribute to the existing literature in six ways through (1) developing a unified economic growth model augmenting for urbanization, energy consumption and pollutant emissions, (2) building theoretical connections
1
Mtce denotes million tons of coal equivalent.
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among urbanization, energy consumption, pollutant emissions and economic growth, (3) utilizing four structural equations allowing to simultaneously analyze the influence of mutual causal linkages among study variables, (4) extending the analysis at disaggregated levels of Chinese regions classified into three zones i.e., eastern zone, intermediate zone, and western zone (5) employing GMM estimator incorporating two types of details i.e., one-step System GMM and one-step Difference GMM, and finally (6) estimating and finding the magnitudes and identifying the directions of causal connections among these variables.
2 Theoretical Model and Econometric Method 2.1
Extended Growth Model
The neoclassical models of economic growth are well recognised among the energy literature. We develop a unified model of economic growth by starting with constant returns to scale Cobb-Douglas production function: Y ¼ AK d E q L1dq
ð1Þ
Where Y is the aggregate output,, K is the physical capital, L is the labour input, E is the energy consumption, and A is total factor productivity. Normalizing Eq. (1) by labour force yields the following form: d q yi;t ¼ Ai;t ki;t ei;t
ð2Þ
Where i is the index of provinces and cities; t is the time index. The variables of output, physical capital and energy consumption are in per-worker form. Next, the conventional total factor productivity (A) is determined by lagged level of per-worker output and existing stock of human capital [10, 17]: Ai;t ¼ hui;t ðyi;t1 Þh
ð3Þ
Moreover, the empirical literature confirms that, the pollutant emissions significantly contribute to total factor productivity [47]. Hence, we augment Eq. (3) for pollutant emissions: Ai;t ¼ hui;t ðyi;t1 Þh Px i;t
ð4Þ
Where P is pollutant emissions. Equation (4) is emissions-augmented total factor productivity. Substituting Eq. (4) into Eq. (2) yields: h i d q yi;t ¼ hui;t ðyi;t1 Þh Px i;t ki;t ei;t
ð5Þ
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Next, we add urbanization as a shift factor of output: h i s d q yi;t ¼ hui;t ðyi;t1 Þh Px i;t ki;t ei;t Ui;t
ð6Þ
Where U is the population living in urban areas. After log transformation and taking difference, the Eq. (6) takes the following form: Dlnyi;t ¼ ulnhi;t þ hDlnyi;t1 þ xDlnPi;t þ dDlnki;t þ qDlnei;t þ sDlnUi;t
ð7Þ
The Eq. (7) can be rewritten in the following form: gyit ¼ ughi;t þ hgyi;t1 þ xgPi;t þ dgki;t þ qgei;t þ sgUi;t
ð8Þ
Where the Eq. (8) is in growth rate form. Rearranging variables, Eq. (8) can be rewritten in following econometric form: gyi;t ¼ a0 þ a1 gyi;t1 þ a2 gUi;t þ a3 gei;t þ a4 gPi;t þ a5 gki;t þ a6 ghi;t þ ei;t
ð9Þ
From Eq. (9), we formulate the system of simultaneous equation to treat urbanization, energy consumption, pollutant emissions and economic growth at the same time. The four-ways linkage among the study variables is empirically examined through following econometric models: gyi;t ¼ a0 þ a1 gyi;t1 þ a2 gUi;t þ a3 gei;t þ a4 gPi;t þ a5 gki;t þ a6 ghi;t þ ei;t;1
ð10Þ
gUi;t ¼ b0 þ b1 gyi;t þ b2 gei;t þ b3 gPi;t þ ei;t;2
ð11Þ
gei;t ¼ c0 þ c1 gUi;t þ c2 gyi;t þ c3 gPi;t þ ei;t;3
ð12Þ
gPi;t ¼ l0 þ l1 gUi;t þ l2 gei;t þ l3 gyi;t þ ei;t;4
ð13Þ
Equation (10) states that economic growth is potentially determined by urbanization growth, energy consumption growth, pollutant emissions growth, physical capital growth and human capital growth [8, 19, 37]. Next, Eq. (11) shows that urbanization growth is potentially determined by economic growth, energy consumption growth and pollutant emissions growth [7, 37, 38]. Then, Eq. (12) illustrates that energy consumption growth is potentially determined by economic growth, urbanization growth and pollutant emissions growth [14, 22, 53]. Finally, Eq. (13) illustrates that pollutant emissions growth is potentially determined by economic growth, urbanization growth and energy consumption growth [20, 48]. 2.2
Theoretical Underpinnings and Hypotheses Formulation
Substantial urbanization process creates huge energy demand [52] which boosts the energy consumption [40]. This rise in energy consumption pushes the industrial output upward which directly spurs economic growth. The rise in economic growth generates further energy demand at household and industrial levels and thus increasing the
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energy consumption [27]. At the same time, the negative externality in terms of pollutant emissions is the aftermath of rise in energy consumption [30]. The high levels of pollutant emissions may lead to negative health impacts on human capital and hence decelerating the economic growth [18, 50]. The famous Environmental Kuznets Curve states that countries at high level of economic development attach more vigorous importance to social cost therefore invest to reduce the level of pollutant emissions [18, 49]. Moreover, urbanization leads to higher economic growth in presence of favourable institutions and infrastructure settings [3, 12, 56]. The enhancement in economic growth attributed to urbanization may significantly contribute to boost in energy use by industry and marginally contributes to rise in energy use by households [53]. In addition, high economic growth implies high level of employment leading to urban concentration. However, urbanization results in pollutant emissions due to massive industrialization and transportation [31]. These theoretical channels are drawn in Fig. 1. Based on these theoretical foundations, the hypotheses tested in the current study are: (1) urbanization is in positive relation to energy consumption, (2) energy consumption is in positive relation to pollutant emissions, (3) pollutant emissions is in negative relation to economic growth, (4) economic growth is in positive relation to urbanization, (5) urbanization is in positive relation to pollutant emissions, and (6) energy consumption is in positive relation to economic growth. 2.3
Estimation Methodology
The dynamic panel data models in the form of four simultaneous equations have been utilized for economic growth, urbanization, energy consumption and pollutant emissions. This study employs System GMM estimator by Blundell and Bond [11], estimating each model including the lagged level of outcome variable as regressor, hence ensuring the dynamic nature of the models. Further, to treat different panels, the study makes use of two types of details concerning GMM estimator. In this regard, one-step System GMM estimator has been employed for country panel, tackling the problems of panel specific autocorrelation and endogeneity. Whereas, one-step Difference GMM estimator has been employed for disaggregated analyses of regional panels to overcome small sample bias issue. Another advantage of using System GMM estimator is that it can rule out the problem of correlation between lagged outcome variable and errors which other approaches like random and fixed effects could suffer from. Finally, the models to be estimated are as follows: gyi;t ¼ a0 þ a1 gyi;t1 þ a2 gUi;t þ a3 gei;t þ a4 gPi;t þ a5 gki;t þ a6 ghi;t þ ei;t;1
ð14Þ
gUi;t ¼ b0 þ b1 gUi;t1 þ b2 gyi;t þ b3 gei;t þ b4 gPi;t þ ei;t;2
ð15Þ
gei;t ¼ c0 þ c1 gei;t1 þ c2 gUi;t þ c3 gyi;t þ c4 gPi;t þ ei;t;3
ð16Þ
gPi;t ¼ l0 þ l1 gPi;t1 þ l2 gUi;t þ l3 gei;t þ l4 gyi;t þ ei;t;4
ð17Þ
Where gyi;t , gUi;t , gei;t and gPit are economic growth, urbanization growth, energy consumption growth, and pollutant emissions growth, respectively; a0 , b0 , c0 and l0
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Fig. 1. Theoretical channels of relationships among urbanization, energy consumption, pollutant emissions and economic growth
are the intercept coefficients; ei;t;1 , ei;t;2 , ei;t;3 and ei;t;4 are the stochastic terms, respectively; and, a1 , b1 , c1 and l1 are the convergence coefficients of the models, respectively. The expected signs of convergence coefficients are negative to validate models’ convergence. The a2 , a3 and a4 capture the effect of urbanization growth, energy consumption growth and pollutant emissions growth on economic growth, respectively; b2 , b3 and b4 capture the effect of economic growth, energy consumption growth and pollutant emissions growth on urbanization growth, respectively; c2 , c3 and c4 capture the impact of urbanization growth, economic growth and pollutant emissions growth on energy consumption growth, respectively; and, l2 , l3 and l4 capture the effect of urbanization growth, energy consumption growth and economic growth on pollutant emissions growth, respectively.
3 Data and Analysis 3.1
Data
The study data come from China Statistics Yearbook [43, 44] comprising 30 Chinese provinces and cities, covering time period of 2000 to 2016. These data include gross regional product i.e., gross domestic product measured at provincial and city level (100 million Yuan) adjusted for CPI inflation and utilized as proxy for economic growth; urban population (percent of total population) taken as urbanization; total energy consumption (10000 tons of standard coal equivalent) used to measure energy consumption; sulphur dioxide emissions (10000 tons) used to measure pollutant emissions;
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gross fixed capital formation (100 million Yuan) used as proxy for physical capital; and educational funds (10000 Yuan) to quantify the human capital. Further, all the study variables are transformed into growth rate form except urbanization, as it already comes in percentage form. 3.2
Empirical Analysis
In this section, four simultaneous-equation models (models 1–4) of dynamic panel data are estimated for country panel including 30 Chinese provinces and cities, and three regional panels classified into three zones. The country panel is estimated by employing one-step System GMM estimator, whereas, regional panels are estimated by using one-step Difference GMM estimator. The Eqs. (14)–(17) are estimated and findings are reported in Tables 1, 2, 3 and 4. The coefficients of convergence variables in case of all the four models are negative and statistically significant, confirming that all the models preserve the property of dynamicity. It indicates that after any deviation, the variables of economic growth, urbanization, energy consumption growth and pollutant emissions growth are likely to converge to their mean path. The coefficient values of convergence variables exhibit the speed of adjustment (Tables 1, 2, 3 and 4). 3.2.1 Model 1 In case of model 1, urbanization has positive and statistically significant impact (at 10, 5, 10, and 10% level for country panel, eastern zone, intermediate zone and western zone, respectively) on economic growth. The elasticity magnitudes are 0.018, 0.029, 0.021, and 0.008 for country panel, eastern zone, intermediate zone, and western zone respectively, with highest elasticity magnitude for eastern zone (i.e., Beijing, Shanghai, Tianjin, Hebei, Zhejiang etc.). The energy consumption growth has positive and statistically significant impact (at 1, 10, 10, and 5% level for country panel, eastern zone, intermediate zone and western zone, respectively) on economic growth. The elasticity magnitudes are 0.069, 0.093, 0.078, and 0.042 for country panel, eastern zone, intermediate zone, and western zone respectively, with highest contribution in case of eastern zone. However, the pollutant emissions growth, having elasticity negative and statistically significant (at 5, 5, 10, and 5% level for country panel, eastern zone, intermediate zone and western zone, respectively), hampers economic growth. Its elasticity magnitudes are −0.039, −0.101, −0.051, and −0.031 for country panel, eastern zone, intermediate zone, and western zone respectively, thus indicating strongest impact in case of eastern zone. In addition, physical capital growth and human capital growth show positive and statistically significant influence on economic growth. These results are reported in Table 1. 3.2.2 Model 2 In case of model 2, economic growth has positive and statistically significant contribution (at 5, 5, 10, and 5% level for country panel, eastern zone, intermediate zone and western zone, respectively) to urbanization. Its elasticity magnitudes are 2.687, 2.791, 2.572, and 2.198 for country panel, eastern zone, intermediate zone, and western zone respectively, demonstrating strongest influence in case of eastern zone. However, the variables of
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Table 1. Model 1: dynamic causality model of economic growth Outcome variable: economic growth Items Country panel Eastern zone Intermediate zone Western zone Convergence variable Lagged level of EG −0.723** −0.654* −0.879* −0.738* (0.311) (0.295) (0.363) (0.327) Causality variables Urbanization 0.018* 0.029** 0.021* 0.008* (0.009) (0.020) (0.011) (0.004) EC growth 0.069*** 0.093* 0.078* 0.042** (0.034) (0.047) (0.036) (0.021) PE growth −0.039** −0.101** −0.051* −0.031** (0.020) (0.058) (0.032) (0.018) Other regressors PC growth 0.102*** 0.134* 0.155** 0.073* (0.086) (0.097) (0.099) (0.053) HC growth 0.158*** 0.106* 0.201** 0.251** (0.075) (0.063) (0.098) (0.164) 0.313* 0.085* 0.092* Constant 0.105** (0.062) (0.128) (0.047) (0.059) Post estimation Hansena (p-value) 1.000 0.993 0.760 0.828 AR (2)b (p-value) 0.539 0.247 0.518 0.421 Observations 420 154 112 140 Cross-sections 30 11 8 11 Notes: The coefficients and elasticities carrying signs of *, **, and *** exhibit significance level at 10%, 5% and 1% respectively. The robust standard errors are recorded in parentheses (). Where, EG denotes economic growth, EC denotes energy consumption, PE denotes pollutant emissions, PC is physical capital, and HC is human capital. a Hansen test verifies the validity of the instruments. b AR(2) test detects the autocorrelation of stochastic terms.
energy consumption growth and pollutant emissions growth have positive but statistically insignificant impact on urbanization. These findings are recorded in Table 2. 3.2.3 Model 3 In case of model 3, urbanization has positive and statistically significant impact (at 5, 10, 10, and 10% level for country panel, eastern zone, intermediate zone and western zone, respectively) on energy consumption growth. The magnitudes of its elasticity are 0.017, 0.022, 0.015, and 0.012 for country panel, eastern zone, intermediate zone, and western zone, respectively. The magnitude is highest in case of eastern zone which subsequently declines for intermediate and western zone. In the like manner, economic growth exhibit positive contribution to energy consumption growth with highest magnitude for country panel (0.790) and second highest for eastern zone (0.753) in
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Outcome variable: urbanization Items Country Eastern Intermediate Western panel zone zone zone Convergence variable Lagged level of −0.824* −0.891* −0.773** −0.851* urbanization (0.410) (0.485) (0.381) (0.416) Causality variables EG 2.687** 2.791** 2.572* 2.198** (0.983) (1.324) (0.901) (0.840) EC growth 0.230 0.218 0.239 0.211 (0.096) (0.083) (0.099) (0.078) PE growth 0.355 0.324 0.332 0.365 (0.182) (0.169) (0.173) (0.192) Constant 0.206* 0.185** 0.212** 0.225* (0.081) (0.101) (0.168) (0.272) Post estimation Hansen (p-value) 0.777 0.623 0.900 0.826 AR (2) (p-value) 0.609 0.251 0.738 0.119 Observations 420 140 112 140 Cross-sections 30 11 8 11 Notes: The coefficients and elasticities carrying signs of *, **, and *** exhibit significance level at 10%, 5% and 1% respectively. The robust standard errors are recorded in parentheses (). Where, EG denotes economic growth, EC denotes energy consumption, and PE denotes pollutant emissions.
comparison to both intermediate and western zones (0.732 and 0.713 respectively). However, the pollutant emissions growth has positive but statistically insignificant impact on energy consumption growth. These findings are presented in Table 3. 3.2.4 Model 4 In model 4, urbanization have positive and statistically significant effect (at 10, 10, 10, and 5% level for country panel, eastern zone, intermediate zone and western zone, respectively) on pollutant emissions growth. The magnitudes of its elasticity are 0.013, 0.030, 0.027, and 0.018 for country panel, eastern zone, intermediate zone, and western zone, respectively. It shows that the effect is relatively more obvious in eastern and intermediate zones. Same is the case of energy consumption growth which shows strongest positive impact on pollutant emissions growth for eastern zone (0.028). On the contrary, economic growth contributes negatively to pollutant emissions growth with particularly stronger effect in case of eastern zone. Its elasticity values are −1.025, −1.301, −1.199, and −0.998 for country panel, eastern zone, intermediate zone, and western zone, respectively. These results are displayed in Table 4. In addition, in case of all four models, the probability values of Hansen test confirm the validity of instruments used. Similarly, the probability values of AR (2) test demonstrate errors are serially uncorrelated, declaring the results reliable. All the findings reported are
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Table 3. Model 3: dynamic causality model of energy consumption growth Outcome variable: energy consumption growth Items Country panel Eastern zone Intermediate zone Western zone Convergence variable Lagged level of EC −0.787*** −0.834* −0.626** −0.806* (0.365) (0.424) (0.323) (0.418) Causality variables Urbanization 0.017** 0.022* 0.015* 0.012* (0.008) (0.010) (0.009) (0.006) EG 0.790* 0.753* 0.732** 0.713* (0.368) (0.334) (0.391) (0.330) PE growth 0.020 0.012 0.016 0.025 (0.141) (0.006) (0.009) (0.019) Constant 0.236** 0.213* 0.198* 0.248** (0.071) (0.119) (0.156) (0.301) Post estimation Hansen (p-value) 0.918 0.910 0.656 0.744 AR (2) (p-value) 0.557 0.693 0.281 0.528 Observations 420 140 112 154 Cross-sections 30 11 8 11 Notes: The coefficients and elasticities carrying signs of *, **, and *** exhibit significance level at 10%, 5% and 1% respectively. The robust standard errors are recorded in parentheses (). Where, EG denotes economic growth, EC denotes energy consumption, and PE denotes pollutant emissions.
consistent across all the panels, enhancing the reliability of analysis and thus confirming the authenticity of nature of relationships identified. 3.2.5 Empirical Summary and Discussion In order to shed more light on the findings and make the comparison of results easier, we summarize the empirics concerning four-ways causal linkages among urbanization, energy consumption growth, pollutant emissions growth and economic growth for the four panels (Fig. 2) as follows: First, there is unilateral positive causality running from urbanization to energy consumption growth. It implies that more people in the urban regions demand for more energy-based facilities hence boosting household energy demand. Similarly, more people in urban regions imply availability of more labor force available to work, reducing the wage rate and inducing the growth of industrial sector, and as a result enhancing energy consumption. Second, there exists bilateral positive causal linkage between energy consumption growth and economic growth. As aforementioned, China is fuel-based energy industry-driven economy and its growth is dependent on industrial output therefore more energy consumption implies fast pace of economic growth. On the other way around, higher economic growth leads to developing and expanding the industries and hence stepping-up the level of energy consumption. Third, there is unilateral positive causality running from energy consumption
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growth to pollutant emissions growth. The implication is noticeable that as the use of energy increases, then the emissions are increased. It confirms the situation that today China is the largest energy consumer and pollutants emitter. Fourth, bilateral negative causal connection is found between pollutant emissions and economic growth. It reveals that pollutant emissions lead to health issues negatively affecting the performance of human capital and thus economic growth. On the other hand, countries having long-term high economic growth rates invest to reduce pollutant emissions. Concerning this, China is rapidly switching to green energy sector to mitigate pollutant emissions. According to current statistics [43, 44], the energy consumption from green sources in 2016 constituted 13.3% of total energy consumption in China. Fifth, there exists positive bilateral causal linkage between urbanization and economic growth. It implies that urbanization in China, through conducive and favorable institutions and infrastructural settings, promotes economic growth. Besides this, high economic growth implies high employment rate which induces urbanization. Base on empirics, it is implied that the western zone of China is less urbanized and hence makes relatively weak contribution to economic growth than eastern and intermediate zones. Sixth, the study found unilateral positive causal link from urbanization to pollutant emissions. It reveals the scenario that more urbanization
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Fig. 2. Empirical summary of four-ways causal linkages among urbanization, energy consumption growth, pollutant emissions growth and economic growth
may lead to congestion of vehicles and massive industrialization, and hence, increasing transportation and industrial pollutants. Note: (a), (b), (c), and (d) refer to country panel, eastern zone, intermediate zone, and western zone, respectively. U, ECG, PEG, and EG denote urbanization, energy consumption growth, pollutant emissions growth, and economic growth, respectively. Single-headed and double-headed arrows indicate unilateral and bilateral causality, respectively. Magnitudes demonstrate strength of linkages.
4 Conclusions and Policy Recommendations 4.1
Major Conclusions
Based on empirics, this study unearths the following main conclusions: First, urbanization positively drives energy consumption but is not driven by the same. It implies China’s situation in recent decades, substantial urbanization is followed by massive energy consumption. Second, energy consumption positively drives pollutant emissions but is not driven by the same. It obviously narrates the present story of Chinese pronounced levels of pollutant emissions driven by huge energy consumption. According to China Statistical Yearbook [43, 44], 86.7% of the total energy consumption in the county is fuelled by fossil fuel-based energy which is direct source of heavy pollutant emissions. Third, pollutant emissions negatively drives and is driven
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by economic growth. The economic growth is more important to pollutant emissions as compared to the opposite side of the coin. Therefore, higher economic growth of China may lead to emissions reduction policies. Fourth, economic growth positively drives and is driven by urbanization. It indicates the fact that urbanization is more sensitive to changes in economic growth, therefore, high economic growth may lead to over-urbanization, hence leading to further environmental degradation. Fifth, urbanization positively drives pollutant emissions but is not driven by the same. It represents the recent situation in China, showing rapid urbanization process along with alarming levels of pollutant emissions. Sixth, energy consumption positively drives and is driven by economic growth. It tells the story of Chinese high economic growth and development of industry. China has been heavily dependent on fossil-fuel based energy industry and hence achieved very high economic growth in last few decades. These high growth rates further boosted the energy consumption in the industries and households. In this way, this two-ways driven mechanism is still working but at the huge environment related costs. And finally, eastern and intermediate zones are relatively more developed in terms of urbanization and economic growth while western zone of China is relatively less urbanized and poorly developed. Therefore, western zone is relatively less polluted because of being less dependent on industries and hence relatively less energy consumption. 4.2
Policy Recommendations
Based on empirical findings, following policy implications and suggestions are drawn: 1. First, the urbanization policies must develop urbanization mechanism supportive to induce more migration to western zone than eastern and intermediate zones. This mechanism can be based on some incentives and subsidies. Because of this policy implementation, the energy consumption and hence the resulting pressure on environment in terms of pollutant emissions can possibly be reduced. 2. Second, the provincial and city level governments of China may collaborate to devise rationing instrument concerning energy prices by setting differentiated prices of fuel-based energy to reduce energy consumption, hence may lead to less emissions. This tool may consider two aspects: Firstly, the more urbanized provinces and cities, opposed to less urbanized ones, should be charged relatively higher energy prices. Secondly, by setting relatively higher prices for type of fuels excessively consumed in contrast to less intensively consumed one. 3. Though having marginal contribution, pollutant emissions are important to economic growth. Therefore, further urbanization is suggestable for China in less urbanized regions, like western zone, focusing on low-emissions based infrastructure and transport-system to sustain prospective high economic growth. China being the largest economy worldwide, may be considered as the leading example by other countries of the world in terms of energy, urbanization, and growth. Hence, the above stated policy suggestions may also have valuable implications towards rest of the world.
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Study on Competitiveness Evaluation of the Intangible Cultural Heritage Town Based on Porter Diamond Model Mei Lu(&), Xingdi Tong, and Qi Li School of Management, Xi’an University of Architecture and Technology, Xi’an, China [email protected]
Abstract. The characteristic town is a major innovation initiative under the new urbanization of China, and the intangible cultural heritage town has built its own urbanization construction and development with intangible cultural heritage resources as an important part of the featured town. Based on the theory of Porter diamond model and analytic hierarchy process, this paper constructs an evaluation index system for the competitiveness of the intangible cultural heritage town. The competitiveness of intangible cultural heritage towns is measured in terms of production factors, demand conditions, related and supporting industries, corporate competition, and government behavior. It provides some reference for the government’s evaluation and selection of intangible cultural heritage towns. Keywords: The intangible cultural heritage town diamond model Competitiveness
The theory of portor
1 Introduction China is currently undergoing a major transformation period of urbanization. The effective promotion of new urbanization has become the key to economic and social development. The characteristic town is one of the new urbanization construction models. It gathers high-end elements, builds characteristic industries, optimizes regional industrial systems, diverts personnel, and shares functions, which promotes the coordinated development of urban and rural areas and the development of new urbanization. Characteristic town is a development platform with clear industry orientation, cultural connotation, tourism and certain community functions. The intangible cultural heritage town is based on one or more characteristic intangible cultural heritage resources and forms a new type of town with features of production, urban, human, and literary functions within a specific spatial environment [1]. The towns can help to improve the original appearance of traditional villages, while also making full use of and promoting traditional Chinese culture. Therefore, it is an important part of the construction of characteristic towns.
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 106–121, 2021. https://doi.org/10.1007/978-981-15-3977-0_8
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During the “13th Five-Year Plan” period, the Chinese economy has entered a new normal phase. Economic restructuring needs to speed up the development of the service industry, and power conversion needs to increase the driving force for domestic consumption, and improvement of people’s livelihood requires the further release of national leisure needs, which all provide important opportunities for the development of cultural tourism. In 2016, the Ministry of Housing and Urban-Rural Development of the People’s Republic of China, the National Development and Reform Commission, and the Ministry of Finance of the People’s Republic of China jointly issued the “Notice on Developing Characteristic Town Cultivation Work”, which said that the cultivation of characteristic towns is required to demonstrate distinctive traditional culture, and traditional culture should be fully excavated, organized and recorded. Historical and cultural remains should be well protected and utilized, and intangible cultural heritage should be inherited in a live form, forming a unique cultural identity and integrating with industry. In 2017, the “Suggestions on Implementing the Inheritance and Development Project of the Chinese Excellent Traditional Culture” by the General Office of the Communist Party of China and the General Office of the State Council of the People’s Republic of China also mentioned the need to protect inherited cultural heritage, implement the inheritance and development project of intangible cultural heritage, and integrate the iconic elements of traditional culture into urbanization. In the context of this policy, local governments actively responded to the call. In September 2017, Jiangxi Province made clear its plan to cultivate 20 provincial intangible cultural heritage towns in the “Work Plan for the Protection and Development of Intangible Cultural Heritage during the 13th Five-Year Plan Period in Jiangxi Province”. In October 2017, Chengdu, Sichuan province also officially announced the first list of 10 intangible cultural heritage towns. In January 2018, Zhejiang Province announced the fourth list of 32 intangible cultural heritage tourist attractions, of which 15 are intangible cultural heritage towns…From the lists of intangible cultural heritage townships or intangible cultural heritage towns that have been successively announced by various local governments, it can be known that the current number of intangible cultural heritage towns is not only rapid but also increases rapidly. However, at present, due to factors, such as inadequate supporting policies and ambiguous planning implementation, the construction of China’s intangible cultural heritage towns is still at the stage of exploration. In the construction process of the town, there have been blindly established projects, large government packages, and complete real estate. In order to ensure the sustainable and healthy development of intangible cultural heritage towns, it is necessary to correctly measure the core competitiveness of intangible cultural heritage towns and establish evaluation standards for the competitiveness of intangible cultural heritage towns, which can provide a reasonable basis for the planning and development path of the town. However, the current industry positioning of most of China’s intangible cultural heritage towns is not yet clear, and the relevant references and data are few, which makes it difficult to carry out complex competitive analysis. The theory of Potter’s Diamond model can use a macro perspective to analyze the internal composition of the observation object and the external environment. It can three-dimensionally and fully analyze the core competitiveness of intangible cultural heritage towns.
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2 The Connotation of Intangible Cultural Heritage Town The characteristic town is not a traditional town in an administrative sense, but a regional concept. According to this concept, the characteristic town can be either a part of the city or a region around the city. The core of its construction is the stable development of the economy driven by industry. Its basic characteristics are based on industry, reflecting its “characteristics” and giving it its connotation. The core of the construction of a featured town is the stable development of the economy driven by industry. Its basic characteristics are based on industry, embodying its “characteristics” and giving it its connotation. The core of the construction of the characteristic town is the stable development of the economy driven by the industry. Its basic characteristics are based on industry that can reflect “characteristics” and give the town its connotation. Therefore, the characteristic town includes four elements in the construction process: industry, towns, people, and culture. The industry is the driving force for the development of a distinctive town and the foundation for sustainable development. Characteristic industries are the core functions of small town development. Small towns without industrial support can only cause huge waste of land and other resources. Therefore, the industry can best reflect the “characteristics” of a characteristic town, and it is also a key factor in determining the development of a characteristic town. Characteristic industries can often concentrate their resources more efficiently. Through the establishment of characteristic industries niches, and the use of market mechanisms to eliminate old industries that have a disharmonious prospect of migration and development of small towns, characteristic industries enhance the endogenous power and effective supply capacity of small town development. The development of characteristic industries is conducive to the transformation of the growth dynamic structure of featured towns. Compared with the traditional industry’s agglomeration mode, featured towns pay more attention to the gathering of talents, science and technology, capital, and other high-end elements when planning and developing characteristic industries [2]. In addition, characteristic towns also have stricter requirements for innovation ability. Therefore, characteristic towns often contain the elements of institutional innovation and organizational innovation for nurturing and developing characteristic industries, so as to constantly optimize the input structure and input methods of the factors. Due to the high requirements of characteristic towns in terms of innovative capabilities, the development of specialty industries can often attract the latest industrial resources, industrial models, and technical talents to the towns where they are located, improve the integration of small towns’ innovative capabilities, and promote the optimization of industrial ecosystems in characteristic towns. Moreover, characteristic industries can absorb large amounts of surplus labor in the region and a part of the rural labor force, which to a certain extent ease the employment of personnel in the region [3]. Cities and towns are carriers, and the formation of characteristic towns needs certain conditions. The conditions referred to here include geographical location, natural conditions, historical culture, transportation, population, and economic conditions. Finding out the advantages and disadvantages of the town and exploring the
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characteristics of the town through a comprehensive analysis of the town’s own conditions clarifies the development direction of the characteristics of the town. The area is a whole, and the town and even the city is only one part of it, and it is closely related to other parts of the area and is closely related to it. Therefore, the development of the town will also be affected by other parts of the area. In the process of constructing the characteristic town, it also needs to take the value and function of the town into account from the perspective of the region and pay attention to the factors of functional complementarity and industrial complementarity, so as to clarify the division of functions of the town in the region, and to form differentiated and dislocated competition with the surrounding areas to avoid similar positioning. People are the construction center of the town and it is also a development guarantee. From the perspective of “man”, the planning concept of the town can be rationalized, and the mechanism design can be effective, and the supporting policies can be improved. Once it deviates from the “people-oriented” principle, it is easy to lose the development vitality of the characteristic town. Any kind of community needs the common spiritual ties to sustain, that is, the cultural cohesion that is the continuation of the spiritual basis for the development of the community. It can be seen that the cultural features are the soul of the town. A good cultural environment is a kind of soft power that promotes the development of characteristic towns. It is the core of the town’s spirit. The rich cultural heritage and spiritual connotation give the uniqueness and distinctiveness of the town’s characteristics, giving the town a powerful vitality. The characteristic culture is a good explanation of what constitutes an important principle for the construction of a characteristic town. The intangible cultural heritage town as a type of characteristic town should also include the above four elements. However, judging from the intangible cultural heritage towns that have emerged from the current survey, many intangible towns have an “empty city” phenomenon in the entire town after the tourists evacuated in the evening, even though they are active during the day, and there is no breath of life. Intangible cultural heritage towns are not only unique in intangible cultural heritage, but more need to combine intangible heritage with contemporary life. With the protection and instinct of intangible cultural heritage, the construction of small towns should also integrate into the real human life. Intangible cultural heritage resources have brought about the “characteristics” of characteristic towns, but to maintain and expand this “characteristic”, it must work hard on the content of “characteristics”. The key lies in promoting the integration of mainstay industry and cultural and creative industries and achieving co-creation and sharing in talents and technologies. It will promote the priority development of the cultural and creative industries at the core of intangible cultural heritage resources. In summary, the intangible towns should be based on cities and towns as the carrier and people-oriented, and form the core industry of the town by excavating their own advantages including history and natural resources. In the process of town construction, the core industry should be closely integrated with the traditional characteristics of the town. New forces, such as cultural creativity and modern culture and science and technology, should be applied to the construction of intangible cultural heritage towns
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to transform the industry and extend the industrial chain, so that the sustainable development of characteristic towns can be achieved.
3 Research on the Competitiveness of Intangible Cultural Heritage Town 3.1
The Theory of Porter Diamond Model
The diamond model is proposed by Michael Porter, a famous American strategic manager and is a rhombic diamond model theory system that uses a qualitative analysis model to interpret and analyze the national industry or enterprises to obtain competitive advantage, as shown in Fig. 1. The definition of “diamond” has been expanded in modern applications. In addition to industry, it can also be a factory or enterprise, an administrative entity, as small as a village, a township, an administrative district, and a country as a whole. The Porter Diamond System consists of six factors. The four basic elements of factors of production, demand conditions, related and supporting industries, and the company’s strategy, structure, and competitors create a basic environment for corporate competition, these four elements interact in both directions and form a system that resembles a diamond shape. In addition, there are two auxiliary factors, namely opportunity and government, in which the opportunities focus on internal factors such as invention and creation in the industry and changes in production costs, financial market turmoil and other external factors, which are not closely related to the research object of this paper [4]. Therefore, this article only analyzes the four essential elements of production factors, demand conditions, related and supporting industries, and the company’s strategy, structure, and competitor, and the government as an auxiliary factor. Opportunities are not included in the analysis.
Fig. 1. Porter diamond model
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Analysis on the Competitiveness of Intangible Cultural Heritage Towns and Its Index System Construction
On the whole, the characteristic towns of intangible cultural heritage share the common characteristics of ordinary featured towns, but also have their own particularities. From the perspective of the interior of the featured town, the intangible cultural heritage town has many common features, but it also has its own personality due to the differences in intangible cultural heritage resources, intangible cultural heritage projects, and planning and design. The competitiveness evaluation indicator system needs to consider two factors. On the one hand, index can examine the fundamentals of the development of intangible cultural heritage towns in order to make the assessment results comparable. On the other hand, index can also reflect the unique advantages of intangible cultural heritage towns. When selecting indicators, it must be able to meet the basic requirements for assessment and assessment, and it must also pay attention to the possibility of current statistics, that is, the indicators are easy to obtain, easy to measure, and easy to evaluate and check. For some of the indicators that are meaningful but difficult to collect statistics, discard them and select indicators that are clear and easy to collect. Therefore, based on the above research ideas and combined with expert surveys, the core competitiveness index system for building intangible cultural heritage towns is as follows. 3.2.1 Production Factors In the theory of Potter diamond model, the production factors are the resources used in the production and management of enterprises, and they are the basic factors that sustain the operation of the national economy and market players. Porter believes that production factors are divided into primary production factors and high-level production factors. Primary production factors refer to natural resources, funds, and facilities. Highlevel production factors refer to knowledge, information and technology. Intangible cultural heritage towns are comprehensive communities with clear industrial orientation, cultural connotations, and tourism characteristics that are built on intangible cultural heritage resources or industries. Therefore, the production factors are the essential foundation for all intangible cultural heritage towns to carry out all development activities, and it is also the key to improving the competitiveness of the characteristic towns. According to the connotation of the intangible cultural heritage town mentioned above, this article focuses on the cultural and human resources of intangible cultural heritage towns in the production factors. There are four secondary indicators of cultural resources, human resources, capital resources and infrastructure under this first-level indicator. (1) Culture resource. China has a long history with rich and diverse cultural resources. Intangible cultural heritage towns are formed by the intangible cultural heritages, such as historical and cultural resources and traditional folk crafts, etc. Cultural resources are the source and driving force for the development of intangible cultural heritage towns, therefore, the type and characteristics of cultural resources determine the development model of intangible towns, the
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certification, excavation, protection and use of traditional cultural resources affect the long-term development of intangible towns [5]. The assessment of cultural resources can be measured by the number of intangible cultural heritages at or above the municipal level, the number of cultural industrial bases, and the degree of development and utilization of cultural resources. The assessment of cultural resources can be measured by the number of intangible cultural heritages at or above the municipal level, the number of cultural industrial bases, and the degree of development and utilization of cultural resources. (2) Human resources. The construction of the characteristic town needs to rely on human intelligence and labor to achieve. Intangible cultural heritage town should integrate human resources, such as cultural creators, cultural designers, operators and managers, with inheritors of intangible cultural heritage to carry out overall planning and development. In addition, the special point of the intangible town compared to other types of featured towns is that some historical culture, traditional crafts or folk festivals have been deeply embedded in the life of the town, and local town residents will also participate in the construction of the town. The quality of human resources determines the quality and innovation of the construction of intangible cultural heritage towns [6]. The professionalism of human resources determines whether intangible features can be fully demonstrated during the construction of intangible towns, therefore, human resources are mainly measured by number of inheritors of intangible cultural heritage, the number of talents introduced and the number of employees in the cultural industry. (3) Capital resources. Capital is an important foundation for the development of the intangible cultural heritage featured towns. The lack of capital industry projects cannot be carried out and the industry cannot be reached. Intangible cultural heritage towns must have strong financial capital as support to ensure the introduction of talented people and effectively promote intangible protection and inheritance, cultural industry development and infrastructure construction. Capital resources can be measured by investment in fixed assets and investment in cultural industries. (4) Infrastructure. The construction of infrastructure is a tangible construction in the construction of characteristic towns. It visually displays the external image of intangible towns and affects the first impression of consumers on intangible towns. The construction of the infrastructure will be reflected in the traffic conditions, cultural industry facilities, living infrastructure, and eco-environmental facilities of the town. The traffic conditions to reach the town represent the ability of the town to communicate and communicate with the outside world. It is a necessary condition for the development of the town and is measured by the rate of passing through the graded road. Cultural industry facilities are the material form of the town’s intangible cultural heritage. They are a way for consumers to understand the history and culture of the town or experience traditional craftsmanship. They are directly related to the travel experience of consumers and bear the industrial characteristics of the construction of intangible towns. The construction of cultural industry facilities must closely integrate the intangible cultural heritage that exists in the town because it is the most important part of the township construction. This is measured by the area of cultural industry facilities.
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Cultural industry facilities are measured by the area of cultural industry facilities; the living infrastructure and eco-environmental facilities reflect the cleanliness and comfort of the entire town, presenting the overall life environment of the town to the consumers, assisting in the formation of the consumer’s travel experience, and should also be planned and improved in the construction of the town; living infrastructure measured by the gas coverage, tap water occupancy rate, domestic sewage treatment rate and harmless disposal rate of domestic garbage. Ecoenvironment facilities are measured by green coverage. 3.2.2 Demand Conditions In the theory of porter diamond model, demand conditions mainly refer to domestic demand. By focusing on the scale, structure, and dynamic changes of domestic demand, we gain competitive advantage. Domestic demand is the driving force for economic growth, because the demand structure determines the degree of market segmentation, and market segmentation can drive the increase in demand size and demand growth. Demand conditions reflect consumer demand, and consumer demand determines market capacity. In 2017, the per capita disposable income of Chinese residents was 25,974 yuan, an increase of 7.3% over the previous year. In 2017, the expenditure on education, culture, and entertainment in the country’s per capita consumer spending was 2,086 yuan, accounting for 11.4% of the total expenditure, an increase of 8.9% over the previous year. In 2017, domestic tourism revenue was 4.56 trillion yuan, an increase of 15.9% over the previous year. From the perspective of the theme of free travel in 2015, 50.7% of the tourists surveyed preferred cultural experience tours, and the theme tourism gradually expanded to 20–40 year old youth and middle aged groups. In 2015, 40% of China’s online hot scenic spot tickets TOP10 in history and culture. From the above data, it can see that with the continuous expansion of urbanization areas in recent years and their continuous improvement, the living standards of urban residents have been significantly improved, and their incomes are gradually increasing, prompting residents to invest more financial resources and time to reach rich and varied spirits and cultural life. Most residents have switched from simple material needs to the pursuit of spiritual and cultural needs, and cultural and educational resources of historical and cultural tourist towns have also become popular consumer products. Therefore, the establishment of two secondary indicators of demand scale and demand structure under the first-level indicators. The scale of demand is measured by GDP per capita and per capita disposable income of urban and rural residents; in terms of demand structure, the proportion of per capita cultural consumption and urban residents’ cultural expenditure as a total expenditure are used as the third-level indicator. 3.2.3 Related and Supporting Industries Related and supporting industries mainly refer to suppliers and associated auxiliary industries. Porter believes that if an industry can gain an international competitive advantage, its related and supporting industries will inevitably also develop, which is mainly due to industrial clusters and spillover effects.
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The connotation of the featured town is reflected in the industry, so the development of the associated industry plays an important supporting role in the development of the characteristic town. First, the intangible cultural heritage town is a product of the integration of the cultural industry and the tourism industry, and has great industrial development space. The tourism industry and the cultural industry are mutually integrated and promoted. Culture is the “soul” of tourism. Tourism is an important carrier of culture. Both are indispensable. In addition, as a subsidiary industry of the cultural industry, the cultural creativity and design industry acts on intangible resources through tangible or intangible methods, and inherits and innovates the intangible cultural heritage through modern thinking, concepts, tools, technologies, and products. In this way, the intangible cultural heritage towns will be transformed from original, demonstrative cultural product offerings to creative and experiential cultural spaces, which in turn will increase the cultural and economic advantages of featured towns. Therefore, two secondary indicators of tourism industry and cultural creativity and design industry were established under the first-level indicators [7]. The status of the tourism industry is measured by the degree of perfection of tourism service facilities and the total annual tourism income; the cultural creativity and design industry is measured by the cultural creativity and the income of the design enterprises. 3.2.4 Business Competition The Porter model points out that the conditions for national competitive advantage are the strategic, structural and competitive conditions of domestic enterprises. Intense domestic competition leads companies to seek ways to increase production and operating efficiency, which in turn makes them become better international competitive companies. The corporate competitive strategy and structure includes both the company’s operating principles and specific business strategies, testing the ability of companies to make correct decisions in a fiercely competitive market. The right strategic decisions, the organizational structure that suits the actual situation of the company, and the financing decisions that help to achieve the lowest cost and the most efficient are the sources of corporate competitiveness [8]. Enterprise competition depends on internal competitive advantage. The scale of the enterprise represents the resources of the enterprise, and to a certain extent determines the competitive advantage of the enterprise. The size of the enterprise’s ability determines whether the company can exist and develop in the market for a long time. Therefore, the analysis of enterprise competition is conducted in two aspects. This paper establishes two secondary indicators, which are enterprise scale and enterprise capabilities. The assessment of the scale of the enterprise is mainly measured by the total number of employees, annual sales, and total assets; the ability of the enterprise is measured by the main business income, brand awareness, and market share. 3.2.5 Government Action As an external force, the government has a complex role. The government often restricts or encourages certain corporate behaviors through relevant regulations and policies. The government created a political and legal environment for the company and brought development opportunities. If an enterprise wants to gain a competitive
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advantage, it must not only comply with the government’s call, but also actively fulfill its social responsibilities and tax liabilities, create a good social image, and establish a healthy relationship of trust and cooperation with the government. The government behavior is a function of the competitiveness of the characteristic town outside the market competition. The government can maintain the fair and free competition. The government’s support behavior is mainly reflected in policies, funds and other aspects. The state and the governments at all levels provide policy support to the characteristic town to different degrees, which can ensure that characteristic towns will improve administrative efficiency in the subsequent development management process, improve supporting policies, and promote the establishment of efficient and reasonable supervision mechanisms [9]. For example, in 2016, China successively issued the “Several Opinions on Further Promoting New Urbanization Construction”, “Notice on Developing the Cultivation of Characteristic Small Cities and Towns” and “Guiding Opinions on Accelerating the Construction of Small Towns with Beautiful Characteristics”. These related documents have all stimulated the construction of characteristic towns, and have also played a guiding role in the planning and construction of various characteristic towns. The financial support can speed up the construction process of the featured towns. In the “Notice of the Ministry of Housing and Urban-Rural Development of the Republic of China, the “National Development and Reform Commission, and the Ministry of Finance of the People’s Republic of China on the Cultivation of Characteristic Townships”, the contents of the organization’s leadership and support policies clearly put forward two funds support channels: the National Development and Reform Commission and other relevant departments support qualified characteristic town construction projects to apply for special construction funds; The central government will give some appropriate rewards to the characteristic towns where jobs are better developed. In some provinces, local governments also issued more detailed financial support measures for the construction of characteristic towns. For example, Zhejiang Province proposed that during the period of establishment and acceptance of the featured towns, the newly added fiscal revenue within the planned space should be handed over to the provincial finances, fully refunded in the previous three years, and returned to the local finance in half within the next two years; for the characteristic towns that have a demonstration in the whole province, the local government will give these towns a certain amount of land use indicators. Therefore, this paper selected financial support and policy support as secondary indicators. There are two three-level indicators under the second-level indicators of financial support, which are the proportion of R&D expenditure to regional GDP and the proportion of cultural business expenditure to fiscal expenditure; policy support is measured by two levels of indicators, namely the number of relevant policies for supporting cultural industries and the implementation of relevant policies in the cultural industry. Based on the above analysis of the porter diamond model, the indicators for evaluating the competitiveness of the intangible cultural heritage town are summarized in Table 1.
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4 The Weight Analysis of Evaluation Index of Intangible Cultural Heritage Town Competitiveness This study use the Analytic Hierarchy Process to determine the index weights and select 5 experts in characteristic towns, 5 experts in intangible cultural heritage and folk cultural awareness research, 5 experts in tourism planning and 50 staff of the intangible cultural heritage town to conduct questionnaire surveys. Hierarchical analysis method YAAHP software is used to build the hierarchical model, and the expert data aggregation method of group decision-making is used [10]. The weighted arithmetic average of each expert’s sorting vector, after passing the consistency test, finally determines the weight of the development evaluation index of the insolvency town, as shown in Table 1. Table 1. Intangible cultural heritage town core competitiveness index system weights First-level indicators (weights) Production factors (0.4859)
Second-level indicators (weights)
Third-level indicators
Weights
Culture resource (0.1188)
The number of intangible cultural heritages at or above the municipal level The number of cultural industrial bases The degree of development and utilization of cultural resources Number of inheritors of intangible cultural heritage The number of talents introduced The number of employees in the cultural industry Investment in fixed assets Investment in cultural industries The rate of passing through the graded road The area of cultural industry facilities Gas coverage Tap water occupancy rate Domestic sewage treatment rate Harmless disposal rate of domestic garbage Green coverage
0.0452
Human resources (0.1045)
Capital resources (0.075) Infrastructure (0.1876)
0.0335 0.0401 0.0382 0.0328 0.0335 0.0362 0.0388 0.0389 0.0301 0.0207 0.0201 0.0209 0.0238 0.0331 (continued)
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Table 1. (continued) First-level indicators (weights) Demand conditions (0.1131)
Second-level indicators (weights)
Third-level indicators
Weights
The scale of demand (0.0557)
GDP per capita Per capita disposable income of urban and rural residents The proportion of per capita cultural consumption Urban residents’ cultural expenditure as a total expenditur The degree of perfection of tourism service facilities Total annual tourism income The cultural creativity and the income of the design enterprises
0.0259 0.0298
Total number of employees Annual sales Total assets Main business income Brand awareness Market share The proportion of R&D expenditure to regional GDP The proportion of cultural business expenditure to fiscal expenditure The number of relevant policies for supporting cultural industries The implementation of relevant policies in the cultural industry
0.0287 0.0316 0.0321 0.0332 0.0311 0.0322 0.0237
Demand structure (0.0574)
Related and supporting industries (0.0977)
Business competition (0.1889)
Tourism industry (0.0664) The cultural creativity and design industry (0.0313) The scale of the enterprise (0.0924) The capabilities of enterprise (0.0965)
Government Action (0.1144)
Financial support (0.049)
Policy support (0.0654)
0.0318 0.0256 0.0322 0.0342 0.0313
0.0253
0.0351 0.0303
5 Illustration Analysis A city is located in the central and eastern regions of China. It has abundant natural resources, human resources and intangible cultural heritage resources. During the establishment of the first batch of provincial-level characteristic towns, a number of intangible cultural heritage towns emerged. According to the resource conditions and development status of each intangible cultural heritage town, the local government conducts the evaluation and judgment of comprehensive competitiveness. Based on the relevant statistical data and the analysis of the above comprehensive evaluation system, the government calculates the comprehensive competitiveness three-level index of each intangible cultural heritage town in this city, as shown in Table 2.
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Table 2. Three-level indicator value of comprehensive competitiveness evaluation of intangible cultural heritage towns Third-level indicators
Town A Town B Town C Town D Town E Town F Town G Town H
The number of intangible cultural heritages at or above the municipal level The number of cultural industrial bases The degree of development and utilization of cultural resources Number of inheritors of intangible cultural heritage The number of talents introduced The number of employees in the cultural industry Investment in fixed assets Investment in cultural industries The rate of passing through the graded road The area of cultural industry facilities Gas coverage Tap water occupancy rate Domestic sewage treatment rate Harmless disposal rate of domestic garbage Green coverage GDP per capita Per capita disposable income of urban and rural residents The proportion of per capita cultural consumption Urban residents’ cultural expenditure as a total expenditur The degree of perfection of tourism service facilities
7
8
6
7
8
5
7
8
6
5
7
8
5
7
6
8
6
8
7
8
6
6
6
7
8
7
8
6
7
7
8
6
5
7
5
6
8
5
6
7
6
5
7
6
7
5
6
5
8
8
7
9
6
7
8
7
8
9
7
8
5
7
8
7
6
5
7
6
8
6
7
6
5
5
6
7
7
7
5
6
7 9
7 8
8 8
9 7
8 8
9 8
8 8
7 9
7
7
8
6
8
8
7
8
8
7
8
8
8
8
6
8
7 7 6
8 7 6
7 8 7
8 7 7
6 8 8
8 7 7
8 9 8
7 7 6
5
6
6
5
5
7
7
6
5
5
6
5
5
6
6
5
7
7
6
7
6
6
7
7
(continued)
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Table 2. (continued) Third-level indicators
Town A Town B Town C Town D Town E Town F Town G Town H
Total annual tourism income The cultural creativity and the income of the design enterprises Total number of employees Annual sales Total assets Main business income Brand awareness Market share The proportion of R&D expenditure to regional GDP The proportion of cultural business expenditure to fiscal expenditure The number of relevant policies for supporting cultural industries The implementation of relevant policies in the cultural industry
8
7
8
7
8
7
8
8
7
7
6
7
7
6
7
8
6
6
7
7
6
7
6
6
6 7 7 8 7 5
7 8 7 7 6 5
6 7 7 8 6 4
7 7 6 7 6 5
7 6 6 7 5 6
7 5 7 7 7 4
6 8 7 6 5 5
8 5 7 8 6 4
5
4
5
5
5
6
4
5
6
6
7
5
6
7
7
8
7
8
8
8
7
7
6
7
According to the weight of the comprehensive competitiveness evaluation index of the intangible cultural heritage towns above, the value of the three-level evaluation index is substituted, and the comprehensive competitiveness evaluation value of each intangible cultural heritage town is obtained, as shown in Table 3. Table 3. Comprehensive evaluation value and ranking of intangible cultural heritage towns in this city Town A Town B Town C Town D Town E Town F Town G Town H The comprehensive evaluation value of towns The ranking of towns
0.2513
0.2532
0.261
0.2651
0.2598
0.2539
0.2548
0.2599
8
7
2
1
4
6
5
3
From the above data analysis, it can be seen that in this batch of intangible cultural heritage towns, the town D has the highest comprehensive evaluation value, followed by the town C, town H, town E, town G, town F, town B and town A, so the government can be sorted as a reference when evaluating and selecting the intangible cultural heritage town.
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6 Conclusion The characteristics of small towns as an important strategic measure for China to enter the new stage of urbanization has been highly valued by the country. At present, intangible cultural heritage towns are one of the characteristic towns. Although national and local government levels have issued corresponding evaluation and assessment clauses in relevant policy documents, specific evaluation standards have not yet been issued. Therefore, it is imperative to build a competitiveness evaluation system for building intangible cultural heritage towns. In this paper, by analyzing the connotation of intangible cultural heritage characteristic towns, combined with the theory of Porter diamond model and analytic hierarchy process, established an evaluation index system for intangible cultural heritage town competitiveness, from the aspects of production factors, demand conditions, related and supporting industries, corporate competition and government behavior to measure the competitiveness of intangible cultural heritage towns. Constructing the evaluation index system for intangible cultural heritage town competitiveness is helpful to the evaluation and comparison of intangible cultural heritage town, providing solutions and guidance for the planning development of intangible cultural heritage town, and also providing a certain reference for the government to evaluate the development of intangible cultural heritage town, and promoting the government’s selection and evaluation mechanism. Acknowledgements. Foundation items: Key Scientific and Technological Innovation Team Project of Shaanxi Province: Industrial Building Environment and Energy Conservation Innovation Team (2017KCT-14); Project of the Ministry of Housing and Urban-Rural Development “Optimization and Simulation Research on Incentive Policy of Green Housing under Life-Cycle Risk” (2018-R1-003).
References 1. Zhang, L., Zhang, K.: On the development paths of intangible cultural heritage towns in the perspective of “cultural creativity prospering town”. J. Beijing Union Univ. (Humanit. Soc. Sci.)15(1), 82–87 2. Wen, Y., Jin, P.: Core competence and evaluation model construction of characteristic town. Ecol. Econ. 33(6), 85–89 3. Zhao, H.: Analysis on the innovation and exploration of the tourist characteristic town. On Econ. Probl. (12) 104–107 (2017) 4. Liu, Y., Lv, W., Li, H.: The evolution and application of the diamond theory. China Soft Sci. (10), 139–144+138 (2003) 5. Cao, S., Deng, Y.: Imagery pattern of intangible cultural landscape gene mining-in hunan province. Econ. Geogr. 34(11), 185–192 6. Shi, W.: On the building model of distinctive town with the public as the main body. J. Tianjin Sino-German Univ. Appl. Sci. (2), 16–21 (2018) 7. Wang, Z.: The construction of systematic index of regional tourism industry competitiveness evaluation. Bus. Manag. J. 31(8), 33–38
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8. Yang, S.: Study on the competitive power of china’s sport-featured towns-analysis based on michael porter diamond model. J. Hebei Inst. Phys. Educ. 32(3), 41–46 9. Tian, X., Zhao, X.: Study on the evaluation index system of sports town development level. J. Chengdu Sport Univ. 44(3), 45–52 10. Jiang, T., Wu, X.: A study on the evaluation model of the cultural industry competitiveness based on AHP. J. Yunnan Univ. Financ. Econ. 27(6), 126–134
The Thinking on Spatial Management and Control of “Urban Growth Boundaries” from the Perspective of Natural Resources Zhiyi Xu1,2 and Yuzhe Wu1(&) 1
2
School of Public Affairs, Zhejiang University, Hangzhou, China [email protected], [email protected] Urban-Rural Planning and Design Institute, Zhejiang University, Hangzhou, China
Abstract. With China's reform and opening up entering the deep-water zone, the development of ecological civilization has become the founding concept, and the development of urbanization has changed from extensive expansion model to smart growth model. “Integration of multiple regulations” and “Three lines and three districts” are the main targets and the grasp of Chinese government on the spatial planning. However, in practice, multi-party interests and conflicts occur on how to define the “Urban Growth Boundaries”, which has become one of the difficulties not only in the spatial planning, but also the transformation and development of China’s economy. This paper tries to discuss the understanding to the concept of “Urban Growth Boundaries” and technical guidance from successful cases of mode at home and abroad, there are the twoway mode of the spatial management and control between government and civil society to develop the Boundaries, and the cross compound utilization mode of “three areas, four lines”, “the combination of rigidity and flexibility” - The spatial management and control mode of “Urban Growth Boundaries”, and change the thinking of managing the spatial control of “Urban Growth Boundaries”, guarantee the quantity and quality of agricultural and ecological land, at what level and scope do we define the “Urban Growth Boundaries” which needs to answer three questions basing on the cases. This paper takes Portland in the United States, Shanghai and Xiamen in China for example. It intends to explain the features of each model represented by three cities and summaries the mechanism of the management and control to the city’s spatial. Later, the paper answers 3 frequently asked questions and tries to use the model discussed in the paper on how to change the thinking of the spatial management and control of the urban growth Boundaries, whether the urban growth Boundaries guarantee the quantity and quality of agricultural land and ecological land and At what level and scope we define the urban growth Boundaries. The “Urban Growth Boundaries” is a spatial instead of a simple line, and can be a system, a goal, a platform, a process, and also a result from the percept of observation. The spatial management and control of the “Urban Growth Boundaries” should make regular adjustment basing on local conditions. Hopefully, the paper can help the readers gain more confidence to deal with the difficulties encountered in the urban planning and may inspire the readers to find more innovative ideas to solve the problems.
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 122–135, 2021. https://doi.org/10.1007/978-981-15-3977-0_9
The Thinking on Spatial Management and Control of “Urban Growth Boundaries” Keywords: Spatial management and control (UGB) Three lines and three districts
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1 Introduction Urbanization is a process of transformation from traditional farming civilization to modern industrial civilization. During this process, the proportion of urban population in the world has risen from 33% in 1960 to 54% in 2017, especially in Asia and Africa, and the urbanization rate of China has reached to 58.52% in 2017. In the next 50 yr, people in China and India will transform from rural lifestyle to urban lifestyle as those in Europe and America did before. Will China become a mainland of suburban motorists or a mainland of urban public transport users? Even in 1970s, [1] it was suggested that human patch spatial could be developed in a way that people concentrate on high buildings and walk to the worksite in order to minimize the damage to the environment. From eighteenth to nineteenth Century, the United Kingdoms experienced the urban agglomeration period, and then went through the urban rural landscape development period after twentieth Century. Mr. P. Geddes applied the theory of evolution and ecology to the research of urban development. The concept of Ruskin and E. Howard's “Garden Cities of Tomorrow” proposed that the village pastoral should be brought into a city. In 1924, Mr. R. McKenzie, an American social ecologist, tried to apply the thought of ecological life cycle to the study of the human community, and to analyze the various stages of the development of the city as “ecological process” and the manifestations at each stage [2]. Thoreau and Wordsworth hold the point of view that “people shall go to the rural for leisure”, which emphasizes the advantages of rural isolation more than urban interaction. It also helps to develop the concept that transportation shall go first in the urban development in the United States, and results in the emergence of many modern and landscaped suburban satellite towns. It is proved that the planning of the human patch spatial adapts to the fast pace of modern metropolitan life. The greening and agricultural zones between the patches have increased the length of the living spatial corridor, however, the automobiles help to merger the patches and lead to the expansion of the city. From the historical accumulation of fossil fuel and industrial consumption between 1870 and 2016 of IFC, the United States has consumed 26%, accounting for 1/4 of the total global carbon emissions, in which Carbon emissions of houses and cars have consumed 40% of the carbon footprint in United States, equal to 8% of the global carbon footprint. The European Union, China, Russia, Japan and India accounted for 22%, 13%, 7%, 4% and 3% respectively. The Climate Investment Research Report, released on November 13, 2017, also shows that urban population density reduces carbon emissions, as is the case in the fastest growing regions [1]. In the past 30 years, China has gone through an unprecedented “city building movement”. China's urbanization and industrialization process is replacing large amounts of farmland, which is strongly driven by the country's land finance regime,
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with the intensified regional/local competition for manufacturing investment opportunities pushing local governments to expropriate farmland at low prices while leasing land at high market value to property developers [3]. It will continue in the next few decades. With the popularization of automobiles, the spatial of agriculture and ecology spatial on the edge of the city is gradually annexed. As the unlimited expansion of urban boundaries may lead to a substantial increase in ecological footprint, it will be unfavorable to the natural ecological environment. In 2012, the Chinese government formally proposed the concept of ecological civilization development, regulating that the government shall “strengthen the position of the main function and optimize the pattern of land spatial development”, and “strengthen the management of 'three areas and four lines' (Three areas mean no building area, limited building area and building area; four lines mean green line, blue line, purple line and yellow line) in the urban and rural planning”. This involves the issue of spatial planning, which was firstly used in the “European Regional/Spatial Planning Charter” adopted at the Ministerial Conference on Regional Planning in Europe in 1983. The charter points out that regional/spatial planning is a geographical representation of economic, social, cultural and ecological policies. “The Summary of the European Spatial Planning System”, published in 1997, further points out that spatial planning is mainly a method used by the public sector to influence the distribution of future activities and intend to form a more reasonable regional organization for land use, to balance the development and the environmental protection, and finally to achieve the development of society and economy. By coordinating the effects of spatial planning from different departments, balanced development of regional economy can be achieved, and the defects of the market can also be made up for, while standardizing the conversion of land and property use. “Spatial planning” is still frequently used in the planning in Europe and the United States, which is also accepted by the majority of government and experts in China. “The Plan and Implementation of Urban Plan”, enacted by the Ministry of development in 2006, clearly required the government should “study the urban growth Boundaries, determine the scale of the development land, and delineate the scope of the development land.” in the urban overall planning. But the official government does not have a clear view on what is the spatial growth Boundaries and how the growth Boundaries is defined. The limits of urban spatial growth can be understood as the scope of the expansion of urban physical spatial. Multiple delineation methods of urban growth Boundaries require more discussion for different types of urban development Boundaries (rigid/flexible, represented by Beijing). An article of Mr. Wang Ying, Mr. Gu Zhaolin, Mr. Li Xiaojiang and etc., comprehensively summarizes the urban growth Boundaries [4]. “The overall plan for the reform of the ecological civilization system”, issued in September, 2015, further demands that the spatial planning system, with the main content of spatial governance and spatial structure optimization, shall be nationally unified, mutually interconnected and hierarchically classified, which intends to solve the overlapping of different spatial planning, the responsibilities of different
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departmental, and the change of local planning and other issues. In 2016, “The Evaluation and Assessment Method for the Constructing Ecological Civilization” was issued. In 2017, “Several Opinions on the Delineation and Strict Protection of the Red Line of Ecological Protection” was also issued. It stipulates that the government shall “delineate the spatial development boundaries for the production, living and ecology, and implement the control of the spatial use by establishing a spatial planning system” [5]. “The Guiding Opinions on the Pilot Project for Urban Overall Planning of the Ministry of Housing and Urban - Rural Development”, released by the Central Committee of the Communist Party of China and the State Council in September, 2017.09, proposes that the government shall scientifically delineate the “three areas and three lines (three areas means urban area, ecological area and agricultural area; three lines means urban growth Boundaries, red line for permanent basic farmland protection and red line for the ecology protection)”, “the management and control of all domain spatial takes the control as the core and becomes an important part of the experiment of spatial planning reform”. The government also needs to determine the functional layout and spatial structure of the urban growth Boundaries, to delineate the urban green line and the blue line, and to clarify the planning requirements for the co-ordination of urban and rural, village and town and linear projects outside the urban growth Boundaries” [4, 5]. “The Notice of the General Office of the Ministry of Land and Resources on Carrying out Pilot Projects of a New-round Overall Planning of Land Use”, issued in January, 2018, points out that the government shall “strengthen the mechanism of the coordination and implementation of the red line for the protection of permanent basic farmland, the ecological the red line for the ecology protection and the urban growth Boundaries in the planning of overall land use”. The “three areas and three lines” has become an important grasp of the national pilot of “Integration of multiple regulations”. Under the guidance of the deepening the reform group of the central government, Jiangxi, Guizhou and Zhejiang are included in the pilot project to accumulate the experience for the national spatial planning.
2 The Discussion of Several Modes of Urban Development Boundaries “The Guiding Opinions on the Pilot Project for Urban Overall Planning of the Ministry of Housing and Urban - Rural Development”, issued in September 2017, regulates “three areas and three lines” and also that “ecological control lines and urban development Boundaries shall be delineated within the limits of the city according to the strictest standards”. However, it is quite difficult to delineate “three areas and three lines”, especially for urban development Boundaries in the planning due to in lack of research on the connotation of the “two lines” above-mentioned and also the lack of the experience of planning, which requires further thinking. We can analyze and compare the cases from home or abroad in order to find the solutions [6].
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The Two-Way Control Between Government and Civil Society Mode to Develop the Boundaries in the West Coast of the United States
In order to reduce carbon emissions by changing land development policies, the hierarchy relationship of the administrative on the planning in the united States is that the state government determines the principles, regional government delimits the Boundaries (for 50 years as a planning cycle), and the municipal government determines the function (for 15–20 years as a planning cycle). Oregon, for example, has a large population and also has rich agricultural products, and the agriculture is the second largest economic sector in Oregon. Therefore, the contradiction between urban development and farmland protection in the William Valley is relatively sharp. In 1973, Oregon established the Land Conservation and Development Commission through Senate Bill 100, which requires that all land use should be met with a series of objectives set by LCDC. The 14th objective - urbanization of 19 state land use objectives set by LCDC clearly states that all the county, municipal or regional governments have the responsibility to delineate and maintain the Urban Growth Boundaries. [7]. The 14th objective - urbanization points out the factors that need to be taken into consideration: the disposal of the community outside the Urban Growth Boundaries and single housing, and the development of the industry outside the Urban Growth Boundaries, when determining the Boundaries of the urban development, the amount of land within the border and the four boundaries of a piece of land the four boundaries of a piece of land the four boundaries of a piece of land the four boundaries of a piece of land. This provision establishes the statutory status of the urban growth Boundaries in Oregon. Let’s take Portland for example. The development of the urban development Boundaries in Portland metropolitan area from 1979 to the present may be divided into three stages by the development concept planning in Year 2040 issued in 1994 and the demarcation of urban and agricultural reserve land in 2011. In the stage between 1979 and 1994, the delimitation of the urban growth boundaries in Portland metropolitan area is simply an urban growth Boundaries that is passively defined to accommodate the growth of population in the next 20 years. It is based on land supply and demand analysis, which is similar to land suitability analysis in China. The demand analysis can be divided into 4 parts: residential land, industrial land, public welfare & semi-public welfare land and flexible land. The method of delineation in the edition of Year 1979– 1994 is: (1). to take into account the relative factors such as the proportion of apartments and the different needs of employment; (2) to add an elastic interval of 25% so that the demarcation of urban development boundaries can cope with the uncertainty of urban development in the next 20 years; (3) no measures to limit the reduction of agricultural land. The method of delineating the urban growth Boundaries is only to control the direction of urban growth, but it cannot control the intensity and model of urban growth, which therefore cannot fundamentally control the urban’s growth [7]. The 2004 edition of the demarcation of urban growth boundaries set up four scenarios: traditional supply and demand growth, traffic led growth, the compact
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development of stock, and the mode of satellite city. Then different spatial structures are delimited according to a specific growth scenario. 46 indicators are analyzed from eight aspects: transportation, land use, housing, employment, the quality of air, water supply and drainage, open spatial and social support. Then a public survey of full coverage will be conducted to weigh the acceptability of the public at every scenario. A comprehensive plan incorporating more than one plan has been put forward to demarcate the urban growth Boundaries. Finally, after the plan was enacted in 1994, the Urban Growth Management Functional Plan was also enacted by the metropolitan government of Portland, which provided the requirements and policy tools for the local government. Regional Framework Plan is a policy collection of the management of spatial growth to instruct the metropolitan government. Metro's Natural Resource Protection Strategy provides specific strategies for the protection to natural resources. The metropolitan government of Portland integrated the Regional Transportation Plan into the targets of the Year 2040 Growth Concept in the summer of 2004. In 2004, the metropolitan government also carried out an evaluation of the performance of the plan from 8 angles, which include the promotion of the economic prosperity, the promotion of the effective use of land, the environment protection, the isolation of the urban growth Boundaries with other cities, the availability of a more balanced transportation system, the maintenance of the community in good order within the urban growth Boundaries, providing various options for housing, living and working to residents in the community. Let’s take “the promotion of the economic prosperity” for example. “The promotion of the economic prosperity” has 16 indicators, which include the amount of land area, the development of the available land, permanent population in the community and employment population on the available land, the average development land unit, the population, the population of employment, the population of unemployment, the disposable income of residents in the community, the amount of retail, total value of the taxable property, total value of the per capita taxable property, the per capita housing value, and the per capita non-housing value, the value of housing, the proportion of housing value and non-housing value at each district in the community, the quality of education at primary, [3] junior and senior high schools, and the change of school free lunch in the Urban Growth Boundaries. In 2008, the metropolitan area of Portland has found that landowners in the surrounding areas of the urban growth border were not willing to invest on the land because of the uncertainty of the future use of land, which of course was detrimental to long-term investment. Therefore, the “Urban and rural reserves” is delimited according to the regulations of Senate Bill 1011 issued by the state government of Oregon in 2007 [7]. Urban reserves is the land suitable for the city’s development in the next 50 years and has the priority to fill the expansion of the urban growth Boundaries; rural reserve (which is similar to the concept of the “no building area” in China) is reserved to protect the land for agriculture, forestry, wetlands, rivers, hills and flood plains. Unspecified area can also be used for the expansion of the urban growth Boundaries, but it has lower priority than the urban reserve (which is similar to the land for future development in China) (Fig. 1).
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Fig. 1. The spatial structure corresponding to four different spatial growth modes (traditional supply and demand growth, traffic led growth, the compact development of stock, and the mode of satellite city) in Portland.
There are three methods to adjust the urban growth Boundaries in the Urban Growth Management Functional Plan. The first method is to assess the urban growth Boundaries every 6 years and make necessary adjustment. The second method is to greatly adjust the urban growth Boundaries in necessity. The third method is to mildly adjust the urban growth Boundaries in necessity. Judging from the latest delineation of the urban growth Boundaries in the metropolitan area of Portland, some areas have exceeded its the administrative jurisdiction. These transitional areas have the priority to be urbanized in the future, but they must win the public vote before becoming a part of the metropolitan areas. As of 2005, 1/4 of the land in the Gulf of California has become a permanent ecological protection zone, which prohibits any kind of development. California Environmental Quality Act, enacted in 1970, regulated that any local government project must undergo an assessment of environmental impact before the commencement of work [1]. 2.2
Shanghai: Cross Compound Utilization Mode of “Three Areas, Four Lines”
The premise of the new edition of Shanghai City’s general planning is the priority of ecology and the lock-in for development land, which forms an elastic control system of zoning with “three kind of spatial and four red lines” as the basic framework.
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The government needs to adhere to the reduction of inefficient development land outside the urban growth Boundaries and to link with the new development land within the urban growth Boundaries. The government also needs to make the differentiation policy to inside or outside the urban growth Boundaries and also need to build the mechanism of balancing the interest with comprehensive supporting policies from the aspects, such as finance, industry, ecology and regulation in order to ensure and promote the implementation of the reducing low efficiency in the land development outside the urban growth Boundaries (Fig. 2).
Fig. 2. The diagram of the relationship between “three types of spatial” in Shanghai (Source: 2035 general planning of Shanghai)
2.3
Xiamen: “The Combination of Rigidity and Flexibility” - the Spatial Management and Control Mode of the Urban Growth Boundaries
The basic idea is to establish the management and control strategy of “rigid control + flexible layout: for the spatial management and control of the urban growth Boundaries, and also to establish the mechanism of spatial retention. It needs to make the adoption to the layout of “group type” to delineate, to realize the control to overall spatial planning of the city, and to guide the intensive green development of the city; the villages located within the city and the villages adjacent to the city should be classified into the urban growth Boundaries, and be given a differentiate planning (Fig. 3).
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Fig. 3. Ecological Control Area and Urban Centralized Construction Area (with the Urban Growth Boundaries) (Diagram Source: General Urban Planning of Xiamen City in 2035)
The urban growth Boundaries delineated by general planning of the city, formal urban growth Boundaries of the county or city after the execution; the integrated management of the information platform; delineated by the county-level’s or citylevel’s government, examined by the city-level’s government, approved by the provincial Housing and Urban - Rural Development. Xiamen also integrates all of the spatial data information of multiple departments, and sets up a full set of 46 index systems with five major development concepts to be executed by multiple Departments. Among the 46 index systems, it includes 16 indicators for green development, and clearly defines the administrative boundaries and the coordination to overlapping parts for various functional departments in the execution (Table 1 and Fig. 4).
Table 1. The mechanism of control and management in cases City Portland
The mechanism of control and management • Define the urban growth Boundaries with multiple angles, multiple indicators and multiple scenarios, and encourage the participation of the public and the supervision of social organizations • Urban reserve for the next 50 years outside the urban growth Boundaries as the priority to expand the urban growth Boundaries • The method to adjust the Boundaries of urban growth Boundaries. The first method is to assess the urban growth Boundaries every 6 years and make necessary adjustment. The second method is to greatly adjust the urban growth Boundaries. The third method is to mildly adjust the urban growth Boundaries (continued)
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Table 1. (continued) City Shanghai
Xiamen
The mechanism of control and management • Adhere to the reduction of the development land inefficiency outside the urban growth Boundaries and link up with the new development land within the urban growth Boundaries • Make the differentiation policy to inside or outside the urban growth Boundaries and build the mechanism of balancing the interest • Rigidly control the permits of land development outside the urban growth Boundaries. A special demonstration report should be prepared for the review and the approval by the original administrative authorities to make the adjustments of the urban growth Boundaries because of the projects related to the major infrastructure of the state and the major livelihood security projects • Flexibly manage and control the dominant functional area layout within the urban growth Boundaries. For the urban strategic areas and unspecific function’s land in the key areas in the near future, it is necessary to establish the spatial retention mechanism • Integrate the data of different departments and centralize the index management
Area of Urban Construction Land (km2)
3050 2550 2050 1550 1050 550 50 1979198119831985198719891991199319951997199920012003200520072009201120202035 Portland
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Year
Fig. 4. The urban growth boundaries change in area in three cities over the years
Portland's Urban Growth Boundaries has grown by an average of 3.8 square kilometers per year from 1979 to 2016, with the largest increase coming in 2002, when people in a region voted to create a new town. Excluding this year, the average annual increase was 1.6 square kilometers. They have designated urban and rural reserves, similar to China's urban prospective development land and agricultural ecological protection land.
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Shanghai's Urban Growth Boundaries has expanded rapidly in the past 30 years, especially in the 1985, 1991 and 2005, when three rapid-growth transition nodes, new area land use dynamics, which with the population distribution and change, economic growth, improve people's living standards, policies and large-scale international events held a major impact. Xiamen’s population from 500,000 to 4 million Between 1979 and 2016, is earlier practice city Urban Growth Boundaries very successful in China. 2001 for node, from the “tailored” planning to the Cross-regional control, from the dynamic planning, action to planning management policy, institutionalization, between the ideal and the reality, between static and dynamic, between guidance and control, to seek the transition from the ultimate blueprint to the dynamic planning. Even rapid human growth in the nearly 20 years, Urban Growth Boundaries have been developed in an orderly fashion.
3 Question and Discussion 3.1
How Can We Change the Thinking of Spatial Management and Control of the Urban Growth Boundaries?
When we are entering the era of “three zones, three lines” in the overall and trans regional planning of the city, what we need to do with the urban growth Boundaries is to make the transformations from 8 aspects: from the functional spatial to the spatial governance, from the land management to the land governance of ecology [8], from the economy, the society and the landscape ecology towards the harmonious relations with spatial, from the brown spatial to the smart spatial, form the operation of spatial to the maintenance, operation, management and control of the spatial, from a single spatial to a characteristic complex spatial, from a single service object to comprehensive management to diverse objects; we need to handle the challenges from four aspects: the spatial planning, the usage control of spatial, the assessment and the monitor of spatial, the operation and utilization; we need to have three supports: rationalizing the division of power between the central government and the local government, promoting the reform on household registration, the reform of taxation, the land system at village level, enhancing the legal system of spatial governance; we also need to get five tools of grasps: unifying the compilation system, establishing the mechanism of risk prevention and control, improving the supervision system, and enriching governance tools for the government. 3.2
Can the Urban Growth Boundaries Guarantee the Quantity and Quality of Agricultural Land and Ecological Land?
As far as China is concerned, the urban growth Boundaries may encounter with the red line of permanent basic farmland, and the local government has the impulse to develop the economy. As a disadvantaged industry, agriculture will not be a dominant industry that local government pushes to develop, and the income obtained by farmers from the agriculture is also low, which causes many farmers to abandon the farmland and work in a city, and of course leads to the decline of many villages. The demand for urban development is simultaneously still very strong, especially in the developed provinces
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in China. The transformation of agriculture land to non-agriculture land remains in short supply. At the same time, a large number of ecological land transforms to agriculture land, and the rehabilitation projects of the development land transforming to agriculture land are undergoing. Under the condition that the total amount of agricultural land is controlled and the index can be allocated, it is still a question whether the delineation of the urban growth Boundaries can restrain the impulse of local government to develop the local economy, and whether it can protect the safety of agricultural land. 3.3
At What Level and Scope Do We Define the Urban Growth Boundaries?
Unlike the United States, the county level government is regional and can make the final decision on how to define the urban growth Boundaries in China. This provides a convenience for the administrative division to unify the management and control of the “three areas and the three lines”. Compared with the general traditional planning of a city, the concept of the urban growth Boundaries is defined not limited to central part of a city, and the delimitation of the urban growth Boundaries is not rigid with the subject of a single level administrative division, but it depends on whether the urban growth is continuous or not, we need to take the national strategy as a criterion of discrimination, which requires the flexibility to determine who is the planning-maker. Therefore, delineating the urban growth Boundaries with the integrity of spatial layout is beneficial to the concentrated function of cities and the effective use of resources.
4 Conclusion The Urban Growth Boundaries is a spatial instead of a simple line. It should be an elastic Boundaries spatial and follows up the concept of “developing the point, protecting the surface”. The management and control of the urban growth Boundaries requires the combination of rigidity and flexibility with the integrity of spatial layout, and can benefit to realize the effective use of urban multiple functions. The Urban Growth Boundaries is a system. The urban growth Boundaries may face many changes and uncertainties. It is an important grasp of the “integration of multiple regulations”. It is involved with the unification of indicators, data, and the management and control of several departments. It is a system composed of multi department, multi technology and the coordination of multi subject. The Urban Growth Boundaries is a goal. In order to achieve this goal, it needs a series of supporting measures, special planning, concept innovation and technological innovation, which also requires the spatial policies collection of the governments at all levels. The Urban Growth Boundaries is a platform. It is the focus of social contradictions, the arena of the interests of different parties, shows the diversity and complexity of social ecology. For the implementation of the urban growth Boundaries, it requires strong determination to make a blueprint come true and also the formation of the community interests.
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The Urban Growth Boundaries is a process. It is necessary to organize an argumentation on a regular basis according to the needs in reality. Long-term problems encountered in the development ca not depend on any movement of technology delineation or the intervention of any administrative. In addition, it also requires professional third party with ethics to conduct the supervision. The Urban Growth Boundaries is a result. It is the result after weighting the advantages and disadvantages of various urban development situations and analyzing the influence of various factors such as spatial structure and spatial form. It is quite necessary to understand the land and understand the social economy to find out the best model of the management and control. The Urban Growth Boundaries is not the Urban Service Boundaries. The land zoned by the Urban Growth Boundaries is supposed to be the direct geographical relation of the city, but the urban system is increasingly inseparable from the service and support of the surrounding rural system, whereas the service function of the urban must be covered to the surrounding countryside, so as to promote the revitalization and sustainable development of the village. The Urban Growth Boundaries is not the disappearing Boundaries of rural culture. The rural culture is the origin of the aboriginal culture for the long history city, is the belief of the ethnic group, does not mean that it can be banned by the modern city culture in the city block, but also the need to avoid the style crisis of “Similar Appearance of more and more Cities”. The Urban Growth Boundaries is not the Boundaries of the land non-agriculture. Population distribution and density agglomeration also have gradients, from the national, provincial and municipal level to manage, Urban Growth Boundaries balance is based on population density distribution as the main parameters, the imbalance of population density distribution represents the form of industrial function, but the embodiment of the ecological civilized city is the diversity of land use and its volume, variety, value and nature. The spatial management and control of “Urban Growth Boundaries” is the technology iteration and system matching of urban and rural development. The “Cities Annex Villages” is not only the “Urban Growth Boundaries” spatial control problem, but the laws of development of the short-term incremental urban in our time. First, the spatial management and control of “Urban Growth Boundaries” technology must build a unified and flexible spatial planning system which integration of multiple regulations, in order to maintain market vitality, gradient positioning national, provincial, city and town level of spatial control responsibility. Second, “Urban Growth Boundaries” The key object of spatial control is not only the problem of land structure in border area, but the problem of fundamental (all-for-one urban and rural natural resources, three lines and three districts), we must take into account protection and development of urban and rural natural resources in high efficiency, balance the allocation of spatial resources. Third, “Urban Growth Boundaries” Spatial control is the combination of town and village, and the spatial control system should be a process of two-way co-ordination with “top-down”, “bottom-up”, and a process of rigidity and elasticity management and relief. Forth, Urban Growth Boundaries can limit the spread of urban sprawl, to protect urban external open space and rural and basic farmland, to achieve a high-density, more compact development model.
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To sum up, facing the ecological civilization of China's development model–C model is inevitable, our spatial management philosophy is the ecological priority, people-oriented, the control objectives are to retain the landscape, remember the nostalgia; the control method emphasizes balanced and coordinated, pluralistic participation; the content of control is efficient configuration, protection of resources, The result of control is to make people live better and to be more harmonious.
References 1. Glaese, E., Liu, R.: The Victory of City. Shanghai Academy of Social Sciences Press (2012) 2. Ding, H.: Social-Ecology. Zhejiang Education Press, Hangzhou (1987) 3. Wu, Y., et al.: Urban growth dilemmas and solutions in China looking forward to 2030. Habitat Int. 56, 42–51 (2016) 4. Wang, Y., Gu, Z., Li, X., et al.: Research progress on the Urban Growth Boundaries at home and abroad. Int. Urban Plann. 29(4), 1673–9493 (2014) 5. The Central Committee of the Communist Party of China and the State Council. Overall plan for the reform of the ecological civilization system (2015) 6. The Central Committee of the Communist Party of China and the State Council. The Guiding Opinions on the Pilot Project for Urban Overall Planning of the Ministry of Housing and Urban - Rural Development (2017) 7. Li, X.: Urban Growth Boundaries in Portland. Portland Chinese Network Portland CN.com (2016) 8. Wu, J.: Landscape sustainability science: ecosystem services and human well-being in changing landscapes. Landscape Ecol. 28(6), 999–1023 (2013)
Evaluation on Performance of Ecological Welfare of Characteristic Small Town——A Case in Chongqing Jiuxia Tan(&), Yu Zhao, and Hao Wu School of Economics and Management, Chongqing Jiaotong University, Chongqing, China [email protected]
Abstract. As a breakthrough point in the development of new urbanization, the construction of characteristic small towns is a major decision for China to accelerate economic transformation, break the bottleneck of urban and rural development, and have gradually become a focus of attention. Based on the analysis of the connotation of ecological welfare performance of characteristic small towns, this paper uses the cross-sectional data of 2016 and the entropy method to analyze the status quo of the ecological environment of 8 characteristic small towns in Chongqing by horizontal comparison from two input indicators of resource consumption and environmental pollution. Using the improved United Nations’ human development index, a quantitative assessment of residents’ welfare output is conducted from the three dimensions of income, health, and education. In this paper, an improved super efficiency DEA model (Super-SBM model) is used to evaluate the ecological welfare performance of 8 small towns in Chongqing. A quantification evaluation of ecological welfare performance was proposed and the index system was constructed in characteristic small towns, which provided a new perspective for the quantitative research of ecological welfare performance of characteristic small town. Keywords: Characteristic small town Evaluation system
Performance of ecological welfare
1 Introduction The characteristic small town development model originated from Zhejiang. At the time, Li Qiang [1], the governor of Zhejiang province, pointed out that characteristic small towns are based on the concept of innovation, coordination, green, openness, and shared development and form an organic combination of “production, city, person, and culture”. The important functional platform has a clear industrial orientation, cultural connotation, tourism function and community function. In February 2016, the State Council issued the “Several Opinions on Further Promoting New-type Urbanization Construction”, and comprehensively deployed to further promote the construction of new-type urbanization, and called for accelerating the development of small and medium-sized cities and characteristic small towns. As a breakthrough point in the development of new urbanization, characteristic small towns have become the most © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 136–150, 2021. https://doi.org/10.1007/978-981-15-3977-0_10
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prominent carrier and presentation mode in the new urbanization construction at the present stage [2]. In June of the same year, Chongqing Municipality issued the “Guiding Opinions on Cultivating and Developing Characteristic small towns of the General Office of Chongqing Municipal People’s Government”. It is clearly proposed that a batch of characteristic small towns should be cultivated and developed in the city, and the development vitality and potential of small towns should be fully released to provide strong support for the further promotion of new urbanization [3]. The construction of characteristic small towns is conducive to transforming the local development model, upgrading of industries, improving the allocation of resources, and accelerating supply-side structural reforms. The construction of characteristic small towns incorporates the concepts of ecological civilization and green development. Therefore, characteristic small towns are great benefit for promoting ecological and environmental protection. This paper evaluates data on three aspects of resource consumption, environmental pollution, and welfare levels, and aims to build a ecological welfare evaluation system for characteristic small towns. It is more intuitive to describe the development and environmental protection of characteristic small towns in Chongqing. In order to optimize the urbanization construction, find the entry point and breakthrough point for promoting the regional economy, and on the basis of an overall analysis of the ecological welfare of the characteristic small towns in Chongqing, put forward corresponding policy recommendations to promote the development of the characteristic small towns.
2 Summary of Studies on Evaluation of Sustainable Development of Characteristic Small Towns 2.1
Construction Evaluation of Characteristic Small Town
Through combing the evaluation literature of the construction of characteristic small town, it is found that the current research mainly focuses on qualitative analysis and quantitative research is relatively rare. Among them, Wu Yizhou et al. [4] made use of the polygon diagram method to compare the three indicators of the basic information, development performance and characteristics of each featured town on the basis of the establishment of the evaluation index system, and provided reference for the construction of featured towns. Dong Xinglin et al. [5] used sustainable development indicators in three aspects of economy, society, resources and environment to construct a sustainable development index system for characteristic small towns in the West Coast New Area of Qingdao, and measured the sustainable development of characteristic small towns using three indices of Ec, Sc, and En. In the end, four sustainable township development proposals were proposed for existing issues. Lei Zhongmin et al. [6], based on the construction of evaluation index system for characteristic small town development and construction, adopted the method of benchmarking, and conducted an empirical analysis of Xia Zhuang ecological agriculture characteristic small town in Qingdao. Wen Yan and Jin Pingbin [7] constructed a key township core competitiveness index system and GSC model based on the GEM model, and used the
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analytic hierarchy process to analyze the environmental resources, infrastructure, capital resources, industrial development, and government support. The weight of 32 indicator elements is established under these five first-level indicators. The existing research results mainly focus on the evaluation of characteristic small towns from the perspectives of urbanization construction, tourism and cultural industry development, science and technology support system, ecological civilization construction, innovation, etc. There are still limitations in the perspective of ecological welfare. Therefore, this paper evaluates from the perspective of ecological welfare. Characteristic small towns, put forward the idea of quantitative evaluation of ecological welfare performance of characteristic small towns and construct index system, and put forward opinions on the construction of characteristic small towns. 2.2
The Concept of Ecological Welfare
The idea of sustainable economic welfare efficiency was first proposed by Daly [8]. On this basis, Zhu Dajian [9] proposed the concept of ecological welfare performance and defined it as the efficiency of natural consumption conversion to welfare level. The ecological input level or welfare level reflects the sustainable development level of a country, region or city. The ecological welfare performance is the relationship between the value of the welfare and the physical quantity of the ecological resource consumption. The time series analysis can reflect the social welfare and the degree of decoupling from the consumption of ecological resources, in turn, reflects the economic quality and energy level of green transformation and development [10]. 2.3
Evaluation of Characteristic Small Towns from the Perspective of Ecological Welfare
At present, the research objects of ecological welfare performance evaluation at domestic and abroad are mainly concentrated in the national level [11], and He Lin [12] applied it at the provincial level, but the few research literature on the ecological welfare performance of the research object of cities and towns. There is still no unified evaluation index system for the measurement of ecological welfare performance [13]. Therefore, establishing a set of ecological welfare performance evaluation system is indispensable for the development of characteristic small towns. This article draws on and refers to the existing research results of ecological welfare performance. From the perspective of regional eco-environmental input and residents’ welfare output, the index of the Residents’ Ecologic Environmental Input (REEI) mainly uses resource consumption and environmental pollution indicators for comprehensive evaluation [11]. Therefore, this article uses resource consumption, environmental pollution, and welfare levels as the first-level indicators, and uses entropy method to analyze the influencing factors of ecological welfare performance of characteristic small towns, finds out its key influencing factors, and constructs characteristic small towns’ ecological welfare performance. The evaluation index system will provide targeted policy recommendations for the sustainable development of characteristic small towns, thereby promoting better and faster development of characteristic small
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towns in Chongqing, and providing reference for the construction of characteristic small towns in other regions of the country. In 2016, the Ministry of Housing and Urban-Rural Development issued the Notice of the Ministry of Housing and Urban-Rural Development on Announcement of the First Batch of Small Towns with Chinese Characteristics, and announced the first batch of 127 state-level featured towns, including four in Chongqing, and the Ministry of Housing and Urban-Rural Development in 2017. The list of the second batch of 276 state-level Characteristics towns was announced, of which 9 were in Chongqing, given that the selected districts need to have a certain degree of representation in terms of their political status and economic strength, and at the same time the data availability and comparability. Therefore, the selected towns under the eight districts and counties were selected in this paper, including Wanzhou, Fuling, Tongnan, Jiangjin, Hechuan, Changshou, Dianjiang and Youyang. This article uses the cross-sectional data of 2016, firstly based on the entropy method, and compares the ecological status of selected eight towns in Chongqing from the two input indicators of resource consumption and environmental pollution, Then, using the improved Residents’ Human Development Index (RHDI), a quantitative assessment of residents’ welfare output from the three dimensions of income, health, and education was conducted, and applying the improved super-efficiency DEA model (Super-SBM model), a comprehensive evaluation of the performance of ecological welfare level of 8 characteristic small towns in Chongqing was produced.
3 Indicator System, Research Methods and Data Sources 3.1
Construction of Evaluation Index System
The selection of performance of ecological welfare evaluation indicators in characteristic small towns should fully reflect the connotation of ecological welfare, and also consider whether the selected indicators are reasonable and effective. In general, the selection of indicators should follow the principles of system availability, comparability, completeness, representativeness, and scientificity. Performance of ecological welfare reflects the relative changes in the consumption of welfare and ecological resources, and carries a large amount of economic, social, and ecological information [10]. Therefore, the evaluation index system that affects the ecological benefits of a featured town is summarized in three aspects. This article selects energy, water resources, and land consumption as indicators of resource consumption of urban ecosystems, and uses standardized coal, per capita consumption of domestic water, per capita construction land area, and per capita arable land. Environmental pollution indicators consist of “three wastes” (wastewater, waste gas, solid waste) emissions, including emissions from industrial sources and life sources. The level of welfare is reflected by three dimensions of economy, education and health, as shown in Table 1.
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Classification First-level indicators
Secondary indicators
Input indicators
Land Per Capita Built-up Area (X1) consumption Per Capita Arable Land (X2) Energy Per Capita Consumption of consumption Standard Coal (X3) Water Per Capita Water Supply (X4) consumption Sewage Per Capita Industrial Wastewater emission Emissions (X5) Per Capita Emission of COD (X6) Exhaust Per Capita Industrial Emission of emission Nitrogen Oxides (X7) Per Capita Industrial Emission of Sulfur Dioxide (X8) Solid waste Per Capita Living Garbage discharge Removal (X9) Harmless Treatment rate of Urban Garbage (X10) Economic GDP Per Capita (Y1) development Health care Average Population Life Expectancy (Y2) Education Average Years of Schooling (Y3) development
Resource consumption
Environmental pollution
Output indicators
3.2
Welfare level
Third-level indicators
Literature
Frequency
[11, 13– 18]
7
[11, 13, 15–22]
10
[11, 13, 15–18, 20]
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Research Methods
3.2.1 Entropy Method The entropy method [23] is an objective weighting method. The weight coefficient is determined based on the degree of dispersion of the information that contain the objective data of each evaluation index, which effectively avoids the interference of human factors so the evaluation result is more authentic and reliable. This paper uses entropy method to determine the index weights of the resource and environment input index, and evaluates the resource and environmental basis of the 8 characteristic small towns in Chongqing. The steps are as follows: 1. Eliminate the raw data dimension and make data standardized. Xij ¼
xij xj ; ði ¼ 1; 2; . . .; n; j ¼ 1; 2; . . .; mÞ sj
ð1:1Þ
Among them, xj ¼
n 1X xij n i¼1
ð1:2Þ
Evaluation on Performance of Ecological Welfare n 2 1X xij xj n i¼1
sj ¼
141
ð1:3Þ
(j = 1,2,…,m), are the sample mean and sample standard deviation of the index of the jth evaluation index. 2. Equalize the degree of quantitative. Xij ¼
xij n P xij
ð1:4Þ
i¼1
3. Calculate the index entropy of j evaluation. ej ¼
n 1 X Xij ln xij lnðnÞ i¼1
ð1:5Þ
4. Define the difference coefficient. gj ¼ 1 e j
ð1:6Þ
5. Normalize and determine the final weight factor. wj ¼
gj ; ðj ¼ 1; 2; . . .; mÞ m P gj
ð1:7Þ
j¼1
6. Calculate the score of environmental pollution of i evaluation object (Qi). Qi ¼
n X
wij Xij
ð1:8Þ
j¼1
3.2.2 Improved DEA - Super-SBM Model Charnes et al. [24] first proposed Data Envelopment Analysis (DEA). Tone [25] first proposed a non-radial, non-angular SBM model (Slacks-Based Measure) based on a modified slack variable in 2001. Based on this, Tone [26] proposed Super again in 2002. The SBM model solves the problem that Song [27] pointed out that the SBM model cannot be effectively evaluated and sorted when multiple decision units are simultaneously valid. The non-angled Super-SBM model considering slack variables is as follows: Pn s i¼1 i xik min q ¼ P þ q 1 1q r¼1 sr yrk 1þ
1 n
ð1:9Þ
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8 m X > > > xij j s > i xik > > > j¼1;j6¼k > > > m < X yrj j þ srþ yrk s:t: > > j¼1;j6¼k > > > > > k; s þ ; s 0 > > > : i ¼ 1; 2; . . .; n; j ¼ 1; 2; . . .; m; r ¼ 1; 2; . . .; q j 6¼ k
ð1:10Þ
Where q is the relative efficiency value; xik, yrk are the input and output variables of the effective decision unit k; m, q are the number of input and output indicators; respectively, the input and output slack; kj is the weight vector. When q 1, the decisionmaking unit being evaluated is relatively effective; when q < 1, the evaluation unit being evaluated is relatively ineffective. 3.3
Data Collection and Processing
The indicator data selected in this paper are mainly originated from the 2017 Chongqing Statistical Yearbook, data districts and counties, by consulting the Chongqing Statistical Information Network, the statistical bulletins on national economic and social development in all districts and counties, the reports of the people’s governments of all districts and counties and government work reports, and related research Reports and field surveys, A few missing data were obtained by interpolation and extrapolation. This article draws on the Human Development Index (HDI) proposed by the United Nations Development Program (UNDP) and improves it to make a Residents’ Human Development Index (RHDI) applicable to this article, from the three dimensions of income, health, and education. The quantitative evaluation of the development of residents’ welfare come from the three dimensions of income, health, and education. The calculated use geometric evaluation values of income index, health index and education index: RHDI ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi p 3 II HI EI
ð1:11Þ
The United Nations Human Development Index (HDI) is used to set the maximum and minimum values of the sub-item evaluation indicators.
Table 2. Human Development Index (HDI) sub-item evaluation index threshold Index Unit Maximum Minimum Life expectancy Years old 83.2 20 Average years of schooling Year 13.1 0 GDP per capita USD 40000 100
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The income index is calculated from GDP per capita: II ¼
logðGDP per capitaÞ logð100Þ logð40000Þ logð100Þ
ð1:12Þ
Among them, the GDP per capita is processed at a constant price. Health level is measured by the life expectancy index (HI): HI ¼
Life expectancy actual value 20 83:2 20
ð1:13Þ
The education index is measured by the average education index (EI) [28]. In statistical data, the average number of years of education is not directly given. The calculation method in this paper is: PE ¼
6 Pprimary þ 9 Pjunior þ 12 Phigh þ 16 Pcollege and above Pprimary þ Pjunior þ Phigh þ Pcollege and above EI ¼
PE 0 13:1 0
ð1:14Þ ð1:15Þ
Where P represents the number of people with educational qualifications.
4 Calculation Results and Analysis 4.1
Evaluation of Ecological Environment
In recent years, the rapid development of industrialization and urbanization has broken through the red line of ecological arable land, and the development of energy-intensive industries has increased the demand for fossil energy, and the emission of exhaust gas has increased year by year, causing the greenhouse effect to intensify. Both resource consumption and environmental pollution are negative indicators, indicating that the higher the score of the ecological status, the greater the resource and environment consumption. According to the formulae (1.1)–(1.8), MATLAB software is used to process the data of 10 secondary indicators in two aspects of 8 characteristic small towns in Chongqing. The total weight of each index system and the indicators of the REIE are given. The results of the calculation of the weights are shown in Tables 3 and 4. The evaluation results of the ecological status of Chongqing’s characteristic small towns in 2016 are shown in Table 5.
Table 3. The weight of ecological status evaluation index system of 8 characteristic small towns in Chongqing Index system Resource consumption (B1) Environmental pollution (B2) Weights 0.3358 0.6642
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X2 X3 X4 X5 X6 X7 X8 X9 X10 Index X1 Weights 0.0734 0.0535 0.1332 0.0757 0.1471 0.1621 0.1143 0.1041 0.0778 0.0588
Table 5. Evaluation of ecological status of 8 characteristic small towns in Chongqing (2016) District
Wanzhou Fuling
Ecological status 9.4257 score
Tongnan Jiangjin Hechuan Changshou Dianjiang Youyang
19.8252 5.6940
21.7083 8.2617
15.9049
14.3245
4.8556
Youyang has the lowest consumption and pollution (4.8556). Due to the vigorous development of the ecological economy, the construction of a standardized agricultural industry standardization base of more than 100 million mu, the formation of a special agricultural product industry chain, and the continuous promotion of tourism development. The successful creation includes a 5 A and two 4 A scenic spots. The scenic sport includes 16 national tourism brands. Jiangjin is the highest (21.7083). The reasons are as follows, with the rapid economic development, the number of small industrial enterprises near Jiangjin City has gradually increased, the amount of industrial waste gas emissions has increased significantly, and the number of urban automobiles has gradually increased, resulting in a large number of automobile exhaust emissions, which has aggravated the air pollution in the ear. In areas such as Fuling, Jiangjin, Changshou and Dianjiang, the intensity of urban construction has been increasing day by day, but the governance of the ecological environment has not yet been able to match the economic and social development. Compared with Youyang, the resources and environment have been consumed too much and the ecological environment has obviously affected these regions. The restrictive role of development is more significant in the process of economic development, we must emphasize the intensive use of land and ecological restoration. For Wanzhou, Hechuan and Tongnan, the ecological environment has not severely restricted the development of these regions. 4.2
Analysis of Residents’ Welfare Output Evaluation
According to Eqs. (1.12)–(1.15), the data of income, health, and education indicators are processed, and then calculated according to Eq. (1.11) using the geometric evaluation values of income index, health index, and education index, The Residents’ Human Development Index (RHDI) of eight characteristic small towns are shown in Table 6. The score range is between 0.837–0.919, with the highest score in Fuling and the lowest in Youyang. The higher the RHDI illustrates the higher the level of residents’ welfare output in the development process of the area, which is also conducive to the development of characteristic small towns.
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Table 6. RHDI values of 8 characteristic small towns in Chongqing in 2016 District Index
Wanzhou Fuling
Tongnan
Jiangjin
Hechuan
Changshou Dianjiang Youyang
Income Index(II) Health Index(HI) Education Index(EI) Residents’ Human Development Index (RHDI) Rank
1.054824 0.914557 0.758702 0.901199
1.112117 0.9250 0.753664 0.918664
1.013385 0.922785 0.774427 0.898018
1.037943 0.931013 0.780992 0.910455
0.995346 0.933228 0.746718 0.885196
1.053251 0.944937 0.707557 0.889676
0.993972 0.926741 0.719389 0.87183
0.910301 0.935759 0.688397 0.837008
3
1
4
2
6
5
7
8
Sources of data: Chongqing Statistical Yearbook 2017; Statistical Communique on National Economic and Social Development; Government Work Report; Data Counties APP; Districts’ Government Network
4.3
Measurement and Evaluation of Performance of Ecological Welfare of Characteristic Small Towns in Chongqing
This paper draws on the existing domestic and foreign research results and fully considers the concept and connotation of the performance of ecological welfare. Based on the 2016 cross-section data, using the DEA-SOLVER PRO 5.0 software, the traditional CCR model, the Super-SBM-Oriented model and the Super-SBM-Non-radial model considering the slack variables were used to measure and compare the ecological welfare performance of 8 characteristic small towns in Chongqing. Using the indicators selected by the REEI and RHDI, an ecological welfare performance evaluation model was established. The results and rankings of the level of ecological welfare performance are shown in Fig. 1 and Table 7.
Ecological Well-being Performance Level 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
Ecological Well-being Performance
Fig. 1. Level of performance of ecological welfare in 8 characteristic small towns in Chongqing (2016)
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Table 7. Results of performance of ecological welfare measurement in 8 characteristic small towns in Chongqing (2016) District
Efficiency value Rank CCR Super-SBM-oriented Super-SBM non-radial Wanzhou 1 1.179738 1.124656 7 Fuling 1 1.225224 1.134707 6 Tongnan 1 1.386236 1.377117 2 Jiangjin 1 1.197235 1.195222 5 Hechuan 1 1.085835 1.085107 8 Changshou 1 1.906556 1.749801 1 Dianjiang 1 1.345736 1.308392 3 Youyang 1 1.311582 1.264485 4 Note: The effectiveness of DEA is essentially a relative validity, the sample changes, and the efficiency of the decision-making unit will change accordingly. The research on the ecological welfare performance level of characteristic small towns in this paper is only conducted in the selected eight regions for internal evaluation, and evaluation with other regions may lead to different results; All DEA models adopted in the paper are investment-oriented. Super-SBM-Oriented represents a super-efficiency DEA model based on radial, and Super-SBM Non-radial represents a nonradiological super-efficiency DEA model considering slack variables.
According to the measurement results under different DEA models, we can see that under the condition of small sample size, based on the non-radiological super-efficient DEA model (Super-SBM model), which taking into account slack variables, solved the problem that traditional DEA models (such as CCR and BCC models) cannot be sorted due to the presence of multiple effective decision units of 1, and the precision is also higher than the radial-based super-efficiency DEA model, which further validates the rationality of the Super-SBM model considering the slack variables. The overall eco-welfare performance level of the 8 characteristic small towns in Chongqing is relatively good, all of which are valid for DEA. The value of the level of ecological welfare performance reflects the efficiency of the welfare level output achieved by the ecological consumption of a regional unit, and also reflects the degree of decoupling between the ecological input and welfare output in different regions in the process of economic and social development, even the higher GDP, ecological welfare performance is not necessarily better. A regional economic and social development level cannot determine the level of its ecological welfare. In this study, Changshou’s ecological welfare performance (1.749801) is higher than other districts, and this evaluation result is consistent with the actual situation. Changshou is positioned as a base of petroleum and natural gas chemical industry, metallurgical building materials, and synthetic material, and it is a regional special logistics node city. Its industrial structure ratio is 8.9:53.5:37.6, more and more attention has been paid to pollution control and ecological protection in recent years, and the development of heavy chemical industry is only an important means of it to
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increase public wealth and strengthen regional strength, it has a high efficiency of converting ecological and environmental input into residents’ welfare. In summary, the performance of ecological welfare of Tongnan (1.377117) ranks second in the evaluation. The county’s eco-environment investment is not large, but its welfare output index is not significantly different from that of Fuling and Jiangjin, which have highest score. Although both Tongnan and Dianjiang belong to the economically underdeveloped regions within the “one-hour economic circle”, the comprehensive development level is relatively low, but the ecological environment input of Dianjiang is much larger than that of Tongnan, so the ecological welfare performance of Dianjiang (1.308392) Slightly lower than Tongnan, which is supported by abundant natural gas resources, vigorously develops the clean energy industry, and exchanges less environmental costs for high-speed economic growth and realizes sustainable development. While Dianjiang has a large investment in the ecological environment, but the level of residents’ welfare output is not high. In the long run, the state of development is not ideal. The primary, secondary and tertiary industries structure of Youyang (1.264485) is 26.0:36.6:37.4. The primary industry accounts for a large proportion of GDP contribution. In recent years, it has also vigorously developed ecological economy, formed a special agricultural product industry chain and 16 national tourism brands. Its resources are consumed less, and the degree of environmental pollution is lower than that of the other seven districts. The current assessment of the ecological environment is the best, but its residents’ welfare level ranked lower, the output of residents’ welfare needs to be improved. Fuling (1.134707) has the highest index of residents’ welfare output, but its ecological and environmental input is also relatively large, which may exceed the carrying capacity of the regional ecosystem. Second, combined with the ecological input of performance of ecological welfare indicators and residents’ welfare output, Jiangjin (1.195222) and Wanzhou (1.124656) also belong to high ecological input and high welfare output level areas. These areas are characterized by high residents’ welfare, but The ecological input exceeds the threshold. In other words, the economic and social development in such regions is based on the cost of high resource consumption and high environmental pollution. Jiangjin, Fuling, and Wanzhou are both well-developed in the secondary and tertiary industries. They have a long history of industrial development and relatively complete infrastructure. However, the secondary industry is the industry with a lot of energy consumption and environmental pollution, which is detrimental to the improvement of the performance of ecological welfare. The results of the calculation of the performance of ecological welfare of the 8 characteristic small towns show that Jiangjin, Fuling and Wanzhou are ranked 5, 6 and 7 respectively, and excessive ecological investment is the main reason for the low level of performance of ecological welfare in these regions. Hechuan (1.085107) ranks behind, belongs to the area where the input level of ecological environment and the residents’ welfare output lever are both low, the ecological environment has no significant limitation on its development.
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5 Conclusion This article uses the cross-sectional data of 2016 and Entropy method to evaluate the status quo of the ecological environment of 8 characteristic small towns in Chongqing through the two input indicators of resource consumption and environmental pollution, a quantitative assessment of residents’ welfare output is also conducted from the three dimensions of income, health, and education. The Super-SBM model was used to comprehensively evaluate the level of ecological welfare performance of each characteristic small town, which verifies the rationality and feasibility of the ecological township welfare performance evaluation index system proposed in this paper, it provides a feasible method to measure and evaluate the ecological welfare performance of a characteristic small towns. Based on the above research findings, this paper proposes the following policy recommendations: (1) Accelerate industrial restructuring and promote industrial upgrading. The performance of ecological welfare is low in Wanzhou, Fuling and Jiangjin., due to excessive ecological investment, excessive pursuit of GDP and neglect of resource that inhibit the growth of ecological welfare performance. We should accelerate the adjustment of industrial structure, vigorously develop the tertiary industry, and promote industrial upgrading. (2) Stick to the ecological red line and use the ecological environment as a hard constraint to plan the socio-economic development goals of the characteristic small town. Taking Changshou as an example, While vigorously developing heavy industry in its region, it also attaches importance to pollution control and ecological protection, and improves the comprehensive utilization of resources to maximize the welfare level. (3) Transform the way of production and life consumption, Taking Tongnan and Fuyang as examples, we should develop advantageous industries with regional characteristics, and combine the conditions of the ecological environment with the needs of the market to promote regional tourism differentiation and specialization. (4) Strengthen urban construction planning and develop transportation. Since Youyang, Tongnan and Dianjiang are far from the main city, the infrastructure construction is lagging behind. Therefore, the government’s investment should focus on the construction of infrastructure. While attaching importance to ecological protection, it should also strengthen urban construction planning, which fundamentally improves its ecological welfare performance. As Chongqing’s characteristic small towns are still in the period of development, some characteristic small towns are in the stage of investment and development. Therefore, it is impossible to conduct fair and reasonable empirical analysis at present. The specific evidence and indicator system verification will continue to be studied with the development of characteristic small towns. In addition, the environmental data of this paper comes from the environmental protection bureaus of various districts in Chongqing, which has certain deviations from the data of the characteristic small towns in the districts and counties. Therefore, it has certain influence on the evaluation of ecological welfare performance. More scholars need to participate in the construction of accurate and reliable survey data sources. This paper has very important guiding significance for the sustainable development of characteristic small towns in the future.
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Problems and Countermeasures of Characteristic Development of Small Towns in Qiannan Prefecture Tong Yuesong1(&) and Wang Chao2 1
Scientific Research Department of Qiannan Polytechnic for Nationalities, Duyun, China [email protected] 2 Wuhan University of Science and Technology, Wuhan, China
Abstract. Although the area of Qiannan has a favorable geographical position and convenient transportation, the agricultural production conditions are poor, the rural labor transfer space is small and the farmers’ income increasing channel is narrow. And it belongs to the poor areas of our country. Speeding up the construction of small towns is the fundamental way to accelerate the adjustment of the distribution of regional productivity, change the way of economic development, and make more farmers obtain employment in the neiborhood. This article explain the problems from the perspectives of the level of urbanization, infrastructure, industrial structure and capital investment existing in the construction of small towns, expounds the restrictive factors of the construction of small towns in Qiannan, meanwhile some relevant countermeasures are put forward to promote the construction of small towns’ characteristics. Keywords: Characteristics of small towns Countermeasures and suggestions
Restrictive factors
1 Introduction The purpose of the construction of small towns is to promote the development of rural non-agricultural industries, activate the rural economy, increase farmers’ income, shrink the gap between urban and rural areas, and promote the local employment of rural labor. Despite its superior geographical location and convenient transportation, the area of Qiannan is a poverty-stricken area in China, with poor agricultural production conditions, small space for rural labor transfer, and narrow channels for increasing farmers’ income. Therefore, the research on the construction of small towns is particularly important. Based on the local reality, this paper makes some preliminary reflections on the significance of speeding up the development of small towns’ characteristic, the existing restrictive factors and the countermeasures in the future.
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 151–158, 2021. https://doi.org/10.1007/978-981-15-3977-0_11
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2 Construction Business Environments in China The first part is to understand the strategic significance of speeding up the construction of small towns fully. According to christakis’s central place theory that is a German economics, the town can be as a regional commercial center and development of processing industry center, almost all cities in different degree, implement the functions of the commodity distribution center and processing center. Since the reform and opening up, the comprehensive economic strength, social production mode and social life style of the area of Qiannan have all undergone qualitative changes. However, the economic structure, especially the industrial structure is still not adapted to the leapfrog development of economy. The secondary industry is underdeveloped, the quantity is small, the science and technology content is low, it still belongs to extensive growth, lacks the fast promotion to the economic development. The proportion of tertiary industry is not in harmony with economic development, which cannot reflect the level and quality of economic development. The construction of infrastructure such as transportation, energy and water conservancy is still the bottleneck restricting economic development. According to the fact that rural and agricultural economic development is the primary driving force of urbanization, industrialization and urbanization always start in areas with good agricultural foundation in the early stage of urbanization of a country and a region. To speed up the construction of small towns, can promote aggregation for township enterprises to small towns, use and promotion of practical technology, vigorously develop scientific technology strategy, that is to say the rural economy maintained steady development of agriculture, developing DouYun screw shell black goat base, deep HuiShui qian mountain villa, set Huang Longshan agriculture comprehensive development project, forage planting base in dushan, dragons and other successful experiment bases. Increase the proportion of secondary industry, the state more than 1,700 species of wild plants, including more than 1,000 medicinal plants. There are 58 species of gastrodia elata, eucommia ulmoides, panax notoginseng, henna, gentian, honeysuckle and prickly pear with important development value. There are more than 400 kinds of wild animals. Belongs to the state of one, two, three kinds of rare animals are the south China tiger, the clouded leopard, monkey, musk, (giant salamander), pangolin, giant salamander and so on more than 30 kinds, including 112 kinds of medicinal vertebrates is raw material base in the development of pharmaceutical industry, support of advanced manufacturing technology, biological medicine, new materials and other high-tech industries, and gradually put headed by “guizhou magic pharmaceutical co., LTD.” dozens of pharmaceutical companies to foster chan head enterprises, actively promote the regional industrialization process, drive the area economic development. Based on domestic interest very much, ethnic customs, natural scenery, developing for a large radio “eye” in China, libo small seven holes as the core technology, with emphasis on the ecological tourism, tourism, promote the third industry better and faster development. Still can use your wide highspeed, shanghai-kunming high-speed, mansion rong highway, airport and luodian DouYun airport construction as an opportunity to promote transportation, energy, water
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conservancy and other infrastructure, forming efficient logistics economic circle of south guizhou.
3 Restrictive Factors in the Construction The second part is about existing restrictive factors in the construction of small towns in the area of Qiannan. (1) The lack of systematic and comprehensive urban planning has severed the link between urban functions and neglected the optimization of the overall urban functions. Embodied in planning focus on considering the hardware construction, lacking attention on the history and culture, natural landscape, lacking regional characteristics and national characteristics and times features, not in coordination with the surrounding ecological environment, affect the overall landscape and living environment of the town. There are many reasons for these problems. First, the idea lags behind current era, only considers the present need, lacks long-term consideration. Second, there is no systematic and feasible study on urban development, and the law and trend of urban development cannot be correctly grasped. (2) The function of the existing small towns is not perfect. Both in information, energy, transportation, water supply and drainage and other infrastructure, or in the culture and education, finance, insurance and other public facilities and social service system for the construction of the lag phenomenon exist in different degrees, It has a direct impact on the overall function of the town. (3) Insufficient industrial support. Rural and agricultural economic development is the driving force of urbanization. Urbanization process depends mainly on agriculture for the amount of commodity grain, to provide the size of the accumulation of capital for industry, and provides industrial raw materials, provide market for urban, rural and agricultural economic development is not only the motive force of the urbanization, but also the foundation of the urbanization. Therefore, in the early stage of urbanization construction of a country and a region, industrialization and urbanization always start in regions with good agricultural foundation. As the experimental zone before the first industry dependence is overweight, but rural and agricultural economy development is relatively backward, so the second and the third industry development is not sufficient, the construction of small towns didn’t take respective advantages, failure to form a more reasonable industrial layout and unique urban economy, restricting the absorption capacity of small towns in rural population. (4) Insufficient capital investment and single financing channels. Small towns construction fund mainly comes from government investment and some central ministries and commissions of rebuilding funds and private investment in the area of Qiannan, less foreign participation in small town construction, so the problem of shortage of funds about the construction of small towns is difficult to be effectively solved.
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4 Analyzing Countermeasures The third part is thoroughly implement Xi Jinping’s socialist ideology with Chinese characteristics in the new era, and actively explores the countermeasures to build small towns with special features in Qiannan. Planning is for the construction of small towns, is to guide the construction of small cities and towns of the basis, using the method of comprehensive balance and regional analysis, in the overall layout and the “five one” “four comprehensive” under the guidance of our strategic layout, closely around trait goals and tasks of a new round of reform and development, closely combined with the actual, accelerate the construction of a state of small towns should adopt the following countermeasures: 4.1
Scientific Planning and Highlighting Local Ethnic Features
(1) Analyzing all kinds of favorable conditions and influencing factors of regional economic development, determine regional advantages, and coordinate the development of its industries and the internal specific industrial sectors. (2) Analyzing the economic characteristics of the planning area, economic structure, including the sector structure and spatial structure, inducing region type, with high-tech zone as guide to strengthen the cooperation between industry and specialization. (3) Our state is a multi-ethnic community, mainly inhabited by buyi, miao, aquatic, yao and maonan minorities. They are good at sing and dancing, Ethnic customs are simple and elegant, life customs have their own characteristics, ethnic culture is colorful, national festivals will be rich, national costumes are colorful and national architecture is exquisite. Therefore it should be carefully analyze, which is that the regional characteristics of regional labor division and area difference the planning of various counties in the region the status, function and development direction and the collaboration relationship between each other. To respect each county area in economy, society and human contact, extensive regional division of labor and cooperation, make each county development balanced. (4) Analyzing of the contradictions in the development of region economy and the mutual relationship, making the production development and all kinds of conditions and resources coordination and balance in spatial configuration, so that the natural conditions and a variety of resources can be full developed and used. (5) The measures should be taken to implement the planning and implementation, to allocate the people, money and material reasonably, to arrange the speed and order of construction, to coordinate production and infrastructure construction, production and capital, technology and labor and production and life, to speed up the pace of construction and to improve the efficiency of investment.
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Improving the Functions of Small Towns and Taking the Road of Sustainable Development
(1) Addressing weak infrastructure as the top priority for development. The key contents of the planning and construction mainly include: migration and relocation, traditional Chinese medicine industry, village roads, farmland water conservancy, drinking water for people and animals, medical and health care and other infrastructure construction projects. A number of key water resources projects and “five small” water conservancy projects have been completed, and the capacity of water resources supply and distribution has been significantly enhanced. (2) In line with the ecology of the industrial construction and the industrialization of ecological construction, the implementation of the traditional Chinese medicine, the grassland ecological animal husbandry and the fruit forest can not only improve the ecological environment, but also increase the income of the farmers, improve the vegetation coverage, improve the trend of rocky desertification in Karst, promote the improvement of ecological environment, and improve the environment for human production. The bearing capacity of life can achieve the best balance between ecological construction and economic benefits. (3) The rural compulsory education, rural health infrastructure, radio and television “coverage” construction of new village, village cultural chamber construction, create civilization, the development of social undertakings such as construction of grass-roots organization and grassroots democracy as to alleviate poverty and promote comprehensive development of important guarantee into planning content. All 12 counties and cities in the state have opened program-controlled telephone, mobile phone and data broadband Internet, and the communication has reached the whole country and major countries in the world. 4.3
Giving Full Play to the Advantages of Regional Resources and Cultivate Special Industries
We will accelerate strategic adjustment of the distribution of pillar industries, optimize the distribution of industries, combine industrial clusters with the development of small towns, and combine the transformation of traditional industries with the cultivation of emerging industries. (1) Actively integrating into the “One Belt And One Road” and Yangtze river economic belt and strengthen regional economic cooperation. It has concluded a number of cooperation agreements with Puerto Rico and elford, Germany. We successfully held the third joint meeting of Guangdong, Guangxi and Guizhou high speed railway economic cooperation, and fourth major international activities such as China Logistics (Tuyun) International Summit. The three year plan for the completion of the Guangzhou Counterpart Assistance cooperation has been worked out, and the Guangdong (Guizhou) Industrial Park has been settled in Tuyun economic development zone. The introduction of state funds in place of 234 billion 114 million yuan, an increase of 36.07% over the same period.
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(2) Developing featured and advantageous agricultural products industry, cultivate efficient animal products industry, and constantly “improve” the economic structure of the secondary and tertiary industries. The three industrial structures are expected to be optimized at 17.4:37.4:45.2. Introducing and cultivating 735 leading agricultural enterprises, agricultural products processing rate up to 80%, non-food 90%, livestock more than 30%. The development and utilization average grade is as high as 25%–30%, and the reserves reach more than 1 billion tons. With the reserves exceeding 10 billion tons, 10 leading enterprises, such as Weng Fu Group, Chuan Heng Chemical Industry and Jin Zhengda, have invested 1 billion 650 million yuan. The main body of e-commerce market is 3700, there are 34 demonstration enterprises, and 17 cross border electric business demonstration enterprises. (3) Inheriting the revolutionary spirit and building a red tourism culture brand. Qiannan is a land of red revolution and great turning point. The Red Army’s long march was six over Qiannan and seven counties and cities through Qiannan. The revolutionary fire was sown along the way. The Weng an monkey field conference made it clear that the major military action must be decided by the Central Political Bureau and laid a solid foundation for the convening of the Zunyi conference. In addition, the whole state is located in the Yunnan Guizhou Plateau, with high altitudes and low latitudes, with 6 national Forest Park and 5 provincial Forest Park, among which Libo Karst world natural heritage site, Maolan World Biosphere Reserve and Zhangjiang 5A scenic area are the most famous, and are famous tourist destinations in the whole country. In 2017, the twelve provincial brigade conference was successfully held. The tourism industry continued to be “blowout”, the infrastructure continued to be perfected, the economic drive continued to increase, and the tourism revenue was 86 billion 235 million yuan, and increased by 43%. (4) Building agricultural science and technology demonstration zone, and build a base for Chinese medicinal materials and agricultural and sideline products. The construction of Chinese medicinal herbs base is based on the different regional environment of the counties and cities, and the traditional Chinese medicinal plants, such as Dendrobium, honeysuckle, Gastrodia elata, Eucommia ulmoides and 37, are established mainly in the “Pharmaceutical Industrial Park” in Long Li County, Gu Jiao Town, which is based on Tuyun Maojian tea, Guiding cloud fog tea, Weng an Qingshan tea, and Luodian upper leaf tea. The brand value of “Tuyun Maojian” has jumped to second in China’s most brand value geographical indication products (tea category), and the tea industry has shown a flourishing and vigorous development trend. (5) Establishing the transportation circle and its service industry. Relying on the state to face the southern coast, and back to the southwest inland hinterland, it is the southwest of the nearest access to the sea advantage. The convenient transportation network is composed of Guizhou, Guangxi, Guizhou and Guizhou railways and 320 and 321 national highway lines. Guixin (Guiyang - Xin Zhai) high grade highway, plant six (Hunan, the Liupanshui - Guizhou Liupanshui) railway compound line has been completed and opened to traffic, the Liboi Airport Airport in Libo county has been completed in 2007, and the Guizhou
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Guangxi railway has also been completed. Now, with the expressway of Guiyang (Guiyang - Guangzhou), the expressway of Guizhou (Guiyang - Guangxi Baise), the expressway of your new (Guiyang - Guangxi Xin Zhai), the expressway of Ma Wu (MA - Chang Ping - Chongqing Wulong), the rapid railway of the GUI Guang (Guiyang - Guangzhou), the fast railway (Guiyang - Changsha) and so on The line has been opened in succession, forming a traffic network of all kinds, forming the “Ray shaped” development pattern of the Tuyun core area for the center point, the food industry, the residents’ service, the transportation and other services, the accommodation industry and the entertainment industry. 4.4
Establishing a Diversified Investment and Financing System
(1) Supporting the development of various economic organizations in small towns and deepening the reform of rural financial system. Drawing on the experience of financial development in Jiangsu and Zhejiang provinces, introducing private capital and actively developing local small and medium private financial institutions, we can not only establish real rural cooperative financial institutions, but also establish private banks, accelerate the transformation of rural credit cooperatives, make full use of the main force of rural finance, and add some postal savings funds. Special reloans are used in the construction of small towns, and the multi-level rural financial organization system is gradually established to provide high quality and comprehensive financial services for the construction of small towns. (2) Developing small-town personal loan business actively. In order to improve the living standard of the residents of small towns, and all financial institutions can take active flexible way of loans, to meet the reasonable requirements of small town residents’ consumption loans, Support a group of farmers to purchase housing and business in towns and towns to promote the transformation of industrialization in small towns and promote the development of local economy. (3) Improving the financial service system and improve the quality of financial services. We should optimize the allocation of human resources, optimize the layout of the agency network, strengthen the construction of the hardware and software of the basic bank, the security system of the network and so on, and focus on the settlement service and establish a smooth channel for the settlement of the settlement.
5 Conclusion The characteristic construction of small towns in Qiannan should absorb the lessons of “heavy benefit, light environmental protection”, deal with the relationship between the good and the environment, grasp the discharge of the enterprise waste water and waste gas, and pay attention to the unity and integrity of the urban (point) and regional (surface) ecological environment, and combine the resources development and the protection of the environment together.
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Acknowledgement. Fund project: Guizhou province sponge system architecture and implementation of the path analysis of city construction (2018qn10).
References 1. Sun, J.,Ye, Y.: Regional Economics Tutorial, no. 4, pp. 193–210. China Renmin University Press, Beijing (2010) 2. Chen, G.: Development mechanism research of small cities and towns under the balance urban and rural cultural. Heilongjiang Sci. (22), 14–15 (2010) 3. Zheng, Z.: The five development concept and green construction of small towns. Seeker (5), 112–116 (2017) 4. Li, B.: The characteristics development path of small towns in HeBei Province. New Ideas (20), 27 (2016) 5. Xu, Y., Wang, Y.: Some thinking of the construction of chinese small towns. Inner Mongolia Financial Research (2), 32–33 (2008)
How Weather Retain Migrants? Evidence from Floating Population Dynamic Monitoring Data Chengen Wu and Xiaonan Zhang(&) Department of Construction Management, Hang Lung Center for Real Estate, Tsinghua, China [email protected]
Abstract. Accompanied with the rapid development of economy and expansion of urbanization, China has experienced a soar growth of floating population. The long-term residence tendency of such migrants is crucial to local citizenization, which is a social process of mobility, residency, and integration. Weather, as a primary natural amenity, has significant influences on urban residents’ physiology and psychology, which may further affect migrants’ longterm residence tendency. Our research applies logit regression model to analyze the effects of weather on migrants’ willingness to stay long-term in cities. With the fixed effects of hometown provinces controlled, the results show that migrants have highest long-term residence tendency for a city whose average annual temperature is 13 °C or 22 °C in terms of average summer temperature. Higher winter temperature, meanwhile, is preferred. As for other weather attributes, cities with strong wind are not welcome and annual rainfall in median level are most favorable for migrants. Besides, through heterogeneous test, we document that the results differ in terms of age cohorts, gender, marital status, as well as wealth status. Our research testifies the existence of environmental poverty trap and suggest urban government to pay attention. Keywords: Long-term residence tendency amenity
Migrants Weather Natural
1 Introduction Accompanied with the rapid development of economy and expansion of urbanization, China has experienced a soar growth of floating population. At the end of 2016, the floating population in China reached 245 million3, which accounted for 18% of total population. Given such huge number of migrants, their long-term residence tendency in cities is no longer a personal question. It is more of a special problem in the process of social development in China. The unique household registration policy in China makes it difficult for migrants to access public services equally as local residents do in the city. Such public services include but not limited to education of children, medical service and qualification of purchasing houses and cars. In this condition, migrants’ willingness to stay long-term in the city reflects how well they integrate into the new citizenship, and will have significant effects on local citizenization, which is a social process of © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 159–171, 2021. https://doi.org/10.1007/978-981-15-3977-0_12
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mobility, residency, and integration. Meanwhile, migrants’ long-term residence tendency will also affect the decision- making of relevant departments, which may promote the rational distribution and the strengthening of public service and social management of cities [1]. Researchers have long been working on the factors that will affect migrants’ willingness to live in cities and those findings mainly come from three aspects. First of all, individual and household demographics, such as age, gender, education, and number of children, are basic elements that will affect the migrants’ decision [2, 3]. Besides, economic characteristics of cities and households are also crucial, which include GDP level, structure of GDP, the household’s income, housing expenses and so on [4, 5]. Finally, the social welfare plays an important role on retaining the migrants. Migrants always concern about their children’s access to education and their social security. Therefore, the household registration policy will hinder their residence willingness [6, 7]. However, limited researches pay attention to natural amenities. Weather, as a primary natural amenity, has significant influences on urban residents’ physiology and psychology. Residents, to some extent, are sensitive to the weather in a way, which they may not be aware of. Temperature, humidity, visibility or even air pressure, residents exposing to, will change their social behavior, which may further affect migrants’ long-term residence tendency. Extremely changing weather may cause disease and increase death rate [8]. Some researchers also indicate that residents migrate due to weather change [9]. Under such background, weather attributes should be put under consideration when analyzing the factors of migrants’ willingness to stay in cities. Our research aims to find out the relationship between weather and the long-term residence tendency of floating population. To realize this purpose, we access migrants’ residence tendency from floating population dynamic monitoring survey conducted by Health and Family Planning Commission in 2014. Combined with weather data from Meteomanz.com, our research adopts logit regression model with the fixed effects of hometown provinces controlled. Moreover, we try to investigate the heterogeneous responses to weather of different population groups, in terms of age cohorts, gender, marital status and wealth status. The rest of this paper is organized as follows. Section 2 reviews the related literature. Section 3 introduces data and empirical model. Section 4 shows the empirical evidence. Section 5 draws the conclusion and discussion.
2 Literature Review Based on our research question, we review related literature mainly in two aspects, long-term residence tendency and natural amenities. In the first subsection, we listed how researchers examined the factors that will affect migrants’ willingness to stay, which include personal and family demographics, flow characteristics and social security. As there is almost no research that take natural amenities into consideration when analyzing the residence tendency, we further review how weather attributes are examined to influence residents’ physiological and psychological reaction. Scholars
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also found weather matters when migrants making location choice, which provide foundation for our research. 2.1
Long-Term Residence Tendency
The emergence of large number of migrants is a special social phenomenon during the urbanization process of China. The long-term residence tendency of migrants is thus also a specific problem with China characteristics. Migrants’ willingness to stay longterm in the city which they flow into are always measured through surveys. The floating population dynamic monitoring survey conducted by National Health and Family Planning Commission since 2009 are widely used in recent years. Our research is also conducted based on this survey in 2014. More details of the survey are discussed in the next section. Yang and Wei (2017) [1] built a logit regression model to examine the influencing mechanisms of migrants’ long-term residence tendency. The results show that personal demographics, including gender, age, marital status, educational level, income and housing expense, flow characteristics, such as how long the migrants have been in the city all have significant effects on migrants’ willingness to stay. Such conclusions are also confirmed by other researchers [2, 10–13]. Take educational level for example, those highly educated are more likely to find suitable jobs and stay long-term in the city. While the longer migrants have been in the city, the stronger their social network are, and they can improve their human capital to better compete with others, which contribute to their residence tendency. Except for demographics and floating period, the family migration characteristics also matters [14]. Floating population who migrated with their children would have higher residence intention. Besides, migrants who have good social security, such as unemployment insurance and endowment insurance, have stronger intention to stay. Specially, the retirement pension, endowment insurance and medical insurance are crucial for elder migrants [15]. 2.2
Weather Attributes
Natural amenities, among which weather is very typical, influences people’s lives in many ways, both physiologically and psychologically. Moore (1998) [16] found that warm temperature would reduce deaths and can reduce the medical cost, and thus workers tend to work in a warmer place. In terms of subjective well-being, a sharp decline in hedonic state was detected when residents expose at extremely high temperature [17]. The urban space equilibrium theory developed by Rosen (1979) and Roback (1982) [18, 19] indicates that population flow between cities is influenced by income, rental cost and amenities. The effect of weather, which is a major natural amenity, is paid close attention by many researchers. Englin (1996) [20] estimated the amenity value of rainfall using hedonic valuation technique. The results showed that homebuyers are willing to pay more for housed located in a less rainy place. Another research about rainfall suggest that people from the drier regions are more likely than those from wetter areas to engage in both temporary and permanent migrations to other rural areas [21].
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Besides, other weather attributes are also examined. In particular, temperature has a nonlinear impact on the migration. If the temperature were above 25 °C, further rises of temperature will lead to population outflow [22]. Studies also indicated there are heterogeneous effects of weather on different population, especially in terms of income. For example, population with higher income level is more sensitive than the poorer group is, because poverty limits their mobility [23]. Overall, while the effects of weather on migration have been investigated well, studies on migrants’ long-term residence tendency has overlooked this factor. Our paper tries to fill this gap and tests how weather in the inflow city will influence migrants’ willingness to stay. By doing so, we can enrich the literature on weather and migration.
3 Data and Empirical Model 3.1
Data Sources
Our data source of migrants’ long-term residence tendency is dynamic monitoring survey conducted by National Health and Family Planning Commission in 2014. This nationwide survey starts at 2009 and is conducted annually. It aims at understanding the living condition of floating population, which can provide data support for relevant policy-making. The survey takes 31 provinces (autonomous regions, municipalities directly under the central government) and the Xinjiang production and Construction Corps as investigation scope. It adopts a stratified, multi-stage and scale proportional PPS sampling method, and focuses on those whose living place differs from domicile place, with age between 15–59 years old and has been living in the city for more than one month. In 2014, this survey is conducted in May and the total sample number is 206,000. The data includes the information about migrants’ basic demographics, employment, income and expenditure, social integration and so on. This dataset has the advantage of large sample size, good representativeness and strong authority. Besides, our research collects weather data from Meteomanz.com which provides daily weather of global monitoring stations, including temperature, wind speed, precipitation, cloud coverage ratio. We match the stations with cities according to their accurate geographical information in ArcGIS and further calculate annual weather attributes in city level. Finally, urban characteristics from Urban Statistical Yearbook 2015 are also included. After eliminating missing data, the final sample amount is 176,948. 3.2
Variables Settings
In the dynamic monitoring survey, migrants are asked “Are you willing to settle down in this city for five years or more?”, the answer of which is regarded as our dependent variable, the long-term residence tendency. The independent variables can be divided into three categories: personal demographics, urban characteristics and weather attributes. We select the most influential factors according to literature review. The variable definitions and statistical descriptions are listed as Table 1.
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Table 1. Variable definitions and summary statistics Variables WILL
Definition
Long-term residence tendency (unwilling & under consideration = 0; willing = 1) Weather attributes TEMP Annual average temperature (°C) TEMP_SUM Average temperature in summer (°C) TEMP_WIN Average temperature in winter(°C) TEMP_DIF Standard deviation of daily temperature within a year (°C) WIND Wind speed (km/hour) RAIN Annual rainfall (m) Personal demographics GEN Gender (male = 0; female = 1) AGE Age MARR Marital status (single = 0; married = 1) EDU Educational level (uneducated = 1; elementary school = 2; junior high = 3; senior high = 4; college = 5; university = 6; graduate = 7) FLOWDUR Number of years that migrants have been in the city NETINCOME Net monthly income (10,000 RMB) Urban characteristics POP Population density (thousand people per km2) GDP GDP per person (10,000 RMB)
Obs.
Mean
176,948
0.56
Std. Dev. 0.50
Min
Max
0
1
176,948
15.37
4.80
−0.32
24.77
176,948
25.30
2.84
10.54
29.41
176,948
3.18
7.98
−23.48
17.98
176,948
9.17
2.50
3.49
17.12
176,948 176,948
8.15 1.02
2.40 0.59
3.29 0
21.32 2.62
176,948
0.42
0.49
0
1
176,948 176,948
33.92 0.76
9.27 0.42
15 0
60 1
176,948
3.40
1.01
1
7
176,948
4.48
4.60
0
50
176,948
0.30
0.72
−12.80
199.20
176,948
0.62
0.48
0.01
2.65
176,948
7.20
3.29
1.02
20.02
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According to the summary statistics, approximate 56% of total migrants have longterm residence tendency, while 44% are still considering or unwilling to stay. 3.3
Logit Model
To test the effects of weather on migrants’ long-term residence tendency empirically, we adopt the logit model as our main method. The model is set as follows. WILLij1;j2 ¼ a0 þ a1 Wj1 þ a2 Yj1 þ a3 Xi þ cj2 þ eij1;j2
ð1Þ
Where WILLij1;j2 is the long-term residence tendency of migrant i living in city j1 whose domicile place is city j2 ; the vector of covariates, Wj1 refers to the weather attributes of city j1 , including average annual temperature, standard deviation of daily temperature through the whole year, wind strength, and number of rainy days and cloudy days; Wj1 is the urban characteristics, consisting of population density, GDP per capita, public books per capita and primary school teacher-student ratio; Xi is personal demographic variables, referring to gender, age, marital status, education, household’s net monthly income and how long the migrant has been in city j1 ; cj2 is the fixed effects of migrants’ hometown city, j2 , and eij1;j2 is the error term. The coefficient of interest is a1, which indicates the relationship between weather attributes and migrants’ long-term residence tendency.
4 Empirical Evidence In the empirical section, we first make correlation analysis between dependent variable and migrants’ personal demographics and urban characteristics, from which we come to preliminary conclusions. Logit regressions results are then listed and provide more exact evidence, especially for the effects of weather attributes on residence tendency. Finally, we make heterogeneous tests of different population groups on their response to weather. 4.1
Correlation Analysis
Here we first illustrate the heterogeneity of floating population’s long-term residence tendency in terms of personal demographics and urban characteristics. As shown in Table 2, 56% of males are willing to stay long-term, while the proportion of females is 57.1%. Compared to males, females prefer to stay, which is consistent with the fact that females may stay through marriage. As for different age cohorts, those above 40 are most likely to stay, 61.4% of which have long-term residence tendency. Younger migrants, which are below 25 years old, however, have the lowest tendency, only 40.6%. This may be due to that the younger is still trying to find the city suitable for them and has higher liquidity with less family responsibilities. In terms of marital status, married migrants have much higher residence tendency than single ones, which can also be explained by family responsibilities.
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Table 2. Residence intention Variables GEN
Male Female AGE 25 25–40 >40 MARR Single Married EDU Uneducated Elementary School Junior High Senior High College University Graduate School NETINCOME 0.12 0.12–0.35 >0.35 FLOWDUR 1 1–6 >6 POP 0.25 0.25–0.80 >0.80 GDP 5 5–10 >10
Willing 56.00% 57.10% 40.60% 59.90% 61.40% 39.10% 61.80% 58.90% 58.60% 53.80% 56.10% 63.20% 69.30% 77.10% 54.10% 54.30% 63.50% 39.60% 57.60% 76.40% 60.70% 53.20% 58.70% 54.30% 56.70% 59.20%
Unwilling 44.00% 42.90% 59.40% 40.10% 38.60% 60.90% 38.20% 41.10% 41.40% 46.20% 43.90% 36.80% 30.70% 22.90% 45.90% 45.70% 36.50% 60.40% 42.40% 23.60% 39.30% 46.80% 41.30% 45.70% 43.30% 40.80%
P-value 0.000 0.000
0.000 0.000
0.000
0.000
0.000
0.000
There are significant differences between migrants with different educational level. Those whose highest educational attainment is senior high or below has the lowest residence tendency, which is no more than 59%. For those who finished colleges, the willingness reaches 63.2%, and this number further increase to 69.3% for those with bachelor’s degree. While 77.1% of migrants with master’s degree or Ph. D have longterm residence tendency in the city. It indicates that the improvement of educational level will enhance migrants’ willingness to stay and the college degree is a cut-off point. The reason may be that higher educated migrants have better jobs and enjoy preferential policies in the city which can retain them to a large extent. The increase of net monthly income is also positively correlated with migrants’ wiliness to stay, which is consistent with common sense. The number of years that the migrants have been in the city has similar trend, which indicates that the longer the migrants stay, the better they integrate with local society and the higher their residence tendency is.
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As for urban characteristics, both small cities and large cities are more likely to attract migrants in comparison with cities with middle level population density, which echoes with the finding of Sun et al. (2014) [24]. The economic development status of cities, which is indicated by GDP per capita will increase migrants’ residence tendency. This can be explained as most migrants are seeking better job opportunities and this is easier in a highly developed city. Considering it is difficult for migrants to access public services provided by local government, we exclude such variables. 4.2
Logit Regression Analysis
We report the central estimates of this paper in Table 3. Each column reports the results of one regression using the logit model shown in Eq. 1. In the logit model, we add three categories of independent variables as mentioned in the previous section: weather attributes, personal demographics, and urban characteristics. Except for annual average temperature, we also regress the average temperature in summer and winter separately to better understand how people react to temperature during different seasons. The annual average temperature and average temperature in summer are added in both linear term and quadratic term, while we only include the linear term of that in winter. This setting is based on our expectation and the results do confirm this. Table 3 contains the following major findings. First, there is a reversed U-shape relationship between the annual average temperature and migrants’ long-term residence tendency. After calculation, the peak-value of residence tendency is realized when the annual average temperature is 13 °C. This temperature ranks lower than about 70% cities. The average temperature in summer has a similar trend, the most popular value of which is 22 °C, which ranks even lower. This indicates that extreme temperature, either too hot or too cold, will decrease the attractiveness of the city for migrants and lower their residence tendency. While the average temperature in winter is positively related to migrants’ willingness to stay, which means people prefer cities with warmer winter. In the first column, we also include the standard deviation of daily temperature within the whole year, which can be regarded as the intensity of temperature changes through the year. The coefficient is negatively significant, showing that stable climate is preferred. These results about temperature are consistent with common sense. As for other weather attributes, cities with strong wind are not welcome. Different from previous literature, we find that the precipitation also has a reversed U- shape relationship with residence tendency. The most favorable rainfall is 0.925 m all over the year, which is close to the median value. This indicates that residents enjoy suitable rainfall, and either too try or too wet will hinder migrants from staying long-term. Next, we report the results of personal demographics and urban characteristics, which are mostly in accordance with the results of correlation analysis in the last subsection. To specify, migrants who are male, aged around 40 years old, married, higher educated, with higher net income and have been in the city for longer time are more likely to have long-term residence tendency. Cities with higher GDP per capita are more attractive for migrants. As for population density, cities with around 1,250 persons per squared kilometer are most unattractive, while higher density or lower density will both increase the residence tendency.
How Weather Retain Migrants? Table 3. Main logit regression result Dependent variable Weather attributes TEMP TEMP_2 TEMP_DIF
(1) WILL
(2) WILL
0.0393*** (5.19) −0.00157*** (−6.39) −0.0393*** (−8.04)
TEMP_SUM
0.207*** (8.89) −0.00469*** (−9.26)
TEMP_2_SUM TEMP_WIN WIND RAIN RAIN_SUQARED Personal characteristics GEN AGE AGE_2 MARR EDU NETINCOME FLOWDUR Urban demographics GDP
(3) WILL
−0.0224*** (−8.43) 0.444*** (9.03) −0.240*** (−13.29)
−0.0238*** (−8.99) 0.655*** (15.15) −0.291*** (−17.14)
0.00982*** (6.92) −0.0197*** (−7.77) 0.494*** (10.04) −0.273*** (−15.41)
0.0630*** (6.03) 0.0446*** (10.24) −0.000561*** (−9.55) 0.716*** (46.15) 0.241*** (42.63) 0.219*** (14.82) 0.133*** (92.19)
0.0630*** (6.04) 0.0446*** (10.25) −0.000563*** (−9.58) 0.719*** (46.32) 0.243*** (43.00) 0.222*** (14.95) 0.133*** (92.04)
0.0627*** (6.00) 0.0443*** (10.19) −0.000558*** (−9.50) 0.716*** (46.18) 0.241*** (42.71) 0.221*** (14.91) 0.133*** (92.22)
0.0175*** (9.13) −0.146*** (−3.52) 0.0649*** (3.90) YES −5.577*** (−16.00) 176,948 0.096
0.0201*** (10.45) −0.329*** (−8.29) 0.130*** (8.11) YES −3.228*** (−14.27) 176,948 0.095
0.0205*** (10.68) POP −0.307*** (−7.27) POP_2 0.123*** (7.31) Hometown provinces fixed effects YES Constant −3.010*** (−12.28) N 176,948 pseudo R2 0.096
Notes: Each column reports the result from one regression with controls for hometown provinces fixed effects. The unit of observation is each migrant. The main entries in columns 1, 2 and 3 report the coefficient estimate from fitting model 1 in the text by logit model, with z-value reported in brackets. * p < 0.10, ** p < 0.05, *** p < 0.01.
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4.3
Heterogeneous Effects
The results thus far have demonstrated the significant effect of weather on migrants’ long-term residence tendency. In this subsection, we examine whether there is any evidence of heterogeneous effect between different population groups. We run the regression defined by Eq. 1 using different sub-samples and the coefficients of interest are shown in Table 4.
Table 4. Heterogeneous test results Male
Female
Under 25 year-old
25–40 year-old
Over 40 year-old
MP
0.0364*** (3.70)
0.0419*** (3.53)
0.0284 (1.58)
0.0367*** (3.51)
0.0497*** (3.55)
TEMP_2
−0.00143*** (−4.47)
−0.00174*** (−4.53)
−0.00153*** (−2.60)
−0.00153*** (−4.54)
−0.00159*** (−3.44)
TEMP_DIF
−0.0332*** (−5.26)
−0.0493*** (−6.33)
−0.0453*** (−4.01)
−0.0425*** (−6.29)
−0.0279*** (−3.04)
RAIN
0.471*** (7.34)
0.390*** (5.09)
0.412*** (3.58)
0.480*** (7.12)
0.429*** (4.59)
RAIN_SUQARED
−0.239*** (−10.05)
−0.235*** (−8.43)
−0.272*** (−6.33)
−0.243*** (−9.91)
−0.230*** (−6.56)
WIND
−0.0226*** (−6.54)
−0.0228*** (−5.45)
−0.0413*** (−6.59)
−0.0179*** (−4.93)
−0.0190*** (−3.75)
Personal characteristics
YES
YES
YES
YES
YES
Urban demographics
YES
YES
YES
YES
YES
Hometown provinces fixed effects
YES
YES
YES
YES
YES
Constant
−3.071*** (−10.08)
−2.697*** (−6.38)
−2.735*** (−3.32)
−2.548*** (−8.34)
−1.269*** (−2.85)
N
102,728
74,213
35,412
95,548
45,986
pseudo R2
0.098
0.093
0.087
0.080
0.079
Single
Married
Net income less than 0.12
Net income 0.12–0.35
Net income over 0.35
TEMP
0.0184 (1.15)
0.0465*** (5.41)
0.0391*** (2.78)
0.0345*** (3.13)
0.0930*** (5.68)
TEMP_2
−0.000747 (−1.43)
−0.00183*** (−6.55)
−0.00131*** (−2.83)
−0.00150*** (−4.22)
−0.00329*** (−6.17)
TEMP_DIF
−0.0553*** (−5.40)
−0.0350*** (−6.28)
0.000464 (0.05)
−0.0532*** (−7.66)
−0.0558*** (−5.39)
RAIN
0.247** (2.35)
0.496*** (8.88)
0.0391*** (2.78)
0.0345*** (3.13)
0.0930*** (5.68)
RAIN_SUQARED
−0.234*** (−6.01)
−0.242*** (−11.82)
−0.00131*** (−2.83)
−0.00150*** (−4.22)
−0.00329*** (−6.17)
WIND
−0.0226*** (−6.54)
−0.0228*** (−5.45)
−0.0184*** (−3.57)
−0.0291*** (−7.75)
−0.0128** (−2.26)
Personal demographics
YES
YES
YES
YES
YES
Urban characteristics
YES
YES
YES
YES
YES
Hometown provinces fixed effects
YES
YES
YES
YES
YES
Constant
−1.324*** (−3.09)
−3.253*** (−10.53)
−2.695*** (−4.82)
−2.914*** (−8.20)
−3.140*** (−7.01)
N
41,759
135,169
46,437
87,609
42,898
pseudo R2
0.078
0.070
0.110
0.092
0.079
Notes: Each column reports the result from one regression with controls for personal demographics, urban characteristics, as well as, hometown provinces fixed effects. The dependent variable for each regression is WILL. The unit of observation is each migrant. The sample for all regressions is listed in the cell header. The main entries in columns 1, 2 and 3 report the coefficient estimate from fitting model 1 in the text by logit model, with z-value reported in brackets. * p < 0.10, ** p < 0.05, *** p < 0.01.
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From the table we can see that most findings for the whole floating population can also be applied to different sub-groups. To make a comparison, females respond more strongly to extreme temperature than males do, while the elderly are more sensitive to temperature than other age cohorts are. This is probably because female and senior people are vulnerable to some degree and therefore care more about the weather. The migrants who are single care less about weather and even show no significant response to temperature, which can be explained that the married have more family consideration than the single do and need to choose a long-term residence city with better weather. If we treat weather as a normal good, we would expect that sensitivity to it would increase with income. To test this hypothesis, we divide the migrants into three groups by 1st and 3rd quartiles of household net monthly income. Results confirm that the poor are less responsive to weather attributes than are the rich are. The conclusions about heterogeneity in terms of gender, age and income are consistent with that of Zhang et al. (2017) [25], who investigate how different groups react to air pollution.
5 Conclusion and Discussion The large number of floating population in China makes their long-term residence tendency in cities a special problem in the process of social development. It reflects how well they integrate into the new citizenship, and will have significant effects on local citizenization, which is a social process of mobility, residency, and integration. Researchers pay a lot of attention to the factors that will affect migrants’ willingness to stay. In this research, we mainly focus on weather attributes, which is a primary natural amenity, and take advantage of dynamic monitoring survey data collected by National Health and Family Planning Commission in 2014 and weather data from Meteomanz.com. Through both correlation analysis and logit model regressions, we get conclusions as follows. First, the relationship between the annual average temperature and migrants’ longterm residence tendency is reversed U-shape and the peak-value is realized when the annual average temperature is 13 °C. Similarly, the most popular average temperature in summer is 22 °C. While the increase of average temperature in winter will promote migrants’ willingness to stay. Besides, stable climate which is indicated by smooth temperature changes within the year is preferred. Second, different floating groups differ in terms of response to weather attributes. Females are more sensitive to temperature and so are the elder. The migrants who are single care less about weather and even show no significant response to temperature. As for income level, sensitivity to weather increases with household’s net monthly income. The conclusions about heterogeneity in terms of gender, age and income are consistent with findings of other researches about air pollution. Lastly, personal demographics and urban characteristics also have significant effects. Migrants who are male, aged around 40 years old, married, higher educated, with higher net income and have been in the city for longer time are more likely to have long-term residence tendency. Cities with higher GDP per capita are more attractive for migrants. As for urban population density, there is a U-shape relationship, which
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indicates that people would like to stay in either highly dense or sparse cities. These conclusions are consistent to our common sense. Based on the findings above, the environmental poverty trap is testified. On one hand, migrants with lower income are less responsive to weather attributes, which can be explained as they cannot bear the migration cost and have to stay [26]. On the other hand, literature illustrated that bad weather, such as extremely hot will decrease productivity [27, 28], which means those poorer who has to stay in places with such weather will earn less compared to others. This vicious circle is the basic idea of environmental poverty trap. Given the fact of global warming, the weather is going apart from suitable condition. In our research, about 70% Chinese cities have annual average temperature above the most favorable level of migrants. Thus, we should make more effort in energy conservation and emission reduction to mitigate the process of global warming, to which optimizing energy structure and developing clean energy can help. Besides, government should improve the ability of undeveloped areas to adapt to extreme weather, so that poorer residents can be protected from its negative effects. For example, urban government in such places should pay attention to well- designed infrastructure and preferential financing policy.
References 1. Yang, X., Wei, H.Y.: New features and influencing mechanisms of migrant long-term residence tendency. Popul. Res. 41(5), 63–73 (2017). (in Chinese) 2. Li, Q., Long, W.J.: An analysis of the influencing factors of migrant workers, retention and their return. China Rural Econ. (2), 46–54 + 66 (2009). (in Chinese) 3. Mei, J.M., Yuan, Y.J.: Empirical analysis on citizenization willingness and influencing factors of migrant workers: based on the survey data of 3375 migrant workers in 31 provinces, municipalities and autonomous regions of China. J. Jiangxi Univ. Finance Econ. (1), 68–77 (2016). (in Chinese) 4. Huang, Z.N.: Empirical study on migrant workers’ housing source and level. Pearl River Econ. 193(9), 59–73 (2007). (in Chinese) 5. Zheng, S.Q., Liao, J.P., Ren, R.R., Cao, Y.: Housing policy for migrant workers and economic growth. Econ. Res. (2), 73–86 (2011). (in Chinese) 6. Zhang, P., Hao, Y.B., Chen, W.M.: Happiness, social integration and migration decision. Econ. Rev. (1), 58–69 (2014). (in Chinese) 7. Sun, X.T., Li, X., Qi, D.M.: The impact of employment and social integration on urban settlement intention of migrant workers: regression analysis based on overall, occupation and income. Agric. Technol. Econ. (11), 44–55 (2016). (in Chinese) 8. Lu, H.Y., Wen, J., Xu, W.L.: Effect of climate change on Chinese population flow. Hubei Soc. Sci. (2), 77–84 (2017). (in Chinese) 9. Li, T.T., Gap, Y.L., Guo, Y.F., Liu, F.: Climate change: effects of temperature on population mortality in Beijing. In: 2010 China Annual Conference on Science, Technology of Atmospheric Environment and Atmospheric Environment Branch of the Chinese Academy of Environmental Sciences (2010). (in Chinese) 10. Li, X.Y., Huang, Y.X., Xu, X.C.: Influencing factors of migrant workers’ “migratory birds” life style: based on the migrant workers investigation in nine main urban zones in Chongqing, China population. Resour. Environ. (9), 70–80 (2015). (in Chinese)
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11. Huang, Q.: An analysis on the factors affecting the rural labor migrations’ desire to settle in cities: an empirical analysis based on the survey of five cities. J. Shan Xi Finances Econ. Univ. (4), 21–27 (2008). (in Chinese) 12. Meng, Z.M., Wu, R.J.: A research on settlement intentions of floating population. Popul. Dev. (3), 11–18 (2011). (in Chinese) 13. Wang, Y.J.: Settlement intention of rural migrants in Chinese cities: findings from a twelvecity migrant survey. Popul. Res. (4), 19–32 (2013). (in Chinese) 14. Yang, Q., Li, P.J.: Family development ability and urban residency tendency of the new generation migrant workers: based on the analysis of 2014 national survey data of the dynamic monitoring of the migrant population. China Youth Study (10), 50–56 (2017). (in Chinese) 15. Hou, J.M., Li, X.G.: The analysis of the status of China’s floating elderly population and its influencing factors. Popul. J. 39(6), 62–70 (2017). (in Chinese) 16. Moore, T.G.: Health and amenity effects of global warming. Econ. Inq. 36(3), 471–488 (1998) 17. Baylis, P.: Temperature and temperament: evidence from a billion tweets. Energy institute working paper (2015) 18. Rosen, S.: Wage-based indexes of the urban quality of life. Curr. Issues Urban Econ. 74–104 19. Roback, J.: Wages, rents, and the quality of life. J. Polit. Econ. 90(6), 1257–1278 (1982) 20. Englin, J.: Estimating the amenity value of rainfall. Ann. Reg. Sci. 30(3), 273–283 (1996) 21. Henry, S., Schoumaker, B., Beauchemin, C.: The impact of rainfall on the first outmigration: a multi-level event-history analysis in Burkina Faso. Popul. Environ. 25(5), 423– 460 (2004) 22. Pratikshya, B.M., Michael, O., Hsiang, S.M.: Nonlinear permanent migration response to climatic variations but minimal response to disasters. Proc. Natl. Acad. Sci. U.S.A. 111(27), 9780 (2014) 23. Lu, H.Y., Wen, J., Xu, W.L.: Effect of climate change on chinese population flow. Hubei Soc. Sci. (2), 77–84 (2017). (in Chinese) 24. Sun, S.B., Huang, W., Hong, J.J., Wang, C.H.: City size, happiness and spatial optimization of migration. Econ. Res. (1), 97–111 (2014). (in Chinese) 25. Zhang, X., Zhang, X., Chen, X.: Happiness in the air: how does a dirty sky affect mental health and subjective well-being? J. Environ. Econ. Manag. (85), 81–94 (2017) 26. Qi, Y., Lu, H.Y.: ‘environmental poverty trap’ mechanism and China environmental Knee, China population. Resour. Environ. (10), 71–78 (2015). (in Chinese) 27. Cattaneo, C., Peri, G.: The migration response to increasing temperatures. J. Dev. Econ. 122, 127–146 (2016) 28. Cline, W.R.: global warming and agriculture: impact estimates by country. Peterson Institute (2007)
Measurement of New Urbanization Construction Level and Diagnosis of Obstacle Factors——A Case of Urban Cluster in the Central Plains Han Jing1,2, Yang Chun1, Ke Nan1, and Lu Xin-hai1(&) 1
College of Public Administration, Central China Normal University, Wuhan 430079, Hubei, China [email protected] 2 Research Center for Land Resource and Real Estate, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
Abstract. Taking zhongyuan urban cluster as an example, based on the connotation of new urbanization, an evaluation index system was constructed. To evaluate the construction level of the new urbanization of Urban Cluster in the Central Plains and diagnose its obstacles factors using the methods of principal component analysis, GIS spatial analysis and obstacle factors analysis. The results show that: from 2006 to 2015, the new urbanization in the 9 cities has steadily increased; the gap between the cities is obvious, Zhengzhou City and Jiyuan City are in high-level clubs, while Xuchang City, Luoyang City, and Luohe City are all in the middle-level clubs. Jiaozuo City, Kaifeng City and Xinxiang City are at low-level clubs. Land urbanization is the biggest obstacle to the construction of new urbanization within 9 cities; however, the 9 cities have different obstacle indicators, in the direction of improving the level of new urbanization construction, Zhengzhou City needs to improve the sustainability of urban land as its main goal, while the other 8 cities need to increase the level of land output as the main goal. Keywords: New urbanization
Construction level Obstacle degree
1 Question Raised As China’s urbanization rate has increased from 17.92% in 1978 to 57.35% in 2016, and in 2011, the rate of urbanization has surpassed 50%. According to the development law of “S” curve of urbanization in the developed countries, the current level of urbanization in China is at a rapid development stage of between 30% to 70%. In the process of rapid urbanization in China, while the urban construction has achieved remarkable achievements, the extensive development of traditional urbanization has triggered a series of problems such as blind expansion of urban space, unbalanced urban and rural development, exhaustion of urban resources, and environmental pollution [1–4]. As China’s urbanization enters a critical period of rapid development, new urbanization based on people-oriented, fair sharing, environmental friendliness, © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 172–184, 2021. https://doi.org/10.1007/978-981-15-3977-0_13
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economic efficiency, urban and rural planning, and ecological livability has emerged. Compared to the extensive development of traditional urbanization, new urbanization assumes the responsibility of the historical task of solving new problems, accomplishing new tasks, and achieving new goals [5–7]. This requires China to take the road of urbanization based on people-oriented, social harmony and a happy life [8–10]. With the continuous development of urbanization in China, evaluating the construction level of new urbanization has become a research hotspot in the domestic academia. The research on the evaluation of new urbanization construction level mainly focuses on several aspects: (1) On the new urbanization theory research, including the concept of new urbanization [13, 14], the connotation [15, 16], and the development path [17–19] and other definition of related concepts and connotations. (2) In the construction of a new urbanization evaluation index system, both the single index evaluation method and the composite index evaluation method have been adopted [20]. (3) In the method of new urbanization evaluation, there are many research methods such as analytic hierarchy process, spatial autocorrelation analysis and entropy method [21–24]. (4) At the research scale of the new urbanization construction level, it mainly focuses on multi-scale research units such as national, provincial and prefecture-level cities [25–27], however as the research scale urban agglomeration is fewer, and most studies did not diagnose the obstacles. Based on this, this paper intends to use the principal component analysis and GIS spatial analysis method to demonstrate the changing characteristics of the new urbanization construction of the 9 cities of the Zhongyuan urban agglomeration from two dimensions of time and space, and through the diagnosis of obstacles to systematically analyze the new urbanization construction problem in the 9 cities. in order to provide reference experience for the scientific advancement of the new urbanization of urban cluster in the central plains.
2 Study Area and Data 2.1
Overview of the Study Area
The urban cluster in the central plains is located in the joint area between the coastal open areas and the central and western regions. It is located in the middle zone where China’s economy develops from east to west, and its geographic location is superior. As of the end of 2016, the urban cluster in the central plains has a total area of 287,000 square kilometers, a total population of 162 million people, and a regional GDP of 604.437 billion yuan. Its GDP is followed by the Yangtze River Delta, Pearl River Delta and Beijing-Tianjin-Hebei urban agglomerations, ranking fourth in the country. With Zhengzhou as the center and Luoyang as the sub-center, the seven regional central cities of Kaifeng, Pingdingshan, Xinxiang, Jiaozuo, Xuchang, Luohe and Jiyuan constitute the core of the Zhongyuan City Cluster, which will be the core strengths of the revitalization of the central region.
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Index System Construction
This article draws on the existing research results of the academic community [28–30] and bases itself on the particularities of the new urbanization construction of urban agglomerations, in accordance with the principles of scientificity, systematism and hierarchy, from five dimensions of population urbanization, economy urbanization, land urbanization, life urbanization and management urbanization to constitute a new urbanization evaluation index system. Among them, population urbanization is the core content of new urbanization which has five indicators; economic urbanization is the driving force for the development of new urbanization with five indicators; land urbanization is an important carrier of new urbanization with six indicators; Urbanization of life is the fundamental goal of new urbanization and has five indicators. Management urbanization is an effective approach to new urbanization which has five indicators. The specific content is shown in the following table (Table 1). Table 1. New urbanization evaluation index system Target layer
Sub-target layer
New Population urbanize- urbanization tion
Economic urbanization
Urbanization of land
Urbanization of life
Indicator layer
Index code
Unit
Expected direction
Urbanization rate of resident population Urban population density
I1 I2
+ +
Resident committee number per 10,000 medical and health institutions number per 10,000 people Number of libraries per 10,000 people GDP per capita
I3 I4
% People/ km2 / / / Ten thousand yuan % % yuan Billion yuan Billion yuan/km2 Billion yuan/km2 m2 m2 % km2 % % % % %
+ +
GDP growth Urban registered unemployment rate Per capita disposable income of urban residents Total investment in fixed assets per 10,000 people Average GDP Average secondary and tertiary industry output value Per capita urban road area Per capita park green area Built-up area green coverage Per million built-up area Urban water penetration rate Town gas penetration rate Engel coefficient Consumer Price Index Family culture and entertainment spending as a share of consumer spending
I5 I6
I7 I8 I9 I10 I11 I12 I13 I14 I15 I16 I17 I18 I19 I20 I21
+ +
+ – + + + + + + + + + + – – +
(continued)
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Table 1. (continued) Target layer
Sub-target layer Management urbanization
2.3
Indicator layer
Index code
Unit
Expected direction
Urban sewage treatment rate
I22
%
+
Urban garbage innocuous treatment rate Expenditure on education expenditure as a proportion of general budget expenditure Expenditure on energy conservation and environmental protection as a proportion of general budget expenditure Public safety spending as a proportion of general budget expenditure
I23 I24
% %
+ +
I25
%
+
I26
%
+
Data Sources and Processing
The data involved in the new urbanization evaluation index of the 9 cities of urban cluster in the central plains comes from the Statistical Yearbook of Henan Province (2007–2016) and the Statistical Yearbook of China’s Cities (2007–2016). In order to eliminate the evaluation error caused by inconsistent index direction, the paper uses the following methods to preprocess each variable. First, according to the purpose of evaluation, the expected direction of each indicator is judged, and the new urbanization evaluation indicators are divided into positive and negative. Among them, the urban registered unemployment rate (I8), Engel coefficient (I19), and consumer price index (I20) is a negative index, and the other is a positive index; and based on the expected direction of the index, formula 1 is used to standardize the index. ( xij Minxij Maxxij Minxij ; when xij is a positive indicator aij ¼ Maxxij Minxij ; when xij is a negative indicator Maxxij xij
ð1Þ
In formula (1), xij is the actual value of the variable, Maxxij is the maximum value of the variable, Minxij is the minimum value of the variable, i is the number of the corresponding indicator, j is the year number of the corresponding indicator, and aij is the standardized standard value.
3 Research Methods 3.1
Principal Component Analysis
The new urbanization evaluation adopts the principal component analysis method. According to the new urbanization evaluation index system, SPSS20.0 statistical software is used to calculate the eigenvalues of the matrix and the corresponding variance contribution rate, the factor loading matrix and the factor regression
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coefficient, according to the factor regression coefficient. Calculate the score of each factor of the sample. The formula is: Fik ¼
n X
Mj Nij
ð2Þ
j¼1
In formula (2), Fik represents factor score of the k indicator in year i; Mj represents factor regression coefficient of index j; Nij represents Z value normalized value of the j indicator in year i. Using the variance contribution rate of the selected principal component as the weight, the scores of each factor are integrated, and the comprehensive factor score Si of each city (2006–2015) or each city is obtained. Then sort according to the score of the comprehensive factor, the formula is: Si ¼
X
Fik Ek
ð3Þ
In formula 3, Si represents the principal component the composite score for each city in Year i; Ek represents the variance contribution rate of the selected principal component. In order to more intuitively display the degree of new urbanization in each year or city, the comprehensive score of the factor can be converted into a percentage system. The formula is as follows: Gi ¼
3.2
Si Smin 40 þ 60 Smax Smin
ð4Þ
Obstacles Diagnosis
In this study, an obstacle analysis model was constructed to diagnose the obstacles that constrain new urbanization construction. The specific model is calculated as follows: The coefficient of variation vi of each variable is calculated using the value of each index xij (5), according to the coefficient of variation vi , the initial weight of each index wi is obtained (6), and then the weight of each sub-object wri is obtained (7). vi ¼
ri xi
ð5Þ
In Formula 5, ri and xi represent the standard deviation and mean of each index respectively; vi wi ¼ P n vi i¼1
ð6Þ
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wri ¼
k X
wi
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ð7Þ
i¼1
In Formula 5, r is the sub-goal of the object being evaluated, k is the number of sub-goals; (1) Index obstacle Bij ¼ ð1 aij Þ wri wi
ð8Þ
In Formula 8, Bij is obstacle measurement value of indicator layer. (2) Sub-target obstacle Bri ¼
k X
Bij
ð9Þ
i¼1
In Formula 9, Bri is obstacle measurement value of sub-target layer
4 Analysis Results 4.1
Time Dimension Analysis of New Urbanization Construction
According to the principal component analysis method of the previous section, the scores of the principal component factors are calculated by (Eqs. 2 and 3), and the conversion of scores into percentages using (Eq. 4) shows more intuitively the new urbanization goals of the 9 cities of the Zhongyuan City Group from 2006 to 2015. Layer comprehensive evaluation score and sub-target layer evaluation score (Fig. 1).
100.00
PERCENTILE SCORE
90.00 80.00
Population urbanization
70.00
Economic urbanization
60.00
Urbanization of land
50.00
Urbanization of life
40.00 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
YEAR
Fig. 1. New urbanization sub-target layer scores and comprehensive scores of 9 cities in the Zhongyuan City Group urban agglomeration from 2006 to 2015
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From the perspective of the target level, the comprehensive scores of the new urbanization target layer in the 9 cities of the Zhongyuan City Group agglomeration remained generally rising from 2006 to 2015. Among them, before 2009 is a period of rapid growth, 2009–2010 is a period of short-term downturn, 2010–2015 is a rebound period. From the sub-target level, the new urbanization sub-targets of the 9 cities of the Zhongyuan City Group Urban Area from 2006 to 2015 show the following characteristics: (1) Economic urbanization and urbanization of the land show an overall steadily rising trend; (2) Population urbanization Urbanization of the land presents characteristics of sharp fluctuations and opposite characteristics; (3) Management urbanization is basically in a leading position among sub-targets. According to the combined scores of the target layer and sub-targets, it can be seen that although the starting point of the new urbanization construction of the 9 cities of the Zhongyuan City Group was not high from 2006 to 2015, the development momentum was strong and the results were significant. 4.2
Spatial Dimension Analysis of New Urbanization Construction
According to the previous method, the scores of principal component factors are calculated using formulae (6) and (7) respectively, and the scores are converted into percentiles using formula (8), then the comprehensive urbanization scores and subtarget scores of each city in the 9 cities of the Zhongyuan City Group in 2015 were calculated. And using the thematic map making tools in Map GIS to classify and spatially display the new urbanization sub-goals of the 9 cities of the Zhongyuan City Cluster, the spatial distribution characteristics of the new urbanization of the 9 cities of the Zhongyuan City Group urban agglomeration were obtained (Fig. 2). From the target level, in 2015, the urbanization level of 9 cities in the Zhongyuan City Group was expressed as the spatial structure features weakened outward from Zhengzhou-Jiyuan Center (a). Among them, the combined scores of Zhengzhou City and Jiyuan City are 100 and 97 respectively, and they are in the high-level clubs in the 9 cities of the Zhongyuan City Group; Together they are ranked in the middle level clubs in the Zhongyuan City Group; The comprehensive scores of Jiaozuo City, Kaifeng City, and Xinxiang City are 68, 61, and 60, respectively, and are located in the low-level clubs of 9 cities in the Zhongyuan City Group. The sub-targets of the new urbanization of 9 cities in the Zhongyuan Urban Agglomeration in 2015 exhibit the following features: (1) Urbanization of population, urbanization of economy, urbanization of land, and urbanization of management appear to showing similar changes that They all show a trend of weakening outwards from the center of Zhengzhou-Jiyuan, and the gap between cities is significant; (2) the trend of urbanization of life is gradually weakening from the center of Jiyuan to the east.
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c. Economic urbanization
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b. Population urbanization
d. Urbanization of land
f. Management urbanization
Fig. 2. Spatial distribution of new urbanization in the core nine cities of the Zhongyuan City Group in 2015
Regardless of whether it is from the new urbanization target layer or the sub-target layer, the gap between the cities of the new urbanization level in the 9 cities of the Zhongyuan City Group is significant. The overall level and sub-goals of Zhengzhou City and Jiyuan City are generally high.
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However, the overall level and sub-goals of Jiaozuo, Kaifeng and Xinxiang are generally relatively low, and Xuchang, Luoyang, and Luohe are at a medium level. 4.3
Obstacles to New Urbanization Construction
4.3.1 Sub-Target Obstacles The calculation results (Table 2) of the sub-target obstacles to the new urbanization construction of 9 cities in the Zhongyuan City Group in 2015 showed that The calculation results of the sub-target obstacles to the new urbanization construction of 9 cities in the Zhongyuan City Group in 2015 showed that the main obstacles to the construction of new urbanization in 9 cities are concentrated on three aspects: land urbanization, population urbanization, and management urbanization. On the whole, the primary obstacle to the development of new urbanization in the 9 cities of the Zhongyuan City Group urban agglomeration is the urbanization of land. Urbanization of population and urbanization of management are important obstacles to the improvement of the level of new urbanization in the 9 cities. Table 2. Sub-target obstacles of new urbanization construction in 9 cities in the Zhongyuan City Group in 2015 City Zhengzhou
Item
Subgoals Obstacle Kaifeng Subgoals Obstacle Luoyang Subgoals Obstacle Pingdingshan Subgoals Obstacle Xinxiang Subgoals Obstacle Jiaozuo Subgoals Obstacle Xuchang Subgoals Obstacle Luohe Subgoals Obstacle Jiyuan Subgoals Obstacle
Sub-goal sort 1 2
3
4
5
Urbanization of land 51.78 Urbanization of land 58.87 Urbanization of land 65.98 Urbanization of land 59.13 Urbanization of land 60.54 Urbanization of land 52.56 Urbanization of land 60.61 Urbanization of land 51.89 Urbanization of land 56.38
Management urbanization 12.35 Management urbanization 12.75 Management urbanization 12.41 Economic urbanization 9.45 Economic urbanization 10.95 Management urbanization 13.29 Management urbanization 12.67 Management urbanization 14.99 Management urbanization 14.60
Urbanization of life 3.07 Economic urbanization 8.08 Economic urbanization 5.37 Management urbanization 9.1 Management urbanization 8.2 Economic urbanization 9.3 Economic urbanization 7.53 Economic urbanization 6.75 Economic urbanization 8.53
Economic urbanization 1.85 Urbanization of life 1.37 Urbanization of life 1.43 Urbanization of life 0.84 Urbanization of life 0.55 Urbanization of life 1.04 Urbanization of life 0.95 Urbanization of life 1.36 Urbanization of life 0.62
Population urbanization 30.95 Population urbanization 18.93 Population urbanization 14.81 Population urbanization 21.48 Population urbanization 19.76 Population urbanization 23.81 Population urbanization 18.24 Population urbanization 25.01 Population urbanization 19.87
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4.3.2 Indicator Layer Obstacle The calculation results of the barriers to the new urbanization construction of the 9 cities of the Zhongyuan City Group in 2015 show that the obstacle indicators of the new urbanization construction in the 9 cities are not the same, The first two indicators barriers in Zhengzhou are per capita urban road area (I13) and per capita park green area (I14) respectively. The first two indicators barriers in Zhengzhou are per capita urban road area (I13) and per capita park green area (I14) respectively. According to China’s Urban Land Classification and Planning Construction Land Standard, The per capita urban road area is controlled at a minimum of 10 m2, and the per capita park green area is between (8–15) m2. In 2015, the per capita urban road area in Zhengzhou is only 7 m2, and the per capita green area is only 7.1 m2. Both indicators have not reached the national standard lower limit. The top two indicators of the remaining eight cities are the average secondary and tertiary industries (I12) and the average GDP (I11). Table 3. Obstacles of the New Urbanization Index in the 9 Cities of the Zhongyuan City Group in 2015 City
Item
Zhenzhou
Index Obstacle Kaifeng Index Obstacle Luoyang Index Obstacle Pingdingshan Index Obstacle Xinxiang Index Obstacle Jiaozuo Index Obstacle Xuchang Index Obstacle Luohe Index Obstacle Jiyuan Index Obstacle
Index 1 I13 20.72 I12 20.64 I12 22.92 I12 19.55 I12 21.07 I12 18.27 I12 18.38 I12 18.70 I12 28.05
sorting 2 I14 16.69 I11 18.31 I11 21.16 I11 17.57 I11 18.95 I11 16.34 I11 16.45 I11 16.49 I11 25.57
3 I16 13.28 I16 10.75 I16 10.33 I16 14.66 I16 13.55 I16 11.71 I16 15.46 I16 12.82 I2 11.19
4 I4 11.48 I25 10.19 I25 9.03 I2 9.96 I2 8.64 I25 10.82 I25 10.93 I25 10.74 I25 10.04
5 I5 10.97 I2 8.30 I2 7.24 I25 7.01 I25 7.71 I2 10.70 I2 10.38 I2 9.46 I7 3.41
5 Conclusion and Discussion From the perspective of time, From 2006 to 2015, the new urbanization construction in the 9 cities of the Zhongyuan City Group has maintained an overall upward trend; From the perspective of space, the gap between cities in the new urbanization level in
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the 9 cities of the Zhongyuan City Group in 2015 is significant, and the comprehensive level and sub-goals in Zhengzhou City and Jiyuan City are generally higher, while those in Kaifeng City and Xinxiang City The overall level and sub-goals are generally low. Therefore, the Zhongyuan City Group urban agglomeration needs to reduce the gap within the urban agglomeration under the overall planning for new urbanization and increase the support for the new areas with lower level of urbanization. At the same time, Kaifeng City and Xinxiang City also need to strive for the advantage of later development, focus on upgrading the level of new urbanization construction, and strive to promote the new urbanization construction level of the entire Zhongyuan City Group urban agglomeration driven by the comprehensive efficiency of urban group collaborative development. Through the analysis of the obstacles in the new urbanization construction of 9 cities in the Zhongyuan City Group in 2015, it can be found that land urbanization is the primary obstacle to restricting the upgrading of new urbanization construction in the 9 cities. On this basis, we further clarified the obstacles in the evaluation index of the new urbanization construction in the 9 cities, and found that the first two indicators of Zhengzhou’s new urbanization barriers are per capita urban road area (I13) and per capita park green area (I14). The top two indicators of the remaining eight cities are the average secondary and tertiary industries (I12) and the average GDP (I11). It can be seen that although the most restrictive factors for the construction of new urbanization in the 9 cities of the Zhongyuan City Group urban agglomeration are the urbanization of the land, but the 9 cities have different paths for solving the same obstacles. Zhengzhou City needs to increase the per capita urban road area and the urban park green area. In order to increase the sustainability of urban land as the main objective; while the other 8 cities must focus on increasing the average GDP and the average secondary and tertiary industries, with the main objective of improving the level of land output. In this paper, the use of measurement models such as principal component analysis, barriers factors and GIS spatial analysis methods, to implement the central region of the central strategy for the rise of the Zhongyuan City Group 9 cities as the object of study, its new urbanization construction measures and obstacles to the level of measurement A diagnosis was made. The study found that as the 9 cities of the Zhongyuan City Group continue to attach importance to new urbanization construction, their construction level and effectiveness have produced relatively clear and good feedback. However, subject to data and model constraints, this paper still needs to be further improved: (1) In the construction of the index system, this article takes into account the connotation of new urbanization, but is limited by the fact that some indicators are difficult to quantify and difficult to obtain. Not comprehensive enough. (2) When the principal component analysis model is used for evaluation, it takes a longer period of study to be more rigorous and scientific. However, the study period of this paper is only 10 years. Perhaps lengthening the study period can make the related issues more clearly reflected. This article uses measurement models such as principal component analysis and barrier factors and GIS spatial analysis methods.In order to implement the central region of central China’s strategy for the rise of the Zhongyuan City Group 9 cities as the research object, the diagnosis and obstacle factors of the new urbanization construction level were diagnosed. The study found that 9 cities in the Zhongyuan City
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Group have continuously paid attention to the new type of urbanization construction, and their construction level and effectiveness have produced relatively clear and good feedback. However, subject to data and model constraints, this paper still needs to be further improved: (1) In the construction of the indicator system, this article takes into account the connotation of new urbanization, but is limited by the fact that some indicators are difficult to quantify and difficult to obtain, and the indicator system is not comprehensive enough. (2) When using the principal component analysis model to evaluate, selecting a longer study period will make the research conclusions more rigorous and scientific. However, the study period of this paper is only 10 years, perhaps lengthening the study period can make the related issues more clear.
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Study on the Impact Between Rapid Urbanization and Fire Safety Management ——A China Perspective Ying Zhang(&) School of Construction Management and Real Estate, International Research Centre for Sustainable Built Environment, Chongqing University, Chongqing, China [email protected] Abstract. Based on the 2005–2014 panel data of the urbanization and fire safety management of provincial administrative units in Mainland China, though regression analysis method, the interrelationship between urbanization development and fire safety management performance is studied. The dimensions for understanding urbanization development are selected as population urbanization, land urbanization, urban traffic condition, social-economic performance, and education development. The regression analysis results show that population and land urbanization indicators are significantly interrelated with fire safety performance, and others are correlated less. It appears that the progress of land urbanization has made significant contribution to the improvement of fire safety management performance, whilst population urbanization has less contribution. Based on the above conclusions, to improving the fire safety management performance effectively, the present urbanization pattern in China should be changed to focus more on the intension of land urbanization development. Keywords: Fire safety management Urbanization Population urbanization Land urbanization Interrelationship Correlation analysis China
1 Introduction With the rapid development of urbanization in China, the benefits from urbanization have been well appreciated, such as promoting economic development, stimulating scientific and technological innovation, adjusting industrial structure and improving people’s living standard. But the fire safety management, as one of the key performance indicators for measuring urbanization performance in governments, is facing unprecedented huge risks and pressures under the rapid development of urbanization in China. The emergence of skyscrapers, large-scale of underground projects, huge shopping malls and others has not offered as effective hand rather than a kind of risk to fire safety management. What’s more, there is a rising population shift from rural to urban area in the past twenty years in China, and most of these floating population live in dangerous buildings and engage in high-risk occupations with less education and fire consciousness. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 185–197, 2021. https://doi.org/10.1007/978-981-15-3977-0_14
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The city is growing up, but the fire safety management has failed to keep pace with the growth of the city. According to China Statistical Yearbook, the population urbanization rate in 1994 in China was 28.51%, and the figure in 2014 was 54.77%, almost as twice as the figure in 1994 [1]. According to China Fire Yearbook, the total number of fires in 1994 in China was 39337, and this figure was 395052 in 2014 which was ten times than that in 1994 [2]. That is to say, the growth speed of fire accidents is about five times faster than that of urbanization in China in the last twenty years. In Fig. 1, from 2005 to 2014, the population urbanization rates in China rose steadily, while the number of fires and the direct economic loss of fires increased sharply. It appears that the level of fire safety management is not synchronized with the development level of urbanization, which is contributed significantly by the lack of understanding on the relationship between the fire safety management and the urbanization. A proper comprehension on this interrelationship should be able to help study strategies of raising fire safety management performance by making use of the opportunity of implementing urbanization.
Fig. 1. Population urbanization rate, the number of fires and the direct economic loss of fires in 2005–2014 in China [1–3].
In particular, considering the scale of urbanization in the country, it is very important to implement urbanization development in a way that can contribute to the promotion of fire safety management performance. Without proper understanding on this issue, fire safety management performance will remain unattended in China, which will in turn affect the sustainability of urbanization development in the country. Therefore, this research aims to understand whether or not fire safety management is attended whilst the urbanization is highly promoted in China. The rest of this paper is designed as follows. Section 2 presents a literature review on the research subject of interrelationship between fire safety management performance and urbanization. Section 3 describes the research design. Section 4 presents the
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results of data analysis. Section 5 analyzes the discussions on the results, followed by the conclusions in Sect. 6.
2 Literature Review Urbanization is a process of profound social and economic change. It includes the process of transformation, centralization, strengthening and differentiation of the population to cities and towns, as well as the process of regional advancement of urban landscape and the adjustment of industrial structure. Urbanization also includes the diffusion of urban economic, social and technological changes in the urban hierarchical system into the rural areas, and even the more abstract spiritual change process of urban culture, life style and values to the rural areas. In the same city, population urbanization and land urbanization may not be synchronized [4–7]. Some scholars at home and abroad had devoted themselves to the study the interrelationship between fire safety management performance and urbanization development, and achieved some results. Wang J H et al. observed the relationship between the number of fires, the direct economic loss of fires, and the degree of urbanization and the speed of urbanization in Beijing, Hefei, Ji’nan and Changfeng, and came to the conclusion that the fire situation depended on the level of urbanization and the speed of urbanization development [8]. Through the regression analysis, Li Shu et al. believed that the population urbanization rate in China was positively related to the direct economic loss of the fire, and there was obvious positive correlation between the urban area division and the number of the fire [9]. Dong Yi measured the level of urban urbanization from four aspects in economic development, science and education, urban transportation, and urban construction, while measured the fire safety management performance by four indicators that were the number of fires, the direct economic loss of fires, the number of deaths in fires, and the number of injuries in fires. Using the method of factor analysis and correlation analysis, the relationship between urbanization and fire safety management in Hebei were discussed, and there was a positive correlation between urbanization development and the number of fires [10]. The above discussion shows that domestic and foreign researchers had done a lot of work on the interrelationship between urbanization and fire safety management, and there was a positive correlation between the urbanization indexes and the fire safety management indexes. However, it appears that little study has been conducted in examining the contribution of urbanization to the improvement of fire safety management particularly in the context of China. There is a clear gap unaddressed whether the performance of fire safety management is properly attended in its dramatic urbanization development process in China. Therefore, this paper tries to fill the missing gap and demonstrate the interrelationship between the urbanization development and the fire safety management at the national level by the relevant data of all the provincial administrative units in Mainland China for the last ten years.
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3 Research Design In this research, it is designed to measure the interrelationship between urbanization development and fire safety management performance by a group of correlation coefficients. 3.1
Research Measurements
There are two groups of measurements which need to be defined clearly, variables for indicating fire safety management performance, variables for measuring urban development. 3.1.1 Variables for Indicating Fire Safety Management Performance Previous studies have presented various variables for measuring fire safety management performance [9, 11]. Based on these research works, the following variables are adopted for indicating fire safety management in an urban area: the number of fires (Y1), and the direct economic loss of fires (Y2). The two variables are the most popular in analyzing fire safety status and evaluating the effectiveness of firefighting works, and they are parameters to represent the fire safety management performance which are easiest to get. 3.1.2 Variables for Measuring the Level of Urbanization In line with previous research works, which were evaluation index system of urbanization development established by Chen Feng-gui, Lv Ping, and Dong Yi [5, 7, 9], under the guidance of the principles in hierarchy, dynamics and completeness, and considering the features of data in the accessible obtaining and conveniently quantifying, the level of urbanization is commonly examined by using five groups of indexes: population urbanization, land urbanization, urban traffic condition, socialeconomic performance, and educational development. And each index group is composed of several specific indexes. The composition of the indexes for measuring the level of urbanization are listed in Table 1. 3.2
Research Methods
Regression analysis model is used in this study to help find out the interrelationship between urban development and fire safety management performance, in which urbanization indexes (Xi) are independent variables, and fire safety management performance variables (Yj) are dependent variables. In conducting regression analysis the independence between independent induces needs to be checked before the analysis on the correlation coefficients between variables. Only those urbanization indexes which are mutually independent are selected. 3.2.1 Independence Verification The following model is commonly used to test the level of independence between two variables XR and XS. It is assumed that the two variables in the index system of urbanization are linear relations, and the two variables are random variables which are
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Table 1. Indexes for measuring the level of urbanization Index group Population urbanization
Land urbanization
Urban traffic condition
Socialeconomic Performance
Index Population urbanization rate (X1) (Resident population in urban areas/Permanent population) Urban population density (X2) (Resident population in urban areas/Urban areas) Per capita GDP(Gross domestic product) (X3) (Regional total GDP/Permanent population) Areas of completed building (X4) Values of completed building (X5) Built-up urban areas (X6) Ratio of built-up urban areas (X7) (Built-up urban areas/Total land areas in the administrative region) Ratio of construction land (X8) (Construction land areas/Total land areas in the administrative region) Utilization rate of construction land (X9) (Built-up urban areas/Construction land areas) the GDP output of per unit land area (X10) (Regional total GDP/Total land areas in the administrative region) the number of public transport vehicles every thousand people (X11) Per capita urban road areas (X12) (Regional urban road areas/Resident population in urban areas) Total annual savings of urban and rural residents in the administrative region (X13) Per capita annual savings (X14) (Total annual savings of urban and rural residents/Permanent population) GDP proportion of the second industry (X15) (GDP of the second industry/Total regional GDP) GDP proportion of the third industry (X16) (GDP of the third industry/Total regional GDP)
Unit
10,000 people per km2 100,000 RMB per person 100 km2 100,000,000 RMB 10,000 km2
100 RMB per m2
10 m2 per person
1000,000,000,000 RMB 10000 RMB per person
(continued)
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Index group Educational development
Index Regional education investment in reported period (X17) Proportion of education investment in gdp (x18) (Regional education investment/Total regional GDP) Percentage of college or above graduates (X19) (Number of college or above population/Total regional sample population)
Unit 100,000,000,000 RMB
no extreme value. They obey a joint bivariate normal distribution, and the linear relationship intensity between the two variables named correlation coefficient is recorded as “r” [11]. The formula is as following: Pn i¼1 ðxRi xR ÞðxSi xS Þ ffi r ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn 2 Pn 2 i¼1 ðxRi xR Þ i¼1 ðxSi xS Þ
ð1Þ
When coefficient “r” between the two indexes is greater than 0.8 and P value is less than 0.05, the two indexes XR and XS are strongly correlated, and only one of the two indexes will be selected for the further correlation analysis [11]. 3.2.2 Correlation Analysis After selecting the independent urbanization indexes, the multiple linear regression model is applied to analyze the interrelationship between the fire safety management index and the urbanization index according to following model: Yj ¼ b0 þ b1 X1 þ b2 X2 þ b3 X3 þ . . . þ bi Xi þ eði ¼ 1; 2; 3; . . .. . .; nÞ
ð2Þ
In (2), Yj is a specific variable for measuring fire safety management performance, which is a linear function of the independent indexes X1, X2, X3,…,Xi. The e is the random error term. The parameters b0, b1, b2,…,bi are the regression coefficients [11]. 3.3
Data Sources
The data used for analysis in this study are from three types of sources, namely, National Bureau of Statistics of the People’s Republic of China, CSMAR Research Data Service, and Fire Department of the Ministry of Public Security of China. The data cover the period from 2005 to 2014 for all the provincial administrative units in Mainland China. Due to the absence of the census in 2010, some related data were missing, and default processing would be taken. Table 2 is partly sample data, which
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presents the data about the indicators for measuring fire safety management performance and the variables of urbanization development.
4 Data Analysis In order to seek the interrelationship between urbanization development and fire safety management performance, regression analysis is conducted by using the model (1) and (2), though the software STATA and the collected relevant data in Sect. 3. 4.1
The Independence Test of Urbanization Index
By using the software STATA and model (1), the variables of urbanization development are tested and calculated, with the data of all 31 provincial administrative units for latest ten years, and the results are in Table 3. As shown in Table 3, the number of the first row in the box is the correlation coefficient “r” of the corresponding two variables, and the number of the second row in the same box is the P value in the significance test of the correlation coefficient. Only when the absolute value of “r” is greater than 0.8 and the P value is less than 0.05, it is accepted that the two indexes are highly correlated [11]. According to this principle, from the calculation results of Table 3, strong correlation combinations are obtained as follows: ①X1 and X3, X1 and X9, X1 and X14, X1 and X19; ②X3 and X14, X3 and X19; ③X4 and X6; ④X5 and X4, X5 and X6, X5 and X13, X5 and X17; ⑤X6 and X13, X6 and X17; ⑥X7 and X8, X7 and X9, X7 and X10; ⑦X8 and X10; ⑧X9 and X14; ⑨X13 and X17; ⑩X14 and X19. From the above combinations, there are four variables strongly related to X1 (the population urbanization rate) and X5 (the values of completed building), and there are three variables strongly connected with X7 (the ratio of built-up urban areas). It indicates the population urbanization rate is very representative, which is closely related to the social economy, education level and urban construction. So do the variables X5 and X7. On the principle of representativeness and universality in selection of strong correlation variables, X1 and X5 are kept in priority, and X7 follows. The urbanization variables that are strongly related to X1, X5 and X7 are excluded, and there are 9 independent and representative variables of urbanization finally obtained (X1, X2, X5, X7, X11, X12, X15 and X18), that will be used as the independent variable Xi in the next correlation analysis.
2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014
Anhui Beijing Fujian Gansu Guangdong Guangxi Guizhou Hainan Hebei Henan Heilongjiang Hubei Hunan Jilin Jiangsu Jiangxi Liaoning Inner Mongolia Ningxia Qinghai Shandong Shanxi Shaanxi Shanghai Sichuan Tianjin Tibet Xinjiang Yunnan Zhejiang Chongqing
0.492 0.863 0.618 0.417 0.680 0.460 0.400 0.538 0.493 0.452 0.580 0.557 0.493 0.548 0.652 0.502 0.670 0.595 0.536 0.497 0.550 0.538 0.526 0.896 0.463 0.823 0.258 0.461 0.417 0.649 0.596
Year X1
Province
2.416 1.525 2.627 3.682 2.999 1.684 2.393 2.069 2.540 5.149 4.946 2.448 3.402 3.171 2.038 4.671 1.615 1.291 1.295 2.604 1.426 3.974 5.474 3.826 3.068 3.328 1.857 4.280 2.853 1.828 1.872
X2
0.344 1.000 0.635 0.264 0.635 0.331 0.264 0.389 0.400 0.371 0.392 0.471 0.403 0.502 0.819 0.347 0.652 0.710 0.418 0.397 0.609 0.351 0.469 0.974 0.351 1.052 0.293 0.406 0.273 0.730 0.479
X3
1.746 0.490 1.309 0.376 2.036 0.926 0.689 0.185 1.644 2.405 0.614 1.783 1.071 0.512 3.724 1.375 1.693 0.564 0.190 0.172 2.830 0.833 0.738 0.268 1.708 0.555 0.034 0.957 1.155 2.311 0.603
X4
1.565 0.634 0.861 0.313 2.416 0.722 0.653 0.667 1.389 1.858 0.666 1.263 1.352 0.361 2.667 0.952 1.406 0.639 0.262 0.207 2.124 1.063 1.047 0.647 1.880 0.639 0.037 0.953 0.842 2.234 1.074
X5 0.184 0.139 0.133 0.078 0.540 0.119 0.072 0.030 0.183 0.238 0.179 0.208 0.154 0.136 0.402 0.120 0.242 0.119 0.044 0.017 0.440 0.110 0.097 0.100 0.222 0.080 0.013 0.112 0.098 0.249 0.123
X6 0.141 0.216 0.065 0.021 0.110 0.051 0.037 0.115 0.153 0.036 0.089 0.076 0.057 0.218 0.075 0.109 0.013 0.046 0.005 0.177 0.065 0.045 0.480 0.037 0.343 0.001 0.009 0.026 0.121 0.079
0.010 0.014 0.004 0.011 0.007 0.007 0.039 0.007 0.016 0.001 0.007 0.000 0.028 0.007 0.005 0.158 0.005 0.067 0.000 0.001 0.003 0.024 0.015
X8
0.013 0.084 0.011 0.002 0.030 0.005 0.004
X7 0.094 0.390 0.165 0.089 0.274 0.099 0.110 0.090 0.085 0.093 0.111 0.125 0.096 0.126 0.179 0.096 0.150 0.074 0.144 0.049 0.158 0.108 0.105 0.328 0.125 0.195 0.089 0.073 0.095 0.197 0.190
X9
0.157 0.209 0.033 0.147 0.128 0.073 0.631 0.094 0.194 0.015 0.041 0.003 0.376 0.081 0.086 3.717 0.059 1.319 0.001 0.006 0.033 0.386 0.173
0.150 1.300 0.195 0.016 0.378 0.066 0.053
X10 1.160 2.484 1.333 0.967 1.328 0.919 1.061 1.197 1.134 0.975 1.278 1.191 1.246 1.032 1.508 0.856 1.179 0.901 1.317 1.440 1.317 0.885 1.585 1.197 1.422 1.814 0.843 1.554 1.236 1.546 1.118
X11
Table 2. Data Sample 2.033 0.744 1.361 1.530 1.320 1.575 1.033 1.797 1.849 1.167 1.332 1.657 1.376 1.462 2.389 1.577 1.275 2.110 2.316 1.108 2.577 1.334 1.538 0.411 1.332 1.671 1.444 1.646 1.712 1.840 1.168
X12
X14
X15
X16
X17
X18
X19
Y1
Y2
1.460 2.400 0.531 0.354 1.046 0.050 0.105 1.224 1.400 2.416 11.226 0.213 0.779 1.094 0.051 0.382 0.448 0.685 1.258 3.305 0.520 0.396 0.893 0.037 0.117 1.142 1.324 0.667 2.576 0.428 0.440 0.518 0.076 0.103 0.603 0.701 5.241 4.887 0.463 0.490 2.736 0.040 0.094 2.225 4.604 1.002 2.108 0.467 0.379 0.859 0.055 0.080 0.531 1.113 0.662 1.887 0.416 0.446 0.770 0.083 0.104 0.422 1.767 0.267 2.959 0.250 0.519 0.241 0.069 0.081 0.142 0.276 2.569 3.479 0.510 0.373 1.086 0.037 0.079 1.118 2.259 2.242 2.376 0.510 0.371 1.639 0.047 0.104 2.332 2.154 1.086 2.832 0.369 0.458 0.628 0.042 0.124 1.888 1.488 1.725 2.966 0.469 0.415 0.987 0.036 0.114 1.045 0.832 1.641 2.436 0.462 0.422 1.129 0.042 0.092 1.824 2.508 0.856 3.109 0.528 0.362 0.535 0.039 0.119 1.324 0.590 3.658 4.596 0.474 0.470 2.080 0.032 0.143 3.242 2.948 1.079 2.376 0.525 0.368 0.893 0.057 0.081 0.833 1.719 2.118 4.824 0.502 0.418 0.870 0.030 0.172 3.029 1.746 0.801 3.199 0.513 0.395 0.639 0.036 0.109 1.141 1.212 0.205 3.104 0.487 0.434 0.170 0.062 0.107 0.423 0.363 0.164 2.814 0.536 0.370 0.198 0.086 0.128 0.158 0.147 3.318 3.389 0.484 0.435 1.885 0.032 0.098 2.951 3.003 1.415 3.878 0.493 0.445 0.704 0.055 0.098 0.738 0.811 1.343 3.557 0.541 0.370 0.910 0.051 0.110 1.313 1.403 2.127 8.767 0.347 0.648 0.989 0.042 0.271 0.585 0.705 2.531 3.110 0.489 0.387 1.451 0.051 0.091 1.897 1.590 0.792 5.219 0.492 0.496 0.633 0.040 0.228 0.360 0.648 0.056 1.759 0.366 0.535 0.153 0.166 0.026 0.011 0.092 0.619 2.693 0.426 0.408 0.635 0.068 0.132 1.350 0.898 0.970 2.058 0.412 0.433 0.920 0.072 0.068 0.524 2.074 3.067 5.568 0.477 0.478 1.608 0.040 0.151 3.982 5.284 1.077 3.602 0.458 0.468 0.698 0.049 0.129 0.638 0.680
X13
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Table 3. Calculation Results of Correlation Coefficient of Urbanization Index System X1 X1 X2
X3
X4
X5
X6
X7
X8
X9
X10 X11
X12
X13
X14
X15
X16
X17
X18
4.2
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
X14
X15
X16
X17
X18
1.0000 -0.1280 0.0243
1.0000
0.8487 -0.0928 0.0000 0.1031 0.0628
1.0000
0.0465 0.2032
0.2700 0.4148
0.0003
1.0000
0.3199 -0.0167 0.4958 0.8806 0.0000 0.7700
0.0000 0.0000
1.0000
0.3215 -0.0641 0.3532 0.8135
0.8348
0.0000 0.2625
0.0000
0.0000 0.0000
1.0000
0.7884 -0.0289 0.6849 -0.0130
0.1644
0.1516
0.0000 0.6144
0.0000 0.8200
0.0039
0.0080
0.7648 -0.0216 0.6871 0.1955
0.3206
0.2814
0.9072
0.0000 0.7061
0.0000 0.0006
0.0000
0.0000
0.0000
0.8278 -0.1707 0.7102 0.0812
0.2858
0.3543
0.8556
0.7259
0.0000 0.0026
0.0000 0.1546
0.0000
0.0000
0.0000
0.0000
0.7015 0.0359
0.6781 -0.0398
0.1407
0.0888
0.9530
0.8592 0.7411
0.0000 0.5300
0.0000 0.4856
0.0133
0.1210
0.0000
0.0000 0.0000
0.4463 -0.0536 0.5444 -0.0317
0.1664
0.0360
0.3704
0.2819 0.4768
0.3004
0.0000 0.3465
0.0000 0.5784
0.0033
0.5292
0.0000
0.0000 0.0000
0.0000
-0.0576 -0.1540 0.2001 0.4451
0.4948
0.3552
-0.2377 -0.0284 -0.1837 -0.2464 0.0942
0.3119 0.0066
0.0004 0.0000
0.0000
0.0000
0.0000
0.6194 0.0012
0.0000
0.0979
0.4604 0.0021
0.5813 0.7087
0.8708
0.8752
0.3235
0.3856 0.5040
0.3112
0.2465
0.2728
0.0000 0.9702
0.0000 0.0000
0.0000
0.0000
0.0000
0.0000 0.0000
0.0000
0.0000
0.0000
0.8381 -0.0570 0.8972 0.0681
0.3524
0.2607
0.7548
0.6602 0.8221
0.7271
0.6016
-0.0649 0.5586
0.0000 0.2316
0.0000
0.0000
0.0000
0.0000 0.0000
0.0000
0.0000
0.2549 0.0000
0.0000 0.3175
1.0000
1.0000
1.0000
1.0000 1.0000
1.0000
1.0000
1.0000
0.5271 -0.2399 0.5214 -0.2805
-0.0417 -0.0599
0.6421
0.4478 0.7545
0.5687
0.5523
-0.2672 0.1868
0.7114
0.0000 0.0000
0.0000 0.0000
0.4649
0.2952
0.0000
0.0000 0.0000
0.0000
0.0000
0.0000 0.0009
0.0000
0.3335 0.0797
0.5245 0.7791
0.9054
0.8420
0.2004
0.2941 0.3581
0.2034
0.2027
0.3764 0.9497
0.4408
0.0557
0.0000 0.1617
0.0000 0.0000
0.0000
0.0000
0.0004
0.0000 0.0000
0.0003
0.0003
0.0000 0.0000
0.0000
0.3281
-0.5217 0.0235
-0.3298 -0.4578
-0.4343 -0.5364
-0.2698 -0.4234 -0.2728 -0.2193 0.0680
-0.0781 -0.4298 -0.2352
0.2152
-0.3631
0.0000 0.6797
0.0000 0.0000
0.0000
0.0000
0.0000
0.0000 0.0000
0.0001
0.2326
0.1704 0.0000
0.0000
0.0001
0.0000
0.2062
0.0926
0.7421
0.6391 0.7776
0.6688
0.7007
-0.1184 0.3377
0.9144
0.6889
0.2502
-0.2326
0.0005
0.1243
0.0000
0.0000 0.0000
0.0000
0.0000
0.0483 0.0000
0.0000
0.0000
0.0000
0.0001
0.8418 -0.0453 0.8246 -0.0508 0.0000 0.4512
0.0000 0.3982
1.0000
1.0000
1.0000
1.0000
Correlation Between Urbanization and Fire Safety Management
According to regression model (2), the nine independent urbanization variables (X1, X2, X5, X7, X11, X12, X15, X16 and X18) are adopted for further correlation analysis on their correlation coefficients with the fire safety management performance variables (Y1 and Y2). The analysis results are demonstrated in Table 4.
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Table 4. Regression analysis results between urbanization variables and fire safety management variables Fire safety management variables Urbanization variables Y1 Y2 X1 0.6023 0.9538* X2 −0.2299 0.7735*** X5 0.3015*** 0.4362*** X7 −6.2222*** −7.0972*** X11 −0.0492 −0.0674 X12 −0.1405 −0.0760 X15 0.9524 1.4199* X17 −4.5606* 2.2840 b0 0.2187 −0.9251*** N 307 307 R2 0.3657 0.4312 F 23.0506 30.0005 P value 0.000 0.000
In Table 4, for variables, the numbers corresponding to the Xi and Yj variables are relative coefficients. *, ** and *** denote the significance level of 10%, 5% and 1% respectively, and it is generally considered that the relative coefficients are significant when marked with ** and *** [11, 12]. For the regression equation, the numbers in the “b0” row are the constant of the equation. “N” represents there are 307 sets of data. “R2” indicates goodness of fit of the regression equation, whose value can be between 0 and 1. For only discussing the relationship between variables in this paper, the regression equation would be accepted when R2 is greater than 30%. “F” is the result of the F-test of the equation, and “P value” is the figure of the equation’s F-test, which should be less than 0.05, if the regression equation is considered valid [11, 12]. According to the results of regression analysis, the following two regression equations are obtained. Y1 ¼ 0:3015X5 6:2222X7
ð3Þ
Y2 ¼ 0:9251 þ 0:7735X2 þ 0:4362X5 7:0972X7
ð4Þ
5 Discussion Based on the analysis results obtained in the previous section, the following discussions can be conducted between urban development and fire safety management from two dimensions Y1 and Y2.
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Discussion Based on Dimension of the Number of Fires (Y1)
From the Eq. (3), when the dependent variable is Y1 (the number of fires), only the land urbanization variables X5 (the values of completed building) and X7 (the ratio of builtup urban areas) are significantly related to it. X5 is positively related to it, while X7 is negatively correlated with it. It can be seen that the correlation between population urbanization variables and the number of fires is not as significant as previous research results, which did not take the land urbanization variables into account. According to statistics, among all kinds of fires, building fires are the most common and harmful. From 2010 to 2014, the direct economic loss induced by building fires accounted for about 80% of the total direct economic loss, while the number of building fires accounted for 60% of the total number of fires [2]. The increase of X5 would accelerate the growth of fires. In referring to X7 (the ratio of built-up urban areas), it has close relation with urban infrastructure which includes fire safety facilities. In other words, the quality of urban infrastructure reflects to large extent the level of fire safety management performance. So the increase of X7 would effectively reduce the number of fires. 5.2
Discussion Based on the Dimension of Direct Economic Loss of Fires (Y2)
As the Eq. (4) shows, when the dependent variable is Y2 (the direct economic loss of fires), X2 (the urban population density) and X5 (the values of completed building) are positively related to Y2, while X7 (the ratio of built-up urban areas) is negatively correlated. That means the direct economic loss of fire could be controlled by the decrease in X2 and X5, and the increase in X7. In fact, the increase of X2 mainly indicates the increase of population flow from rural to urban area. Most of those rural-to-urban migrants have received limited education and gained little fire safety knowledge. Some of their behaviors present fire risks, such as smoking in those no-smoking places and occupying the fire safety evacuation passages. Furthermore, these migrants are mainly engaged in labor intensive jobs, and live in crowed buildings where the condition of fire safety management facilities are very poor. This is why the increase of urban population density can result in the increase of direct economic loss from fires. Similarly, the increase of X5, has induced the increase of economic loss from fire accidents, and this has been discussed in previous section. However, X7 has significant negative relation to Y2. It is therefore considered that the increase of built-up urban areas can lead to the reduction of economic loss from fire accidents, largely because of the improvement of fire safety facilities. For example, the number of municipal fire hydrant was 506,895 in 2005 and increased to 984,500 in 2014 [2], with an increment of 94.2% during the ten years.
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6 Conclusions The main findings of this study are as follows. Firstly, for measure the interrelationship between urbanization and fire safety management in China more comprehensively and reliably, a new index system for measuring the level of urbanization is established, which is added the indexes of land urbanization, based on the previous studies. Secondly, the increase of urban population density can generally cause the increase of urban fire hazards in China. In other words, the fire safety management can be better attended during the dramatic urbanization process in China if people’s fire awareness and behavior norms can be changed towards improving the performance of fire safety management across the country. Thirdly, urban buildings are found as the major sources to the urban fires, evidenced by the positive interrelationships between the value of completed urban buildings and the urban fires. Therefore, buildings can play key roles in improving fire safety management performance in the urbanization process. It is highly advocated that proper fire safety policy measures should be introduced across building’s life cycle (including design, construction and operation) to ensure that fire safety management is better attended. Fourthly, the fire accidents can be reduced significantly by increasing the built-up urban areas, which depends on the construction of urban infrastructure. In other words, the increasing amount of urban infrastructure, which includes fire safety facilities, will decrease the fire accidents effectively. The research results of this paper also enrich the research content of urban fire management, fill the blank of the research on the relationship between land urbanization and fire management, and have great significance to the development of urbanization strategy, the transformation and upgrading of economic structure, and the improvement of fire safety management. However, there are some limitations in this study. Limited indicators are used for measuring the performance of fire safety management, and this can be further expanded. Secondly, the empirical research can be used in future studies. Acknowledgement. This study is part of the research project sponsored by the Chinese National Social Science Program Fund15AZD025, 15BJY038 and 17ZDA062.
References 1. 2005–2014 China Statistical Yearbook [DB/OL], National Bureau of Statistics of the People’s Republic of China. http://www.stats.gov.cn/tjsj/ 2. Fire Department of the Ministry of public security of China, 2005–2015 China Fire Yearbook, Yunnan Publishing Group 3. CSMAR Research Data Service [DB/OL]. http://www.gtarsc.com/Home 4. Chuan-jiang, L., Ling-yun, Z.: Urbanization and Sustainable Development of Urban and Rural Areas, The Science Publishing Company, May 2004 5. Feng-gui, C., Hong-ou, Z., Qi-tao, W., Wei-lian, C.: A study on coordinate development between population urbanization and land urbanization in China. Hum. Geogr., 25(5), October 2010 6. Xin, L., Jing, W., Jian, L.: Review of research on land urbanization and related studies. Progress Geogr., 31(8) 2012
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7. Lv, P., Zhou, T., Zhang, Z.-F., Tian, Z.: Construction and application of land urbanization and corresponding measurement index system. China Land Sci., 22(8), August 2008 8. Wang, J.H., Sun, J.H., Lo, S.M., Gao, L.J., Yuen, R.K.K.: Statistical analysis on the temporal-spatial characteristics of urban fires under typical urbanization features. Procedia Eng., 11, 437–444 (2011) 9. Shu, L., Lu Z.-H., Tang, C.-G, Liu, L., Yang, Z.-G.: An analysis of the influence of the urbanization of fire accident. Fire Sci. Technol., 25(3), May 2006 10. Yi, D., Ning, C., Ming-yan, L.: The multiple correlation analysis between the characterization factors of new urbanization level and 4 fire indicators. Fire Sci. Technol., 34(7), July 2015 11. Jun-ping, J.: Statistics, China Renmin University Press, January 2016 12. Zhi-ning, H.: STATA/EVIEWS Econometric Analysis, China Renmin University Press, January 2016
Study on Land-Use Efficiency Evaluation of Development Zones Based on DEA—Take Hi-Tech Zones as an Example Yi Li and YuZhe Wu(&) School of Public Affairs, Zhejiang University, Hangzhou, China [email protected]
Abstract. With the rapid development of industrialization and urbanization in China, land resources have gradually become the important constraint factors for the sustainable development of China’s socioeconomic. Development zones play an important role in the development of high technology industries and scale economy and export-oriented economy, while the land-use is mainly extensively and waste of land is relatively serious. Therefore, promoting landuse efficiency is the crucial issue. Based on the definition of the concept of land use efficiency, this paper uses DEA method to analyze the land-use efficiency and economic efficiency of high-tech zones from 2009 to 2014. And taking the calculation results of DEA in 2014 as an example, this paper puts forward the adjustment of production factors input in high-tech zones. Consequently some relevant policy suggestions are proposed according to the analysis results. Keywords: Hi-tech zones
Land use efficiency DEA
1 Introduction It is well known that development zones have unique advantages in terms of land supply in China, which leads to its relatively low land-use cost. Furthermore land-use is mainly extensive, land-use efficiency needs to be improved urgently. Therefore, the research on the efficiency of land-use in development zones, especially in Hi-tech zones, is beneficial to improving the benefits of land output in the park and providing reference for the improvement of other types of development zones. What’s important is that it helps promote sustainable economic development and build a resource-saving society. Efficiency was originally a concept of physics, referring to the ratio of useful energy to total energy consumed during mechanical motion. With the development of economy, the word efficiency has been used in the field of economics. In 1957, the economist Farrel divided Overall efficiency into two parts: technical efficiency and allocation efficiency. And he thought technical efficiency refers to the ability of a manufacturer to obtain a given output with a minimum input, or it also can be defined as the ability of a manufacturer to obtain maximum output under a certain input. Allocation efficiency refers to the ability to achieve the optimal combination of production requirements under a given set of resources and technical conditions. Based on © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 198–213, 2021. https://doi.org/10.1007/978-981-15-3977-0_15
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this, this paper argue that the efficiency of land use in development zones is defined as: the degree of land-use in the development zones in the current level of economic and technological development, in order to obtain a certain amount of output. Formulated as follows: LUE ¼
ALI ELI ELI TLI ¼ 1 ¼ ALI ALI ALI
Among them, LUE (Land Use Efficiency) represents the land use efficiency, and ALI (Actual Land Input) represents the actual input of land resources, and ELI (Excessive Land Input) represents the excessive land resource input, and TLI (Target Land Input) is the target input of land resources. LUE means that at the current level of economic and technological development, the minimum amount of land resources required to achieve a given output. It is expressed as a ratio of target input to actual input, which is between 0 and 1.
2 Methodology and Data 2.1
Data Envelopment Analysis
Data Envelopment Analysis (DEA) is a brand-new system evaluation method based on the concept of “relative efficiency evaluation” proposed by A. Charnes and W. W. Cooper. Also it is a non-parametric mathematical programming approach, which means it does not need to pre-set the parameters and the specific form of the frontier production function. The DEA method is based on the observation of a large number of actual production conditions, based on the linear programming method to determine the production frontier. The Decision Making Unit (DMU) is considered to be effective when the corresponding point of DMU is on the effective production frontier. In addition, the DEA method does not need to artificially weighted to avoid the influence of subjective factors. And it is more convenient that the DEA results will give the direction and magnitude of non-DEA effective DMUs the specific way to improve efficiency [1, 2]. Therefore, the DEA method has obvious advantages in the research of land-use efficiency evaluation for land-based systems with multiple inputs and multiple outputs. Using the Hi-tech zones as a DMU, the CCR-DEA model with non-Archimedean infinitesimal quantities is expressed in Eq. 1: 8 min½h eð^eT s þ eT s þ Þ ¼ VDe > > n > P > > > s:t: kj xj þ s ¼ hx0 > > < j¼1 n ðDe Þ P kj y j s þ ¼ y 0 > > > > j¼1 > > > > kj 0; j ¼ 1; :::; n : s 0; s þ 0
ð1Þ
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In 1984, Banker, Charnes and Cooper proposed the BCC-DEA model which is an efficiency evaluation under the change of return of scale. As follows: 8 min½h eð^eT s þ eT s þ Þ ¼ VDe > > > n > P > > s:t: xj kj þ s ¼ hx0 > > > j¼1 > > > n > P < y k s ¼ y j j 0 ð2Þ ðDe Þ j¼1 > > n P > > > kj ¼ 1 > > > j¼1 > > > k 0; j ¼ 1; :::; n > > : j s 0; s þ 0
2.2
Index selection and data processing
The production function Y ¼ fðT; K; LÞ is constructed on the basis of Cobb-Douglas production function, that introduces the input elements of land resources. And Y represents the economic output there, T represents the input factor of land resources, K represents the capital input elements and L represents the labor input factor. The land area (square kilometers) of high-tech zones is used as an input indicator of land factors, and the number of employees (persons) at the end of the year as an input indicator of labor factors, and assets at year end (thousands of yuan) as input indicators for capital elements. In this paper, industrial gross output (thousands of yuan), business income (thousands of yuan) and the earning of foreign exchange through export(thousands of dollars) are selected as output indicators. Considering the data statistical continuity, this paper just selected the data of 56 high-tech zones from 2009 to 2014 for analysis. The efficiency during this period can also reflect the current situation and development trend of the land-use efficiency of high-tech zones after the 2008 financial crisis to some extent. In addition, it is unnecessary to carry out dimensionless processing on the data because of the DEA measuring relative efficiency and not directly integrating the index data. The DEA method is satisfactory as long as the consistency of the annual data of the research object is ensured.
3 Results and Analysis 3.1
Analysis of Overall Land-Use Efficiency
Through the software DEAP (version 2.1) to calculate the efficiency, it is capable to obtain the technical efficiency (TE) and pure technical efficiency (PTE) and scale efficiency (SE) of 56 high-tech zones in 2009–2014. Based on this, the average efficiency of the high-tech zones is calculated as show in Fig. 1.
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Fig. 1. Average efficiency of 56 Hi-tech zones and national GDP growth, 2009–2014
According to Fig. 1, it is obvious to find that the overall average efficiency of the 56 Hi-tech zones during the period from 2009 to 2014 have generally changed little. In other word it remained stable basically. However the change in average efficiency can still be roughly divided into two stages. Between 2009 and 2010, the average of TE and PTE and LUE shows an upward trend except the small decrease in SE, and the LUE increased significantly. After 2010, the average efficiency of each item showed a downward trend, which may be linked to China’s macroeconomic development. In 2010, the GDP growth rate of China reached a peak of 6 years. However during 2010– 2014, the economic downward pressure increased with China’s GDP growth rate keeping decreasing, and the pressure on resource input has tightened, which to a certain extent has also affected the efficiency changes in the Hi-tech zones. It is worth noting that the LUE have maintained a significant upward trend in the past six years, which is consistent with the notification of the ministry of land and resources of China on the evaluation of intensive land use in national development zones. As it shows, the national high-tech zones have the best level of intensive utilization and rapid improvement as a whole, whose land use pattern is constantly optimized and land-use efficiency trending to be improved. However, the score of TE and PTE and LUE is far from the optimal efficiency in 2009–2014. The low efficiency of land-use indicates that the actual input of land in the Hi-tech zones is still too large, and the extensive land-use is serious. The average value of SE is very close to the optimal efficiency and remains above 0.9 for 6 years basically, indicating that the reason for the low TE is mainly caused by the low PTE. The average value of PTE which is far from the optimal efficiency also proves it. It also shows that the high-tech zones fail to make full use of the current technical and management conditions to maximize the output. At the same time, the scale efficiency is very close to the optimal efficiency, which indicates that the scale effect of the
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economic development of high-tech zones is significant under the existing technology and management conditions. From another perspective, it also should be noted that the development of high-tech zones is mainly driven by scale expansion, which alarmed us to improve the level of technology and management in force. Table 1. Hi-tech zones efficiency of 75% in the 56 countries in 2009–2014 2009 2010 2011 2012 2013 2014
TE 0.859 0.900 0.910 0.882 0.852 0.857
PTE 1.000 1.000 1.000 1.000 1.000 1.000
SE 0.995 0.995 0.997 0.997 0.998 0.995
LUE 1.000 1.000 1.000 1.000 1.000 1.000
Table 1 shows the 75% quantile of TE and PTE and SE and LUE of high-tech zones. From 2009 to 2014, both of the 75% quantiles of PTE and LUE reached 1, indicating that the number of Hi-tech zones that achieve optimal efficiency is not less than 25%. Meanwhile the 75% quantile of SE is also near the optimal efficiency which turns out that 1/4 of the high-tech zones is in the optimal scale approximately. However, it is worrying that there is a gap between the 75% quantile of TE and optimal efficiency, showing that the number of high-tech zones that have reached technological efficient frontier is still less than 1/4. Obviously the phenomenon have increased the badly need to take some measures to improve the technical efficiency. Table 2. Amounts of Hi-tech zones with an efficiency value of 1 and an efficiency value of >0.9
2009 2010 2011 2012 2013 2014
TE =1 11 10 10 10 10 11
>0.9 13 14 15 14 14 13
PTE =1 17 19 18 17 16 18
>0.9 19 20 21 23 20 21
SE =1 11 10 12 10 10 12
>0.9 42 40 45 38 39 35
LUE =1 >0.9 17 18 19 20 18 20 17 22 16 19 18 21
As shown in Table 2, the number of high-tech zones with TE of 1 and greater than 0.9 have stayed the same basically during 2009 to 2014, which means that the capacity of the high-tech zones to utilize resources and technologies in a given scale has not made significant progress in the past six years. And the number of high-tech zones with PTE of 1 and greater than 0.9 has a very slowly increasing trend, illustrating that the capacity of the high-tech zones to make full use of resources and technologies have increased slightly when the six-year development scale is assumed to be the optimal size. The number of Hi-tech zones with SE greater than 0.9 is extremely large and the minimum number in six years is 35 accounting for 62.5% of the total number of
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high-tech zones. It turns out that the scale effect of the high-tech zones has performed well. But beyond that, high-tech zones with SE greater than 0.9 is in a clear decrease in the number, which shows that the change trend of scale of return of parks may be in a state of decline to some extent. The number of high-tech zones with LUE of 1 and greater than 0.9 also has increased slowly, signifying that the efficiency of land-use has raised during the 6 years and the land-use structure has improved. 3.2
Regional Difference Analysis of Land-Use Efficiency
In order to study the economic efficiency and land-use efficiency of high-tech zones in different regions, this paper divides 56 high-tech zones into eastern high-tech zones and central Hi-tech zones and western Hi-tech zones according to the east, middle and west economic belts. The specific directory is as follows (Table 3): Table 3. Regional division of Hi-tech zones East area
Central region Western region
Beijing, Tianjin, Shijiazhuang, Baoding, Shenyang, Dalian, Anshan, Shanghai, Nanjing, Changzhou, Wuxi, Suzhou, Taizhou, Hangzhou, Ningbo, Fuzhou, Xiamen, Jinan, Qingdao, Zibo, Weifang, Weihai, Guangzhou, Shenzhen, Zhuhai, Huizhou, Zhongshan, Foshan, Hainan Taiyuan, Changchun, Jilin, Harbin, Daqing, Hefei, Nanchang, Zhengzhou, Luoyang, Wuhan, Xiangfan, Changsha, Zhuzhou, Xiangtan Baotou, Nanning, Guilin, Chongqing, Chengdu, Mianyang, Guiyang, Kunming, Xi’an, Baoji, Yangling, Lanzhou, Urumqi
Fig. 2. Average efficiency of land use in Hi-tech zones in the three major regions
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Figure 2 shows the average LUE of the high-tech zones of east, middle and west area from 2009 to 2014. It is obvious to find that the LUE of eastern high-tech zones is much higher than that of the Midwest generally. In addition, the value of LUE presents a spatial distribution feature of east high and west low, which is mainly in accordance with the development pattern of east, middle and west economic belts. This may be relevant to the economic development stage, industrial structure, land use structure and resource endowment status of different regions. Compared to the midwest, the eastern region is economically developed in China. However, due to the increasingly strict control of the cost of resource utilization, the traditional industries in the eastern region have to land to the middle and western areas where the resource of land and labor are more abundant and cheaper. On the one hand, it is conductive to develop high-tech industries which is relatively intensive in land and higher technical content for the hightech zones in eastern region. As a result, the structure of land-use of the eastern hightech zones have been turning to intensive, meanwhile the LUE is higher than that of the midwest regions. On the other hand, it is beneficial for the high-tech zones in the middle and western regions to accelerate their own industrial development and speed up the industrialization in the process of accepting the industrial transfer in the eastern high-tech zones, in which the land-use efficiency and output have been continuously improved. As can be seen by the above, the difference of average LUE between the middle and western and eastern high-tech zones is gradually narrowing. The average LUE of eastern high-tech zones in 2009 was 0.288 higher than that of the middle hightech zones and 0.296 higher than that of the western high-tech zones while the average LUE of eastern high-tech zones was only 0.129 higher than that of the middle hightech zones, and only 0.159 higher than that of the western high-tech zones. The benefits and output of the Hi-tech zones have been continuously improved, and the efficiency of land use has been significantly improved. It can be seen that gap of the average ratio of land use efficiency in the Midwest and eastern Hi-tech zones have been narrowed. In 2009, the average efficiency of land use in the Eastern Hi-tech zones was 0.288 higher than that of the central Hi-tech zones and 0.296 higher than that of the Western Hi-tech zones, and in 2014, the average efficiency of land use in the Eastern Hi-tech zones was only 0.129 higher than that of the central Hi-tech zones, and only 0.159 higher than that of the Western Hi-tech zones. The gap in land use efficiency has shown a trend of shrinking year by year, and it is also a reflection of the effectiveness of the policy of the development of the western region of the country and the rise of the central region. The gap of average LUE have been shrinking during the past six years, which is also a reflection of the effect of the national policy of the West development and the Rise of Central China.
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Fig. 3. Average technical efficiency of Hi-tech zones in the three major regions
Figure 3 shows the average TE of the high-tech zones in eastern, middle and western regions in 2009–2014. Similar to the average LUE, the average TE of eastern high-tech zones is much higher than that of the midwest high-tech zones while average TE does not maintain a significant upward trend. It shows that the ability of making full use of technology and managing resources in the eastern high-tech zones is higher than that in the middle and western high-tech zones whose ability to utilize the technological resources needs urgently to be improved under a given scale. Figure 4 above shows the average PTE of the Eastern, middle and Western Hi-tech zones from 2009 to 2014. The average value of PTE in the eastern high-tech zones is much higher than that in the Midwest, and the gap between the average PTE of the middle high-tech zones and the eastern high-tech zones was narrowed, while the average value of PTE in the Western high-tech zones fluctuated slightly. That means the ability of utilizing technical resources in the middle high-tech zones have been improved, assuming that the established scale of the high-tech zones is the optimal scale. However the technological application and innovation ability of the western high-tech zones have not shown the trend of better. It is necessary to increase the investment of independent innovation and improve the ability of technological innovation in the western high-tech zone to undertake the industrial transfer in the eastcentral high-tech zones.
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Fig. 4. The average pure technical efficiency of Hi-tech zones in the three major regions
Fig. 5. Average efficiency of scale in Hi-tech zones in the three major regions
Figure 5 is the average SE of the east-west high-tech zones in the 6 years. Obviously, the average SE of the high-tech zones in the east and the middle is relatively close to the optimal efficiency, which shows that the SE of the high-tech zones in the
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mineast is better, and the intensive economic development pattern of land, capital, labor and technology is formed. The SE of the middle high-tech zones is slightly higher than that of the eastern high-tech zones, mainly because of the low efficiency of the Hainan high-tech zones in the east high-tech zones because of the poor coordination of factors of production such as land, capital, labor and technology which leads to the inability to exert scale effect. Compared with the middle and eastern high-tech zones, the average value of SE of the western high-tech zones is lower, which indicates that the scale effect of the high-tech zones in the west is poor, and the enterprises in the high-tech zones have not yet formed scale and it is unable to obtain economies of scale. 3.3
Comparative Analysis with Different Land Efficiency
Table 4 below shows the average TE, PTE and SE of the 11 Hi-tech zones with landuse efficiency of 1 and 10 high-tech zones with the lowest efficiency of land use during 2009–2014 (Table 5). Table 4. The average efficiency of high-tech zones with land-use efficiency of 1 Beijing Anshan Changchun Shanghai Suzhou Taizhou Ningbo Xiamen Shenzhen Zhongshan Yangling
TE 0.845 1.000 1.000 0.996 0.851 0.956 0.986 1.000 1.000 1.000 0.360
PTE 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
SE 0.845 1.000 1.000 0.996 0.851 0.956 0.986 1.000 1.000 1.000 0.360
Table 5. Average efficiency of 10 high-tech zones with the lowest efficiency of land use Baotou Changzhou Nanchang Zhuzhou Zhuhai Nanning Guilin Xian Lanzhou Urumqi
TE 0.520 0.602 0.597 0.596 0.572 0.592 0.504 0.701 0.426 0.468
PTE 0.536 0.608 0.612 0.613 0.589 0.619 0.612 0.840 0.501 0.637
SE 0.966 0.990 0.976 0.972 0.973 0.955 0.823 0.849 0.849 0.729
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The PTE of the 11 high-tech zones with LUE of 1 is 1, and the SE and TE of the 5 high-tech zones also reached the optimal efficiency. Since TE is the product of SE and PTE, the reason that the efficiency of the technology is not optimal is the SE not reaching the optimal for the other 6 high-tech zones whose TE has not achieved optimal especially the yangling agricultural high-tech zone. As capital, labor, enterprises and other factors of production has not yet formed scale, so can not achieve the scale effect. In addition to Xi’an high-tech zone, TE and PTE have not reached the average efficiency of 56 high-tech zones of the 10 high-tech zones with lowest land-use efficiency, which shows that the high-tech zones with low LUE is not good enough to utilize resources and technology under the established scale. Although some of the high-tech zones are above the average in terms of scale efficiency, they do not achieve optimal efficiency, indicating that the current production scale of the 10 high-tech zones with the lowest land efficiency is not the optimal scale (Table 6). Table 6. Leading industries of Hi-tech zones with land use efficiency of 1 Leading industries Electronic information, bio-medicine Energy conservation and environmental protection, new material Bio-medicine, optoelectronic technology, advanced manufacture technology, information technology, new material Integrated circuit, software, bio-medicine Shanghai Suzhou Electronic information, electrical machinery Taizhou Bio-medicine Ningbo Electronic information, bio-medicine, new materials and energy Xiamen Optoelectronic, electronic information, electric appliance, new material Shenzhen Electronic information, biological engineering, software, new material Zhongshan Electronic information, bio-medicine, new material Yangling Biological engineering, environmental protection, green food, tourism of agricultural Science and Technology Source: Li Jingxin. Research on industrial agglomeration and development of China High-tech Industrial Park. Wuhan University, 2011 Beijing Anshan Changchun
In 11 high-tech zones with LUE of 1, Beijing, Shanghai, Suzhou, Taizhou, Ningbo, Xiamen, Shenzhen, Zhongshan are located in the eastern coastal areas of China. The city is economically developed whose industrial structure is more optimized for the Midwest. In addition land resources are more tense relative to Midwest region. So there is the possibility and urgency of increasing land-use efficiency. Such as China’s first national high-tech zone—Beijing Zhongguancun National Independent Innovation Demonstration zone, sophisticated industrial structure has been preliminarily formed. And it takes the electronic information industry and the biomedicine industry as the leading industry, and has formed the large-scale industry agglomeration phenomenon that causes the scale effect in the park remarkable. This is why the land-use more efficiently. Shanghai Zhangjiang high-tech zone has formed two industrial clusters,
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including medical health industry and internet industry which based on internet and mobile internet, which is more intensive and more efficient for land-use than traditional industries. Although Anshan and Changchun are located in the northeast of China, where the development of economy is not optimistic, there are the old northeastern industrial base of China whose great industrial foundation is conductive to industrial development. In addition, the policy effect of rejuvenating the old northeastern industrial base of China is significant in recent years, which makes land output better and land use efficiency higher. Yangling high-tech zone is an agricultural high-tech industries demonstration zone, with biological engineering, green food, agricultural science and technology and agricultural tourism as the leading industry. What’s important is the environmental protection and biological engineering has formed a certain degree of agglomeration. Although the effect of scale has not yet played an excellent role due to the input of elements such as labor and capital insufficient, the optimal level of land-use efficiency has been achieved (Table 7). Table 7. Leading industries of 10 Hi-tech zones with lowest land use efficiency Leading industries Rare earth materials Electronic information, automotive and Construction Machinery Electronic information, application software, bio-medicine, Energy saving and environmental protection, household appliances, automobile manufacturer Zhuzhou Electronic information, electricity, non-ferrous metal processing Zhuhai Software, bio-medicine, data communications, network technology Nanning Bioengineering and medicine, electronic information, new material, mechatronics Guilin Electronic information, mechatronics, new material, biological engineering, environmental protection Xian Mechatronic, new material, electronic information, mechatronics, bio-medicine Lanzhou New material, bio-medicine, electronic information, advanced manufacture technology, energy conservation and environmental protection Urumqi Biological engineering, mechatronic, new energy Source: Li Jingxin. Research on industrial agglomeration and development of China High-tech Industrial Park. Wuhan University, 2011 Baotou Changzhou Nanchang
The 10 high-tech zones with the lowest LUE are all located in underdeveloped areas in middle and western China, except Zhuhai and Changzhou. The land-use efficiency and intensity of the above-mentioned high-tech zones is not satisfactory due to the macroeconomic development of the city, although it is still dominated by hightech industries. In addition, most of the leading industries in the above-mentioned hightech zones have a low degree of agglomeration, which results in failing to give full play to the agglomeration effect and lower output. Finally the land-use efficiency are badly affected.
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Analysis of Optimization of Land-Use Efficiency
It can be seen from the above research that the target value of land input in this paper is determined when both technical efficiency, pure technical efficiency and scale efficiency are achieved at the same time. Therefore the adjustment of input factor in hightech zones with inefficient land use efficiency should not only include land, but also labor and capital. The following analysis is about the adjustment direction and scale of production factor input in high-tech zones without DEA’s effectiveness based on the DEA results in 2014.
Fig. 6. Adjustment of input factors in 56 Hi-tech zones in 2014
As shown in Fig. 6 above, there are 18 high-tech zones such as Beijing and Shanghai that is unnecessary to be adjusted for input factors in 2014, accounting for 32% of the national high-tech zone. In other word, nearly 2/3 of high-tech zones have redundant input of production factors. Moreover it can be clearly seen from the figure that the adjustment range of most high-tech zones is relatively large, and some of them are even over 30%, indicating that the waste of production factors in high-tech zones is serious. More seriously, the adjustment of land is the largest and even the three hightech zones in Changzhou, Zhuzhou and Nanchang is more than 85%. It turns out that the land-use waste of high-tech zones is definitely serious and the development pattern is given priority to with extensive land-use. There is particular concern about land structure improvement, which may be related to the fact that local governments take land leasing as a preferential policy to attract investment for granted. The adjustment of the capital element is larger than that of labor element, indicating that the industrial structure of high-tech zones have a trend of changing from labor-intensive to capitalintensive, which is in accordance with the prediction of the imminent disappearance of
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“demographic dividend period” in China, which is helpful to tap the development potential of high-tech zones. In general, there are large redundancy in the input of three kinds of production factors. Based on the consideration of saving resources and promoting the sustainable development of high-tech zones, it is pressing for all high-tech zones to accelerate the adjustment of input of production factors, avoid resource waste, improve the structure of input of production elements and promote the transformation and upgrading of industrial structure.
50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0%
2009
Adjustment of land elements 45.72% Adjustment of labor elements 21.51% Adjustment of capital elements 21.14%
2010
2011
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39.49% 20.37% 20.69%
44.77% 19.48% 20.24%
37.14% 18.70% 24.89%
38.02% 20.10% 28.24%
35.93% 18.91% 20.91%
Fig. 7. Changes in the adjustment range of production factors in Hi-tech zones from 2009 to 2014
Figure 7 shows the changes in the adjustment range of land, labor, and capital in all 56 Hi-tech zones in 2009–2014. It is obvious that the adjustment range of land use area shows a significant downward trend. The adjustment range of land use area has decreased by nearly 10% in the six years, indicating that the land use efficiency of hightech zones has been continuously improved. It also showed that land-use structure have been improving and the development pattern of land-use have gradually changing from extensive to intensive. However, the adjustment range of land area is much higher than that of capital and labor, indicating that the waste of land resources in high-tech zones is still serious in the past six years, probably because the situation of attracting investment with land as a preferential policy is relatively common. Over the past six years, the adjustment range of the number of employees and the assets at the end of the year has slightly decreased. The adjustment of the number of employees is the smallest of the three types of input factors, which indicates that the industrial structure of hightech zones have shifting from labor-intensive to capital-intensive. Overall the sustainable development of high-tech zones still needs technical progress to support.
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4 Measures and Suggestions It is time to strengthen the property of land as assets and capital and implement unified accounting of land assets under with the opportunity of the establishment of the Ministry of Natural Resources, which aim at the scientific management of land resources. The establishment of Ministry of Natural Resources means to take natural resources as a unified whole for consideration, which is consistent with the integration of the input and output of the economic system. The overall improvement of efficiency of the economic system is strongly linked to the optimal combination of all kinds of production factors including land resources. It is also crucial to improve the current institution of land supply and land expropriation, which is helpful for restoring the market value of land, making the enterprise invest under the inherent constraint of the land cost and urging enterprises to assume the social responsibility of land-use. The high-tech zones are an important driving force of China’s economic development, which leads to its unique advantage in land supply. Therefore it is common that the land cost of high-tech zones are not satisfactory. At present, the land efficiency of high-tech zones in China has not been increased because of the increase of input of land. On the contrary, the results show that the land supply in high-tech zones still has a greater redundancy which means that the development pattern is driven by extension land expansion till. And it is urgent to optimize the land structure. In the future development and construction of high-tech zones, it is necessary to strengthen the formulation and strict implementation of the land-use planning, improve the existing structure of land-use, optimize the layout of land-use, rationally control the land scale, and take the road of land conservation and utilization. Industrial structure plays a crucial role in the land-use structure and land-use efficiency of high-tech zones. However the major industries are quite similar based on the comparative analysis of the major industries of 11 high-tech zones with the optimal land-use efficiency and 10 high-tech zones with the lowest land-use efficiency, indicating that each high-tech zone has not formed its own characteristic industries. Therefore it is worth emphasizing the rational planning and optimization of the industrial structure based on the development level of region, resources conditions and advantages [3]. Carrying out a planned and focused system of industrial cultivation and development and produce the characteristic industries of their respective high-tech zones to avoid uniformity in the industrial structure. Meanwhile it is an effective way to improve the efficiency of land-use by cultivating and developing regional brands to form large-scale industrial agglomeration and achieve scale effect. In terms of land supply, local governments, for the purpose of promoting local economic development and increasing revenue, usually take “low land price” or even “zero land price” as a tool to attract investment in the process of attracting investment [4]. Even though many local governments have already provided land in accordance with the requirement of the lowest price of industrial land, they have subsidized the land in other ways, which has not changed the essence of the low cost of land in hightech zones. Apparently it is the way of land supply that can neither embody the market value nor impose cost constraints on enterprise land-use. To sum up, it is important and urgent for local government to change the concept of land supply. It is the
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responsibility of local governments to restore the land market price mechanism, innovate the way of land activating, clarify the cost of land elements and put an end to the behavior of offering land with low price and zero price. Moreover the government should do a good job in the examination and approval, law enforcement and market supervision of the land-use of industrial park. In the process of land use, enhanced sense of social responsibility for enterprises in the park is urgently needed. Enterprises avoid to the land suppliers, that is the local government, to demand more than the need for their own development, which will lead to the hoarding and idling of land resources, which is an effective way to reduce land waste and strengthen the economical and intensive use of land resources. Additionally, sustainable development of enterprises is the precondition for improving land-use efficiency. Therefore, enterprises in high-tech zones are bound to enhance their ability of technological innovation and management so as to satisfy the land-use efficiency and economic efficiency.
References 1. Charnes, A., Cooper, W.W., Lewin, A.Y., et al.: Data Envelopment Analysis: Theory, Methodology, and Applications. Springer Netherlands (1994) 2. Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision-making units. Eur. J. Oper. Res. 3(4), 339 (1979) 3. Li, J.: Research on industrial agglomeration and development of China High-tech Industrial Park. Wuhan University (2011) 4. Zhang, X., Lin, Y., Wu, Y., et al.: Industrial land price between china’s pearl river delta and southeast asian regions: competition or coopetition. Land Use Policy Int. J. Covering All Aspects Land Use 61, 575–586 (2017)
The Evaluation of Land Development and Utilization Based on 11 Prefecture-Level Cities in Hebei Province Yongsheng Wang, Yuan Zhang, Yulong Li, and Guijun Li(&) School of Management Science and Engineering, Central University of Finance and Economics, Beijing, China [email protected]
Abstract. This paper presents the evaluation of land development and utilization of 11 prefecture-level cities in Hebei Province. Based on the revision of previous evaluation indicators, we firstly set four new indicators including population density, per capita living space, per capita area of land used for construction and built-up area/urban area. Secondly, the geographical differentiation of all prefecture-level cities in four indicators is compared; Thirdly, the time series network method is used to establish the similarity matrix between cities, and each city with the provincial average level as well. Through these processes, we can quantify and compare the relative level of land development and utilization for each city. Finally, we believe that this work is important to the integration process of Beijing-Tianjin-Hebei and the easing of non-capital functions. Keywords: Land development and utilization
Evaluation Hebei province
1 Introduction The shape and surface of our cultural landscapes are driven by a multitude of factors and stressors, particularly urban areas representing a land use type of probably the highest density and intensity of multiple land uses [1]. In China, with acceleration in urbanization process, a large of rural population continuously move to cities, which give rise to high-density population in cities [2]. On the one hand, due to the constraints of geographic space in cities, the growth of cities makes the land more scarce and precious. Therefore, it is extremely urgent to explore potential for urban land and facilitate intensive use of land [3]. On the other hand, extensive operation of land, blind expansion and low efficiency are serious in our country at present [4]. As consequence, it is of great significance to assess rationality of urban land use conditions for a specific district. Land use intensity is an indication of the amount and degree of development of the land in an area, and a reflection of the effects and environmental impacts generated by that development [5]. In general, in early stage of urbanization, urban expansion has low demands of land and the land supply can meet demands of expansion. With constant accumulation of population and factors of production in cities, and directly driving by economies of © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 214–225, 2021. https://doi.org/10.1007/978-981-15-3977-0_16
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scale, enlargement in production scale and expansion of industry spatial agglomeration will expand the size of urban land development and utilization [6]. There is no doubt that the increase in land development level does not indicate land utilization is more reasonable. In most cases, increase in land development level is on the premise of damaging ecological benefits and this is the beginning of unsustainable utilization of land [7]. Therefore, it is necessary to control intensity of urban land development and utilization and realize coordination and sustainability of economic benefits, social benefits and ecological benefits [8]. Then, how to assess current situation and level of land development and utilization in cities at present? In previous researches, scholars have proposed many evaluation indicators and frequently used indicators include land development rate, land supply rate and land construction rate [9–11] as well as some detailed items such as industry, commerce and road construction [12, 13]. Nevertheless, these indicators are only for single-dimension evaluation of land utilization in cities. In case focus on land ignores that the land development in driven by human kinds, it shall be subject to development of human kinds. As for cities with different population sizes, even though their development rate and construction rate are basically the same, economic benefits, social benefits and habitat benefits produced by land utilization have great difference. Hence, to explore the development and utilization of urban land, we need to consider urban population size so that the development level of urban land can be assessed more accurately. To consider population factor, we also need to emphasize many indicators such as population density and per capita area of land used for construction [4, 14]. Provided the land used for urban construction is stable, the higher the population density is, the higher the urban development and utilization level will be and the worse the comfort and convenience in city will be. Moreover, apart from population density, we shall also consider living conditions of human kinds, namely per capita living space; apart from per capita area of land used for construction, we shall comprehensively consider spatial scale of urban construction, namely the proportion of built-up area in total area of city. As a consequence, four indicators/observation dimensions (namely population density, per capital living space, per capita area of land used for construction and area of built-up area/municipal district) have been determined in the research to measure and assess development and utilization level of urban land. As for specific evaluation methods, analytic hierarchy process [15], entropy evaluation method [12], weighted average method [9] and comprehensive evaluation [14] are mainly adopted in previous researches and some foreign scholars have introduced geographic information technologies such as RS [16] and GIS [17]. The problem is that these methods are selected from a certain time to analyze land use conditions in single or multiple cities and thus the long-term dynamic changes are ignored. The analysis on trend change is mainly aimed at comparison of simple characteristics and few analyses can be carried out to accurately quantify similarity in change trend among different cities. In view of this, time series network method will be adopted in this paper to compare land development and utilization level among different cities within a province, summarize their similarities when the changes happened in timeline and thus provide some enlightenment for sustainable development of urban land for other cities.
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In this paper, all prefecture-level cities (11) in Hebei Province located in North China Plain are selected as analysis objects. The reasons for selecting this province are as follows: 1) The province has high population density and the urbanization process is very fast. Besides, there are few in-depth analyses on urban land development and utilization about this province so far; 2) The west and north of the province are mountains and plateaus, and the south central is in North China Plain. Therefore, this province shows great difference in urban characteristics and population density as well as varying land development degrees in different cities; 3) In recent years, coordinate development in Beijing, Tianjin and Hebei is regarded as important national strategy. Therefore, it is of great significance to analyze internal diversity in Hebei Province, unravel non-capital functions, speed up integration process in Beijing, Tianjin and Hebei, and prepare targeted regional development plan. Based on the above-mentioned discussion, the rest of the paper is structured as follows. In Sect. 2, the background of Hebei Province and its prefecture-level cities will be introduced. In Sect. 3, the relevant data and methods are described. Section 4 shows the static comparison of different prefecture-level cities on the four indicators, and then measure the difference of their land development and utilization level. Section 5 shows the similarity evaluation of these cities on the four indicators and some discussions are made. In the final section, we draw some useful conclusions.
2 Background In 2016, the total area of Hebei province is 187693 square kilometers (sq.km) and it mainly consists of mountain (37.4%), plain (30.5%), plateau (12.97), basin (12.1%) and few of other land which can not be easily utilized. At the end of 2016, the total permanent resident population is 75195200, increasing by 494700 than that of last year. In all permanent resident population, permanent resident population in cities and towns is 41364900, increasing by 1534600 than that of last year; its proportion in total population (urbanization rate of permanent resident population) is 55.01%, increasing by 1.69% that that at the end of last year. The urbanization rate of registered population is 39.89%, increasing by 1.16% that that at the end of last year. As for four evaluation indicators, the population density of whole province in that year is 398 people/square kilometers (sq.km), per capita living space of urban people is 33.45 square meters (sq. m), per capital area of land used for construction is 77.18 square meters and the proportion of built-up area/urban area is 23.1%. There are 11 prefecture-level cities in Hebei province and the provincial capital is Shijiazhuang City with area of 13056 square kilometers and GDP is 321.5 billion RMB (13056, 321.5). Likewise, other cities from north to south are respectively: Chengde (39493, 30.5), Zhangjiakou (36797, 66.5), Qinhuangdao (7802, 93.4), Tangshan (13472, 332.4), Langfang (6382, 90.3), Baoding (22185, 114.1), Cangzhou (14035, 71.0), Hengshui (8815, 400.0), Xingtai (12433, 31.4) and Handan (12065, 136.6).
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3 Data and Methods 3.1
Data Source
The data of this research are from China City Statistical Yearbook and the time is from 2007 to 2016. The indicators used in paper including annual average population (10000 persons), total land area of administrative region (districts under city), built-up area, area of land used for urban construction, area of land used for living and land used for urban construction as percentage to urban area. 3.2
Research Method
As for the research methods, time series data are used to construct trend network (time series network), thus reflecting similarity in changes of land development and utilization in different cities. In fact, all data in indicators of city development can be deemed as time series data but it is not easy to quantify and summarize changes and trend of these data. In case time series network is adopted, data change trends of all indicators can be converted into network structure. On this basis, all indicators can be used to describe the network and to know quantified data about development trend of all indicators. These quantified data are comparable to generate similarity distribution of all indicators in different cities. Rules to establish time series network are as follows (Fig. 1). a. Connecting side shall be established for both sides of time series b. Large number will keep out data behind c. The interval in the middle has specific numerical value. In case the average value of both ends is greater than the median, connecting side shall be established between both nodes d. When interval in the middle has two numerical values, connecting side shall be established in case the value at 1/3 and 2/3 position is greater than corresponding value e. The rest can be done in the same manner. Cosine value of included angle of two vectors can be measured to determine their similarity. The cosine value of 0-degree angle is 1 and cosine value of any other angle can not be greater than 1; the minimum value is −1. Cosine value of included angle of two vectors can be also used to determine whether two vectors roughly point to the same direction. In case two vectors have the same direction, the value of cosine similarity is 1; if included angle of two vectors is 90°, the value of cosine similarity is; when two vectors point to two totally opposite directions, the value of cosine similarity is −1. In case results are unrelated to length of vectors, results are only related to pointing direction of vectors. In general, cosine similarity is used in positive space and its value is 0 to 1.
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Fig. 1. The schematic diagram of rules to establish network
n P
Ai Bi AB i¼1 ¼ sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi similarity ¼ cosðhÞ ¼ k A k kB k n n P P ðAi Þ2 ðBi Þ2 i¼1
i¼1
4 Static Comparison of Land Utilization in All Cities This part will reflect distribution of spatial difference (as shown in Fig. 2) of 11 prefecture-level cities on four indicators of land development and utilization in Hebei Province. By comparing the performance of each city on different indicators, we can observe the relative level of land utilization. In addition, the correlation between different indicators helps to analyze the current situation and problems of land use among 11 cities in a more comprehensive way. 4.1
Population Density
The population density refers to the proportion between permanent resident populations in city and land area. It reflects density of population distribution in spatial scale of city. If this indicator is too low, it means intensification degree in cities is insufficient and it may cause jam if this indicator is too high. Population density is directly related to regional
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natural environmental conditions and social and economic development. Populated regions in Hebei are mainly in plain areas and/or areas with convenient transportation. In 2016, the average population density in Hebei Province was 950 person/sq.km. There are 5 cities below this level and 6 cities above this level respectively. Among them, the top three cities with highest population density are Cangzhou (3060 person/sq.km), Langfang (2945 person/sq.km) and Xingtai (2094 person/sq.km). The city with the lowest population density is Zhangjiakou, only about 1/9 of Cangzhou. We can see that the population density among cities are remarkable difference. 4.2
Per Capita Living Space
Per capita living space means the proportion between area of urban residence and urban population and it reflects whether urban land utilization structure conforms to population agglomeration scale. It is clearly that the per capita living space in Shijiazhuang and Langfang with highest population density is relatively smaller while Cangzhou has larger living space. Besides, the per capita living space in Chengde which located in north is relatively larger. In other cities such as Zhangjiakou and Handan, the per capita living space is at the minimum level. In 2016, the average per capita living space in Hebei Province was 31.5 sq.m and 8 cities below this level. The gap between the largest and the smallest cities in this indicator reached 2.66 times. 4.3
Per Capita Area of Land Used for Construction
Per capita area of land used for construction is the proportion between area of land used for construction and total population. It is an important indicator to measure coordination degree between development of construction land and population increase. The distribution of this indicator is basically same as per capita living space and it indicates that housing construction in all cities conforms to overall construction of these cities. The overall distribution trend is, the development level in eastern cities (coastal and plain areas) is relatively higher while development level in western cities is relatively lower. In 2016, the average per capita area of land used for construction in Hebei Province was 69.2 sq.m. There are 5 cities below this level and 3 cities over 100 sq.m. As we can see from the Fig. 2, the per capita living space have similar distribution with per capita area of land used for construction, which means the pace of construction between municipalities and human settlements is largely consistent among cities. 4.4
Built-Up Area/Urban Area
Usually, area of built-up area/municipal area can reflect land utilization rate in cities. We can see that top-ranking cities include Cangzhou, Langfang, Xingtai and Shijiazhuang and these cities are basically developed areas or plain areas, which consistent with the results reflected in other indicators. In general, in a certain population density, the greater proportion of built-up area in urban area, the larger the per capita living space and per capita area of land used for construction will be. In the provincial capitalShijiazhuang, the built-up rate is close to the provincial overall level, but its high population density reduces its per capita living space and built-up area. In 2016, the
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Fig. 2. The degree of land utilization for 11 prefecture-level cities
built-up area/urban area in Hebei Province was 7.3%. There are 5 cities below this level and the city with highest rate is Cangzhou, close to 40%. As the original region of Xiongan New Area, the proportion of built-up area in urban area of Baoding just at medium level (7.3%), and there will be much room for its improvement in the future. At the same time, as one of the host cities for the 2022 Winter Olympics, the rate of this indicator for Zhangjiakou is only 2.3%, and a large amount of infrastructure construction will greatly increase this proportion.
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5 The Similarity Evaluation of Land Utilization in All Cities In this part, we use the 10-year data from 2007 to 2016 to obtain the changes of time series network of 11 cities, and then establish the similarity matrix (as shown in Fig. 3). The advantage of this method is that it can make the comparison of land use changes among cities become possible (enhance comparability of all cities). We will use the average level of Hebei Province as a benchmark to analyze the relative degree of deviation from the average level for each city. It is generally acknowledged that the similarity value below 0.4 is the low level and the value above 0.8 is the high level and the value between both values is the general level.
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The trend of population density in the whole province of Hebei is as follows: steady increase from 2007 to 2014, sharp decrease in 2016 and slight increase in 2016 (Fig. 4). In general, the population density decreases to 95 person/sq.km from 106 person/sq.km. Take the average level of whole province as a benchmark, the cities show the highest similarity degree are Baoding (0.81) and Zhangjiakou (0.81). Both are steadily increases in early stage but turns to sharp fluctuation in later period. In general, they show the decrease tendency. The lowest similarity degree is Handan (0.39). Even though it steadily increases in early stage but sharp decrease since 2014 and there is no increase sign later on. 5.2
Per Capita Living Space
The trend of per capita living space is basically the same as population density and the only difference is the trend of former indicator decreased in 2014, which means the supply speed of housing area was lower than increase of urban population that year. We can see that the city has similarity level closest to provincial average level is Baoding (0.80). Although their interannual change is consistent, in later periods, Baoding showed sharp decrease and therefore its housing area declined to the value (21.75 m2) below provincial average level in 2016 from the highest level (39.96 m2) in the whole province in 2008. The city with lower similarity degree is Chengde and it shows a trend of fluctuating increase. It increases in most of time but the decrease range in some year is small. Besides, the similarity degree between Xingtai, Zhangjiakou, Cangzhou and province average level below 0.5.
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Per Capita Area of Land Used for Construction
The trend of per capita area of land used for construction for whole province is the increase from 2007 to 2011 and fluctuating decrease in later period. In general, it decreases to 69.15 m2 from 77.18 m2. The similarity level of all 11 prefecture-level cities are above 0.6 and the city with highest similarity is Shijiazhuang (0.84). It increases slowly in the beginning and decreases sharply in later period. Therefore, the overall per capita area of land used for construction decreases. 5.4
Built-Up Area/Urban Area
The trend of the built-up area/urban area for whole province shows fluctuating increase from 2007 to 2012 and sharp decrease after 2012 and the proportion decreases to 7.3% from 23.1%. The built-up area in cities will increase with the increase of urbanization rate. Therefore, decrease of the proportion is mainly due to substantial expansion of urban area. For example, in Shijiazhuang, the urban area in 2013 is 306 square kilometers. But in 2014, after three counties such as Gaocheng, Luquan and Luancheng were revoked and turned into cities from aspect of administrative division, the urban area sharply increased to 2243 square kilometers and the indicator decreases to 11.8% from 70.9%. Compared with average changes in Hebei Province, similar cities include Xingtai (95.4%), Chengde (86.1%) and Tangshan (82.0%). All these cities go through the process of increase and sharp decrease, which indicates urban area of these cities are expanded at the same time. Other cities with lower similarities do not indicate that they have not experienced substantial expansion, but there are differences in the time of expansion. As for Handan with lowest similarity (0.42), it is stable in early stage but the sharp decrease occurred in 2016. That is why its network structure has the lowest similarity with the provincial average level. When we combine the dynamics of the indicators with its static distribution characteristics, we can make some discussion. In terms of the value of population density, the southern plains and convenient transportation areas show relatively high in the context of the overall population density gradually decline. At the same time, the population density of some cities in southern Hebei continues to increase (Cangzhou, Langfang), which aggravates the difference between cities in the province. In fact, cities with increased population density are generally closer to Beijing and Tianjin. With the rise of housing prices and the penetration of high-speed intercity railways, more and more people working in Beijing and Tianjin areas choose to buy houses in these cities. The population density declining will directly lead to the expansion of urban per capita living space (Xingtai), while the expansion of urban housing construction will also alleviate the negative impact of urban population growth (Cangzhou). In any case, the population density and housing construction should be carefully considered when determine the speed of urban land development. Per capita area of land used for construction reflects the relationship between overall construction level and the population density. We can see that the cities in the southeast are higher in this index, and they grow faster as well, while the cities in the central and western regions tend to decrease. Finally, we use the built-up area/urban area to reflect the land
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utilization rate of each city, and found that most cities have experienced a significant decline, which is mainly caused by the expansion of urban area in recent years.
6 Conclusion In this paper, we have discussed the land development and utilization in 11 prefecturelevel cities in Hebei province. The main findings of the research are as follows: 1) cities in plain and/or with developed economy are higher in two indicators such as population density and proportion of built-up area/urban area; 2) Higher population density will reduce per capita living space and per capita area of land used for construction and therefore requirements on urban land development are much higher; 3) Too fast population urbanization will make supply speed of housing lower than increase of urban population and thus damages livability and conform of cities; 4) In recent years, most of cities in Hebei Province show rapid expansion of urban area and therefore the proportion of built-up area in the whole city is very low. Based on this, we believe that urban land development must maintain the coordination between population growth, construction development and land expansion. Any part of them changes too quickly or too slowly will reduce the efficiency of land development and utilization. Moreover, in the context of the Beijing-Tianjin-Hebei integration and the easing of non-capital functions, the cities around Beijing, Tianjin and Hebei shall combine their own land development and utilization with coordinated development plan of Beijing, Tianjin and Hebei. For further research work, we can also do some predictions and simulations. For example, the land development and utilization trend of all cities in the medium and short term can be predicted according to time series network. Of course, to achieve these goals, more in-depth theoretical and methodological explorations need to be carried out.
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The Study of the Expansion of Urban Functional Land in Ganzhou Xiying Hu, Cuiping Huang(&), and Wei Wu School of Urban Construction, Jiangxi Normal University, Nanchang, China [email protected]
Abstract. As one of the fastest growing regions in the world, the expansion of China’s construction land has attracted wide attention. This paper comprehensively analyzes the expansion strength, expansion rate and expansion direction of three different construction functional land (residence, industry and commerce) in Ganzhou City, and further discusses the influencing factors of urban land expansion. Aim to provide a scientific reference for the expansion of urban functional land use, spatial planning pattern of land use optimizationly and regionaly. The research shows that the residential land expansion is the most intense and continues to extend to the periphery of the city. The expansion of industrial land is greatly affected by the policy, and its expansion along the transportation hub is obvious. The expansion of commercial land is gradually accelerating and is closely related to the expansion of residential land. There are main factors influencing the expansion of urban construction land in Ganzhou, including natural conditions, economy, population, transportation, policy and urban planning. And the driving effect of transportation facilities construction is most significant. Keywords: Ganzhou city Construction land Extended feature Mechanism of influence
1 Introduction The expansion of urban construction land is the most prominent feature of urban development in space. It is an area of common concern of many disciplines such as urban geography, land science, and urban planning [1]. It is of great significance to carry out this research in order to optimize urban land patterns and urban spatial structure and achieve sustainable urban development [2, 3]. The study of urban space in China started relatively late. With the accelerating process of economic development and technology of RS, GIS and remote sensing, the study of urban spatial expansion has developed rapidly. For example, Wang Q [4] analyzes the urban expansion and driving force in Nanjing from 1979 to 2005 by Landsat Image; Shen F et al. [5] used remote sensing images and based on geoscience information map to analyze the spatial and temporal characteristics of urban expansion and driving force in Hefei from 1987 to 2011. Huang H C et al. [6] analyzed the urban spatial trajectory of the core area of Tianjin since 1998 based on RS and GIS technology, and preliminarily predicted the trend of urban spatial expansion; In terms of research methods, many scholars have © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 226–234, 2021. https://doi.org/10.1007/978-981-15-3977-0_17
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introduced measurement indicators such as expansion speed, expansion strength, compactness, fractal dimension and spatial autocorrelation index [7–10], based on which the spatial morphological characteristics and temporal and spatial evolution of urban areas are studied. such as Li Y and Feng Y [11] make a comprehensive analysis of the quality of ecological land and temporal, spatial features and foemoation mechanism of ecological land’s evolution in Tianjin through the use of center of gravity transfer model, kernel density estimation, geographical detector and marketvaluing method of ecosystem services; while Xiao L, Tian G J etc. [12] introduced the urban extended area index quantitatively identifying the urban expansion model, and combined the quadrant orientation method and the buffer zone method to analyze the spatial expansion characteristics of Tianjin. With the deepening of research, more and more scholars have begun to pay attention to the internal relationship between urban functional land use and urban expansion. For example, Liu X T and Gu C L [13] took Nanjing as the research object, and the research shows that residential land, industrial land and commercial land show different spatial structures; Qu A X and Qiu F D [14] extract the information of residential, industrial, and commercial land and study on the temporal and spatial patterns of urban construction land expansion by circle grid analysis in Xuzhou. It is found that the succession of urban functional land is the intrinsic reflection or spatial response of urban spatial expansion, urban functional agglomeration and diffusion, which can reveal the intrinsic characteristics of urban spatial expansion and the spatial representation of urban functional agglomeration and diffusion. In summary, the current research results of land use are abundant, but most of them focus their research on single aspect like the expansion mode or mechanism, what’s more,the results on urban functional land research are few. Due to the imbalance in urban development, the research on urban expansion in China is mostly concentrated in developed regions such as Beijing, Shanghai, Tianjin and Guangzhou. There are few researches on the expansion of functional land for the construction of underdeveloped cities in China. Ganzhou City is an inter-provincial fringe city with abundant natural resources and developed geographical location. In recent years, its economy has developed rapidly and the land use has undergone dramatic changes. Therefore, it has certain practical significance for the study of functional land in Cangzhou City, and will further enrich the research results of urban space expansion. Based on this, this paper uses the ArcGIS 10.2 platform to adopt research methods such as expansion intensity and expansion rate, to makes a comprehensive analysis of the intensity, rate, direction, and influencing factors of the three types of functional land in Ganzhou City. The paper’s goal is to obtain the characteristics of urban functional land expansion and its expansion influence mechanism in Ganzhou City, and to grasp the laws and trends of urban land expansion. It is believed that the functional land use in the built-up area of Ganzhou City provides a scientific reference for the expansion of land use and the rational use of regional land, and provides empirical sample support for the expansion of land use in underdeveloped areas of the country.
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2 Research Methods and Data Sources 2.1
Data Sources
The data in this paper is derived from the overall urban planning and land use planning of Ganzhou City provided by government agencies, which guarantees certain reliability and authenticity. Methods of data processing are: Data on functional land-use were extracted from the current status map of urban land use in the three time periods of 2003, 2010, and 2016. Construction land includes residential land, industrial land and commercial land. Combining data from the second land survey in Ganzhou City with ArcGIS10.2 platform, it can correct spatial pattern. The spatial distribution map of functional land expansion in central downtown of Ganzhou is made by overlay analysis, which is beneficial to analyze the direction of expansion of functional land. 2.2
Study Area
Ganzhou (24029’-27009’N, 113054’-116038’E) is located in the southern part of Jiangxi province. It is adjacent to the Pearl River Delta, the Hercynian economic zone and the Pearl River Delta. It is the fastest-growing inter-provincial border in Jiangxi province which has obvious advantages in location. The research object of this article is the downtown area of Ganzhou City. With reference to the new round of the 《2012– 2030 Master Plan of Luzhou Metropolitan Area》, the city of Ganzhou has expanded the scope of the original central city area. In 2013, Nankang withdrew from the county, and in 2016, the county was withdrawn. In the counties and districts, the new construction of the Rongjiang District was started. The built-up area of the central urban area was expanded to 158 square kilometers, and some of the surrounding counties, especially the Bohai Bay area, were allocated to the planning area of the new central city and the development framework of the city was expanded. The construction area of Ganzhou includes: Zhanggong District, Jingkai District and Rongjiang District; Nankang District, Rongjiang Street, Dongshan Street, Longling Town, Jingba Town, Taiwo Township, Tangjiang Town, Longhua Township, There are some administrative villages in Zhufang Township; the whole area of Meilin Town in Yuxian District and some villages in Maodian and Chutan have a total area of about 1,165 square kilometers. This study selects the second level of the core area of Luzhou City as the research area, including the four counties of Zhanggong District, Jixian County, Nankang City, and Shangyou County. This region is the key development area during the planning period, and is also the land use change and The region with the most severe conflicts between man and land has a certain significance in the analysis of the expansion of functional land use. 2.3
Research Methods
2.3.1 Expansion Intensity Expansion intensity index is used to describe the percentage of expanded area of certain type of land accounts for total land area of that category in a given period of time,
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which is used to compare the intensity of land expansion in different periods. The formula is: K¼
Ub Ua 1T 100% Ua
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In this formula: K is the expansion intensity index of construction land during the research period; Ua is the area of this type of land at the beginning of the study; Ub is the area of this type of land at the end of the study; T is the interval number of years. 2.3.2 Expansion Rate Expansion rate index refers to the extent of land area change per unit of time, which is used to represent the overall scale and trend of expansion of urban construction land. The formula is: S¼
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In this formula: S is the expansion rate index of construction land; MUij is the extended amount of urban area of administrative unit i during j period; Mtj is the time span of j period; ULij is the built-up area of the administrative unit during the early time of j period.
3 Pattern Analysis of Expanding Process of Construction Land 3.1
The Expansion Intensity and Rate of Construction Land
Based on ArcGIS10.2 and overlay analysis of current situation land-use map of Ganzhou City, spatial statistics of the functional space scale for the three years (Table 1). According to Eqs. (1) and (2), the expansion intensity and the expansion rate of three different functional lands are calculated respectively (shows at Fig. 1 and Fig. 2). From the aspect of expansion intensity, the two-stage expansion intensity of residential land ranks the top of the three. The expansion rate of residential land (14.65%) was largest during 2003−2010.The expansion rate of commercial land in 2010–2016 was 13.72%, which was higher than the 6.56% of residential land and promoted to the top. The expansion intensity of the residential land is equivalent. They are 0.21% and 0.20%, respectively. During the period of 2010−2016, its expansion rate was 7.16%, a decrease of 7.49% comparing with the previous period. The expansion intensity and the expansion rate of industrial land have declined from 2010 to 2016. Compared with the same period of 2003–2010, they decreased by 0.05% and 8.68% respectively. Contrary to residential land and industrial land, expansion intensity and expansion rate of commercial land are significantly higher than the previous stage. The respective rate of increase was 0.04% and 8.50%.
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2003–2010 Extended pieces (piece) Residential land 1094 Industrial land 406 Commercial land 591
Amplified area (ten thousand m2) 2070.36 1961.55 396.7
Fig. 1. Comparison chart of expansion intensity
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2010–2016 Extended pieces (piece) 2070 617 517
Amplified area (ten thousand m2) 2095.22 1456.52 598.42
Fig. 2. Comparison chart of expansion rate
The Direction of Functional Land Expansion
3.2.1 The Expansion of Residential Land From 2003 to 2016, the residential lands generally have a spatial pattern of south-west to north-east direction. As Zhang River and Gong River enclose the Hetao old city, it limits the scope of citizen’s activities and the distribution of residential land in early time to some extent. The resident population of Zhanggong District is the most populous, so the residential land in 2003 is mainly distributed near the Gold Campus of Gannan Normal University in Zhanggong District. In 2010, the expansion of residential land towards the north-east and south-west appeared to decrease. But Zhanggong District is still a hot area for the expansion of residential land. In 2016, the residential expansion center and direction of expansion moved northwestward. The expansion constantly breaks the shackles of urban landscape pattern instead of limiting to internal padding. Thus it affects the expansion of the entire living space. 3.2.2 The Expansion of Industrial Land Expansion of industrial land is slightly different from that of residential land in central area in Ganzhou. The industrial land expansion center was located near the People’s Government of Shuinan Town, Zhangjiang New District in 2003. Driven by the development of industrial zones and the construction of new districts, industrial land took the lead in breaking through the landscape pattern of the two rivers in Ganzhou, extending across the river to the Ganzhou Economic Development Zone, and expanding in a contiguous manner to form a sub-center of the new city. In 2010, under
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the development strategy of undertaking gradient transfer of coastal industries, industrial parks based on Ganzhou Economic Development Zone to guide agglomeration of industrial land. The scale of disordered and dispersive expansion is relatively small. The number of industrial land has increased, and it has expanded in small pieces, showing a trend of overall expansion and local accumulation. In 2016, the characteristics of expansion of industrial land towards the southwest is very obvious. It is shows a obvious trend of traffic trunk expansion guidance. At the same time, the expansion of the industrial space along the extension axis is even more prominent. The 324 provincial highway from Ganzhou Economic Development Zone to Tangjiang River and the 238 provincial road from Tangjiang to Nankang become the new expansion axis. 3.2.3 Expansion of Commercial Land The distribution of commercial land and residential land is similar. They expand stably along the city’s south-west to north-east direction and distribute separately along northwest to south-east direction, which is generally consistent with the distribution of residential land. It explains that the direction of distribution of two types of living space has a close relationship. In 2003, commercial land was mainly distributed in the vicinity of Tiger Village in Zhanglong Town, Zhanggong District. From 2003 to 2010, commercial land expansion moved from the south-west to the north-east. There is no tendency to transfer to Nankang, still gathering in Zhanggong District. In 2006, commercial land expands stably along the city’s southwest-northeast direction and distribute separately along northwest – southeast direction.
4 Analysis of Factors of Construction Land Expansion The expansion of urban construction land is affected by many factors, such as economic development, population growth, urbanization, natural conditions, location conditions, and national macro policies. Looking at the pattern of expansion of construction land in Ganzhou City from 2003 to 2016 and combining with the actual situation in Ganzhou City, the influence mechanism of expansion mainly are summarized as the following aspects: 4.1
Natural Conditions
Ganzhou central urban area is surrounded by Zhangjiang River and Gongjiang River, which divides the city into Hetao Old City, Zhanggong District, Shuidong District, Shuixi District, Nankang District and Jixian District. It also makes water transportation of Ganzhou city developed and provides opportunities for the development. At the same time, it also affects the land expansion. The barrier of two rivers makes the city’s expansion intensity index low. The expansion of urban construction land begins to develop across the river and urban overall framework has been expanded.
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Economy and People
The degree of economic development determines the level of urbanization. The rapid economic development can promote the expansion of urban space. The growth of population can develop urban housing, commerce, industry and transportation, and thus promote the expansion of urban space. From 2005 to 2015, the growth rate of GDP per capita in urban areas exceeds 200%. With the continuous advancement of urbanization, the urban population of Ganzhou has increased from 365,200 to 3,889,700 and urbanization rate has increased from 8.3% to 45.51%. It shows that there is a strong correlation between urban expansion and its economic development and population growth. 4.3
Traffic Location
Traffic network constitutes the basic skeleton of the city. The development of transportation can accelerate the speed of urban material exchange and increase the efficiency of resource allocation. It has an important role in urban expansion. Ganzhou is located in the border areas of Jiangxi, Hunan, Guangdong, and Fujian which has unique traffic location advantage. The conditions for opening up make Ganzhou’s economy more open. There is a certain degree of enthusiasm in undertaking the industrial transfer of the Pearl River Delta and the strength of economic links. 4.4
Policy and Urban Planning
Under the requirements of the upper planning, such as urban system planning in Jiangxi Province, Ganzhou undertakes the arduous task of helping the old revolutionary base areas in southern Jiangxi out of poverty as the central city for regional development and poverty alleviation planning of the Luoxiao Mountain area. In recent years, Ganzhou has vigorously promoted the main development strategy of industry and major industrial projects, including New Energy Automobile Science and Technology City, Modern Home City, Qingfeng Medicine Valley and so on. Gathered national development zones, hi-tech zones, bonded zones and other national platforms, the whole city of Ganzhou will enter a stage of rapid development. In the future, the population of Ganzhou will further agglomerate in the downtown area.
5 Conclusions and Discussion Since 2003, there have been drastic changes in the construction of functional land in Ganzhou City. With the continuous accumulation of population and the further reduction of land resources,study on the urban land expansion of Ganzhou during 2003–2016 can provide a scientific reference for the spatial expansion of urban functional and regional land use in Ganzhou City. It has certain significance for the sustainable development of the city in the future. This study extracts layer data of three different construction function lands by three status charts of land use. It analyzes
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respectively the expansion of functional land from intensity, speed, and direction and discusses its influencing mechanism. The result shows: ①The expansion of residential land is dominant in the expansion of three types of land. In the early period, the urban area was filled in the old city of Hetao, and the city continued to develop across the river in the later period. In the period of 2003–2016, the expansion intensity is always the largest. From 2003 to 2010, the expansion rate is also the first. owever, the rate of expansion decreased between 2010 and 2016. The direction of expansion of residential land gradually moves from southwest-northeast to the northwest. ②The expansion of industrial land is greatly affected by policies. Obviously it can be seen that industrial land expands towards the traffic trunk. Affected by policies such as “retreat into the city” and driven by the development of industrial parks, the expansion of industrial land presents an trend of overall expansion and local accumulation. The characteristics of distribution spreading towards south-western are remarkable. And the trend of spreading along the 324 Provincial Road, 238 Provincial Road and other major traffic lines is very clear. ③The expansion of commercial land is gradually accelerating and is closely related to the expansion of residential land. From 2003 to 2016, commercial land’s expansion intensity is the smallest among the three. The distribution of commercial land and residential land is similar. Under the influence of commercial matching demand, the expansion rate increases, They expand stably along the city’s south-west to north-east direction and distribute separately along north-west to south-east direction, which is generally consistent with the distribution of residential land. It shows that the direction of distribution of two types of living space has a close relationship. ④There are many factors influencing the expansion of urban construction land in Ganzhou, including natural conditions, economy, population, transportation, policy and urban planning. The driving effect of transportation facilities construction is most significant, and the impact of population growth on urban expansion is greater than that of economic development. With the construction of ring network transportation facilities, the driving effect of natural conditions and economy on urban expansion is gradually weakening. But policy still determines the overall direction of urban expansion. This paper mainly analyzes the strength, velocity, direction and the influencing factors of functional land use in Ganzhou City by using the two indicators of construction land expansion intensity and expansion rate. But the method selection can not fully study the expansion features of construction land use, and the selection of influencing factors mainly focused on macroeconomic factors such as economy, population, transportation, and policy planning, which did not consider all possible macro and micro factors. The scope of this study was limited to residential, industrial, and commercial land in the built-up area of Quzhou City, and did not include all of its construction function land. Due to data acquisition limitations, it was unable to discuss the expansion of the city’s construction land in Ganzhou and failed to further in-depth analysis. Explore the demographic, economic, social, and ecological effects that have led to the expansion of various functional land uses. Future research can proceed from the influencing factors in different aspects to further explore the impact mechanism for
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the expansion of construction land. It is also possible to simulate and predict the expansion of construction land based on the factors that have a greater impact.
References 1. Cao, G.Z., Gao, X.W., Liu, T.: Characteristics of land growth in urban and non-urban areas: takes the yangtze river delta as an example. Hum. Geography 26(5), 65–71 (2011) 2. Wang, X.L., Li, X.R., Feng, Z.K.: Research on Urban Expansion in Beijing based on information Ebtropy. China’s Population Resourc. Environ. 20(3), 89–92 (2010) 3. Liu, T., Cao, G.Z.: Urban land expansion and its driving forces. Progress geography Sci. 29(8), 927–934 (2010) 4. Wang, Q., Zhang, Z.X., Yi, L., et al.: Research on urban expansionin Nanjing, China using RS and GIS. Resour. Environ. Yangtze Basin 16(5), 554–559 (2007) 5. Sheng, F., Yuan, J., Huang, W.W., et al.: Analysis on spatiotemporal characteristics and driving forces of Hefei urban expansion based ongeo-informatic map. Resour. Environ. Yangtze Basin 24(2), 202–211 (2015) 6. Huang, H.C., Yu, Y.X.: Research on urban spatial expansion of Tianjin core area based on RS and GIS. J. Arid Land Resour. Environ. 26(7), 165–171 (2012) 7. Cai, B.F., Zhang, Z.X., Liu, B., et al.: Analysis of Urban Spatial Temporal Changes in Tianjin Based on Remote Sensing and GIS, 9(5), 89–93 (2004) 8. Jiang, F., Liu, S.H., Yuan, H.: Measurement and analysis of urban sprawl in Beijing. Acta Geogr. Sin. 62(6), 649–658 (2007) 9. Rong-hua, M.A., Chao-lin, G.U., Ying-xia, P.U., et al.: Spatial pattern and measurement of urban expansion along the Yangtze River in southern Jiangsu Province. Acta Geogr. Sin. 62 (10), 1011–1022 (2007) 10. Zhang, K., Zhao, Y.L., Fu, Y.C., et al.: Fractal dynamics of land use in Dianchi Lake Basin from 1974 to 2008. J. Resour. Sci. 35(1), 232–239 (2013) 11. Li, Y., Feng, Y., Peng, F., et al.: Evolution of pattern of ecological land in Tianjin based on geographical detectors. Econ. Geography 12, 180–189 (2017) 12. Xiao, L., Tian, G.J.: Study on Urban expansion space model and driving mechanism in Tianjin. Resour. Sci. 7, 1327–1335 (2014) 13. Liu, X., Chaolin, G.U.: Decoding Urban land-use spatial structure: a case study on the city of Nanjing. Urban Plan. Forum. 21(5), 78–84 (2008) 14. Qu, A.X., Qiu, F.D.: Study on the Expansion Process and Pattern of Urban Construction Land in Xuzhou. Geographical Sci. 33(1), 61–68 (2013) 15. Wu, Q.Y., Zhang, J.X., Zhu, X.G., et al.: Theoretic study on the differentia-ting mechanism of residential space in modern Chinese cities. Hum. Geography 17(3), 26–30 (2002) 16. Lu, Z.W., Xu, L.H., Wu, C.F., et al.: An analysis of the evolution of urban expansion forms in Hangzhou based on convex hull principle. Geographical Sci. 35(12), 1533–1541 (2015) 17. Liu, S.H., Wu, C.J., Shen, H.Q.: A GIS based model of urban landuse growth in Beijing. Acta Geogr. Sin. 55(4), 407–416 (2000)
Temporal-Spatial Evolution Characteristics of Economic Development of Hangzhou Bay Area and Its Influencing Factors Na Liu(&) and Yuzhe Wu Department of Land Management, School of Public Affairs, Zhejiang University, Zhejiang, China [email protected], [email protected]
Abstract. This paper builds an index system based on the economic data of the regional units in Hangzhou Bay Area from 1997 to 2016. The entropy method is used to determine the index weights in this paper in order to calculate the comprehensive level of economic development. The standard deviation and coefficient of variation are used for analysis on temporal-spatial evolution of Hangzhou Bay Area. This paper analyzes the temporal and spatial development of the Hangzhou Bay Area from the view of region factors such as external environment, regional characteristics, and regional development policies. This study found that: 1) The comprehensive economic development level of Hangzhou Bay Area shows a rapid growth from 1997 to 2016. The economic index shows that Shanghai has the highest economic development level in Hangzhou Bay Area, and Hangzhou and Ningbo are developing rapidly, which are lower than Shanghai. 2) The absolute difference in the Hangzhou Bay area is expanding on the whole from 1997 to 2016 and the relative difference is decreasing, which shows a good signal. 3) The economic structure of Hangzhou Bay Area presents the pattern of “1 + 2 + 3 + X”. 4) Location characteristics, external environment, and regional development policies are the main factors, which affect regional economic development. Besides, there are also other factors, included transportation factors, development paths, resource endowments, and government planning, which affect the development of region economy. Keywords: Economic development Regional development policy
Hangzhou Bay Entropy method
1 Introduction The Bay Area is a dense urban area, which is based on the bay, and is composed of spatial elements as powerful urban groups and port groups, as well as such as highly efficient transportation systems that are connected to each other (Zhang 2017). This region is often characterized by excellent natural ecological environment and superior economic and geographic location, high population density, and agglomeration of innovative resources. It is the driving force of world technological changes and the engines that drive the development of the global economy. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 235–250, 2021. https://doi.org/10.1007/978-981-15-3977-0_18
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Since the country’s proposal for the construction of the Guangdong-Hong KongMacau Greater Bay Area, another growth pole of the Chinese economy – the Yangtze River Delta Region is also drawing the eyes, in which the concept of the Bay Area economic belt has been put out. In 2003, the Zhejiang Provincial Government first proposed the Hangzhou Bay Industrial Belt. Then in June 2017, Zhejiang Province put forward the “Hangzhou Bay Area” development strategy in combination with the regional economic development status and accelerated the construction of the Hangzhou Bay City Group. In July 2017, Zhejiang Province government visited Shanghai. The Shanghai Party Secretary proposed cooperation to promote the construction of Hangzhou Bay. At present, there are a few studies on Hangzhou Bay Area. The existing literature mainly focuses on functional positioning and development strategies. Based on the aim of economic development in Hangzhou Bay Area, it is also very necessary to analyze the characteristics of the temporal-spatial evolution of the economic development of the Hangzhou Bay urban agglomeration so as to make up for the research gaps of scholars in this study area.
2 Research Area, Research Method and Data Sources 2.1
Research Area
Hangzhou Bay is located on the western coast of the Pacific Ocean, in the Northern Hemisphere, in the middle of the coastline of mainland China, between Zhejiang Province and Shanghai City. In terms of geographical location, it has natural advantages. The Hangzhou Bay Area connects the Silk Road on the one land and connects the Maritime Silk Road on the other hand. At the same time, it’s the estuary of the Yangtze River Economic Belt. Moreover, it has the world’s most dense port group. At present, the definition of the region in the Hangzhou Bay is different. This article defines the Hangzhou Bay Area as that it includes a super-central city- Shanghai, a center city included Hangzhou and Ningbo in Zhejiang, and three major cities, which are Jiaxing, Shaoxing and Zhoushan. It is an urban agglomeration formed by big cities. Compared with the world’s four major bay areas, such as San Francisco Bay Area, New York Bay Area, Tokyo Bay Area, and Guangdong Hong Kong and Macao Bay Area, Hangzhou Bay relies on two major natural harbors. At present, Ningbo-Zhoushan Port is the top three container port of world. The Shanghai-Yangshan Deepwater Port is the world’s largest automated container terminal currently. As far as the economic hinterland is concerned, because the Hangzhou Bay is located in the middle of the eastern region, and the Hangzhou Bay Area connects both northern area and southern area in China. Moreover, the linked transport channels of ocean shipping and Railway Transport and the linked transport channels connect the rivers, sea and land, which makes the Qiantang River Basin, the Yangtze River Basin, etc. become the hinterland of the Hangzhou Bay Area. Therefore, the Hangzhou Bay area can form a spatial structure called “1 + 2 + 3 + X” with Shanghai as the leading engine. In this Bay Area, Shanghai is the leading point, and Hangzhou and Ningbo are two major development engines. Zhoushan, Jiaxing and Shaoxing are the three major cooperative channels, and “X” represents the coastal and hinterland space that can be affected by the Hangzhou Bay Area.
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Fig. 1. The location of Hangzhou Bay Area
2.2
Research Method
Firstly, this paper builds a comprehensive index system for economic development. Then it uses the entropy method to determine the weight of each indicator and uses the comprehensive evaluation model of economic development to calculate the 20-year economic index of six cities in Hangzhou Bay Area, and next uses relative development analysis. The characteristics of spatial-temporal evolution of the economic development of Hangzhou Bay Area were analyzed by methods such as relative development rate, standard deviation, coefficient of variation, and GIS spatial analysis. 2.2.1 Building a Comprehensive Development Index System for Economic Development Based on the relevant literature, this paper builds a comprehensive evaluation index system for regional economic development from the five aspects, included economic aggregates, economic structure, economic benefits, economic externality, and economic development rate, in order to measure the comprehensive level of regional economic development. This paper uses local fiscal revenue, local fiscal expenditure, GDP and GDP per capital to measure Economic aggregate. And the economic structure is measured by the proportion of the output value of the second industry to GDP and the proportion of the output value of the third industry to GDP. Also, this paper uses average wages of employees on the job, average secondary industry output value, and Average tertiary industry output value to measure economic performance. The economic externality is
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measured by foreign trade import and export and foreign trade dependence. The economic development speed is measured by regional GDP growth rate and FDI. The evaluation index system is shown in the Table 1. Table 1. Comprehensive economic development evaluation index system Target indicator Comprehensive level of economic development
Feature layer
Indicator code Economic A1 aggregate A2 A3 A4 Economic structure B1 B2 Economic C1 performance C2 C3 Economic externality
D1
D2 Economic E1 development speed E2
Indicator layer Local fiscal revenue Local fiscal expenditure GDP GDP per capita The second industry/GDP The third industry/GDP Average wages of employees on the job Average secondary industry output value Average tertiary industry output value Foreign trade import and export Foreign trade dependence Regional GDP growth rate FDI
2.2.2 Entropy Method Since the entropy value can reflect the degree of disorder of information, and the reflection of information can be measured. This paper chooses the entropy method to get the objective weight, and uses the entropy information represented by each indicator to caculate the index weight, which effectively avoids the subjective bias caused by human factors and makes the evaluation more in line with objective conditions. In this paper, the steps to calculate the weights of the above economic indicators using the entropy method are mainly as follows (Zhang et al. 2011): (1) Raw data transformation: This paper selected 13 indicators to measure the five aspects of comprehensive level of economic development. The 13 indicators have different units and have different orders of magnitude. Therefore, the original data needs to be dimensionlessly processed to form a matrix Yij. Yij ¼
Rij minj Rij maxj Rij minj Rij
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If there are m regions and n evaluation indexes, the original data matrix R = (Rij) m * n is formed according to the sample data. Rij is the initial sample matrix of m regional units and n indexes in the Hangzhou Bay region. The Yij results is shown in the Table 2. (2) Calculate the index j entropy. After getting the matrix of Yij, then calculate the entropy of each indicator according to the following formula: ej ¼
m 1 X pij ln pij ln m i¼1
Table 2. The results of matrix Yij (Comprehensive level of economic development) Indicator 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997
A1 1 0.88 0.72 0.65 0.59 0.53 0.43 0.36 0.33 0.28 0.2 0.17 0.12 0.09 0.06 0.05 0.02 0.01 0 0
A2 1 0.91 0.71 0.65 0.59 0.54 0.45 0.38 0.36 0.28 0.21 0.18 0.14 0.1 0.07 0.05 0.03 0.02 0.01 0
A3 1 0.88 0.82 0.74 0.68 0.62 0.53 0.44 0.4 0.34 0.26 0.21 0.17 0.12 0.08 0.06 0.04 0.03 0.01 0
A4 1 0.87 0.81 0.88 0.82 0.75 0.62 0.51 0.45 0.39 0.31 0.25 0.2 0.14 0.1 0.07 0.05 0.03 0 0
B1 0 0.32 0.48 0.43 0.68 0.82 0.86 0.84 1 0.98 0.95 0.89 0.87 0.92 0.75 0.67 0.64 0.8 0.76 0.82
B2 1 0.78 0.69 0.7 0.57 0.49 0.46 0.47 0.38 0.38 0.36 0.35 0.33 0.25 0.29 0.43 0.24 0.4 0.06 0
C1 1 0.9 0.82 0.74 0.67 0.62 0.53 0.46 0.42 0.36 0.29 0.26 0.22 0.2 0.15 0.12 0.07 0.04 0.02 0
C2 0.75 0.8 0.78 0.71 1 0.94 0.8 0.65 0.62 0.53 0.42 0.33 0.27 0.19 0.12 0.08 0.06 0.04 0.02 0
C3 1 0.71 0.63 0.56 0.67 0.59 0.5 0.41 0.36 0.3 0.24 0.19 0.16 0.11 0.09 0.09 0.05 0.05 0.01 0
D1 0.92 0.94 1 0.96 0.92 0.71 0.52 0.37 0.48 0.49 0.39 0.31 0.22 0.15 0.23 0.07 0.05 0.02 0.01 0
D2 0.54 0.66 0.79 0.84 0.91 0.71 0.55 0.42 0.66 0.69 0.64 0.57 0.39 0.29 1 0.21 0.13 0.05 0.02 0
1 þ Yij . 1 þ Yij i¼1
In the formula, pij can be measured by the formula: pij ¼ Pm (3) Next calculate the weights of indicator j.
1 ej wj ¼ Pn j¼1 1 ej
E1 0.43 0.14 0 0.05 0.06 0.65 0.77 0.03 0.47 0.98 0.56 0.82 1 0.84 0.48 0.8 0.62 0.32 0.17 0.13
E2 1 0.99 0.95 0.94 0.83 0.85 0.77 0.64 0.64 0.63 0.44 0.38 0.35 0.26 0.2 0.14 0.03 0 0.02 0
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2.2.3 Evaluation Model of Comprehensive Level of Economic Development The comprehensive level evaluation model of economic development selected in this paper refers to that it uses entropy method to calculate the weights of the regional geographical unit economic index system, and measures the economic index. The evaluation model is as following: Si ¼
n X
wj Yij
j¼1
Si represents the economic index of i region. wj represents the weight of index determined by the entropy method. Yij represents the data of the original data with dimensionless process. The greater the value of Si, the greater the overall level of economic development reflected in the region and vice versa. 2.2.4 Relative Rate of Development In addition, this paper introduces the relative development rate to measure the relationship between the economic index of each regional unit in the Bay Area of Hangzhou Bay and the economic index of the entire region during the same period. The relative development rate is represented by Nich. The formula is as following: Nich ¼ ðY2i Y1i Þ=ðY2 Y1 Þ In the formula, Y2i and Y1i represent the economic index of i area at time 2 and time 1, respectively; Y2 and Y1 represent the economic index of the whole area at time 2 and time 1, respectively. The larger the Nich value, the faster the relative speed of regional development and vice versa. 2.2.5 Standard Deviation and Coefficient of Variation Standard deviation and coefficient of variation are the most common methods for measuring absolute differences and relative differences in regions. They can objectively reflect the degree of dispersion of a set of data or the degree of differences between regions. In general, the larger the standard deviation and the coefficient of variation are, the greater the absolute and relative differences in the representative areas respectively. This paper uses the spatial analysis module of ArcGIS to analyze the economic development trend of Hangzhou Bay and its characteristics. 2.3
Research Data
The research data of this paper mainly come from the statistical database of China’s economic and social development, the National Bureau of Statistics of the People’s Republic of China, the Statistical Yearbook of Shanghai, Hangzhou and Zhejiang Province and the Statistical Bulletin of National Economic and Social Development of Ningbo over the years, and the national economy of Jiaxing and Zhoushan over the years.
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3 Temporal and Spatial Evolution of Economic Development in Hangzhou Bay Area 3.1
Overall Economic Development Level Shows Rapid Growth
This paper uses entropy method to determine the weights and calculates the 20-year regional economic index of 6 cities in the Hangzhou Bay Area. It finds that the regional economic development in Hangzhou Bay shows a period of rapid growth. Based on the characteristics of regional economic development, This article divided the economic growth of the region mainly into four stages, which is as shown in Fig. 1.
Fig. 2. The changing of economic level of Hangzhou Bay Area
3.1.1 Slow Growth Phase of Economic Development (1997–2000) At this stage, the regional economic index of Hangzhou Bay increased from 0.0414 in 1997 to 0.1284 in 2000, with an average annual increase of 0.0218. Since the reform and opening up, the Yangtze River Delta region has used the country’s preferential policies and cheap but abundant labor resources to attract foreign advanced technology, management, and investment. The economic development in the region grew a little rapidly. The Asian financial crisis in 1997 also had an unavoidable impact on the six cities in Hangzhou Bay Area, resulting in a slow-development economy.
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3.1.2 Accelerated Economic Growth (2001–2007) During this stage, the regional economic index of Hangzhou Bay increased from 0.1867 in 2001 to 0.4931 in 2007, with an average annual increase of 0.0438. After the Asian financial crisis, the economy began to slowly recover. In 2001, China officially joined the WTO. A series of favorable policies stimulated economic growth and accelerated economic growth. 3.1.3 The Turbulent Phase of Economic Development (2008–2013) At this stage, the economic index of the Hangzhou Bay fell from 0.4881 in 2008 for the first time and gradually resumed growth to 0.6988 in 2013. In 2008, the global financial crisis began, and the economic development of the Bay Area in Hangzhou Bay, which is dominated by an export-oriented economy, was impaired and fell for the first time. Economic development has entered a period of short-term shocks and development has been very slow (Fig. 3).
Fig. 3. The level of different economic aspects of the Hangzhou Bay Area
3.1.4 Rapid Economic Development (2014–2016) At this stage, the economic development index increased from 0.7249 in 2014 to 0.8555 in 2016. With the development of the Internet+ and the country’s new strategy and policies being put out, the rapid development of Zhejiang Province, under the influence of favorable factors such as the G20 and the Asian Games, the development of Hangzhou Bay Area grows rapidly. With the development of the Hangzhou Bay Area proposed by the Zhejiang Provincial Government and actively seeking cooperation with Shanghai, the development cooperation in the Greater Bay Area of Hangzhou Bay has entered a new phase.
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Overall Economic Development Level Shows Rapid Growth
Based on the above calculation data, this paper calculates the comprehensive economic value of every feature layer in each year, which is shown in Fig. 2. It finds that the economic development, export-oriented economy, and economic efficiency of the Hangzhou Bay Area from 1997 to 2016 is growing faster. The changes in economic structure and total economic volume from 1997 to 2016 are relatively small and the growth rate is slow. However, in short, the economic development of Hangzhou Bay Area is good. The above content shows that during the 20 years of development in the Hangzhou Bay, the economy has developed rapidly, the export-oriented economy has also developed rapidly, and the Export-oriented economy has developed a lot and continued to expand. In the contrast, the adjustment of the industrial structure has been very slow. 3.3
The Economic Index of Shanghai Ranks the Highest in the Bay Area
According to the basic panel data of the studied region units, the economic indexes of the six cities in Hangzhou Bay are calculated, which are shown in Fig. 4. As can be seen from the Fig. 4, Shanghai’s economic index is much higher than other studied units, and it always stays at the level above 0.7, which is the highest value of the region’s economic index. And Hangzhou has grown significantly compared to other cities and has been rising. Ningbo is roughly the same as Hangzhou in terms of index, but after 2012, the index has slightly declined. The remaining cities, including Jiaxing, Shaoxing and Zhoushan, have increasingly different economic indicators. Both Jiaxing and Ningbo have a tendency to overtake Shaoxing. In general, the changes in the rankings of the cities in the Hangzhou Bay Area are small, and the economic pattern of “1 + 2 + 3 + X” in Hangzhou Bay can be seen in Fig. 4.
Fig. 4. The economic development level of each studied units in the Hangzhou Bay Area
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In order to further be able to know the economic development differences of the regional units in the Hangzhou Bay, this paper selects the relative development rate to measure the development speed of each region in different periods. According to this article, the Hangzhou Bay Area is divided into four stages: 1997–2000, 2001–2007, 2008–2013, and 2014–2016. Calculate the Nich value of each phase in each area based on the calculation formula of relative development rate - Nich and get the following Table 3. Table 3. The relative economic development of each unit The first stage 1997–2000 Shanghai −0.2734 Hangzhou 0.4710 Jiaxing 0.1995 Shaoxing 0.1102 Ningbo −0.3361 Zhoushan −0.4983 Region unit
The second stage The third stage 2001–2007 2008–2013 0.0685 0.4506 −1.4407 0.5367 −0.0593 0.1548 −0.3367 −0.6384 0.0832 −0.0514 0.4222 −0.3076
The fourth stage 2014–2016 0.3289 0.4113 0.2980 −0.3838 −0.6176 0.0320
From the data in the Table 3, it can be seen that the relative speed of the development in each region in the first stage is not the same and the difference among regions is large. With time going by and the increasingly close collaboration among the regions, the relative development rate has gradually decreased. The relative development speeds of Shanghai, Hangzhou, and Jiaxing are relatively growing fast, while the relative development speeds of Shaoxing, Ningbo, and Zhoushan are relatively slow. In this paper, Nich value is divided into 6 levels according to 0, 0.05, 0.10, 0.15, 0.2, among which Nich < 0 is the 6th level, indicating that the relative development speed is very small. Nich > 0.2 indicates that the relative development speed is very large. The Fig. 5 also can show the results. 3.4
Absolute Differences in Regional Economies Increase and Relative Differences Decrease
In order to fully reflect the changes in regional differences, this paper chooses the standard deviation and coefficient of variation for each year from 1997 to 2016, as shown in the Fig. 6 below. The comparison results show that the standard deviation is lower than the coefficient of variation, indicating that the absolute difference in Hangzhou Bay area is not significant and the relative difference is significant. As a whole, absolute differences show a trend of expansion, and relative differences show a more stable trend, especially at certain stages. This shows that the total difference in the Gulf of Hangzhou Bay area has been expanded. Due to the different development speeds of different cities and different policies received, regional differences maintain the trend of stability, which indicates good performance in the overall economy of the Hangzhou Bay area.
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Fig. 5. The distribution of Nich of the Hangzhou Bay Area
Fig. 6. The change of economic disparity in the Hangzhou Bay Area
3.5
The Economic Spatial Pattern of the Hangzhou Bay Area Presents a Pattern of “1 + 2 + 3 + X”
As is shown in Fig. 7, judging from the current status of the development of Hangzhou Bay, The Hangzhou Bay Area has now formed a spatial pattern of “1 + 2 + 3 + X” with Shanghai as the leader of the Hangzhou Bay Area, and Hangzhou and Ningbo are two major development engines. Zhoushan, Jiaxing and Shaoxing are the three major cooperative channels. The “X” represents the coastal and hinterland space that can be radiated, and all formed the geographical distribution of the “V” character.
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4 Factors Influencing the Spatial-Temporal Evolution of Economic Development in the Hangzhou Bay Area 4.1
Location Characteristics
The Bay Area is an economic complex based on geographical location. Its main features are an active economy, an interconnected space system, and resource agglomeration. Located in the Yangtze River Delta, Hangzhou Bay is an important meeting point for the “The Belt and Road Initiative” strategy and the “Yangtze River Economic Belt”. The cities of Hangzhou Bay Area are classified into port-side and nonportal-type. The regions with a mainly export-oriented economy have relatively high geographical requirements, and the port-oriented cities have natural advantages under this kind of export-oriented economy.
Fig. 7. The spatial pattern of “1 + 2 + 3 + X” in Hangzhou Bay Area
Hangzhou Bay has an intensive high-speed rail and expressway network. An hour and a half of traffic circles can cover the four major international airports in Shanghai Pudong international Airport, Shanghai Hongqiao international Airport, Hangzhou Xiaoshan international Airport and Ningbo Lishe international Airport, and have the world’s top three container ports – Ningbo Zhoushan-Ningbo port and the world’s largest automated container terminal - Shanghai Yangshan Deepwater Port (Fig. 8).
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Fig. 8. The location of Hangzhou Bay area
4.2
Regional Development Policy
Regional development policies have a very large impact on the evolution of the economic structure in the Greater Bay Area. Judging from the changes in the comprehensive index of economic development, the economic development in the Hangzhou Bay has been particularly affected by policies. Since the reform and opening up, especially the establishment of 14 coastal open cities in 1984, the Hangzhou Bay area has made considerable progress. In 1992, the State further established the Pudong New Area of Shanghai to radiate the surrounding areas, which has allowed the region to develop substantially. China’s Accession to the WTO in 2001 has become an opportunity for the further rapid development of the Hangzhou Bay Region which focused on foreign Trade-Based economy. With the proposal of the Hangzhou Bay Economic Zone in the 14th Zhejiang Provincial Party Congress, the transportation infrastructure in the Bay Area will be interconnected and interlinked, and efforts will be made to intensify the links between the urban areas of the Bay Area, which will play a decisive role in the development of the future Hangzhou Bay Area. 4.3
Changes in the External Environment
The GDP growth rate of each city in the Greater Bay Area is closely related to changes in the external environment. The Asian financial crisis in 1997, the accession to the WTO in 2001, and the global financial crisis in 2008 have had a profound impact on the economic development of the Hangzhou Bay. Shanghai is China’s financial center,
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and Hangzhou, Jiaxing, Shaoxing, Zhoushan, and Ningbo are also the main exportoriented economies and they are greatly affected by changes in the external environment (Fig. 9).
Fig. 9. The GDP growth rate of each studied units in the Hangzhou Bay Area
4.4
Other Factors
Since the cities in Hangzhou Bay Area are different in terms of talent introduction and economic development, each city has its own resource endowment. Therefore, besides location factors and policy factors, the factors affecting the economic development of Hangzhou Bay Area are different. In addition to changes in the external environment, it also includes factors such as transportation factors, development paths, resource endowments, and government plans. 4.4.1 Traffic Factors Compared with Guangdong, Hong Kong, and Macao, the Bay Area of Hangzhou Bay covers a wider area, and the distance between cities is far from one another, and the contact between them is weak. Therefore, the links between cities need to be strengthened in terms of spatial connections. At present, with the construction of high-speed railways, ports and large bridges in the Hangzhou Bay Area, dense high-speed rail and expressway networks have been formed. The half-hour traffic circle formed covers Shanghai Pudong international airport, Shanghai Hongqiao international airport, Hangzhou Xiaoshan international airport, Ningbo Ningbo international airport, and other international airports. And there are two major international ports. The increasingly perfect traffic circle promotes the economic development of Hangzhou Bay.
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4.4.2 Development Path The economic basement of each city in the Hangzhou Bay Area is different. With the change of the every city’s development path, it will have an important impact on the economic development of the Hangzhou Bay Area. For example, Ningbo’s urban development has changed from the original “the port of three rivers” to the Gulf era. Ningbo accelerated the construction of U-shaped bay cities in Xiangshan Port, and formed a “two-city interaction” with Hangzhou. The change in the development path has greatly promoted the economic development of the “1 + 2 + 3” economic structure in Hangzhou Bay. 4.4.3 Resource Endowment Classical economists generally believe that resource-rich regions often have comparative advantages in development, so resource endowments are an important driving force for economic development. Each city in the Hangzhou Bay Area has a different resource endowment and therefore has a different influence on the development of the city and on the development of the area. Taking Hangzhou as an example, Hangzhou is rich in tourism resources, and its own Internet economy is very developed. Because of its rich resources in tourism resources and Internet resources, Hangzhou is committed to building an “Internet+” innovation and entrepreneurship center with global influence and an International tourist and leisure cities, which also triggered the impact on the surrounding areas. Another example is Shanghai, which is an important financial center of the country. Its financial resources and human resources are very rich. Shanghai’s regional advantages and transportation advantages have made Shanghai a leading position in regional economic development and have radiated its surrounding areas. Therefore, Resource endowment has always played an important role in region economy development.
5 Conclusion This paper uses the economic data of six cities in Hangzhou Bay from 1997 to 2016 to analyze the characteristics of the spatial and temporal evolution of economic development in the region. This paper sets a region development model and quantitatively analyzes the Hangzhou Bay Area. After data analysis, the study finds that: Hangzhou Bay’s comprehensive development level of the overall economy of the district has shown rapid growth in a fluctuating manner. The economic index has generally shown a trend of “1 + 2 + 3”. That is to say, Shanghai’s economic development level is far ahead in the Hangzhou Bay Area and has the highest value. Hangzhou and Ningbo are at a relatively high level, and Shaoxing, Jiaxing and Zhoushan are at a lower level. In general, the export-oriented economy in the Hangzhou Bay Area has been continuously strengthened, but relative to the economic development speed, the adjustment of the industrial structure is relatively slow. The absolute difference in the regional economy in the Hangzhou Bay Area is generally stable. The relative differences are widened. The economic structure is still centered in Shanghai, followed by Hangzhou and Ningbo.
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This article simply analyzes the factors affecting the economic development of the Hangzhou Bay Area through location factors, changes in the external environment, policy factors, and other factors, hoping to provide some reference for the development of strategy in the Hangzhou Bay Area.
References Zhang, R.: Experience and enlightenment of world bay area economy development. China National Conditions Strength 5, 31–34 (2017) Ren, S., Li, X., Chen, T.: Retrospect and prospect of guangdong, hong kong and macao’ economic relations since reform and opening up. Urban Plan. Int. 32(3), 21–27 (2017) Zhou, C., Luo, L., Shi, C., Wang, J.: Spatio-temporal evolutionary characteristics of the economic development in the guangdong-hong kong-macao greater bay area and its influencing factors. Tropical Geography 37(6), 802–813 (2017) Chai, X., Zhu, S.B., Xu, C., et al.: Take the wisdom of the whole area to guide the transport development in Hangzhou Bay area. Comprehensive transportation, 2 (2018) Zhiguo, L., Feng, P., Zhenkun, Y.: Global bay area economic comparison and comprehensive evaluation study. Sci. Technol. Progress Counter Measures 11, 112–116 (2015) Junwei, L.: Construction path of Hangzhou Bay Economic Zone. Zhejiang Econ. 17, 16–17 (2017) Guan, Y., Bao, Y., Gu, C.: Research on comprehensive evaluation of economic development of 11 cities in Jiangxi Province based on entropy method. Constr. Old Revol. Basic Area 6, 16– 21 (2013) Hong, M.: The Spatial and Temporal characteristics of regional economic development and its geographical analysis in Inner Mongolia. Inner Mongolia Normal University, Hohhot (2016) Yanhong, J., et al.: Evaluation of grassland ecological security based on entropy-weighted method: a case study of pastoral areas in Gansu Province. J. Ecol. 25(8), 1003–1008 (2006) Zhang, J., Luo, J.: Assessment on eco-city construction of wuhan based on entropy method. Resour. Dev. Market 27(10), 887–889 (2011) Zhang, S., Zhang, M., Chi, G.: The science and technology evaluation model based on entropy weight and empirical research during the 10th five-year of China. Chinese J. Manag. 7(1), 34– 42 (2010)
Impacts of Land Expropriation on the Entrepreneurial Decision-Making Behavior of Land-Lost Peasants: An Agent-Based Simulation Haijun Bao1, Hao Dong2(&), Jinshui Jia1, Yi Peng2, and Qiuxiang Li2 1
School of Business Administration, Zhejiang University of Finance and Economics, Hangzhou, China 2 School of Public Administration, Zhejiang University of Finance and Economics, Hangzhou, China [email protected]
Abstract. The rapid urbanization of China results in a large number of landlost peasants and relevant social problems that impede sustainable development. Land-lost peasants are encouraged to venture into entrepreneurship to improve their survival and development. However, a few studies investigated the dynamic process of the entrepreneurial decision-making behavior of land-lost peasants. Therefore, the effectiveness of promoting entrepreneurship to land-lost peasants remains unknown. This study establishes an agent-based simulation model for the entrepreneurial decision making of land-lost peasants based on the revised Todaro model. Relevant measures are also proposed to provide effective guidance for promoting entrepreneurship to land-lost peasants based on the simulation results. The findings can provide references for local government to promote entrepreneurship among land-lost peasants in China and other regions. Keywords: Land acquisition Land-lost peasants Entrepreneurial decision making
Agent-based simulation
1 Introduction The survival and development of land-lost peasants are major social concerns during the rapid urbanization of China. The China Urban Development Report 2011 released by the Chinese Academy of Social Sciences forecasted that the total number of land-lost peasants in China will exceed 110 million by 2030 [1]. Peasants faced serious challenges after the expropriation of land [2]. Considering unreasonable compensation and lack of reemployment training system, most peasants belong to the “three Nos” of fringe people, that is, those who have no land, no job, and no insurance. Rapid changes in their physical living spaces separated them from their social networks, and their ability to acquire social resources is losing. The passive status of land-lost peasants also resulted in their fuzzy identity during the urbanization of China [3]. In addition, land-lost peasants have unequal access to public services and social security compared with urban residents. Therefore, the settlement of land-lost peasants is a key issue in their transformation from rural to © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 251–268, 2021. https://doi.org/10.1007/978-981-15-3977-0_19
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urban areas [4]. As the urbanization of China continues to advance, helping land-lost peasants in terms of survival and development and enabling them to adapt to rapid urbanization will leave a significant effect on social harmony and stability. Entrepreneurship is one of the most important approaches allowing land-lost peasants to achieve long-term development. Unlike general peasants, most land-lost peasants live in urban villages or urban–rural fringe areas, which have substantial access to information and entrepreneurial opportunities. After land acquisition, simple compensation cannot protect the rights and interests of land-lost peasants [2]. This type of security will not help land-lost peasants meet their development needs. The entrepreneurial activities will provide land-lost peasants with reasonable use of compensation and help them optimize the allocation of capital. From the perspective of international experience, encouraging the unemployed and disadvantaged groups to move toward entrepreneurship is an effective way so that they can eliminate the disadvantaged status and then embark on the road of development [5]. Examples of encouragement include supporting immigrants’ entrepreneurial activities [6, 7], reducing the barriers to female group entrepreneurship in Finland, Sweden, and the UK [8], and increasing the proportion of business owners of minority groups in the UK, the USA, and Sweden [9]. The experience of successful entrepreneurship of these disadvantaged groups will provide reference for encouraging entrepreneurs who have lost land. From China’s domestic practice, the venture capital investment of land-lost peasants includes two forms: capital appreciation and job enlargement. The former occurs when land-lost peasants have started the businesses before losing land. The compensation for entrepreneurship after losing land will contribute to their value maintenance and appreciation. However, the main purpose of venture capital investment based on job enlargement is to seek employment opportunities for individual and family members so as to solve the livelihood problems [10]. Job enlargement-oriented entrepreneurship of land-lost peasants will receive a series of policy assistance provided by the government, including project supply, skills training, and financial support. These measures help the land-lost peasants to develop capabilities of selfaccumulation, self-absorption, and self-development, which effectively increase the success rate of their entrepreneurship, increase disposable income per capita, and improve their quality of life [11]. In addition to the aforementioned material-level improvements, entrepreneurial training has increased the self-confidence and enhanced the diathesis of land-lost peasants. The launch of entrepreneurial activities has strengthened social contacts, which has actively promoted the exchange of land-lost peasants and their offspring with mainstream culture. This condition will help them eliminate exclusion and integrate into mainstream society [12]. However, only a few studies investigated the entrepreneurial decision-making behavior of land-lost peasants, which limited the effectiveness of current polices on guiding their entrepreneurship. Thus, the present study aims to fill this gap by examining the dynamic behavior of land-lost peasants in their entrepreneurial decision making. Section 2 reviews relevant studies to provide a solid basis for this research. Section 2.1 introduces the Todaro model to characterize the entrepreneurial behavior change of land-lost peasants. The Todaro model explains issues related to the migration of rural labor force to urban areas, including the decision-making behavior model and employment probability of labor mobility behavior [13]. This study further establishes
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the agent-based simulation model to investigate the entrepreneurial decision making of land-lost peasants. Section 3 presents the simulation results of the dynamic evolution of the entrepreneurial decision making of land-lost peasants. Section 4 provides an indepth discussion and offers relevant policy suggestions to facilitate promoting entrepreneurship of land-lost peasants. Section 5 concludes this study with specifications for future studies.
2 Research Method 2.1
Revised Todaro Model for Explaining Entrepreneurial Behavior of Land-Lost Peasants
The Todaro model is an economic behavioral model to explain rural urban migration based on the simple wage differential approach [13]. The Todaro theoretical model is highly consistent with the reality of developing countries and has been widely used in China to explain the non-agricultural employment of rural laborers [14]. The key hypothesis in the model that the expected income leads to the migration of urban and rural population in China is also applicable to the entrepreneurial selection of land-lost peasants. The reason is that the selection of employment or entrepreneurship of landlost peasants is also fundamentally based on the consideration of expected income. If selecting entrepreneurship can achieve more expected income than selecting employment, then land-lost peasants will prefer to start businesses rather than be employed. The Todaro model can explain the rational selection behavior of the surplus rural labor force’s transfer from low to high expected income industries under the incentive of comparative benefits. Therefore, this study revised the Todaro model to analyze the entrepreneurship decision-making behavior of land-lost peasants as follows: 1. To introduce institutional variable p, which represents the state’s supporting policy for land-lost peasants’ entrepreneurship. This approach aims to improve the business environment and other conditions to influence the business of land-lost peasants. 2. To introduce entrepreneurial risk variable a, which represents the failure of land-lost peasants. A non-entrepreneurial unemployment risk b is introduced provided the risk of not finding a job even though land-lost peasants do not decide to start a business. 3. To introduce k, which represents the entrepreneurial knowledge of land-lost peasants, and learning ability lactive , knew denotes the renewal of peasant entrepreneurship knowledge, and kn signifies knowledge without entrepreneurship, which can be interpreted as working knowledge. The renewal of knowledge, which is related to the influence of personal endowments, such as knowledge and skills, connects the personal traits of land-lost peasants. This concept may have an influence on the entrepreneurial decision of the land-lost peasants. Learning ability, which reflects the ability to accept new knowledge, can embody the individual characteristics of land-lost peasants.
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As the agent of simulation modeling, a single land-lost peasant has two options, namely, to start a business or not. This study examines the dynamic selection of landlost peasants and assumes that each land-lost peasant is constantly updated on entrepreneurial and non-entrepreneurial perception earnings and on the entrepreneurship selection behaviors performed around these factors. In this study, the definition of entrepreneurship and non-entrepreneurship tendencies of land-lost peasants are shown as follows: ry ¼ p ð1 aÞ Gy
ð1Þ
rn ¼ ð1 bÞ Gn
ð2Þ
In Eqs. (1) and (2), ry denotes the tendency to select entrepreneurship for land-lost peasants; and rn refers to the tendency to work instead of selecting entrepreneurship. Land-lost peasants select entrepreneurship when ry [ rn , but they will not start a business when ry \ rn . The expression of perceived benefits of whether or not land-lost peasants select entrepreneurship is as follows: Gy ¼ knew Ey ; knew 2 ½0; 1
ð3Þ
Gn ¼ kn En ; kn 1
ð4Þ
In Eqs. (3) and (4), knew , which assumes a value between 0 and 1, represents the renewal of peasant entrepreneurship knowledge, i.e., knew 2 ½0; 1. kn denotes knowledge without entrepreneurship and can be interpreted as working knowledge assuming that land-lost peasants are knowledgeable about working, i.e., kn 1. This equation shows that selecting to be employed relatively stabilizes earnings, which removes the risk of unemployment. Ey is the income that land-lost peasants obtain from entrepreneurship. Theoretically En refers to the income that land-lost peasants obtain from selecting to be employed. Ey and En have a positive influence on the perceived benefits of land-lost peasants. This study examined the dynamic process of the entrepreneurial decision making of land-lost peasants. Thus, the new knowledge on entrepreneurship of land-lost peasants was assumed updated for each period. Heterogeneity was observed. Thus, the knowledge of land-lost peasants is different. This study assumes that land-lost peasants mainly learn entrepreneurial knowledge by communicating with other land-lost peasants in a social network. The equation showing that the entrepreneurship knowledge of peasants is consistently updated and described as follows: 0 knew ¼ knew þ lactive
ki s
ð5Þ
0 In Eq. (5), knew represents the entrepreneurial knowledge that land-lost peasants obtained during the last period. lactive denotes the learning ability of land-lost peasants, which can also be interpreted as the ability of land-lost peasants to gain knowledge of
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entrepreneurship from other land-lost peasants in their social networks. They obtain different knowledge because each of them varies in ability, and the entrepreneurial knowledge obtained by other land-lost peasants in the social network also differs. This study assumes that lactive , i.e., the learning ability of land-lost peasants, behaves in accordance with a random distribution or lactive 2 ½0; 1. s indicates that land-lost peasants only communicate with and learn from a limited number of land-lost peasants in their networks, and their communication ability is limited. ki represents peasant i’s knowledge on entrepreneurship. An uncertain stochastic relation exists between the theoretical income of the entrepreneurship and non-entrepreneurship ventures of land-lost peasants. The equation is described as follows: Ey ¼ En þ e
ð6Þ
where Ey , En represent the theoretical incomes of the entrepreneurship and nonentrepreneurship ventures of land-lost peasants, respectively. e, which assumes a value between a and c, is a random number with uniform distribution, i.e., e 2 [a, c]. This study assumes that land-lost peasants can obtain more income with entrepreneurship than with non-entrepreneurship; thus, e > 0. 2.2
Multi-agent Simulation of the Entrepreneurial Behavior of LandLost Peasants
2.2.1 Modeling of Entrepreneurial Behavior of Land-Lost Peasants Within Land Expropriation Scenarios Compensation for land acquisition, social security, and land location are found to be critical for settling land-lost peasants in existing studies. Therefore, the present study includes the three factors into analysis. Compensation for land acquisition is of great importance. Several scholars found that compensation has a negative influence on the entrepreneurial intention of land-lost peasants [4, 10]. This model assumes that the compensation of land-lost peasants (hereinafter, referred to as c) is subject to random distribution. When land-lost peasants’ compensation for land acquisition exceeds the perceived benefits of entrepreneurship, they will exit the simulation experiment in the next cycle. Therefore, this model considers parameter c, i.e., c 2 ½1; þ 1. 1 ry ¼ p ð1 @ Þ Gy c
ð7Þ
1 rn ¼ ð1 b Þ G n c
ð8Þ
Good social security may have a catalytic effect on the ability of peasants to resist risk. For instance, urban households can take more risks than rural ones. This finding may be related to a series of social security systems in China, such as urban and rural pension and healthcare systems. Therefore, this model considers parameter B, i.e., B 2 ½1; þ 1.
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a ry ¼ p 1 Gy B b rn ¼ 1 Gn B
ð9Þ ð10Þ
The higher the social security, the lower the risk the land-lost peasants of will take on entrepreneurship. This finding is similar to the risk of unemployment of land-lost peasants. Land location reflects the geographic position of the expropriated land. In this study, land location is divided into three types, i.e., the area from the city center to the suburbs is divided into urban villages, urban–rural fringes, and remote villages. In accordance with location theory of economic geography, opportunities and resources showed a decreasing trend from the city center to the suburbs. Accordingly, the amount of resources and potential opportunities for land-lost peasants in different locations is described as follows: urban villages > the urban–rural fringes > remote villages. To a certain extent, the benchmark land price can represent the economic development level and resource status of a region [15]. Therefore, this paper will estimate the relationship between the resources and potential opportunities of the three land acquisition types based on the benchmark land price. The placement and social security guarantee of land-lost peasants in Zhejiang Province has always been at the forefront of China, and it plays an important role in supporting the entrepreneurship of land-lost peasants [16]. According to the GDP rankings of Zhejiang cities in 2016, Hangzhou, Wenzhou, and Jiaxing are located in the upper, middle, and lower levels respectively. Therefore, the ratio calculated based on the three cities’ benchmark land prices can represent the entrepreneurial resources and environmental status in the urban villages, the urban-rural fringe and the remote mountain villages in average sense. This paper selects the six-level land price standard. Grades 1 and 2 are defined as urban villages in this article. Grades 3 and 4 are specified as urban–rural fringes. Grades 5 and 6 are classified as remote villages. Assuming that the rural land price in Wenzhou City is 1 in rural areas, the relative land price ratio of urban villages to urban–rural areas can be calculated. Hangzhou and Jiaxing Cities perform the same calculation. Finally, on the basis of the ratio of the three cities, the ratio of urban villages is 5.26, and that of the urban–rural fringes is 3.2. Therefore, the theoretical income of the entrepreneurship of land-lost peasants is assigned as follows: 5.26Ey in urban villages, 3.2Ey in urban–rural fringes, and 1Ey in remote rural villages, indicating the differences among the three types of expropriated land. Table 1 presents Wenzhou City benchmark land price, and Table 2 shows the comprehensive land price factor of three cities.
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Table 1. Wenzhou City benchmark land price Grade Commercial land price
Total
1 2 3 4 5 6
16170 4.63
9900 6270 4360 2770 2120 1370
Ratio Housing land price
7130 2.04 3490 1.00
13230 10190 7470 5540 3620 2680
Total
Ratio Industrial land price
23420 3.72 13010 2.07 6300 1.00
2140 1810 1220 770 560 480
Total Ratio Comprehensive ratio 3950 3.80
4.05
1990 1.91
2.01
1040 1.00
1.00
Table 2. The comprehensive land price factor of three cities Wenzhou City Hangzhou City Jiaxing City Total Comprehensive ratio 4.05 7.61 4.13 15.79 5.26 2.01 5.67 1.92 9.60 3.20 1.00 1.00 1.00 3.00 1.00 Data sources: Zhejiang Provincial Department of land and resources. the price of construction land for key cities of Zhejiang Province in the 2nd quarter of 2016.
According to the previous analysis, the entrepreneurship tendencies of land-lost peasants in urban villages, urban–rural fringes, and remote villages are respectively shown as follows: 1 a ry ¼ p 1 5:26knew Ey c B 1 a ry ¼ p 1 3:2knew Ey c B 1 a ry ¼ p 1 knew Ey c B
ð11Þ ð12Þ ð13Þ
2.2.2 Simulation On the basis of the model specified in 3.2.1, this study investigates entrepreneurial decision making of land-lost peasants using the factors that influence their entrepreneurial decision making with multi-agent simulation. In this model, land-lost peasants are abstracted as agents. On the basis of the behavior rules of various subjects, the design includes properties, behavior standards of various types of agents, inter-subjective behavior of the rules, and entrepreneurial system evolution mechanisms and constraints. This model is divided into two categories, namely, necessity and opportunity entrepreneurship. In the initial stage, the simulation process is mainly designed to complete three tasks, which are number setting, model simplification and to create a partial environment for each land-lost
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peasant with the radius of the social network. The simulation model of land acquisition scenarios is based on the increasing number of factors that affect the compensation for land acquisition, security, and location. If land-lost peasants have a certain venture capital in the initial state, then they will obtain a positive policy support in entrepreneurial skills training, financial support, and other aspects with the guidance of the active entrepreneurship policy of the government. Land-lost peasants enrich their knowledge on entrepreneurship by exchanging and learning in their social networks, thereby improving their entrepreneurial skills and their ability to identify entrepreneurial opportunities. Land-lost peasants vary in their ability to learn new knowledge. This study assumes that entrepreneurship knowledge k obtained by trained land-lost peasants is uniformly distributed on [0, 1]. Entrepreneurial knowledge increment, which land-lost peasants obtained by exchanging and learning in their social networks, will be updated. Thus, they will be affected by the new state of knowledge in the new entrepreneurship decision making. Figure 1 shows the simulation process.
Fig. 1. Simulation process.
2.2.3 Parameter Description In this study, the agent’s simulation clock algorithm is platform owned, the range of the model is set to time t 2 ½1; 1500. We set up land expropriated village A as a study area, where the number of households randomly distributed is N/2. We assumed that each family consists of two persons facing employment or entrepreneurship. The number of peasant agents in this model is N. Table 3 shows the parameter names and definitions in the simulation model.
Table 3. Parameters setting A2 b Parameters P a b knew kn lalive A1 Value (0.1, 2) [0,1] [0,1] [0,1] 1 [0,1] [0,100] [100, + ∞] [1, +∞]
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3 Simulation Result Analysis This study examines the dynamic process simulation of the entrepreneurial decisionmaking behavior of land-lost peasants. Therefore, comparative experiments are designed in the simulation experiment. Each simulation experiment is controlled at 1,500 h, the number of land-lost peasants is 300, and the number of people in the social network is 39. Figure 2 presents the main interface of the simulation.
Fig. 2. The main interface of net logo simulation platform
The model involves compensation for land acquisition, social security, land location, and other factors that may have a significant effect on entrepreneurial selections. We discuss the effects of these factors on entrepreneurial selections. 3.1
Compensation for Land Acquisition
Experiment 1: To test the influence of compensation for land acquisition (hereinafter referred to as c), three values (36, 40, and 42) were selected in this simulation while fixing other parameters. The effects of different levels of compensation on entrepreneurial decision making are reflected, as shown in Figs. 3, 4 and 5. When c = 36, the simulation results (Fig. 3) revealed the number of land-lost peasants who decide to start a business is more than the number of land-lost peasants selecting not to start a business at a period of approximately 550. The number of peasants who decide to start a business showed a high increase rate when the entrepreneurship opportunity of land-lost peasants began to appear. At this time, the simulation result demonstrated that the compensation plays a relatively less obstructive role in the selection of entrepreneurship of land-lost peasants. When c = 40, the simulation results (Fig. 4) indicated that the number of land-lost peasants who did not select entrepreneurship increased due to high probability of increased compensation. In this case, the gap between non-entrepreneurial and entrepreneurial peasants is small. The number of entrepreneurs increased slowly. When c = 42, the simulation results (Fig. 5) showed that most of the land-lost peasants would not decide to start a business and their entrepreneurial enthusiasm was relatively low.
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Fig. 3. Simulation figure of c = 36.
Fig. 4. Simulation figure of c = 40.
Fig. 5. Simulation figure of c = 42.
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Social Security
Experiment 2: We fixed other parameters and changed the social security value B, which were separately set as 30 and 100, to observe the entrepreneurial selections of land-lost peasants. The higher the level of social security, the stronger the ability to cope with risks of land-lost peasants. Figures 6, 7 and 8 show that the stimulus to employment is stronger than the stimulus to entrepreneurship when the level of social security increased. A comparison of three intervals reflected the change in number of people when the social security value changes from low to high. When t 2 [0,800], the gap of land-lost peasants deciding to start a business or not was small. After t = 800 or so, the number of land-lost peasants at a higher social security level deciding to start a business was less than that at a lower social security level. When t = 1500 or so, the gap between the numbers began to close. Accordingly, when social security increased from low levels, the individual factor of social security has a limited effect on the promotion of entrepreneurship but is effective in promoting employment.
Fig. 6. Comparison on the number of non-entrepreneurs when B = 30
Fig. 7. Comparison on the number of necessity entrepreneurs when B = 30
B = 100.
B = 100.
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Fig. 8. Comparison on the number of opportunity entrepreneurs when B = 30
3.3
B = 100.
Land Location
Experiment 3: The effects of land location are investigated by fixing other parameters and changing the location factor. To establish the model, this study selected the benchmark land prices of Jiaxing, Hangzhou, and Wenzhou Cities, where different levels of land prices in zones were compared to obtain the location factor. In the following analysis, Zone 1 represents remote rural areas, Zone 2 refers to urban–rural fringe, and Zone 3 indicates urban villages. Supposing that the number of people in three regions is the same, in the simulation test, the number of land-lost peasants deciding to start a business in different regions is not the same even if other factors remain the same. Figures 9, 10, 11 and 12 show the simulation results. The results indicate that when the land is close to the city center, the entrepreneurial land-lost peasants appear early. Opportunity entrepreneurship occurs early as well. When t = 571, the number of entrepreneurs in Zone 3 (urban villages) is largest, and the number of entrepreneurs in Zone 2 (urban–rural fringe) is less than that in Zone 3. The number of land-lost peasants deciding to start a business in Zone 1 (remote rural areas) is the smallest. The number of people decreased as the zone changed from the city to the urban–rural fringe to the remote rural area.
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Fig. 9. Comparison on the number of entrepreneurs in different locations.
Fig. 10. Comparison on the number of non-entrepreneurs in different locations.
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Fig. 11. Comparison on the number of necessity entrepreneurs in different locations.
Fig. 12. Comparison on the number of opportunity entrepreneurs in different locations.
4 Discussion Excessive compensation for land acquisition plays a significantly negative role in the entrepreneurial decision-making behavior of land-lost peasants. High compensations for land will inhibit the entrepreneurial activity of land-lost peasants. In Experiment 1, the active participation of land-lost peasants in entrepreneurship decreased rapidly with the increase in the compensation, and entrepreneurial activities appear slowly. Thus, few land-lost peasants decide to start their own businesses. When the compensation reaches a high level, the majority of land-lost peasants will not decide to start a business. Compensation that can meet the needs of their lives will inhibit the emergence of entrepreneurial intention of land-lost peasants. Therefore, the amount of compensation payments should be calculated scientifically and reasonably and not only be distributed fairly but also used effectively so as to meet the livelihood needs of landlost peasants and promote its long-term development.
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The current compensation for land-lost peasants in China due to the different levels of economic development and other factors is generally low and lower in the mid-west than that in the east. At present, the transaction of land property rights in the eastern region is active, and the peasant households have a wide range of economic sources and compensation for land acquisition. Therefore, starting from the aspects of creating an entrepreneurial environment and establishing a business model is necessary to foster entrepreneurship of land-lost peasants. Local governments should hold entrepreneurial competition activities to attract innovative land-lost peasants to participate in entrepreneurial activities so as to enhance the entrepreneurial atmosphere. In addition, proclaiming typical stories through the mass media and establishing the rural elite effect are also alternatives. The typical story can stimulate the entrepreneurship intention of the land-lost peasants. The rural elite refers to the people who have entrepreneurial marketing and technical abilities in the countryside, including the entrepreneur elite, the technical elite, and the village cadres. Many practices in China’s rural areas have proven that the typical story and leading path of the rural elite are simple and effective. As for the mid-west peasants who have less compensation, the government can provide initial capital assistance and support through the entrepreneurial policies, for example, providing free entrepreneurship training in the early stages, self-employed awards, small-sum guaranteed loan, and rent subsidy of self-employed place. Then, the government should step up the guidance of the rational use of compensation. Present studies found that land-lost peasants, who are a special group, have unique group characteristics and intuitive behaviors [3]. Land-lost peasants with sudden wealth accumulation fail to create reasonable and rational consumption planning, such as purchasing luxury goods, and even abusing drugs. These situations decrease the effectiveness of demolition compensation, which is not conducive to social stability. Therefore, the government should appropriately arrange for land requisition compensation and resettlement and address demolition compensation to improve its efficient use. The local government can establish land-lost peasants’ venture capital fund to control the number of compensations that directly inflows to the land-lost peasants and place a certain proportion of land acquisition compensation into the venture fund. Moreover, land-lost peasants in collective land expropriation can consider village collective entrepreneurship, which means that the collective economic organization of peasants builds plants and shops for rent or start a collective business in nonagricultural industries. A new industry development can promote the local economy and provide employment for peasants, which further enhancing peasants’ sustainable livelihoods and their own rural hematopoietic function [17]. The improvement in the level of social security has minimal effect in promoting the entrepreneurial decision-making behavior of land-lost peasants. Experiment 2 shows that the level of social security played a significantly positive role in promoting the employment of land-lost peasants, whereas its effect on entrepreneurship was limited. A good level of social security is of great importance for land-lost peasants. However, single social security can only guarantee stability of land-lost peasants without promoting their development and providing a powerful stimulus of entrepreneurship. Unlike the point of view of several scholars, sound social security can reduce the risk of entrepreneurship and leave a significantly positive effect in promoting the emergence of activities. However, in terms of China’s current situation, establishing a
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sound social security system is difficult due to limited funds and large number of landlost peasant groups. From the view of the current development trend, the social security of land-lost peasants should be based on their family needs and combined with the family population structure, to prevent trouble following land-lost peasants who like to start their own businesses. The improvement of their social security is able to start from the following three aspects: The first one is to ensure that all the land-lost peasants are included in the low insurance coverage and all of them should be granted the basic living allowances. The second one is to provide as many opportunities as possible to participate in pension and social insurances for the middle-aged and elderly land-lost peasants. Enhancing their follow-up living security is of great importance to ensure that the living standards reach the level prior to land acquisition. The third one is to establish an unemployment registration system of land-lost peasants to grasp their employment status at any time. Unemployment insurance is granted to eligible landlost peasants, and non-insured groups are encouraged to start businesses. In different land acquisition areas, the degree of activity of the entrepreneurship of land-lost peasants differs and follows the rules of descending order from city villages to the urban–rural fringe and the remote rural areas. In Experiment 3, the activeness of entrepreneurship of land-lost peasants decreased from city villages to the urban–rural fringe and remote rural areas. Therefore, considering different geographical conditions and the implementation of regional differentiation guidance policies is of great importance. For places with high economic development, such as urban villages and urban–rural fringe areas, the local entrepreneurial environment should be improved first, including increasing business projects and business opportunities. Moreover, local entrepreneurial channels (i.e., the establishment of business incubators and business service centers) should be expanded to improve service levels to help land-lost peasants transform from necessity entrepreneurship to opportunity entrepreneurship. In remote rural areas, priority should be provided to protecting the livelihood of land-lost peasants after land acquisition (i.e., to increase satisfaction with compensation standards and implement local employment and social security policies) so as to eliminate doubts. Then, the government can guide entrepreneurial training through “compensatory education, guide training, skills training, and planning training” model. First, compensatory training will eliminate the cultural deficiency of the land-lost peasants as much as possible and will lay the foundation for entrepreneurship. Second, entrepreneurship intention is the first step to implement entrepreneurial behaviors [18]. Cultivating the entrepreneurial consciousness of the land-lost peasants, including awareness of hard work, risk, and cooperation, is necessary. Consciousness is a guide to action. Entrepreneurial awareness plays a direct guiding role in entrepreneurial behavior and is an important part of entrepreneurial quality. Next, entrepreneurial skills training will be in progress, including industry technical and business management skills trainings, which focus on the cultivation of entrepreneurial operation skills. Finally, a complete entrepreneurial plan is created through entrepreneurial plan training to help land-lost entrepreneurs start their own businesses and clarify the entrepreneurial tasks at each stage so as to increase the probability of entrepreneurial success.
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5 Conclusion Rapid urbanization in China resulted in the presence of land-lost peasants. The government should help this vulnerable group solve the problem of survival and development and encourage them to make entrepreneurial decisions. However, only a few studies investigated the dynamic decision-making process of land-lost peasants in the land acquisition scenario. Therefore, providing effective guidance for land-lost peasants remains difficult. From the perspective of scenario simulation, this study modified the Todaro model and established the model of entrepreneurial decision making for landlost peasants under land acquisition scenario. This study then performed a dynamic simulation on the NetLogo platform to access the dynamic evolution of the entrepreneurial decision making of land-lost peasants. The results indicate that excessive compensation for land acquisition plays a significantly negative role in their entrepreneurial decision-making behavior. The degree of activity and entrepreneurship of land-lost peasants varies in different areas and follows the rules of descending order from city villages to the urban–rural fringe and remote rural areas. Social security hardly affects the entrepreneurship activities of land-lost peasants. The visualization of this study will help clarify the relationship among compensation for land acquisition, social security, and location of expropriated land and the entrepreneurial decision-making behavior. This finding provides a quantitative and experiential basis for the government in formulating policies to promote the entrepreneurship of land-lost peasants. However, this study has several limitations due to the limited research objectives and time constraint. Research variables of land expropriation scenarios are not comprehensive enough. In addition, the parameters of the simulation experiment are set up with reference to relevant studies of other scholars in combination with the comprehensive selection of this study. Although the parameters are close to reality, several parameters remain subjective. Thus, future studies should consider additional factors. Moreover, the design of the parameters should be made objectively, which can be achieved by consulting highly influential journals and conducting practical research. Acknowledgements. This work was supported by National Natural Science Foundation of China (grant numbers 41371187 and 71503228), Natural Science Foundation of Zhejiang Province of China (grant number LQ16G030006), Qianjiang Talents Program of Zhejiang Province (QJC1602006), and Philosophy and Social Sciences Planning Project of Hangzhou (M17JC032).
References 1. Wei, H., Song, Y., Sheng, G.: China Urban Development Report No. 4. Social Sciences Academic Press, Beijing (2011). (in Chinese) 2. Bao, H., Fang, Y., Ye, Q., Peng, Y.: Investigating social welfare change in urban village transformation: a rural migrant perspective. Soc. Indic. Res. (4), 1–21 (2017). https://doi.org/ 10.1007/s11205-017-1719-9 3. Bao, H., Zhu, X., Cen, Y., Peng, Y., Xue, J.: Effects of social network on human capital of land-lost farmers: a study in Zhejiang Province. Soc. Indic. Res. 137(1), 167–187 (2017)
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4. Bao, H., Peng, Y.: Effect of land expropriation on land-lost farmers’ entrepreneurial action: a case study of Zhejiang Province. Habitat Int. 53(Suppl. C), 342–349 (2016). https://doi.org/ 10.1016/j.habitatint.2015.12.008 5. Gohmann, S.F.: Institutions, latent entrepreneurship, and self-employment: an international comparison. Entrepr. Theory Pract. 36(2), 295–321 (2012) 6. Constant, A., Shachmurove, Y., Zimmermann, K.F.: What makes an entrepreneur and does it pay? Native men, Turks, and other migrants in Germany. Int. Migr. 45(4), 71–100 (2010) 7. Kontos, M.: Self-employment policies and migrants’ entrepreneurship in Germany. Entrepr. Reg. Dev. 15(2), 119–135 (2003). https://doi.org/10.1080/0898562032000075131 8. Lockyer, J., George, S.: What women want: barriers to female entrepreneurship in the West Midlands. Int. J. Gend. Entrepr. 4(2), 179–195 (2012). https://doi.org/10.1108/ 17566261211234661 9. Mcevoy, D., Hafeez, K.: Ethnic enclaves or middleman minority? Regional patterns of ethnic minority entrepreneurship in Britain. Int. J. Bus. Glob. 3(1), 94–110 (2009) 10. Han, L., Bao, H., Peng, Y.: Which factors affect landless peasants’ intention for entrepreneurship? A case study in the South of the Yangtze River Delta, China. Sustainability 9(7), 1158 (2017). https://doi.org/10.3390/su9071158 11. Zhao, C., Li, Y., Lan, Q.: “Polarization” and in-depth analysis of the income of landless peasants in suburban areas. Rural Econ. (4), 54–59 (2015). (in Chinese) 12. He, Y., Huang, X., Yang, X.: Adaptation of land-lost farmers to rapid urbanization in urban fringe: a case study of Xi’an. Geogr. Res. 36(2), 226–240 (2017). (in Chinese) 13. Todaro, M.P.: A model of labor migration and urban unemployment in less developed countries. Am. Econ. Rev. 59(1), 138–148 (1969). (in Chinese) 14. Li, S., Xiong, Y.: Study on the impact factors of non-farm employment based on the Todaro model amendment. Stat. Inf. Forum. 26(12), 74–79 (2011). (in Chinese) 15. Ouyang, A.J., Ang-Yang, G.E.: Study on the confirmation of the connotation of urban benchmark land-price and its benchmark condition. J. Zhejiang Univ. 29(5), 585–588 (2002) 16. Li, Y., Xu, N.: The individual characteristics, the factors in systems and the urbanization of peasants who have lost their land. Manag. World (1), 62–70 (2011). (in Chinese) 17. Peng, Y., Zhu, X., Zhang, F., Huang, L., Xue, J., Xu, Y.: Farmers’ risk perception of concentrated rural settlement development after the 5.12 Sichuan Earthquake. Habitat Int. 71, 169–176 (2018). https://doi.org/10.1016/j.habitatint.2017.11.008 18. Wilson, F., Kickul, J., Marlino, D.: Gender, entrepreneurial self-efficacy, and entrepreneurial career intentions: implications for entrepreneurship education 1. Entrep. Theory Pract. 31(3), 387–406 (2007)
Analysis of the Land Use Situation of China in the Last Decade Juan-er Zheng1(&), Ling-xia Cao1, Wen-bin Tan2, and Feng Deng2 1
2
China National Institute of Standardization, Beijing, China [email protected] Chinese Academy of National Resources Economics, Beijing, China
Abstract. This paper analyzed the situation of the land use in China in the last decade. During 2008 to 2018, land approved by the government for construction use from agricultural use has increased at the start, and decreased since 2012. The percent of industrial land, residential land and commercial land are decreasing while the land for infrastructure is growing generally. The GDP per hectares continues to fall due to the high efficient use of construction land. The distribution of land resources was more market-oriented and quite stable since 2011. Except for some periods, land price was rising all the time in the last decade, especially in 2009, 2010, 2013, 2016 and 2017. The local government relies highly on land and this situation has not improved significantly in 2012 to 2018. In the near future, it is expected that the demand for land will decreasing compared with the last decade, the price will go up steadily. Keywords: Land price
Land market Land supply Land grant
China’s economy has grown tremendously in the past decade. Land plays a positive role in economic growth. Also, we face and criticize the problems brought by land, e.g., high housing price, overdependence of local government on land revenue. It is necessary to analyze land use situation in the past decade so that we can management land well in the following years.
1 Construction Land Supply 1.1
Area of Construction Land Supplied by Government
During 2008 to 2018, the land approved by the government for construction use from agricultural use has increased at the start, and decreased since 2012, see Fig. 1. The peak point is 615 thousand hectares. In the first three quarters of 2018, the land approved by the government for construction use is 205.7 thousand hectares, which were down 11.9% from a year earlier. The state-owned construction land supplied has showed a little different trend, see Fig. 1. It increased at 2008, decreased since 2013 and increased in 2016 again. In the first three quarters of 2018, the state-owned construction land supplied by the government is 361 thousand hectares, down 8.5% from 2017. The main cause of this situation is the slowing down of economic growth, more attention to the stock of construction land due to the consideration of farmland protection. China’s strategy of economic development has transferred from rapid growth to high-quality growth. The demand for construction land is not as strong as before. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 269–277, 2021. https://doi.org/10.1007/978-981-15-3977-0_20
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Another key factor for the decrease of the construction land is that land acquisition is becoming more and more difficult. The central government encourages the local government to use more stock land than newly-added construction land.
Fig. 1. Supply of construction land (Unit:10 thousand hectares)
Data resource: the data of 2001 to 2015 is from the Yearbook of Land and Resources Statistics; Data of 2016, 2017, and 2018 is from Bulletin on Statistics of Land and Resources yearly. 1.2
The Structure of Land Supplied by the Government
During 2008 to 2018, the structure of state-owned construction land is shown in Fig. 2. The percentage of industrial land, residential land and commercial land are decreasing while the land for infrastructure and public affairs is mainly growing. From 2008 to 2017,the proportion of industrial land is decreasing from 39.57% to 20.36%, the commercial land is from 11.49% to 5.13%, the residential land is from 26.38% to 13.97%. As a comparison, the proportion of land for infrastructure and public welfare was increasing from 22.55% to 60.54% (see Fig. 2). Data resource: the data of 2008 to 2015 is from the Yearbook of Land and Resources Statistics; Data of 2016, 2017, and 2018 is from Bulletin on Statistics of Land and Resources yearly. According to the data issued by the Ministry of Natural Resources, during the first three quarters of 2018, the percentage of industrial land, residential land, commercial land, public infrastructure sites is 24.5%:19.4%:6.5%:49.6%. The proportions of land for infrastructure and public welfare is lower than 2017. The reason for the increase of the proportion of residential land in 2018 is probably due to the adjustment of national macro-control policies on real estate market. The housing price had an upsurge during 2016–2017. So the central government decided to establish long-term mechanisms in real-estate market. So, the supply of residential land increased correspondingly.
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Fig. 2. Structure of land supplied by the government (2008–2018)
2 The Efficiency of Land Use 2.1
GDP Per Hectares
From 2008 to 2018, the GDP per hectares continues to fall, see Fig. 3. In 2008, if the GDP grow by 1 billion, the construction land input was 1034.6. But in 2017, only 495.8 hectares was needed. According to the prediction by the Chinese Academy of Social Sciences, China would achieve a 6.6 percent GDP growth in 20181. If so, the billion GDP per hectares would be 468.81, lower than 2017. So, in the past decade, it is obviously that the efficiency of land use has been improved. Data resource: the data of construction land is from the service platform of Ministry of Land and Resource for sharing land survey results. Data of GDP is from the State Statistical Bureau of China; the construction land of 2017 and 2018 is based on the data of construction land in previous years and the approval of construction land in the current year.
1
The blue book released by the Chinese Academy of Social Sciences. http://sh.sina.com.cn/news/m/ 2018-12-24/detail-ihqhqcir9884081.shtml.
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Fig. 3. GDP per hectares
2.2
The Proportion of Cultivated Land Occupied by Construction
In the resent years, the proportion of cultivated land occupied by construction is decreased in general (Fig. 4). Due to the lack of data, we can only get the data from 2012–2017, see Fig. 4. In 2012, the proportion is 42.2%. After that, the proportion dropped to 38.5% in 2016 but had a slight increase in 2015. In 2017, proportion of cultivated land occupied by construction is 42.6%, higher than the past years.
Fig. 4. Cultivated land occupied by construction
Data resource: Bulletin on Statistics of Land and Resources yearly.
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3 The Distribution of Commercial Land During the past decade, the distribution of land resources was more market-oriented. Since 2011, the proportion of land granted by bidding, auction and listing system (BAL) is more than 90% both in area and income (Table 1). In 2013, the area percentage of land granted by bidding, auction and listing system increased by 1.6 percent compared with 2012. After that, it remained basically constant, but due to the growth of land price, the proportion of income increased as a whole. In 2016, 96.2% of the total revenue from the land grant was obtained by bidding, auction and listing system. In 2017, it is 97.5%. Since 2004 land granting by negotiation was at last totally prohibited for profitoriented developments, land pricing system has started to positively and significantly improve urban land productivity; the land pricing system also promotes more productive urban land usage by stimulating more intensive investment and better business management (Jinfeng Du, Richard B. Peiser 2014). Table 1. Land granted by bidding auction and listing system (2008-2018) Year
All of land granted(10 thousand hectares
Revenue of land granted (billion RMB)
Area of land granted by BAL (10 thousand hectares
Revenue of land granted by BAL(billion RMB)
Percent of area granted by BAL(%)
Percent of revenue granted by BAL(%)
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018(1–9)
23.50 16.59 22.08 29.37 33.51 33.24 37.48 27.73 22.49 20.82 22.54 17.64
12216.72 1025.98 1717.953 2746.448 3212.608 2804.228 4374.53 3437.737 3122.064 3556.83 4986.21 4162.55
11.73 13.92 18.72 25.95 30.50 30.16 34.62 25.65 20.73 19.15 20.82 Lack of data
10074.86 952.874 1629.559 2636.342 3081.827 2665.343 4210.95 3276.515 2975.55 3419.98 4861.45
49.92 83.94 84.79 88.36 91.01 90.74 92.37 92.51 92.19 91.98 92.37
82.47 92.87 94.85 95.99 95.93 95.05 96.26 95.31 95.31 96.15 97.50
Data resource: the data of 2007 to 2015 is from the Yearbook of Land and Resources Statistics; Data of 2016, 2017, and 2018 is from Bulletin on Statistics of Land and Resources. The data of the Revenue from the Ministry of Land and Resource is slightly different from the data offered by the Ministry of Finance.
4 Land Price The change of land price from 2008 to 2018 is shown in Fig. 5. Except for some periods (in the fourth quarter of 2008 and 2011, and the first quarter of 2012), the land price was rising all the time, especially during the third quarter of 2009 to the third quarter of 2011 and the first quarter of 2016 to the third quarter of 2018. Different land uses had different trends. Residential land and commercial land were pioneers of the rising or falling. From 2016 to 2017, the residential land price rose rapidly due to the
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upsurge housing price. But the price of industrial land, comprehensive land and commercial land grow slowly comparatively. One thing worth discussing was the change of industrial land price. In the past decade, it was the most stable one. This was mainly due to the tendency of local governments to lower industrial land price to attract investment. But due to the high dependence on land revenue to build infrastructure, the city government had to grant commercial land and residential land with higher price. During the recent years, mainly in 2015 to 2018, residential land price was higher than commercial land. But in 2008 to 2012, commercial land was generally higher than residential land. Now, let’s see the annual data, see Table 2. Land price was high in 2009, 2010, 2013, 2016 and 2017, and relatively peaceful in 2011, 2014 and 2018. According to the Centerline Group, nearly 282 land auctions failed in the first eleven months of 2018 in the first and second tier cities, the highest in the past 6 years. At the same time, 944 land auctions failed in the third and forth tier cities, compared with 766 in 20172.
Fig. 5. Quarter-on-quarter grow rate of different land use types (%)
Data resource: Urban Land Price Dynamic Monitoring Group of China Land Surveying and Planning Institute.
2
Land auctions failed in the first eleven months of 2018 in more than 114%. http://www.cs.com.cn/cj/ fcgs/201812/t20181203_5899603.html.
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Table 2. Price of land granted (2008—2018) Year Price of land granted (billion/thousand hectares) Growth rate (%) 2008 6.18 18.96 2009 7.78 25.81 2010 9.35 20.19 2011 9.59 2.52 2012 8.44 −12.00 2013 11.67 38.35 2014 12.40 6.22 2015 13.88 11.98 2016 17.08 23.06 2017 22.12 29.49 2018(1–9) 23.60 6.67 Data resource: Data of 2007 to 2015 is from the Yearbook of Land and Resources Statistics; Data of 2016, 2017, and 2018 is from Bulletin on Statistics of Land and Resources.
5 Land Revenue and Land Finance From 2008 to 2018, revenue from land granted was rising except some years. In 2013, the revenue is as high as 4374.53 billion, much more than 2012. There was a peak in 2017 when the revenue from land granted was almost 5000 billion, see Table 3. Let’s compare the revenue from land granted with the General Budget Revenue of Regional Finance now, see Table 3. It can be seen that during 2008 to 2017, the ratio of land granted revenue to General Budget Revenue of Regional Finance fluctuated. The highest point was in 2013, followed by 2014 and fell to 0.38 in 2015, rebounded in 2016 and 2017. The ratio of 2018 is as same as 2017. Between 2008 and 2018, the ratio is mainly in the range of 0.4–0.6, see Table 3). According to the standards by the Ministry of Finance, this paper took deed tax, land value-added tax, real estate tax, land occupation tax and urban land use tax as land and real estate related tax, see (E). We added the revenue of land granted together with the land and real estate related tax, and divide the aggregated data by the General Budget Revenue of Regional Finance. We get (G). (G) is higher than (D), and also fluctuated like (D). So, it is obviously that the local government relies highly on land and this situation didn’t improve significantly over the past few years. So in China, we call this phenomenon “Land Finance”.
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J. Zheng et al. Table 3. Land revenue compared with the local finance
Year
All of land granted(10 thousand hectares (A)
Revenue of land granted (Billion RMB) (B)
General budget revenue of regional finance (Billion Yuan) (C)
Ratio of land granted revenue to the general budget revenue of regional finance (D = B/C)
Land and real estate related tax (Billion Yuan) (E)
Revenue of land granted + land and real estate related tax (Billion Yuan) (F) = B+E
All of land revenue/general budget revenue of regional finance (G) = F/C
2001
9.04
129.589
780.33
0.17
50.03
179.62
0.23
2002
12.42
241.679
851.5
0.28
67.61
309.292
0.36
2003
19.36
542.131
984.998
0.55
90.07
632.197
0.64
2004
18.15
641.218
1189.337
0.54
120.78
761.996
0.64
2005
16.56
588.382
1510.076
0.39
159.06
747.442
0.49
2006
23.30
807.764
1830.358
0.44
196.19
1003.956
0.55
2007
23.50
1221.672
2357.262
0.52
275.53
1497.206
0.64
2008
16.59
1025.98
2864.979
0.36
365.66
1391.642
0.49
2009
22.08
1717.953
3260.259
0.53
481.23
2199.185
0.67
2010
29.37
2746.448
4061.304
0.68
652.99
3399.434
0.84
2011
33.51
3212.608
5254.711
0.61
822.85
4035.453
0.77
2012
33.24
2804.228
6107.829
0.46
1012.80
3817.026
0.62
2013
37.48
4374.53
6901.116
0.63
1224.64
5599.173
0.81
2014
27.73
3437.737
7587.658
0.45
1381.87
4819.606
0.64
2015
22.49
3122.064
8300.204
0.38
1402.09
4524.152
0.55
2016
20.82
3556.83
8723.935
0.41
1501.80
5058.63
0.58
2017
22.54
4986.21
9144.754
0.55
1643.70
6508
0.72
2018(Q1-Q3)
17.64
4162.55
7624.9
0.55
1385.30
5547.85
0.73
Data resource: Data of 2001 to 2015 is from the Yearbook of Land and Resources Statistics; Data of 2016, 2017, and 2018 is from Bulletin on Statistics of Land and Resources. General Budget Revenue of Regional Finance Billion, Land and real estate tax is from the State Statistical Bureau and the Ministry of Finance.
6 Forecast of the Near Future 6.1
Land Supply
The reports of the 19th National Congress of the Communist Party of China pointed out that China’s economy should shift from high-speed growth to high-quality development. We must adhere to quality and pay more attention to efficiency. It is expected that in the near future, the demand for land will decrease. The local government will rely more on the stock of land due to the reform of China land requisition system. At the same time, in order to establish a long-term mechanism of the real estate market, the residential land supply may increase in the near future. Land supply policies should be innovated and combined with other means to establish classification and guidance policies for the sustainable development of urban housing system (Yuzhe Wu 2018). In order to promote the real economic growth, the proportion of industrial land supply may increase in some cities like Shenzhen who is going to strengthen its industry further. As to the regional structure of land supply, since the poor mainly live in the central and Western of China, the land supply in these areas will increase in order to realize the aim of a well-off society in these regions simultaneously with other provinces.
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Land Market and Land Price
Based on the land market development situation in the past decade and the policy orientation, it is expected that in the near future, the proportion of land granted by bidding, auction and listing system (BAL) will remain high and stable. Considering that the central government continues to reform the real estate market and establish a long-term mechanism, it is expected that the housing price will not rise in the next future. However, due to the downward pressure on the economy, the real estate regulation policy of China may not continue to tighten. Some forms of policy loosening may be adopted in 2019. Therefore, land price may rise modestly in the next following years. 6.3
Land Revenue and Risk Brought Land Mortgage
The high dependence of local government on land revenue will continue but the level may decrease as the lower expanding rate of cities or the imposed of property tax. One of the most noteworthy problems is the cities’ debt related with land mortgage. In recent years, the local debt grows rapidly. According to the data issued by the Ministry of Finance, by the end of November 2018, the balance of local government debt was 18290.3 billion Yuan. Among them, the general debt is 10861.6 billion Yuan; the special debt is 7428.7 billion Yuan3. Many debts are intended to repay by land revenue. Local governments often obtain loans through land mortgage. If the land market collapses, the financial risks may expand and damage the real economy finally. China should be aware of something bad thing such as the deterioration of the Sino-U.S trade environment and so on. These things may trigger series problems on economy, and finally affect the real estate market and land market and in verse form. Acknowledgements. This paper is supported by Presidency Fund of China National Institute of Standardization. The Projects No. are “602019Y-6681” and “602019Y-6680”
References Jinfeng, D., Peiser, R.B.: Land supply, pricing and local governments’ land hoarding in China. Regional Sci. Urban Econ. 48, 180–189 (2014) Wu, Y., Wang, W.: Suggestions on the classification and guidance policies for the sustainable Development of Urban Housing System. J. Zhengzhou Univ. 51(4), 42–47 (2018)
3
China issues a total of 4101.4 billion bonds in the first eleven months. http://www.sohu.com/a/ 283196065_116897.
Research on the Governance Modality of Village-in-City Based on Mitchell Score-Based Approach Qin Wang and Yuzhe Wu(&) School of Public Affairs, Zhejiang University, Hangzhou, China [email protected]
Abstract. Village-in-city is a non-agricultural village formed by the rapid advancement of urbanization in China and the urban-rural dual structure, where the urban service boundary (USB) failed to keep up with the urban growth boundary (UGB). The governance of village-in-city is a complex system involving a large number of stakeholders. In addition to local governments, village collectives and villagers, floating population is also its core stakeholders. This paper took 14 villages in Beilun District, Ningbo as the research object, selected typical cases to conduct field surveys, questionnaire surveys and interviews. Then classified each group based on the Mitchell score-based approach, and summarized Demolition and Reconstruction (M1), Partial demolition and space Optimization (M2) and Facilities and Landscape Comprehensive Consolidation (M3) three types of governance modalities. The internal mechanisms of each modality were analyzed and compared through SCM to compare their distribution characteristics. Finally, it proposed future governance directions in terms of housing, employment, planning and government. Keywords: Village-in-city Governance modalities
Mitchell score-based approach Stakeholder
1 Introduction Since the reform and development in China in 1978, a large number of rural people have been transferred to cities. The permanent population in urban areas has increased from 172 million in 1978 to 823 million at the end of 2016, and the urbanization rate has reached 57.35%, it is expected to increase to 70% by 2050. With the rapid urbanization, the level of urban construction management has lagged behind. In the place where USB has not kept up with UGB, China’s unique village-in-city has been formed. There are problems such as lagging urban planning, imperfect infrastructure, severe fire hazards, and disorderly population in these villages. It has become a big challenge for China to build inclusive, safe and sustainable cities and communities. The village-in-city is the result of the mutual connection of different interests of various stakeholders. Its governance is a long-term and systematic social collective action involving a large number of stakeholders. The difficulty lies in how to dynamically and effectively coordinate various stakeholders. Because of the complex relationship between them, different governance modalities need to be adopted. In addition, the current system © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 278–304, 2021. https://doi.org/10.1007/978-981-15-3977-0_21
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of affordable housing in China is not yet complete. The government’s official low-cost housing cannot meet the needs of flouting population. Village-in-city is an informal supplement to the urban housing security system and plays an important role in maintaining economic and social stability. Therefore, there is still the necessity of existence in village-in-city at this stage. From the perspective of social equity, its governance should pay more attention to the interests of vulnerable groups. This paper introduced the Mitchell score-based approach and stakeholder communication matrix (SCM), combined Beilun’s practice to analyze the characteristics of stakeholders in different governance modalities and their mutual relations. Then summarized governance experience and existing problems, and proposed more inclusive and sustainable governance directions of village-in-city in the future.
2 Research Methods and Study Area Overview 2.1
Research Methods
Stakeholder Analysis is a decision analysis method that addresses the balance of interests and objectives of multiple parties [1]. Its main purpose is to analyze the interconnections, obstacles, and existing network structures among stakeholders [2], to understand the system and assess the impact of system changes by identifying the main stakeholders in the system and their respective interests, and the impact on system changes [3]. The Mitchell score-based approach is a method of defining the types of stakeholders by scoring stakeholders from three aspects of power, legitimacy, and emergency [4]. Legitimacy refers to whether the group has invested dedicated assets during the governance [5]; power refers to whether a group has a status, ability or means to influence the government’s decision; urgency is whether a certain group’s demands can immediately attract the attention of the government. Mitchell defines three major categories of stakeholders, among which definitive stakeholders have all three attributes, expected stakeholders have two of them, and potential stakeholders have only one attribute. Since the classification model is dynamic, any stakeholder will change from one form to another after gaining or losing certain attributes [6], thus the classification under different modes will be different (Table 1). 2.2
Study Area Overview
Beilun District, Ningbo is located at the easternmost point of land in Zhejiang Province, surrounded by sea on three sides and has rich port resources. The district has a total area of 872 km2 and currently governs 11 streets. By the end of 2015, it had a registered population of 395492, of which 246495 were urban residents, accounting for 62.3%; the permanent population was nearly 900000, and the urbanization rate of permanent residents was 73.6%. This paper focuses on the core area of the Beilun central area (Fig. 1). A survey in 2016 shows that there are 15 urban villages in the area, with 26650 household registration population and 13952 households, while the number of flouting population is 81200.
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Q. Wang and Y. Wu Table 1. Guidelines for stakeholder ratings in the governance of Village-in-city
Rank
High
Legitimacy
Power
Urgency
Their dedicated assets have been
Actually participating in the
Take the initiative and can raise
invested in the process of
governance of the Village-in-cit,
the concern of the government.
governance in Village-in-city,
and is part of the participants.
taking risks and being directly affected by the effectiveness of governance.
Medium
Although no dedicated assets
Can't participate in the
Their self-demand can be
have been invested, they are
governance process in
passively received the attention of
affected by the effects of
Village-in-city, but has the
the government, or they can take
governance.
status, ability, or means that can
the initiative to ask for it but it
influence government’s
has caused less attention.
decision-making. Low
They are hardly affected by the
Neither the participants nor the
There is no interest appeal related
effects of governance.
ability to influence government
to the governance of
decision-making.
Village-in-city.
Fig. 1. Distribution of the villages-in-city in the Beilun central area
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3 Case Study According to the investigation, the author conducted a comprehensive evaluation of the influence of stakeholders on the basis of three factors: legitimacy, power, and urgency. Using the three impact factors as variables, the authors deduced the overall demolition reconstruction type and local demolition space. Three types of urban villages governance model of optimized and comprehensive renovation of the landscape of facilities, and selected Longshun, Datong and Xiangjia Village as typical representatives of these three types of models for empirical analysis. 3.1
Demolition and Reconstruction (M1)
3.1.1 Typical Village Survey of Longshun Village Longshun Village was once the most famous village-in-city in Beilun, and the Daidi Qiujia was its last plot. It was located on the north side of Beilun District Government and was about 1 km south from Metro Line 1. In 2013, District Land expropriation and demolition Office included the plot as an demolition and reconstruction plot for commercial residential project development. The demolition started on July 1st, 2016, it was the second village-in-city of M1 since the implementation of “Sunshine Demolition”. The actual demolition involved 247 households. 245 households had signed a contract with a success rate of 99.2% in December 2016. The entire demolition officially ended in May. At the end of 2017, the plot was listed with an auction price of 9500 yuan/m2, which was the record high for the Beilun floor price. The total sale area was approximately 45108 m2, and the final floor price was 15400 yuan/m2, 12.5 billion transactions totally (Fig. 2).
Fig. 2. Location map of Daidi Qiujia plot
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3.1.2 Stakeholders and Their Importance In the process of governance in village-in-city, the interests of different stakeholders are different (Table 2). A necessary precondition for the success of governance in villagein-city is that each stakeholder clearly identifies their own legitimate interests [7]. The size of each stakeholder’s interest determines how much each of them is willing to pay to achieve their benefits in governance; on the other hand, the extent to which the interests of all parties can be realized depends on how different The status, power, and influence in the governance model.
Table 2. Stakeholder objectives of M1 Stakeholders Higher level government Local government
District Land and Resources Bureau Local government unit
District Land expropriation
Interests Comprehensive optimization of economic and social benefits Complete the demolition mission in village-in-city; Improve performance; Improve the look of the city Complete the annual transformation goals and tasks; Improve the level of land intensive use; Minimize the cost of demolition; Get land appreciation income Complete land acquisition and demolition tasks
and demolition Office District Planning Bureau District People's Congress of
Plan as required Control the cost of demolition
the people's Congress Village collective villagers
Floating Population
Construction Organization News Media Financial Institution Real estate Evaluation Agency Real estate Agency Ordinary Citizen
Get some land appreciation income; Increase collective income Maximize compensation for demolition; Improve living conditions and environment; Get long-term social security Safeguard their legal residency; Can continue to base in Beilun; Improve their voice in the transformation Get a reasonable profit; Establish a good relationship with the government; Establish the image of the people Attract public attention;Get their legal benefits Maintain good relations with the government;Get legal benefits Maintain good relations with the government;Get legal benefits Competitive high quality plots; Maximize corporate profits Enjoy the convenience of the demolition and relocation of village-in-city
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After clarifying the interests of all stakeholders, this paper classified the various stakeholders in M1 into three categories according to the classification of the Mitchell score-based approach (Table 3).
Table 3. Identification of stakeholders under the demolition and reconstruction modality Stakeholder type
Interest group
Legitimacy
Power
Definitive stakeholder
Local government
H
H
Urgency H
District Land and Resources Bureau
H
H
H
District Planning Bureau
H
H
H
District Land expropriation and
H
H
H
Village collective
H
H
H
Villagers
H
H
H M
demolition Office
Expected stakeholder
Floating Population
H
M
Higher level government
L
H
H
Construction Organization
M
H
M
District People's Congress of the
M
M
H
people's Congress
Potential stakeholder
News Media
L
M
M
Real estate Evaluation Agency
L
H
M
Financial Institution
H
M
L
Real estate Agency
M
L
L
Ordinary Citizen
M
L
L
3.1.2.1 Definitive Stakeholder Beilun District Government, Land and Resources Bureau, Planning Bureau, and Land expropriation and demolition Office all have high legitimacy, power, and urgency in the demolition and reconstruction modality. These departments and village collectives and indigenous people are definitive stakeholders. They are the core stakeholders in M1 and have high interest demands for the overall demolition and reconstruction of villagein-city, they participate in them and invest in specific assets, and their status ensure that their interests appeal can affect the decision-making. 3.1.2.2 Expected Stakeholder Such stakeholders play a minor role in the demolition and reconstruction of village-incity governance. Their interests are not too great or lack of influence. They often influence definitive stakeholders to achieve their own interests.
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According to a survey in February 2018 (Fig. 4), 70.13% of the floating population in Beilun lived in leased houses, and the main source of renting was village-in-city. There were also 18.28% of floating population living in the firm. The ratio of the local population to the floating population in Datong village and Xiangjia village has reached 1:3 and 1:5 respectively, which shows that the residential needs of the floating population are the main reasons for the continued existence of the village-in-city. They have invested in relationship-specific assets in village-in-city and have a high level of legality. However, the floating population is not included in the government’s compensation and resettlement in M1. They can only solve the leasing problem privately with the aboriginal people, and indirectly express their demands through affecting the villagers. Their power and urgency are only moderate, so they are expected stakeholders (Fig. 3).
Fig. 3. Beilun district registered number of floating population over the years
Fig. 4. Distribution of floating population of beilun district in February 2018
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Besides, higher level government, construction organizations, news media, real estate evaluation agencies and financial institutions also are expected stakeholders. 3.1.2.3 Potential Stakeholder In addition to the above two categories, there are potential stakeholders such as real estate developers and ordinary citizens who have certain legitimacy. 3.1.3 SCM Analysis of Governance Modality in Village-in-City The relationship between different stakeholders is complex, not only involves economic interests, but also involves social and other interests. These factors overlap each other and form a network, which determines the success or failure of governance in the village-in-city. Based on the definition of stakeholders, this paper analyzes the conflicts and cooperation between stakeholders in the governance of village-in-city through the construction of stakeholder communication matrix (Table 4).
Table 4. The stakeholder communication matrix of M1 No
Stakeholder
1
Local government
2
District Land and Resources Bureau
3
District Planning Bureau
4
District Land expropriation and
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
demolition Office 5
Village collective
6
Villagers
7
Floating Population
8
Higher level government
9
Construction Organization
10
District People's Congress of the people's Congress
11
News Media
12
Real estate Evaluation Agency
13
Financial Institution
14
Real estate Agency
15
Ordinary Citizen
Note: "+" means that both groups have the same purpose; "-" means that there may be competition or conflict; "±" means that there is cooperation and competition; " " means that there is no direct relationship between the two.
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Different stakeholders seek to maximize their own interests and have a strong incentive to erode the interests of other stakeholders [8]. According to the SCM (Table 4), there are both cooperation and conflicts between stakeholders in M1. Overall, there are two major conflicts of interest: ① Conflict between villagers, village collectives and the local government (including organizational units) The local government carries out the transformation of the village-in-city according to the requirements of the higher level government, sets up a special leading group for the reconstruction, coordinates the various units. And they expect to use as few fees as possible to vacate as much land as possible to maximize their own interests. Villagers hope to get as much demolition compensation as possible and obtain long-term livelihood protection as well. They largely determine the communication costs of M1. The village collectives cooperate with the government in propagating the demolition and coordinate the conflicts between the government and villagers. On the other hand, they also hope to obtain the benefits of the land appreciation. The contradiction between these three groups has become a key factor in the implementation of villagein-city demolition and the effectiveness of governance. ② Conflict between villagers and floating population There is a symbiotic relationship between aboriginals and migrants in village-incity, migrants (renters) rent for less rent, while villagers (landlords) receive rental income [9]. Because floating population often lack the ability to purchase commercial houses or rent expensive houses, they generally choose to transfer to another village-incity under M1. As long as the living problems of these people have not been resolved, the problem of village-in-city will not be eradicated [10]. This conflict is actually the result of the government shirking responsibility, whether or not this can be reasonably resolved depends on the actual effect of governance. 3.2
Partial Demolition and Space Optimization (M2)
3.2.1 Typical Village Survey of Datong Village Datong Village is located 5 km west of the main city. There are currently 432 households in the village with a total of 978 people. The village collective’s economic income mainly comes from the lease of three production houses. In 2017, the village collective’s income was more than 700 million.
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There were many bungalows and wooden structures in Datong Village before 2009. The houses were scattered and outdated, with obsolete facilities and large fire hazards. In 2009, Datong Village carried out the in-place urbanization. The community’s management, demolition and lease of houses broke the existing dependency. Apart from buildings built for conversion purposes, the village also built Datong New Village Community, Cultural Auditorium Datong Commercial Street, etc. The division of residential, industrial and commercial areas has gradually become clear and the land has been optimized (Fig. 5).
Fig. 5. Location map of Datong new village community
3.2.2 Stakeholders and Their Importance The general idea of the M2 governance of the village-in-city is to resettle the aboriginal people on the spot, and at the same time concentrate on the construction of low-cost housing for the floating population. As the governance goals and tasks change, the appeals of stakeholders also differ (Table 5).
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Q. Wang and Y. Wu Table 5. Stakeholder objectives of M2 Stakeholders Higher level government
Interests Comprehensive optimization of economic and social benefits Reserve land for urban construction; Promote urban-rural
Local government
integration and improve the appearance of the city; Improve performance
District Land and Resources Bureau District Land expropriation and Local
Improve the level of land intensive use; Promote land appreciation Complete land acquisition and demolition tasks
demolition Office
government
District Planning Bureau
unit
District Housing Construction Bureau District People's Congress of
Plan as required Guarantee construction project quality and safe production; Improve the look of the city Control the cost of demolition
the people's Congress Village collective
Get some land appreciation income; Increase collective income Get reasonable compensation for demolition; Protection of
Villagers
residency; Improve living conditions and environment; Get long-term social security
Floating Population Construction Organization News Media Financial Institution Real estate Evaluation Agency Ordinary Citizen
Safeguarding your own legal residency; Can continue to live in Beilun; Improve their voice in the transformation Get a reasonable profit; Establish a good relationship with the government; Establish the image of the people Attract public attention;Get their legal benefits Maintain good relations with the government;Get their legal benefits Maintain good relations with the government;Get their legal benefits Enjoy the convenience of the village-in-city
Similarly, after clarifying the interests of all stakeholders, according to the Mitchell score-based approach, the various interest groups in M2 are divided into three categories, as shown in Table 6 below.
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Table 6. Identification of stakeholders under the partial demolition and space optimization modality Stakeholder type Definitive stakeholder
Interest group
Legitimacy
Power
Urgency
Local government
H
H
H
District Land and Resources Bureau
H
H
H
District Land expropriation and
H
H
H
demolition Office
Expected stakeholder
District Planning Bureau
H
H
H
Village collective
H
H
H
Villagers
H
H
H
Floating Population
H
M
M
Higher level government
L
H
H
Construction Organization
M
H
M
District Housing Construction
M
H
M
M
M
H
Bureau District People's Congress of the people's Congress
Potential stakeholder
News Media
L
M
M
Real estate Evaluation Agency
L
H
M
Financial Institution
H
M
L
Ordinary Citizen
M
L
L
The definition of the stakeholders in M2 is almost the same as that of M1, which increases the district housing construction bureau and reduces the real estate agencies. 3.2.3 SCM Analysis of Governance Modality in Village-in-City Rational stakeholders will put forward different requirements for the governance of the village-in-city from their own perspective, pursuing the maximization of explicit and implicit returns, which results in conflicts of interest among the various groups. With the adoption of M2, the demolition of the whole village has completely changed its interests, and the cooperation and conflict between them have also changed (Table 7).
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Q. Wang and Y. Wu Table 7. The stakeholder communication matrix of M2
No
Stakeholder
1
Local government
2
District Land and Resources Bureau
3
District Land expropriation and
4
District Planning Bureau
5
Village collective
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
demolition Office
6
Villagers
7
Floating Population
8
Higher level government
9
Construction Organization
10
District Housing Construction Bureau
11
District People's Congress of the people's Congress
12
News Media
13
Real estate Evaluation Agency
14
Financial Institution
15
Ordinary Citizen
Note: "+" means that both groups have the same purpose; "-" means that there may be competition or conflict; "±" means that there is cooperation and competition; " " means that there is no direct relationship between the two.
The major conflicts of interest are as follows: ① The conflict between villagers and the local government (including organizational units) The conflict between the villagers and the government is still the key to governance. Villagers expect to receive reasonable demolition compensation, safeguard their own right of residence and obtain long-term social security. Although the in-place urbanization belongs to the people’s livelihood project, it still needs to control the cost and scale. There is an unavoidable conflict between the two in the compensation for resettlement. ② Conflicts and cooperation between floating population and identified stakeholders Floating population in these villages are mostly employees of the surrounding industries. They hope to protect their legal residency rights by increasing their voice, but adding their housing needs to governance will increase costs. At the same time, the rebuilt community still retains the population relationship in the original village. Because the aboriginal people have a poor stereotype about the floating population, they often link the floating population with “dirty, chaotic and bad”, so the concept of the aboriginal to the new residents needs to be changed. New residents must abide by the community rules of the new environment to improve their own living habits. And the village collective also has the responsibility to promote mutual communion.
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3.3
291
Facilities and Landscape Comprehensive Consolidation (M3)
3.3.1 Typical Village Survey of Xiangjia Village Beilun District Xiangjia Village is located west of Yan River, east of Songhuajiang Road, south to Hengshan Road and north to Beiqi Village, with a total area of approximately 1.2 km2. The total population of the village in the end of 2017 was 1551. The number of “new Xiangjia members” (floating population) who applied for a temporary residence permit was approximately 9000 (Fig. 6).
Fig. 6. Location map of Xiangjia village
Since 2001, Xiangjia Village rented third industrial housing as the economic growth point. At present, a total of approximately 28180 m2 of third industrial housing has been built. And the available funds of the village collective reached RMB 8.9 million in 2016. The village has implemented the share system of the village since 2003, the total number of shares has reached 52692, with 55 yuan per share in 2016. After a demolition in 2009, the focus of governance in the village has shifted to the protection of landscape and the improvement of facilities.
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3.3.2
Stakeholders and Their Importance Table 8. Stakeholder objectives of M3 Stakeholders Higher level government Local government District Land and Resources Bureau
Local government unit
District Environmental Protection Agency District Housing Construction Bureau
Village collective Villagers Floating Population Construction Organization News Media Financial Institution
Interests Comprehensive optimization of economic and social benefits Promote land appreciation; Promote urban-rural integration and improve the appearance of the city; Improve performance Promote land appreciation; Promote urban and rural environmental improvement Complete the goals of "A total of five water treatment"; Improve urban living environment Guarantee construction project quality and safe production; Improve the look of the city Improve village appearance; Increase the attractiveness of third industrial housing Improve living environment; Enhance the attractiveness of rental housing Improve living environment; Increased sense of belonging; Improve their voice and position in the transformation Get a reasonable profit; Establish a good relationship with the government; Establish the image of the people Attract public attention;Get their legal benefits Maintain good relations with the government;Get their legal benefits
Scientific research Institution
Maintain good relations with the government
Ordinary Citizen
Enjoy the convenience of the village-in-city
As shown in Table 8, compared with the former two modalities, the stakeholders under the facilities and landscape comprehensive consolidation are different, and their interests have also been changed. Mitchell score-based approach is dynamic. Any interested group gains or loses certain attributes, it will change from one form to another. The properties of some stakeholders have been improved under M3. Definition of them also need to be adjusted accordingly (Table 9). In particular, the floating population’s power and urgency increase, and it has entered the definitive stakeholders.
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Table 9. Identification of stakeholders under the facilities and landscape comprehensive consolidation modality Stakeholder type
Interest group
Legitimacy
Power
Urgency
Definitive stakeholder
Local government
H
H
H H
Expected stakeholder
Potential stakeholder
District Land and Resources Bureau
H
H
District Environmental Protection Agency
H
H
H
District Housing Construction Bureau
H
H
H
Village collective
H
H
H
Villagers
H
H
H
Floating Population
H
H
H
Higher level government
L
H
H
Construction Organization
M
H
M
News Media
L
M
M
Scientific research Institution
L
M
M
Financial Institution
H
M
L
Ordinary Citizen
M
L
L
3.3.2.1 Definitive Stakeholder The government has added district environmental protection agency. The duties, powers and aspirations of various departments are different, but the general goals for improving the human settlement environment are the same. The village collective played a leading role in M3. This is a feature that distinguishes it from the former two modalities. The renting of land for third industrial housing is the main source of collective economic income, and also the source of funding for M3. Improvement of the environment and infrastructure can not only improve the village appearance but also strengthen the attractiveness of the third industrial housing. The village collective efforts to rectify the environment, plays an irreplaceable role in the comprehensive consolidation. Another feature of M3 is that the floating population has become a definitive stakeholder. The “new Xiangjia members” volunteers were established in Xiangjia Village, who regularly cleaned up the garbage. The floating population protected their right of residence and improved their living environment while participating in governance. The increasing of the right to speak and status is a reflection of the improvement of power and urgency. 3.3.2.2 Expected Stakeholder Compared with the former two modalities, the opinions of scientific research institutions in the areas of water consolidation are valued by the village collectives and departments, and they have certain power and urgency.
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3.3.3 SCM Analysis of Governance Modality in Village-in-City Villages adopting M3 governance have enhanced the participation space of the floating population, which has led to the change of new interest relationships. Based on the foregoing principles, SCM analysis is now carried out for M3 (Table 10).
Table 10. The stakeholder communication matrix of M3 No
Stakeholder
1
Local government
2
District Land and Resources Bureau
3
District Environmental Protection Agency
4
District Housing Construction Bureau
5
Village collective
6
Villagers
7
Floating Population
8
Higher level government
9
Construction Organization
10
News Media
11
Scientific research Institution
12
Financial Institution
13
Ordinary Citizen
1
2
3
4
5
6
7
8
9
10
11
12
13
Note: "+" means that both groups have the same purpose; "-" means that there may be competition or conflict; "±" means that there is cooperation and competition; " " means that there is no direct relationship between the two.
The major conflicts of interest are as follows: ① Cooperation and conflict between government departments In the governance of village-in-city, the authority and appeals of each unit are different. They have professional monopoly advantages in their respective areas of management, which exacerbates the information asymmetry between each other and makes the district-level unit departments risk deficiencies. M3 involves more departments, and the complexity of governance has increased. Due to the lack of a unified plan, the risk of internal organizational failure has increased. ② Conflicts and cooperation between village collectives, villagers and floating population The floating population has become a definitive stakeholder. They are both the object of comprehensive management by the village collective and the participants of governance. The relationship between the floating population, village collectives and villagers is also the main contradiction of this modality. Villagers’ profit-sharing and setting up illegal structures for rent to the outside population have not only damaged the landscape of the village in the city, but also caused potential safety hazards. In addition, the overall quality of the floating population is not good. Their accumulation
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is the major causes of poor architectural landscape, poor sanitation and fire hazards in the village. However, in addition to conflicts of interest, the three also have common interests and there is a basis for cooperation (Fig. 7).
Fig. 7. The shanty town (left) and a corner(right) of Xiangjia village
4 Investigation of the Governance Modality of Village-in-City Based on Mitchell Score-Based Approach 4.1
Demolition and Reconstruction (M1)
4.1.1 Urban Village and Its Governance Features This model is represented by Longshun, Lushan, and Beiqi villages. Is mainly aimed at villages that are located in the central area of the city or landscape portals, which have poor construction quality, large development potential and strong willingness to transform. There are many aborigines in this type of villages and there are many migrants. The dependency relationship formed by leasing is very strong. These villages often belongs to the city’s UGB but not completely within USB. The government completely or partially demolishes the original building, then changes its use and reconstructs according to the urban planning. It basically belongs to the situation of urbanization and the reconstruction of the village-in-city at the same time. This type of governance modality is mostly government-led, and it is a top-down management idea. The government formulates the demolition plan through administrative orders, uses special funds or directly invests in bank financing to transform village-in-city, and protects the economic interests of the villagers as less as possible. The government solves all problems such as villagers’ resettlement and compensation. Due to the high cost of resettlement and relocation, the area for M1 is often limited (Fig. 8).
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Fig. 8. Stakeholder relationship diagram under M1
4.1.2 Analysis of the Advantages and Disadvantages of the Governance Modality 4.1.2.1 Advantages First, the entire government-led demolition has high operational efficiency and significant results. Urbanization of land has been achieved, and the land is directly incorporated into USB. As land prices have skyrocketed, it is a thorough urbanization of village-in-city in space. Second, through the “sunshine demolition”, which weakens the contradiction between the government and the public, this modality considers the interests of the aborigines more fully. It properly solves the problem of housing and land acquisition compensation of aboriginal population, which helps to achieve the urbanization of the aborigines.
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Third, the organization is relatively tight and the cooperation inside is smooth. Beilun District has included such reconstruction project of village-in-city in the government investment plan, and has established the Village-in-city Demolition Working Group to make overall arrangements. The district people’s congress of the people’s congress supervise the progress of the project and the use of government special funds. Government-led efforts can better integrate the resources of various departments and give full play to the expertise of each department. 4.1.2.2 Disadvantages On the one hand, it neglects the needs of vulnerable groups. Villages of M1 are often close to USB and small in size. They can basically meet the needs of the floating population to enjoy urban public services, so their main appeal is housing demand. However, this modality does not include floating population in definitive stakeholders. There is a situation of “stronger and weaker” between land urbanization and population urbanization. As long as there is a housing demand of the floating population, it will not be able to fundamentally prevent new the emergence of the village-in-city. On the other hand, there is a problem of funding gaps. The government has invested a large amount of special assets in the demolition, and has also assumed significant risks on its own, limiting the single scale and scope of application of the model.
4.2
Partial Demolition and Space Optimization (M2)
4.2.1 Urban Village and Its Governance Features This modality is represented by Datong, Gaotang and Yanhai villages. These villages are mainly distributed in the urban fringe area. They are usually not fully in UGB and not in USB at all. The overall environment is still good and does not require overall demolition. However, these villages have problems such as fragmented layout, lack of planning, low land use efficiency and poor construction. M2 is still government-led, using small-scale renewal, partial demolition, perimeter renovation and internal improvement, while aboriginals are conducting “urbanization on the spot”. Compared with M1, the role of the market and the community in this modality has been improved, the participation of villagers in governance through the market mechanism has been significantly increased, and their right to independent choice has also been improved. The government constructed community infrastructure and supported third industrial housing for “property management” in the early period, and village collective economic organizations become owner-operated real estate leasing, which provided continuous financial support for later-stage governance (Fig. 9).
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Fig. 9. Stakeholder relationship diagram under M2
4.2.2 Analysis of the Advantages and Disadvantages of the Governance Modality 4.2.2.1 Advantages Firstly, the cost of demolition and relocation is lower than M1. Most of these villages belong to the urban-rural integration that is not covered by USB or even UGB. The land price of the land is relatively low. The government and the aborigines have strong advantages in organizing and operating. The transaction costs are also lower. The second is that the market mechanism has played a more important role in this modality. Under M2, the coordination between the villagers and the government, the floating population and the village collective has introduced a market mechanism. The villagers choose the method of combining production and resettlement and monetary resettlement to obtain more compensation that reflects market value; and the village collective has put the third industrial housing into market transactions, which not only met the residential needs of some floating population, but also standardized the lease relationship. The third advantage is the combination of the demolition work and the improvement of public services. In addition to establishing new communities, Datong and Gaotang villages also launched large-scale supermarkets, cultural halls, health service centers and schools, gradually included these villages into the USB.
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4.2.2.2 Disadvantages The unified construction of resettlement houses has enabled the village-in-city to have an urban form in the external architectural landscape, realizing the land urbanization, but neglecting the transformation of people. The nature of human beings tends to get nothing for nothing. There is special unemployment caused by no pressure of survivors in the relocation households. The aborigines still lack urban survival skills and have not really integrated into the city.
4.3
Facilities and Landscape Comprehensive Consolidation (M3)
4.3.1 Urban Village and Its Governance Features This modality is represented by Xiangjia, Fengyang and Dalu villages. Most of them are resettlement villages in the 1990s, distributed between industrial areas and residential areas, belonging to the urban-rural complex that is not entirely in UGB and not completely in USB. These villages have a small number of aborigines and a large number of migrants. Due to the high cost of demolition and relocation, the internal layout is relatively reasonable and the environment is good, comprehensive management has been carried out based on the renovation of internal facilities, complete infrastructure, improvement of external image and improvement of environmental hygiene (Fig. 10).
Fig. 10. Stakeholder relationship diagram under M3
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M3 integrates the improvement of the facilities and the protection of landscape in the village-in-city. This modality is led by the village collective or the community, and the relevant government departments provide guidance. The current governance is combined with “Cure and break down”, “Environmental comprehensive renovation in small towns”, “A total of five water treatment” and so on. Funds is mainly collected by the streets and villages, and the district finances provide appropriate subsidies. 4.3.2 Analysis of the Advantages and Disadvantages of the Governance Modality 4.3.2.1 Advantages On the one hand, the floating population has moved from “marginal” to “core”. M3 has incorporated these people into definitive stakeholders. Under the guidance of the village collective, it has greatly increased the number of volunteer teams of the floating population. The power and urgency of the floating population in comprehensive consolidation has promoted the population urbanization of this group. On the other hand, M3 actually expands USB through comprehensive consolidation to provide public services and slow down the deterioration of the village-in-city. Such villages are closer to the city level in terms of roads, hydropower, transportation, public services and social governance systems, and have basically been freed from rural characteristics. 4.3.2.2 Disadvantages First, the modality is dominated by the village collective. The government departments carry out guidance and cooperation based on their own interests, lack unified planning, and have not formed working groups to coordinate work and inter-departmental relations. There are problems of inefficiency and government failure. Second, there are symptoms and imperfections in some comprehensive renovations. For example, Dalu Village and Xinqi Street jointly carried out streetscape remediation for Dalu Village in 2016. However, the author found that there are still piles of rubbish behind the wall that improves the streetscape, and the sanitation situation still needs to be improved (Fig. 11). Third, the participation of the floating population is unable to achieve the desired value because of lack of coercive force, and its actual effectiveness cannot be guaranteed. Voluntary service activities can easily lead to sluggish situations (Table 11) (Fig. 12).
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Fig. 11. Dalu Village along Mingzhou Road (left) and a corner of Xiangjia Village (right)
Industrial Area
M1:Demolition and Reconstruction
UGB
M2:Partial demolition and space Optimization
USB
M3:Facilities and Landscape Comprehensive Consolidation
Fig. 12. The Distribution of governance modalities of the village-in-city in Beilun District
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Dominant subject
Transformation mode and measures
Completely in UGB
Completely
One-step overall demolition and reconstruction;
Not fully in USB
government-led
Full conversion use; Aboriginal monetary settlement.
characteristics M1
M2
M3
Not fully in UGB Not in USB at all
Government-led Increased market and community role
Partial demolition and reconstruction for space optimization; Local Aboriginal Placement; Build appropriate low-cost housing for floating population.
Not fully in UGB
Village collective-led
Combination of landscape repairs and improved
Not fully in USB
(community-led)
facilities; Comprehensive improvement.
5 Policy Suggestions 5.1
Housing: Build Low-Cost Housing for Floating Population and Include It in USB
The essence of village-in-city is the non-integration of urban development and urban poverty alleviation [11]. The ultimate goal of its governance is to build our cities into places that are more livable, thus the key lies in the issue of “living”. The resettlement compensation for the aborigines is mature and reasonable both in number and payment methods, and the key to the survival of the village-in-city in the future lies in the satisfaction of the housing needs of the floating population. The government needs to formulate a more open and people-oriented low-rent housing policy for floating population. At the same time, some of the collective land in villagein-city will be introduced into the leasing market. The village collective will run the real estate leasing as the owner to break the existing non-standard leasing relationship. Promote the establishment of a “Multi subject supply, multi channel guarantee and lease purchase” housing system. 5.2
Employment: Provide Employment Skills Training Services to Promote Population Urbanization
The management of village-in-city should be “people-oriented”. In addition to meeting the needs of the population housing, the government should also carry out comprehensive reforms for residents including lifestyle and modern cultural quality. Currently, there is no “employment resettlement” for village-in-city reconstruction to solve this problem. In order to increase the human capital of the village-in-city, enhance its competitiveness and adaptability in urban life, and narrow the gap between land urbanization and population urbanization, the government should increase the employment services for the aborigines so that the villagers’ employment options will be diversify. For aboriginals who are converted into urban residents, they should be included in the unified urban employment system management, and enjoy vocational and technical
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training, employment guidance and social security legitimately; and for the aboriginal and floating population who continue to stay in village-in-city, government ought to provide employment skills training, improve the employment services platform and provide employment services for them. And promote the construction of a unified urban and rural employment service system, so as to build a unified urban and rural labor market information network. 5.3
Planning: Combine Governance of the Village-in-City with the Overall Planning of the City
Urban village governance is an important part of urban renewal and serves the development of the entire city. The government should also study supporting urban renewal plans when formulating urban planning, such as reducing commuting costs in outlying areas through traffic planning and increasing the flow of traffic outside the main urban area. The attractiveness of the population, in conjunction with housing policies, will open up space for low-cost housing so as to reduce the appearance of new village-in-city. On the one hand, we can provide targeted infrastructure and public services in areas with low house prices and convenient transportation. For example, the “Xiapu Station” of Metro Line 1 has the above conditions, which is an advantageous part of building low-cost housing. On the other hand, improving the public transportation in the outskirts of the city where the cost of commuting is high can enhance its attractiveness and ease the governance pressure of internal USB villages. Beilun District plans to add 3 new stations by the year 2020 and set a total of 10 rail transit stations. Fuchunjiang Road Station is close to several villages, which will enhance the attraction of the block to the floating population. 5.4
Government: Departmental Collaboration Reform
The government mostly plays a leading role in the governance of village-in-city. However, due to the large number of governance goals and the wide range of involvement in multiple government departments, the overall governance operation has extremely high complexity. The current governance of village-in-city lacks a unified special plan. All departments expect to maximize their own profits on the premise of ensuring that they are not accountable. Therefore, there is inevitably a situation of culling responsibility and organizational inefficiency. According to this paper has three suggestions. Firstly, combine the specialties and responsibilities of various government departments, and formulate specific plans for the governance of village-in-city, promote “Multi-disciplinary one” and “Multi-disciplinary fusion”. And implement government responsibilities with a unified plan as a vehicle and platform. It also guarantees the benefits that all departments deserve in the governance of the village-in-city. Secondly, establish and improve the work coordination mechanism for all departments to coordinate the governance of the village-in-city. Thirdly, strengthen dialogue and communication among departments, enhance understanding of each other’s work and reduces information. Thus promoting the achievement of a common will.
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References 1. Zhou, N.X., Yu, K.J., Li, D.H.: Analysis of relevant stakeholders in the planning of scenic spots–taking Wulingyuan science spot as an example. Econ. Geogr. 25(5) (2005) 2. Ramirez, R., Buckles, D.: Stakeholder analysis and conflict management (1998) 3. Grimble, R., Wellard, K.: Stakeholder methodologies in natural resource management: a review of principles, contexts, experiences and opportunities. Agri. Syst. 55(2), 173–193 (1997) 4. Mitchell, R.K., Agle, B.R., Wood, D.J.: Toward a theory of stakeholder identification and salience: defining the principle of who and what really counts. Acad. Manage. Rev. 22(4), 853–886 (1997) 5. Liu, Y.: Discussion on the definition of stakeholders in ecotourism—taking the mitchell method as an example. J. Bus. Cult. 1, 275–348 (2008) 6. Chen, H.: Progress in theoretical research on stakeholders at home and abroad. Econ. Res. Guide 14, 5–6 (2011) 7. Zhang, X., Zhao, D.Y., Zhu, X.D., et al.: Analysis and response of interest relations in urban village reconstruction. Econ. Geogr. 26(3), 496–499 (2006) 8. Jia, S.H., Zheng, W.J., Tian, C.H.: Theory and countermeasures of stakeholder governance in urban village reconstruction. City Plann. 5, 62–68 (2011) 9. Liu, Y., He, S.: Chinese urban villages as marginalized neighbourhoods under rapid urbanization (2010) 10. Yin, W.: The theory of government responsibility in the reconstruction of villages in cities. J. Shaanxi Admin. Inst. 21(4), 63–66 (2007) 11. Wu, Y.Z.: Research on the Temporal and Spatial Evolution of Urban Housing Price. Science Press, China (2011)
The Legislation of Transfer of the Right to Use Homestead Jianfeng Ye1 and Yuzhe Wu2(&) 1
2
Zhejiang College of Construction, Zhejiang University, Hangzhou, China [email protected] Department of Land Management, Zhejiang University, Hangzhou, China [email protected]
Abstract. This study is useful to farmers standard trading house base, to reduce idle waste of homestead, to inventory the assets of rural homestead, and to solve the dilemma of financing difficulty due to lack of collateral. It is conducive to the integration of urban and rural areas, so that rural residents can share the fruits of social and economic development with the urban residents, and realize a new type of urbanization that is people-oriented. This study of housing land use right transfer of all kinds of practical problems and the system of laws and regulations were analysed, from the perspective of farmers, the government and the urban and rural integration, summarized the necessity of land transfer, finally to put forward the six concrete Suggestions of housing land use right transfer. The research result of this project is that the transferer of the right to use the homestead, must satisfy the condition that the transfer object is not the only one from the residence, and the object of transfer of the homestead must have the legal right certificate. The assignee can obtain the residence permit and enjoy the basic public service according to the residence permit through the use of the right to use the house site to obtain the membership of the special collective economic organization. Establishment of the right to use the system that needs paying and has period, perfecting real estate registration, and the existing laws, administrative regulations and departmental rules. And judicial interpretation modification proposals are submitted. Finally, the author puts forward the legislative provision on the transfer of the right to use the homestead. Keywords: The homestead Trade dispute collective economic organization
Urban-rural integration The
1 Introduction The homestead accounts for a large proportion of its household assets. Many farmers have become new urban residents through urbanization. The homestead that has been owned before urbanization can still be held, or as a new resident and hold the homestead by inheritance. The right to use the homestead is one of several usufructuary rights stipulated by the property law, which is recognized in the legal rights and obligations of the owner. Xinyong chen believed that the right to use the homestead is the right to the possession and use of the land owned by the collectives according to law and to use the land to build houses and their ancillary facilities according to law © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 305–316, 2021. https://doi.org/10.1007/978-981-15-3977-0_22
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[1]. Under the current legal system, the homestead is restricted by the initial acquisition, the exercise of possession and the transfer of punishment, resulting in countless problems. These problems are all the more prominent in the context of deepening reform, urban-rural development and new urbanization. In recent years, numerous scholars have pointed out that, for the application of economic and social development and the need to further deepen the reform, the residence guarantee function of the homestead should be weakened and the property function should be enhanced. Many scholars believe that the homestead and the state-owned construction land use rights are the same as for residential purposes of usufructuary right, If the stateowned construction land use rights can transfer, mortgage, inheritance, and so on, so the corresponding homestead right should have the same rights. Xiaoming Li proposed that the right to use the homestead is a type of usufructuary right, and should have a complete right. The right to use the homestead is free to buy and sell, lease, mortgage and inheritance [2]. and the central government encourage rural residents to accrue monetary income from homesteads [3]. Change the current system of right to use house sites related to allow free land transfer in order to constitute an efficient land transfer market, reflects the asset attributes of the homestead, the homestead can have more property rights. However, the homestead complimentary transfer is not suitable for the status qua of our country, and the transfer conditions and the scope of the transfer be established for the transfer of the homestead. It is more in line to use the homestead on condition and scope.
2 The Problem of the Transfer of the Right to Use the Homestead 2.1
Poor Transfer Channels Lead to Idleness
In China, a large number of rural homestead and houses are idle and have formed a considerable scale and proportion [4]. Government proposed farmers are relocated into centralised communities by consolidating their original homestead into farmland, but farmers don’t satisfy with the policy [5]. There are numerous factors that cause idle waste in the homestead, which is mainly reflected in the following aspects. In recent years, rapid urbanization has attracted numerous rural migrants to work and live in urban areas. Whereas the highly restrictive rural land transfer system has left their rural homesteads unused [6]. First, although the land ownership corresponding to the homestead belongs to the village collective, the homestead is not having use a fixed number of years. In the opinion of the villagers and most of the masses, they are equivalent to their private property. When the villagers reach a certain age, they can obtain the homestead for the first time by applying for approval. At the same time, it can be obtained by inheriting the ancestor’s homestead, the result is that the homestead is largely ineffectual and inefficient. Secondly, urbanization brings about the change of household registration. Some people remain in the city after graduation. Some people enter the city through the form of a home purchase. They have their houses in the city, they still retained the pastoral homestead, causing the use of the homestead wasted. Once again, migrant workers have long settled in cities, and their homestead and
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corresponding houses in rural areas has been unoccupied for a long time. Their preferences for low price house, as they couldn’t sell their rural homestead [7]. The large number of idle homesteads, why not through the market to solve the idle problem. The reason is that the current laws and regulations restrict the transfer of the homestead in the collective interior of the village. However, homestead transactions have occurred in private. A large number of rural residential buildings have been unoccupied for a long time, and there is a wide demand for rural housing in the market, which leads to the formation of “invisible market” of homestead circulation [8]. The important factor in these situations is that the transfer conditions and transfer channels of the right to use the homestead are not clear, and the ways of the people to leave the homestead are lacking. 2.2
The Lack of Transfer Mechanism Leads to the Continuous Dispute of the Sale and Purchase Contract
The usufruct of the right to use the homestead is usually associated with the interests of the house seller, the house buyer and the village committee. The legal relationship between the house sale and sell conflict is complicated, and there are many lawsuits in judicial proceedings. The buyer of the homestead requests to confirm that the contract is invalid and the seller returns the property and compensates for the corresponding loss; The homestead buyer asks for confirmation of the sales contract valid and requires the seller to deliver the homestead; The homestead seller requests confirmation of the sales contract and requires the buyer to pay the sale price; The homestead seller request to confirm the invalidation of the sale contract, and claim object obtains the undeserved benefit of the resettlement compensation in the subsequent moving process, that the buyer obtains after the contract. Buyer requests the village committee to pay for the resettlement. Judicial practice has historically been controversial in these cases. At present, there are various kinds of results in the trial of the house sale dispute. (1) Confirm the invalidation of the homestead sales contract, and ask the seller to get back the payment of the contract. (2) Confirm the validity of the homestead sales contract and reject the invalid lawsuit request. (3) Conclude that the homestead sale and purchase contract is invalid, and reject the appeal of the buyer to the village committee for the compensation for resettlement. (4) Confirm that the homestead and aboveground housing sales contract is valid, and support the buyer to obtain the compensation for the demolition of the housing part, and not to support the resettlement compensation for the part of the homestead. In short, there are two separate kinds of judgments in judicial practice about the conflict between homestead sale. The reason for these two distinct rulings is that there is a discrepancy between the homestead and the ownership of the property in the house. In our country homestead and house ownership is inseparable, so whether farmers can dispose of their home ownership is largely dependent on the disposal of the right of homestead [9]. 2.3
The Subject Restriction Causes Property Defects
There are huge differences in property and assets between farmer housing and urban commercial housing and affordable housing. The main reason is that the urban
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residents and other non-collective members cannot be allowed to obtain the right to use the homestead. As a result, the quantity of the homestead buyer is limited. The seller can’t get the normal market price. Transaction prices are grossly undervalued, even below the cost of construction. In this case, the market is definitely not practicing. The seller is not willing to sell. And compared state-owned construction land use right and land contract management right, the right to utilize construction land can set up the mortgage right, the land contract management right after reform can also set mortgage right. The property rights of the right to use the homestead are not enough, which seriously affects the property of peasant households into the credit system. It restricts the equality between farmers and urban residents in economic rights and restricts the development of urban and rural integration [10]. The right to use property right of homestead is incomplete, there are major defects and need to be reformed. And through the analysis of homestead property rights system, paper finds that incompleteness degree of rural homestead property rights varies from period to period [11]. 2.4
The Property Right of the Homestead Is Defective
The right to use the homestead system is the peasant housing system with Chinese characteristics, and the rights involved are quite complicated [12]. By contrast, the right to use construction land has relatively complete rights,The right to land use and occupation; The right to transfer it to a third person; The right to lease it to a third person for income; The right to hypothecate the mortgage as a guarantee; Can be inherited; It can set easement as an object. Different land rights mean that the right subjects have different rights and different obligations to the land [13]. The premise condition to buy a homestead wants to be a member of the collective economic organization and get the treatment of the villagers. The main body of inheriting the homestead is not only the members of the collective economic organization, but also the condition to obtain the homestead. As a result, homeowner is more restricted. Some restrictions are quite narrow. The usufruct right of homestead is defective. 2.5
The Homestead Transfer Property Registration Is Insufficient
The transfer of homestead has two rights which belong to the scope of real estate registration, the right to use the homestead and the ownership of the house. Both of these are recorded to be effective, subject to registration. Real estate change registration means that the homestead is changed from the original owner’s name to the new obligee’s name, and the registration of the original registration is changed due to the change of the right [14]. The transfer and inheritance of homestead and house have the change of the subject of rights. They all need real estate registration. Even both parties sign the homestead and the house transfer agreement and pay the corresponding contract price, and change possession in fact, if the real estate registration is not carried out, the property rights will not be produced. Finishing the initial registration of homestead completely. It is the basis for the change registration of homestead and housing. There are numerous problems in the registration of real estate of homestead and aboveground, such as, illegal land, unclear
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property rights, one family residence, cross-regional house purchase, etc. [15]. Since the implementation of the unified registration of real estate, the real estate registration of rural homestead and land has been improved. Since the implementation of the unified registration of real estate, real estate registration of rural homestead and land has been improved. Since real estate is unified and registered, whether the sale of the homestead and housing can be included in the sale of second-hand housing transaction supervision. In this way, the real estate transaction market for rural housing and urban residential areas can be formed together, so as to realize the standardized transaction of the transfer of the right to use the homestead. 2.6
The Regulation of the Right to Use Homestead Is Insufficient
As for the transfer of homestead, there are provisions in the constitution, property law and the land management law. Specific provisions are: article 10, paragraph 4, the constitution stipulates that “the right to use the land may be transferred in accordance with the provisions of the law.” Article 153 of the property law stipulates that “land use right transfer shall be governed by the land management law”. Article 62 of the land management law stipulates that “if a villager sells his house and applies for a homestead. He shall not approve it.” “The notice of the general office of the state Council on strengthening land transfer management strictly prohibits the sale of land” stipulates that “farmers’ houses shall not be sold to urban residents.” Above about land transfer laws and regulations, and it exists the shortage of the two aspects, one aspect is to transfer the homestead of the transferee subject scope is too small, lead to low efficiency of the market, another aspect is no related provisions to guide housing land transfer.
3 The Necessity of the Reform of the Right to Use Homestead 3.1
In Favor of “Farmers”
The reform of the household registration system in 2016 will no longer distinguish between agricultural and non-agricultural accounts. The “farmer” refers to a villager who owns the right to use a homestead. The “farmer” will be the biggest beneficiary of the system reform of the transfer of the right to use the homestead. Transfer reform of the right to use the homestead will provide more exit channels for the homestead of peasants after the cauterization. After the agricultural household registration and non-agricultural household registration are unified as residents, the system of residence permit management is implemented, and the basic public services such as education, pension service and medical and health care are met. It is expected that by 2020, about 100 million new “farmers” will be transferred to cities or towns to realize the cauterization of urban farmers. If these new citizens, each with 35 m2 of homestead, will have an idle capacity of 3.5 billion m2. If the average house is 3 floors, the building area is 10.5 billion square meters. We need to create an efficient exit mechanism for homestead.
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Transfer reform of the right to use the homestead is beneficial to the farmer’s sunshine standard trading homestead. The main problem of homestead circulation is that the law does not play a useful role in the circulation of the homestead market [16]. The transfer of homestead to non-collective economic members under the existing laws and regulations cannot complete the registration of real estate, however, the hidden transaction is repeatedly happened. Establish the related system of homestead transfer, and to break the identity limit of the transfer of the homestead from the collective economic members. The reform of the transfer of the right to use the homestead will help farmers to solve difficult financing difficulties. Farmers have financing difficulties, and the problem of high financing interest rate has long restricted peasants from getting rich. The development research center of the state council has carried out investigations of 107 rural cooperative economic organizations, Only 9.25% of the operating funds of the cooperative organizations are loans to financial institutions, and all the rest from themselves [17]. From the perspective of financial institutions, the cause of this dilemma lies in the lack of credit for farmers and the lack of corresponding collateral. The construction cost of the homestead and house is not low, the cost of a house is often up to million yuan, need to expand the family’s many years of savings. However, when the homestead and the house are built, it becomes a sleeping asset, which cannot realize its due value through the transfer, and it cannot set up the mortgage as collateral to reflect its anticipated value. When financial institutions accept rural houses as collateral, they will find it difficult to cash when they are required to dispose of collateral. The establishment of a homestead transfer system can solve these problems. The reform of the right to use the homestead can solve the dilemma of “farmer” homestead inheritance. Rural home ownership belongs to private property, can be inherited according to law, and the inheritance of the homestead can only be a collective member. For the farmers who already have a homestead, there is a dispute over whether to succeed the homestead under the principle of one household. The farmer may inherit the ownership of the house, but cannot inherit the right to use the homestead. 3.2
In Favor of “Government”
In recent years, the reform of the homestead has been an important part of our government’s deepening reform. We will enrich the property rights of the homestead, reasonably set the control limits of government planning and approval, and promote the diversified development of the homestead market and the voluntary participation of farmers [18]. Broaden the scope of homestead transfer, allow homestead to transfer and mortgage to non-collective members, and allow it to be inherited. It will help the government to revitalize the social assets, foster new economic industries, and bring additional tax sources to the government. An important reason is the urban-rural dual structure. The twofold structure of China’s urban and rural areas was established in the early days of the founding of the People’s Republic of China and solidified in the period of “single ownership structure” and planned economy [19]. It has to be in
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conformity with the government’s interest demand orientation to deepen the reform of rural land use system. The reform of the current land use right transfer system will activate the dormant the homestead assets. If the farmers have a home base of 35 square meters per capita, the houses are calculated at the average level is 3 floors, and the building area of each rural household is 420 square meters,and the construction cost of the rural houses is 800 RMB. The house that does not include the land value is 336 thousand RMB. Private transaction price of 108 square meters in the outskirts of Hangzhou is about 3 million RMB, and it is in the case that the property transfer cannot be completed. At present, the annual completion of the transaction of homestead and housing is less than 1% of the total. The reform of the current land use right transfer system, will build the industry of homestead and housing transaction market, and will become the new growth point of economy. The scope of real estate brokerage business is mainly urban commercial housing, including new and second-hand housing, not including rural housing and land. If homestead and house transfer is allowed, a large number of real estate agents are to provide services such as transaction and property transfer. Thus will developing real estate brokerage industry. Homestead and houses are taxable in the process of transaction. So real estate appraisal should be carried out in accordance with requirements. Financial institutions and mortgagees also need professional real estate appraisal companies to carry out mortgage valuation as an important reference. These will lead the development of the real estate appraisal industry. Land and housing transfer need the change of real estate registration, need land registration agents to provide related services, will encourage the growth of the real estate registration agency related industries. These new growth points will bring additional revenue to relevant enterprises, drive economic growth, and prosper the social economy. Reform of the current homestead transfer system, will increase the tax revenue of government real estate. Improve the system and mechanism so that farmers can participate in the modernization process equally and share the fruits of modernization [20]. At the present stage, there are few types of taxes to be paid for homestead and house transfer, mainly in the stage of change of the property right certificate, and the taxes involved are mainly VAT and stamp duty. Without the change of property right, can avoid paying deed tax and stamp duty. It is necessary to design the related taxes and taxes in the system for the transfer of the homestead. Nowadays, the proportion of land use right transferring fee is very important, which makes the government depend on it to some extent. The government has already considered introducing a real estate tax, which is a property tax.
4 Specific Advice 4.1
The Transfer Subject of the Right to Use the Homestead
The property owner who transfers the right to use the homestead must meet certain requirements in the subject condition. After the homestead and the transfer of the house, it is necessary to examine the basic living and social security of the transferor.
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Depending on the survey of the farmers in Shanghai, if they can obtain stable social security and non-agricultural income after exiting the homestead, then the willingness to quit is high [21]. We need to set definite transfer conditions in the system, which will bring the social security of the transferor. First of all, the transfer of the homestead and the ownership of the corresponding houses get another residential property. To meet this condition, the transferor transfer the homestead and the aboveground house, there will not be the problem of no housing. Second, the assignee should have three years of proof of social security. Insurance certificate issued by human resources and social security department, if the normal full pay social insurance for three years, can be thought of in the town have job security, you can enjoy the social security system. The assignee is unrestricted and may be a natural person or legal person. 4.2
The Transfer Object of the Right to Use the Homestead
The object scope of the transfer of the right to use the homestead refers to whether the transferred object needs to meet certain range conditions, and the homestead is allowed to be transferred in certain areas. Allow homestead to transfer, need to face a lot of “small property” house in the market. These houses without real estate property right card, or the property right sealed by the township government, and in the current system of township government has no right to license issuing and so “small property house” in the legal sense for no legal property rights houses, even some “small property house” for illegal structures. “Small property house” is the product of the game between different interest groups, and it is also an informal development form of interest redistribution [22]. The homestead and the “small property house”, although in the ownership of the land of the two both belong to the collective ownership of land, but the difference in the legitimacy, the homestead is legal real estate property. A family that accords with the approval conditions of the homestead can have the homestead, and is approved according to the procedures stipulated by law, and is in line with the requirements of land use planning and village planning, and has legal property rights. However, the “small property right” room does not meet the planning of the village or the land use, and does not complete the land expropriation procedure required by the commercial housing development. The homestead has the full right of real estate in the case of the unified registration of the real estate, while the “small property” house has no relevant property rights. 4.3
The Homestead Had a Certain Year and Need to Pay Rent
The right to use a homestead has no rent and years of service. It reflects the welfare and guarantee of farmers. The transferee of the homestead will not become a member of the collective and receive the treatment of the villagers. Cooperative members obtain the standard by reference to the Chinese standards of international private law, including the original acquisition and subsequent acquisition of two kinds [23]. The transferee of the right to use the homestead is a member of the non-collective economic organization, and if it continues to possess the homestead for free, which is obviously contrary
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to the original intention of welfare and indemnity. It is suggested to establish the system of use right of homestead, pay rent and certain number of years. It is useful to optimize the allocation of rural land resources and protect farmers’ rights and interests [24]. Transferred to non-members of the collective land use right, and will be delivered to the assignee of the right to the use of a certain period of years, the price is the assignee shall, in accordance with the contract, pay a certain fixed number of year of the rent of land use. There are several things need to give further consideration. First, the time of the use of the homestead is when the homestead is acquired, or when the homestead is first transferred; Secondly, the right to use the homestead has a period of years, but how many years? How are the land rents determined? Again, is the rent paid by the transferor or the transferee? In the end, the rest is owned by the collective landowners or the state?
5 Legislative Proposals for the Transfer of Homestead 5.1
Suggestions for Improvement of Homestead Laws and Regulations
The above Suggestions on homestead reform is necessary and feasible, but there are some conflicts with the existing laws, administrative regulations and departmental rules in China. The following Suggestions are made in accordance with the legal hierarchy of the constitution, laws, administrative regulations, departmental rules and judicial interpretations. The provisions of the constitution concerning homestead are mainly article 10.”The right to use the land may be transferred according to the provisions of the law.” The constitution does not prevent the transfer of homestead according to law. There are several laws, such as property law, land management law and guarantee law, to make provision for the right to use the residence. Terms of reference include article 184 of the property law, article 63 of the land administration law, and article 37 of the security law. This paper proposes the legislative idea of the transfer of homestead, which needs to be modified and perfected in article 184 of the property law, and it is suggested to delete several words of the homestead in this article. At the same time, article 63 of the land management law needs to be improved, proposed additional article: “However, the eligible homestead transfer, mortgage or inheritance is excluded.” In addition, it is necessary to amend the article 37 of the promise law, remove the three words of the homestead and remove the restrictions on the mortgage of the homestead. Administrative rules and regulations concerning homestead mainly include the land management law enforcement regulations, article 6 “the transfer of houses on the land of the homestead, which leads to the transfer of homestead, shall be registered according to law.” It is not appropriate to make Suggestions for modification. Normative documents related to homestead mainly have two documents, the state council general office on strengthening land transfer notice it is forbidden to sell land management and the state council general office on strictly implement relevant notice of rural collective construction land laws and policies. It is necessary to adjustment, and it is suggested that “the farmer’s residence shall not be sold to the urban residents “should be deleted, which in the first document referred to in this paragraph. At the same time, delete the
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provision of “urban residents do not get rural purchase homestead and peasant housing”, in the second document mentioned in this paragraph. 5.2
Proposal on the Transfer of Homestead Legislation
It is suggested that the administrative measures for the transfer of the right to use the homestead should be adopted nationwide, and the form of law may be the law, administrative regulations or departmental rules. The proposed terms are as follows: Article XXX. The paid use of the right to use the homestead is the representative of the administrative department of land and resources to transfer the usufruct of the homestead to the land users in a certain number of years, the land user pays the land and resources administration department for the use of rent. Article XXX. The maximum period of use of the homestead is 70 years. Article XXX. The use of the right to use a homestead shall be subject to agreement, tendering, or auction. Specific procedures shall be prescribed by the people’s governments of provinces, autonomous regions and municipalities directly under the central government. The secretarial department of natural resources, the collective economic organization and the right to use the homestead should sign a contract for the right to use the right to use the homestead. Article XXX. The transfer of the right to use the homestead refers to the situation of recharging the right to use the homestead, including the transfer, exchange and donation of the right to use the homestead. Article XXX. Transfer contract shall be concluded for the transfer of the right to use a homestead. When the right to use the homestead is transferred, the right to use the right to use the homestead to use the contract shall be transferred accordingly. Article XXX. The right to use the premises shall be transferred, leased, mortgaged and terminated, should registration of real estate. Article XXX. The transfer of the right to use a homestead is not the sole residence of the transferor, and the transferor must have the proof of social security for more than three years. Article XXX. The right to be transferred the right to use the homestead must have the legal right to prove, including real estate registration certificate, land certificate, property certificate and so on. Article XXX. The lease of the right to use the homestead refers to the use of the right to use the homestead together with the above-ground buildings and the attached objects, to the lessee to be payed the rent to the lessor. Article XXX. The right to use the homestead can be mortgaged. When a homestead is mortgaged, its above-ground buildings and fixtures are mortgaged together. The right to use the homestead shall be registered in accordance with the relevant provision. Article XXX. If the mortgagee of the right to use the homestead fails to perform his obligations or declares dissolution or bankruptcy in the period of the mortgage contract, the mortgagee shall have the right to dispose of the mortgaged property in accordance with the relevant provisions of the state.
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Article XXX. When the right to use the homestead expires, the homeowner can apply for renewal. If it is necessary to renew the contract, the contract shall be re-signed in accordance with the provision, and the right to use the premises shall be paid and registered. Article XXX. The expropriation of the right to use the homestead and the land on the ground has to be compensated. Article XXX. The value of the homestead and the house on the ground shall be assessed and determined by the real estate or land appraisal institution in accordance with the applicable norms. Article XXX. The expropriation compensation for the right to use the homestead belongs to the right person, and collective land ownership compensation belongs to the village collective economic organization.
6 Conclusion In this paper, the current legal system and various practical problems of homestead use right are analyzed and studied in this paper. From the perspective of farmers and government to analyze the necessary to the transfer of the right to use the homestead. Finally, put forward the housing land use right transferrer need to meet the condition, the condition of the object of land use right transfer of, paid a term use, current land use right of law amendments, such as specific advice. These specific proposals adjust the idea of allowing the use of homestead to be transferred unrestricted. It is proposed that the transfer of homestead should meet certain conditions, and the transfer of the object is not the only house of the transfer subject, and it also should have three years of social security payment proof, which is innovative. The proposed changes in the current laws and regulations and the specific provisions of the legislation are of practical value.
7 Acknowledgement This research was conducted with the support of Fund project: National natural science foundation funding project (71373231); Zhejiang province construction research project (2014Z024).
References 1. Chen, X.Y.: Civil Law, pp. 258–261. Zhejiang University Press, Hangzhou (2011). (in Chinese) 2. Li, X.M.: Research on the use right of rural homestead in China, pp. 12–13. Anhui University, Hefei (2013). (in Chinese) 3. Tian, C., Fang, L.: The impossible in China’s homestead management: free access, marketization and settlement containment. Sustainability 10(3), 798 (2018). https://doi.org/ 10.3390/su10030798 4. Qi, Q.M.: The present situation cause and management measures of idle homestead in rural China. Rural Econ. (8), 21–27 (2015). (in Chinese)
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5. Cheng, L., Liu, Y., Brown, G., Searle, G.: Factors affecting farmers’ satisfaction with contemporary China’s land allocation policy – the link policy: based on the empirical research of Ezhou. Habitat Int. 75(5), 38–49 (2018). https://doi.org/10.1016/j.habitatint. 2018.04.004 6. Wu, Y., et al.: Market-driven land nationalization in China: a new system for the capitalization of rural homestead. Land Use Policy 559–569 (2018). https://doi.org/10.1016/ j.landusepol.2017 7. Tao, L., Wong, F.K.W., Hui, E.C.M.: Residential satisfaction of migrant workers in China: a case study of Shenzhen. Habitat Int. 42(2), 193–202 (2014). https://doi.org/10.1016/j. habitatint.2013.12.006 8. Xu, M.H.: Legal research on the transfer system of the right to use rural homestead in China, pp. 23–24. Henan Normal University, Xinxiang (2012). (in Chinese) 9. Yang, J, Zhang, X.Y, Tang, B.: Exploration and analysis of rural housing sales in the context of deepening reform. China Land Sci. (6), 67–74 (2015). (in Chinese) 10. He, P.L.: The research on the establishment of the system of property rights of farmers in China, pp. 35–36. Xinyang Normal College, Xinyang (2015). (in Chinese) 11. Li, N., Chen, L., Long, K.: Rural homestead property rights system study: based on analysis perspective of the relationship between incomplete property rights and subject behavior. J. Publ. Manage. 1, 39–54 (2014) 12. Zheng, S.Y.: The nature of the right to use the homestead and the protection of farmers’ living rights. China Law (2), 142–157 (2014). (in Chinese) 13. Meng, F.S.: Research on the major disputes of the right to use construction land in China’s property law, p. 16. China University of Political Science and Law, Beijing (2015). (in Chinese) 14. Kang, S.J.: Analysis of the reasons and solutions for the registration of the right to use the homestead. China Land (11), 249–250 (2012). (in Chinese) 15. Wang, P.: Research and countermeasures on the existence of the right to use the right to use rural homestead. Agric. Technol. 20, 225 (2015). (in Chinese) 16. Wang, Y.: Research on the transfer of land use right under the background of rural land system reform, pp. 11–12. Yunnan University, Kunming (2015). (in Chinese) 17. Hu, Z.H.: Discussion on the problem of professional cooperatives of financial services farmers. J. Central Univ. Finan. Econ. (8), 34–38 (2010). (in Chinese) 18. Long, K.S.: The real logic and path selection of the reform of the tenure system of homestead. Soc. Sci. (2), 10–15 (2016). (in Chinese) 19. Qiao, Y.Z., Gong, J.Q.: The generation solidification and remission of urban-rural dual structure in China. J. Shanghai School Admin. 4, 84–92 (2014). (in Chinese) 20. The third plenary session of the 18th CPC central committee: The decision of the CPC central committee on several major issues concerning comprehensively deepening reform. People’s Daily (2013). (in Chinese) 21. Gao, X, Zhang, A.L, Li, C.: Social security non-farm income expectations and homestead exit decision behavior, based on the economic developed regions such as Shanghai Jinshan and Songjiang districts of empirical analysis. J. China land Sci. (6), 89–97 (2016). (in Chinese) 22. Chen, Y.T, Luo, X.L, Zhang, L.: Social network research on the development of small property houses in China-a case study of the villages and villages in the city of Hangzhou. Human Geogr. (2), 48–52 (2014). (in Chinese) 23. Liu, H.L.: Research on the standard of membership of rural collective economic organizations, pp. 21–22. Shandong University, Jinan (2016). (in Chinese) 24. Yang, Y.T.: Exploration and construction of paid use system of homestead in China. J. Nankai Philos. Soc. Sci. Edn. 4, 70–80 (2016). (in Chinese)
Measures of Fire Protection Design for Embedded Substations Xiner Luo1, Hong Yang2(&), Peng Yu1, and Changfu Sun3 1
Shenzhen Power Supply Bureau Co., Ltd., Shenzhen, China School of Mechanical and Electrical Engineering, Shenzhen Polytechnic, Shenzhen 518055, China [email protected] Shenzhen Experts Federation of Energy Conservation and Integrated Resource Utilization, Shenzhen, China 2
3
Abstract. The high density of urban construction in China has caused land shortages in urban centers and has also caused high land costs. Embedded substations, because they do not occupy land separately, have high land-use efficiency and are increasingly favored by urban managers. This paper uses the method of case analysis, analyzes the fire protection design of embedded substations in detail from aspects of architectural design, structural design, evacuation design, equipment and material selection. The embedded substation is a new integrated form. In the case of the Code of Design on Building Fire Protection and Prevention without clearly specifying the fire protection design measures for embedded substations, combining with the fire protection evaluation conclusions of built-in embedded substations, this paper proposes the fire protection design ideas for embedded substations in light of the technical difficulties in fire protection. The results of the research provide reference for the future fire protection design of embedded substation, and provide the basis construction of fire protection standards for the embedded substation. Keywords: Embedded substation Civil architecture Fire protection design Measures
1 Introduction The Chinese economy continues to develop at a rapid rate and electricity demand continues to grow. In 2017, the peak power grid load in 11 cities across the country exceeded 10 million kilowatts. The following Fig. 1 shows the changes in the peak load of the power grid in Shenzhen in the past 10 years. There are 228 substations of 110 kV and above in Shenzhen, covering an area of approximately 2.1 km2. The transmission line of 110 kV and above is 4,306 km and covers an area of about 120 km2. According to Shenzhen Planning and Land Resources Committee’s “Special Plan for Shenzhen Electric Power Facilities and High Pressure Corridor” (2012–2020) [1], it is estimated that the city’s saturation load will be 30 million kW, the total number of substations in the city will reach 430, and the power grid facilities will cover an area of nearly 200 km2. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 317–324, 2021. https://doi.org/10.1007/978-981-15-3977-0_23
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Annual Peak Loads in Shenzhen (million kW)
Fig. 1. Annual peak loads in Shenzhen in the last 10 years
In order to meet the city’s demand for electricity, it is estimated that 200 substations will need to be built in Shenzhen, with an area of 5,000 m2 per substation and a total substation area of more than 1 million square meters. The value of land in Shenzhen City is 100,000 yuan per square meter, and the total land value of the substation is more than 100 billion yuan. Therefore, in 2011, Shenzhen city proposed the idea of carrying out the research and pilot of substation “indoorization and miniaturization” [2, 3].
2 The Problems and Solutions of Fire Protection Design for Embedded Substation Due to the situation of government administration in the power industry and the construction industry, substations are usually all independently allocated by the government to the power system. Even in the commercial center area where the land is extremely tight, independent substations will be planned. The conventional layout of substations that independently occupy the following areas is to arrange fire control loops, accidental oil storage pools, and fire water tanks centered on the switch building, so the floor space is large, as shown in Fig. 2. But in the embedded substation, as shown in Fig. 3, the switch room, transformer room, and auxiliary room are integrated and attached to a civil building without using a separate land.
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Fig. 2. Plan layout of independent substation
Fig. 3. Embedded substation
2.1
Fire Problems in Embedded Substations
Early transformers generally used oil-immersed equipment. The “Code for Fire Protection in Building Design” GB50016-2014 (hereinafter referred to as “Fire Protection Code”) [4] also equates the substation’s hazard level with that of the boiler house, and adopts the same fire-fighting measures as the boiler house. Therefore, inertial thinking is that the embedded substation has a high fire hazard level. “Fire Protection Code” 5.4.12 stipulates that fuel oil or gas boilers, oil-immersed transformers, high-pressure capacitors filled with fuel, and multi-fuel switches, etc., should be installed in special rooms outside the building. When it is really necessary to put it in close proximity to civil buildings, it should be separated from the building adjacent to it by a firewall, and it should not be placed close to densely populated places. The fire-resisting grade of this special room shall not be lower than Grade 2. When it is really required to be arranged in a civil building, it should not be arranged on the upper floor, the next floor or the adjacent side of a crowded place, and should meet the following requirements: 1 The fuel or gas boiler room and the transformer room should be located on the outer wall of the first floor or basement, but the regular (or negative) fuel oil or gas boiler can be installed on the second floor or on the roof. The regular (or negative) pressure gas boiler installed on the roof should not be less than 6 m away from the safety exit leading to the roof.
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2 The evacuation doors of the boiler room and the transformer room should pass through the outdoors or safety exits. 3 Class A fire doors and windows shall be used when fireproof partitions with a fire-resistance limit of not less than 2.00 h shall be used between the boiler room and the transformer room and other parts. 4 A fireproof partition wall with a fire-resistant limit of not less than 2.00 h should be installed between the transformer room, the transformer room and the power distribution room. 5 Oil-immersed transformers, multi-fuel switch rooms, and high-voltage capacitor rooms should be provided with facilities for preventing the dispersion of oil products. Under the oil leaching changer, an accident storage facility capable of storing the entire oil quantity of the transformer should be installed. It can be seen that the “Fire Protection Code” is allowed for substations of oilimmersed transformers built in civil buildings. Therefore, the use of dry-type transformers with less fire hazard equipment in civil buildings should be allowed. According to Rule 11.1.1 of “Code for Designing Fire Protection of Thermal Power Plants and Substations”, the hazard levels of equipment and buildings in substations are shown in the following Table 1. The oil-free dry-type transformers have a fire hazard rating of class D, the same as a cable sandwich hazard rating. Non-oil-containing electrical equipment has a fire risk rating of class E, and has the same hazard level as life and fire pump house. It can be seen that if oil-free equipment is used, the substation’s hazard level can be greatly reduced. Table 1. Hazardous degrees of construction of thermal power plants and substations Name of building (structure) Master Communication Building Relay room Cable sandwich Distribution device Oil of single unit is less building (room) than 60 kg No oil-containing electrical equipment Outdoor power Oil of single unit is less distribution device than 60 kg No oil-containing electrical equipment Oil-immersed transformer room Gas or dry type transformer room Capacitor room (with flammable medium) Dry capacitor room Oil immersed reactor room Dry core reactor room Total accident oil pool Life and fire pump room
Fire risk classification E E C D
Fire-resistant level 2 2 2 2
E
2
D
2
E
2
C D C D C D C E
1 2 2 2 2 2 1 2
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According to the above analysis, the main problem of embedded substation fire protection is that transformers and distribution equipment contain oil. If non-oilcontaining electrical equipment is used, the fire hazard level is reduced by one level. The oil-immersed transformer room uses a gas or dry-type transformer room, and the hazard level drops from C to D. 2.2
Control of Fire Hazard Level in Embedded Substation Equipment
In order to reduce the fire hazard level of embedded substation equipment, transformers are used for gas or dry-type transformers, oil-immersed transformers are not used, and cables use Category A flame-retardant cables. Specifically refer to the following Table 2. Table 2. Fire Hazard Ratings of Embedded Substation Equipment Main equipment room
Main electrical equipment
Fire characteristics
Main transformer room
SF6 gas transformer
110 kV distribution equipment room 10 kV distribution equipment room
GIS combination appliances
SF6 gas is chemically stable, nonflammable, and does not react with water, alkalis, ammonia, hydrochloric acid, sulfuric acid, etc. Below 150 °C, the gas is chemically inert SF6 gas is odorless, non-flammable, non-toxic inert gas. Combustibles are mainly cables Oil-free, flame-retardant, nonexplosive
10 kV capacitor room 10 kV station and grounding transformer room Cable sandwich room
2.3
Metal armored Removal high voltage switch cabinet SVG dynamic reactive power compensation Epoxy resin cast dry type transformer Cable
Adopts a thin film capacitor, which is made of an organic plastic film and is free from oily liquids Epoxy resin cast dry type transformer is class F or class H insulation, safe operation at high temperatures Class A flame-retardant cable
Fire hazard level D
D
D
D
D
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Fire-Resistant Rating of Embedded Substation Enclosure Structure
The fire resistance rating of the underground and above-ground walls of the embedded substation should all be one grade. The embedded substation should be separated from the adjacent area by a firewall, and doors and windows should not be opened in the
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wall. When the underground cable floor needs to share an evacuation stairwell with an adjacent area, the front room leading to the stairwell should be added, and a positive air pressure should be provided in the walkway [5, 6]. The fire resistance limit of the partition wall between equipment rooms is greater than or equal to 2.0 h, and that of the floor slab is greater than or equal to 1.5 h. Both are non-combustible materials and form a separate fireproof unit with Class A fire doors. Each main transformer is a separate room, separated by a firewall. The opening of the main transformer room shall lead directly to the outside, and the fireproof integrity of the fire shutter at the entrance shall not be less than 3 h. Above the opening of doors, windows, etc. on the external wall of the substation, a non-burning body with a width of not less than 1.0 m should be provided or a window sill wall with a height of not less than 2.0 m should be provided. Take the embedded substation of Shenzhen as an example, as shown in Fig. 4. The fire resistance limit of the substation roof is greater than or equal to 2.0 h. The distance between the outer wall of the west side of the substation and the outer wall of the adjacent area is 13 m. The outer wall on the south side is a firewall with no openings for doors and windows. The distance between the glass curtain wall of the east side lobby adjacent to the substation and the outer wall of the east side of the substation is greater than or equal to 3 m, and the horizontal distance from the opening of the external wall of the substation is greater than or equal to 3 m. In the entrance from outside into the room, at the exit and entrance of the cable shaft, and between the main control room and the cable layer, the cable should be fire-retardant and separated measures to prevent cable fire from spreading. The cable is partially coated with a fireretardant coating or partially fire-resistant or fire-resistant tanks. Interior decoration use Class A non-combustible materials.
Fig. 4. Firewall settings of embedded substation in Shenzhen
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The fire protection curtains between the underground fire protection partitions of the embedded substations are Class A, and all the room doors are open to the evacuation direction. In addition to the main transformer room, there are two evacuation doors in the rooms with a building area of more than 60 m2. When the basement and the ground floor share the evacuation stairway, at the entrance and exit of the first floor and the underground floor, a partition wall with a fire-resistance limit of not less than 2.0 h and a Class B fire door are installed.
3 Conclusions Through the above analysis, the fire protection design of the embedded substation is a fuzzy area in the specification. [8, 9], there is no provision in the “Fire Prevention Code” prohibiting the construction of embedded substations, but there is no clear provision that allows the construction of embedded substations. Therefore, it is recommended to write a special design for fire protection design at the stage of scheme design and construction drawing design of embedded substation, Or conduct firefighting performance design in accordance with the Ministry of Public Security of the People’s Republic of China, the “General Principles of Building Performance-based Fire Protection Design”, and invite the provincial and municipal public security fire department to organize expert assessments. The fire protection design of the 110 kV embedded substation in the Shenzhen Bay Eco-city was reviewed by experts from the Public Security Department of Guangdong Province. The above cases and analysis results show that the substation with no oil-containing electrical equipment and transformers has a fire hazard rating that is not higher than that of the oil-fired boiler house. Therefore, the construction of the embedded substation is feasible from the perspective of fire protection design. According to the literature [5, 6], in the past five years, more and more substation construction projects have been adopted, and the equipment used has become more and more advanced, There are no fire accidents in domestic embedded substations, and a large number of cases [10] also verify this conclusion. Therefore, when the Code for Fire Protection of Building Design is revised, the fire hazard level of the substation should be reduced, and the relevant provisions of the fire protection design for the embedded substation should be increased to improve the construction efficiency, reduce the time for government review, and enhance the intensive use of urban land resources. Acknowledgement. This article is supported by the project of “Integration and Evaluation of Embedded Substation Comprehensive Evaluation Technology and Applied Technology Development” of Shenzhen Power Supply Bureau Co., Ltd.
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References 1. Planning and Land Resources Commission of Shenzhen Municipality. Special Plan for Shenzhen Electric Power Facilities and High Pressure Corridor (2012–2020) 2. Shenzhen Planning and Land Resources Committee of Shenzhen Municipality. Research on Land Use Policy and Scheme for Embedded Substation (2012) 3. Economy, Trade and Information Commission of Shenzhen Municipality. Request report of Resources for Reducing Land and Other Resources, Promoting Substation Indoorization and Miniaturization Construction, Document 149 (2011) 4. Liao, W.L.: Applied research of embedded substations. Power Electron. 13(33), 94–99 (2014) 5. Zhou, Y.L., Kang, H.: Analysis on the Causes of Urban Electrical Fire Accidents and Countermeasures, Low Carbon World, August, pp. 70–71 6. Tao, Y.H.: Analysis of the correlation between the causes of electrical fire accidents and suggestions. Technol. Innovat. Appl. 16, 125–126 (2018) 7. Tianjin Fire Research Institute of Ministry of Public Security, Sichuan Fire Research Institute of Ministry of Public Security. Code for Fire Protection Design of Buildings, GB50016-2014, China Planning Press, August 2014 8. Chen, G., Wu, Y., Tang, D.X.: Brief introduction of electrical fire in civil buildings and design of automatic fire extinguishing system for electrical buildings. Water Wastewater Eng. 10, 104–108 (2016) 9. Ni, Z.C., Ding, L.: Views on the article “Electric fire in civil buildings and the design of automatic fire extinguishing system for electrical buildings”. Water Wastewater Eng. 1, 143– 144 (2018) 10. Shenzhen Power Supply Planning and Design Institute Co., Ltd., Research report on indoor miniaturization of substation, Economic, Trade and information Committee of Shenzhen Municipality, pp. 10–28 (2013)
The Conceptual Model of Belt and Road Infrastructure Projects Jelena M. Andrić1, Jiayuan Wang1(&), Patrick X. W. Zou2, and Ruyou Zhong3 1
2
College of Civil Engineering, Shenzhen University, Shenzhen, China [email protected] Department of Civil and Construction Engineering and Centre of Sustainable Infrastructure, Swinburne University of Technology, Swinburne, Australia 3 Center for Special Economic Zone Research, Shenzhen University, Shenzhen, China
Abstract. The Belt and Road (B&R) Initiative is a Chinese Policy with the aim to gain greater international influence of China, connect and raise regional cooperation and development of vast regions in Asia, Europe and Africa. Behind the Policy, opportunities arise for many countries along the Silk Road route. However, opportunities are always followed by risks. In this paper, the conceptual model for B&R projects is developed and opportunities and risks in B&R projects are investigated. The conceptual model of B&R projects is based on the three essential agreements: agreements on cooperation between the Chinese government and the government of B&R country, the commercial contract of B&R project between the Chinese Contractor and the government of B&R country, and loan agreement between the Chinese bank and the government of B&R country. Opportunities in B&R projects lie in the following sectors: Infrastructure; Energy and resources; Banking; Transport and trade; Manufacturing; Financial services; Agriculture; Healthcare; Tourism; Ecommerce and logistics; and Culture and education. In total, 43 risks in B&R projects are identified, which are grouped into three categories: risk related to B&R Policy, construction market and project. Keywords: Belt and Road Initiative The silk Road economic belt The 21st maritime silk road Infrastructure projects Opportunities Risks
1 Introduction The Belt and Road (B&R) Policy, “一带一路” (pinyin: Yī dài yī lù) in Chinese, is a development strategy with the focus on establishing connectivity and cooperation between B&R countries in order to sustain economic growth and greater international influence of China, create closer economic ties, deepen cooperation and expand development of vast regions in Asia, Europe and Africa [1]. The Chinese government has characterized the spirit of Silk Road as “peace and cooperation, openness and inclusiveness, mutual learning, mutual benefit and win-win results” [2]. During the visit to Kazakhstan on September 7th, 2013, Xi Jinping, the President of the People’s Republic of China, delivered a historic speech at Nazarbayev University in © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 325–340, 2021. https://doi.org/10.1007/978-981-15-3977-0_24
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Astana, in which he mentioned the famous trade route that once linked China and Kazakhstan and proposed the revival of the ancient Silk Road in an Initiative called the Silk Road Economic Belt, in Chinese. “丝绸之路经济带” (pinyin: Sī chóu zhī lù jīng jì dài). In the following month, during his visit to Indonesia, he addressed that Southeast Asia occupied the key position in the ancient time and proposed that China and Southeast Asian countries should enhance their cooperation by sea building the 21st Century Maritime Silk Road, in Chinese “21 世纪海上丝绸之路” (pinyin: 21 Shì jì hǎi shàng sī chóu zhī lù). The modern B&R consists of two main components: the land-based “Silk Road Economic Belt” and oceangoing “Maritime Silk Road” (Fig. 1). The Silk Road Economic Belt links China with Europe through Central Asia and Western Asia by inland routes. On the other hand, the 21st Century Maritime Silk Road connects China with Southeast Asia, Africa and Europe by sea routes. On land, the focus is building economic corridors based on the existing international transport routes, keep the interrelation centers and major industrial parks. At sea, the focus is opening fast, secure and efficient ship routes connecting major seaports.
Fig. 1. B&R route [3]
The Silk Road is a historic and cultural heritage symbolizing communication and cooperation between the East and West [4]. Traditionally, there are two well-known routes, The Northern Silk Road and the Maritime Silk Road and one less-known, the Southern Silk Road [5]. The NorthernSilk Road starts in Xi’an and spreads northwest through Gansu and Xingjian into Central Asia and reaches even as far as Europe. The Maritime Silk Road begins in Guangdong, over Malacca extent to Southeast Asia, Sri Lanka and India. The Southern Silk Road consists of several routes: 1.) route through
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Sichuan, Yunnan, Myanmar, India; 2.) route from Yunnan to Vietnam Road through Red River; 3.) route through Yunnan, Laos, Thailand, Cambodia [5]. In total, B&R Initiative includes more than 900 infrastructure projects which are planned to be implemented in the period between 2013 and 2030, with the planned investment of $4 trillion [6]. This Initiative brings huge opportunities for all countries along B&R route and businesses. However besides the opportunities, there are certain risks in B&R infrastructure projects. In this research, we are trying to answer to the following questions: (1) What is the conceptual model of B&R project? (2) What are opportunities in B&R Policy? (3) What are risks in B&R projects? The aims of this study are: to develop the model of B&R projects and identify opportunities and risks in B&R projects.
2 The Conceptual Model of B&R Projects The conceptual model of B&R projects is developed and proposed in Fig. 2 based on the agreements on cooperation between the Chinese government and the government of B&R country [7, 8], commercial contract of B&R projects between the government of B&R country and the Chinese Contractor [9], and the loan agreement between the Chinese banks and the government of B&R country [8, 10, 11]. B&R Initiative is open to all countries and organizations for cooperation with China and it is not limited to regions of the historic Silk Road [4]. Firstly, the diplomatic relations between China and other country must be established with the agreement on jointly implementing B&R Initiative. By signing the agreement on mutual cooperation between two governments, the country officially becomes a member of B&R Initiative [4, 7].
Fig. 2. The conceptual model of B&R projects
According to the provisions from agreement on cooperation, the contract on B&R projects is signed between the government of B&R country and the Chinese Contractor. Therefore, it is necessary to discuss risks in B&R projects from Chinese Contractor’s perspective. In the Contract between the government of B&R country and the Chinese Contractor, the Laws of B&R country is applied [9]. If there are no laws or regulations for construction in the domestic Laws, international rules as FIDIC conditions of Contract for Plant and Design First Edition in 1999 will be used [9].
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Based on the signed contract between these two parties, contracting parties need to prepare documents necessary for submission of loan application. The loan agreement is signed between the Chinese bank or fund and the government of B&R country. A few banks and funds are established to finance the B&R projects. Since the majority of B&R members are developing countries without sufficient funds for large-scale complex infrastructure projects, special banks and funds are established for the purpose of financing B&R projects. These banks are Asian Infrastructure Investment Bank (AIIB) and the Silk Road Fund. AIIB is a medium-sized multilateral bank with capital base of $100 billion, which is positioned on the third place after the World Bank (capital base of more than $250 billions) and Asian Development Bank (capital base of more than $150 billions) [12]. Beside the AIIB, the Silk Road Fund with the capital base of $40 billion was established in order to provide financing support for trade, economic cooperation and connectivity under the framework of B&R Initiative [13]. In addition to support Policy, two Chinese banks, The Export-Import Bank of China (Exim Bank) and China Development Bank (CDB) are included. The Exim Bank provides advance international economic cooperation, supports China’s economic development, and construction of B&R projects, with the vision of becoming the most influential international economic cooperation bank [14]. CDB is the largest Chinese bank for foreign investment and financing cooperation, long-term lending and bond issuance, which provides medium to long-term financing facilities that serves China’s long-term economic and social development [15]. Compared to traditional international projects, B&R projects are: 1.) geopolitical, strategic and development-oriented since the aim of these projects is to enhance cooperation and trade which will have huge impact on the economic growth and society development; 2.) geographically-distributed as they are located on three continents (Asia, Europe and Africa); 3.) unique since they connect people from different societies with different social, cultural and religious backgrounds; 4.) complex due to their scope, long duration, large-scale operations, high technical and modern technology procedures; 5.) many different stakeholders including two governments (Chinese government and B&R country government), special funds, international organizations and others; and 6.) funded by special funds and banks, such as AIIB, The Silk Road Fund, The Exim Bank and CDB.
3 Opportunities in B&R Infrastructure Projects There are huge opportunities in B&R Initiative in different sectors for every country which have joined the Initiative. Practically, there is no sector which remained intact by B&R cooperation: Infrastructure; Energy and resources; Banking; Transport and trade; Manufacturing; Financial services; Agriculture; Healthcare; Tourism; E-commerce and logistics; and Culture and education. B&R Initiative brings vast opportunities for infrastructure development since it includes more than 900 infrastructure projects which are completed, under construction or negotiated at the moment. The majority of infrastructure projects include rails, roads, ports, airports, transport hubs, logistic centers, gas and oil pipelines, power grids and other. Such a large number of infrastructure projects will improve connectivity within
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China between west regions Xinjiang, Shaanxi, Sichuan and Yunnan and between China and external routes which follow the ancient Silk Road. Moreover, construction projects are great opportunities for Chinese Contractors “going global” practices. The cooperation in energy sector is based on the connecting energy facilities by building oil and gas pipelines and power networks along B&R countries. In this sector, the aim of policy is to improve energy safety and to optimize the distribution of energy sources by integrating regional energy markets and pushing forward the green and lowcarbon development of regional energy [16]. From China’s perspective, B&R Initiative will enable expansion of Chinese commercial banks and more branches will be opened in B&R countries [17]. Chinese commercial banks will promote the use of Chinese RMB in trading and investment with countries along B&R Initiative. Further, maximizing the application scope of RMB in trading and investment activities with countries along B&R route could lead to internationalization of Chinese RMB (Fig. 3) providing a great opportunity for strengthening China’s geopolitical and geo-economic position in the World.
Fig. 3. Chinese RMB
Using new Eurasia land bridge corridor, China has launched direct international rail routes for freight trains. According to China Railway Corporation, there are freight train services between 34 cities in China with 34 cities in European countries [18]. Recently, new routes between China and Europe are opened: Chongqing – Duisburg in Germany, Wuhan - Pardubice in Czech Republic, Chengdu - Lodz in Poland, and Zhengzhou – Hamburg in Germany [19]. Transporting goods by railway is more efficient compared to air and sea transportation. By railway, it needs 12 days for goods to reach from China to European cities, which is one-third of time needed for sea transportation. The cost of railway transportation is only 20% of air transportation. In January, 2017 the first freight train from China to the
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UK traveled the 12,000 km journey and arrived in London (Fig. 4) [20]. Besides railway transport, China have started new airline routes and signed bilateral air transport agreement with 116 countries. With established new rail routes and sea routes under B&R initiative, an amount of trade between B&R countries will rise. Chinese government expect that the trade will exceed $2.5 trillion per year within the next decade [21].
Fig. 4. The first freight train from China to the UK
Agricultural exchanges on the Great Silk Road have originated from ancient times, when seeds of alfalfa, planting grapes, flax, crops, such as onions, haricots, carrots, pomegranates, Circassia walnuts have been brought to China [22, 23]. Also, rice was carried to Eastern Europe from Central Asia. There are many opportunities in agricultural sector for cooperation along B&R countries. Due to growing demand for food, China is trying to increase agricultural productivity by shifting from individual farming models to one of cooperatives, which will increase demand for agricultural machinery. Since there is a lack of advanced agricultural technology and management skills in China, there is opportunity for cooperation with other countries along B&R. In addition, China is planning to build a global food supply chain. Agriculture cooperation under B&R Initiative is signed for common pursuit to fight hunger, eradicate poverty, and achieve food and nutrition security [23]. Secondly, B&R countries have an opportunity to export agricultural, food and drinks products to China. China is the largest manufacturer in the world. Manufacturing sector is highly competitive in several industries and it is priority of cooperation in B&R Initiative. “Made in China 2025” is China’s plan to upgrade industry from traditional to more
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innovative-driven, efficient and integrated in order to occupy the highest parts of global production chains [24]. B&R countries represent new markets for Chinese manufactures and opportunities to expand production and open factories in these countries. In addition, Chinese government encourages manufactures to “go global” and invest in various ways in B&R countries. Since healthcare and tourism sectors are not the priority of B&R Initiative, though secondary opportunities are lying in these sectors. In 2013, Chinese government allowed establishment of more private hospitals and foreign-owned private hospitals in Beijing, Tianjin, Shanghai, Fujian, Guangdong, Hainan, and Jiangsu. Under B&R Policy, China suggested the cooperation in the prevention and control of contagious diseases, medical system and policies, health care capacity buildings, personnel training and exchange, and traditional medicine among B&R countries [2]. For every country, educational system is very important for development and prosperity of nation. Therefore, educational exchange plays a fundamental role in B&R Initiative for deepening people-to-people bounds and the cultivation of talent can support the efforts of these countries toward policy coordination, connectivity of infrastructure, free trade and financial integration [25]. In addition, some of the world’s biggest religions, such as Buddhism and Islam came to China through ancient Silk Road [26]. Buddhism spread from India to Central Asia (Tibet), East Asia and Southeast Asia (Sri Lanka, Thailand) [27]. Later, Islam came to China by Arabic traders who arrived to Guangdong Province [28].
4 Risk in B&R Infrastructure Projects A preliminary list of 43 risks is established according to references in Table 1. These risks are obtained from different literature reviews which include journal articles, technical papers, case studies and other sources. Compared to traditional risk assessment frameworks, risks in B&R projects belong to three levels, B&R Policy, Construction market and Project as depicted in Fig. 5. 4.1
Risk Related to B&R Policy
The B&R Policy level risks are related to policy and strategic relationship between China and B&R country. Hence, B&R Policy risk group consists of geopolitical risk, credit risk and cooperation and bilateral relationships between China and member of B&R Initiative. B&R is a geopolitical project that aims to build infrastructure in order to enable flows of trade and investment, exchange ideas, information and philosophies along the countries and change geopolitics in different regions in the World [29, 54]. The B&R projects are influenced by serious geopolitical risk since some countries are located in complex geopolitical regions, where political, religious and ethnic conflicts are common, such as Afghanistan and Pakistan. As a result of this, the connectivity of the Silk Road can be easily disrupted. Secondly, the New Silk Road and the 21st Century Maritime Silk Road present a threat to economies of certain countries. For instance, Chinese development, economic growth and greater influence on the Eurasia continent will put the United States outside of Asian’s market [30]. From the USA
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Risk id 1 2 3 4 5
Risk category
Risk Category
Risk
B&R Policy
Geopolitical Credit Cooperation between China and B&R country Economic Legal
[29–32] [32] [32]
Construction market (host country)
6
Political
7
Social
8 9
Cultural difference Different Religious background Majeure Force
10
Project risks related to environment
11
Unforeseeable ground conditions Noise pollution Soil and water pollution Critical weather conditions
12 13 14 15 16 17 18 19 20 21 22
23 24
Project risks related to design process
Design errors Inadequate design quality Changes in design for construction permit Changes in design for road/rail routes Changes in design for waterworks Changes in design for sewerage Changes in design for traffic signalization Changes in design for telecommunication installations Changes in design for electrical installations Changes in design for geotechnical documentation
[33–38] [33, 34, 36, 38, 39] [33, 34, 36, 38] [33, 34, 38, 40] [41] [33, 34] [33–35, 38, 39] [33–35, 39, 43, 44] [45–48] [47, 48] [37, 39, 42, 43, 49] [34–37] [33, 34, 39, 50] [32] [32] [32] [32] [32] [32]
[32] [32] (continued)
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Table 1. (continued) Risk id
Risk category
Risk Category
Risk [32]
30
Changes in design for technical documentation Changes in design for bridge Changes in design for tunnel Poor access to construction site Poor organization of construction site The lack of equipment
31
Failure of equipment
32 33 34
Delay of equipment delivery Increase cost of equipment use Bad quality of materials
25 26 27 28 29
Project risks related to construction
Process
35
Increase cost of material
36
Delay in supplying materials
37 38 39 40 41 42 43
Project risks related to staff and management of the project
The lack of labor Poor management skills of project managers Lack of coordination between different sectors Poor team communication Inadequate quality control inspection Accident occurrence Safety measures on the site
[32] [32] [51] [43, 50] [33, 37, 43, 50] [36, 43, 50] [37, 50] [36] [34, 35, 43, 49] [34, 36, 47, 49, 52] [34, 43, 50, 53] [37, 43, 47, 49, 50] [47, 49] [34, 39, 50] [34, 37, 43, 50] [34, 37, 43] [53] [33, 35, 39, 47]
point of view, B&R is related to “new international order”, “new economic model” and “new civilization exchange”. The New Silk Road is a diplomatic approach by China in order to establish a new economic and political order in East Asia and West Asia [31]. Besides the USA, B&R Policy is potential threat to Japanese and Indian economies, since Japan and India are Chinese neighboring countries. The majority of B&R members are developing countries which have insufficient funds for large-scale complex infrastructure projects. Credit risk rises from the Loan agreement between B&R country and Chinese bank, as it is shown in Fig. 2. Loans for
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Fig. 5. Risk Levels
B&R projects can be approved or denied depending on B&R country’s ability to return credit. Also, loan effectiveness and procedures for loan approve are included in credit risk. Compared to the traditional international construction projects, B&R projects are result of the cooperation and bilateral partnership agreement between Chinese government and B&R country government. In order to implement this project, the bilateral agreement between China and B&R country are signed by their governments as shown in Fig. 2. Hence, risks which can influence the execution of the B&R project in the host country are related to cooperation and diplomatic relationships between China and B&R country. If some issues or misunderstanding appear in cooperation between China and the B&R member country, it can lead to interruption of project. 4.2
Risk Related to Construction Market
The second group contains of economic, law and political risks associated to the construction market of host country and social, cultural and religious difference since Chinese Contractor is operating in the foreign country. Economic risk appears due to inflation, fluctuation in currency exchange rate, taxes and price instability. Currency exchange rate is significant economic factor for B&R projects since Chinese Contractor is working in foreign country which has its local currency. In addition, some materials and equipment for the requirements of project are imported from China. The loss due to currency exchange could increase the cost of the project. Legal risks are associated with the law background of the country. In some countries, laws are complex, unclear, incoherent, changeable, and open to interpretation. Legal issues appear due to changes in laws of planning and construction, rules, regulation, contractual matter, and human rights. Contract negotiations and obtaining project approval can be lengthy and resulted in project delays. In addition, some clauses in contracts could be risky to manage and could cause conflicts in contract forms and documents. Political risks are related to the political situation of the country where the project is taking place, political stability, political changes, sovereignty, government effectiveness, bureaucracy and excessive
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procedures and corruption and bribes. Political changes could change the outcome of contract signed with previous government. B&R projects include stakeholders from different social, cultural and religious backgrounds. As a result, the language barrier between different stakeholders could cause misunderstandings during the project implementation and it could have major impacts on the project goals [34]. In order to avoid difficulties in cross-cultural communications, translators and interpreters should be employ who will translate documents from one language to another and intermediaries in communication between stakeholders. For example, Chinese contractor will need translators to write documents in official language for obtaining the construction permissions from local authorities. Beside language barrier as social risk, other social risk is the acceptance of B&R project by local community. Local community can oppose or support the implementation of project. If local community doesn’t accept the project, it could lead to serious consequences such as delay and increase in cost. Further, the risk can arise due to the cultural difference between investor, designer, contractor, sub-contractors since they come from different cultural backgrounds. The cultural difference between stakeholders could lead to misunderstandings, conflicts and disputes [41]. However, the cultural background of China, Singapore and other Southeast Asia countries are more or less similar due to geographical location and historical issues [55]. But there is cultural difference between Asian and African cultures which can influence projects in Africa. Also, the cultural of Middle East is quite different from Chinese culture, which can also affect B&R projects. Hence, cultural difference is significant risk for Chinese contractors when they are working on B&R projects in Europe, Africa, Middle East and South Asian countries. The Chinese culture is mainly based on the Confucian-TaoistBuddhist philosophies [56] and cultural dimension is very important for implementation of B&R projects. As well as different cultural background of stakeholders, different religious believes could influence the project implementation. For example, religious believes can affect the perceptions of safety management in construction [57]. 4.3
Risk Related to Project Environment
The third group is project risks related to environment where construction project is implemented. This group contains of majeure force, unforeseeable ground conditions, critical weather conditions, noise pollution on the construction site and soil and water pollution caused by construction works on the site. Majeure force is risk related to natural disasters such as earthquakes, floods, tsunamis, hurricanes, as well as, war, riots and others. From a geotechnical perspective, unforeseeable ground conditions present uncertainties in subsurface [44]. Hence, there is a need for geotechnical site characterization which includes composition and properties of subsurface materials. The critical weather conditions are related to storms and heavy rain falls during the construction process. In the case of the majeure force and critical weather conditions, some equipment and materials can be destroyed, damage to the structure could be caused, and the productivity of labor and equipment could be decreased in such conditions. During the construction, some construction operations and machines generate loud sound and produce noise. Noise is a pollutant which have negative impact on the workers and living environment [58]. Sometimes it could cause serious damage to
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worker’s health. Construction site’s surroundings are exposed to loud sound which could disturb neighborhood and lead to disputes. In the case of seaport projects, construction activities, such as underwater blasting, pilling produces high-intensity noise that impacts underwater environment and, in some cases, causing death of fishes and mammals [59]. Since the construction works of infrastructure projects are outside activities, the waste which is produced by these activities can pollute the soil and water near the construction site. Cause of soil and water pollution at the construction site are erosion, earthworks, storm water runoff, sediment, lack enforcement, compaction, waiting time and delay during earthwork and site development and other [48]. 4.4
Risk Related to Design Process
The fourth group risks consist of risks which appear in design phase. During the design process, infrastructure projects are exposed to many risks, which are related to design errors, inadequate design quality, and changes in design. Further, changes in design contain of changes in design for different types of projects, which are considered here separately. Hence, changes in design includes changes in design for the construction permit, road/rail routes, waterworks, sewerage, traffic signalization, telecommunication installations, electrical installations, geotechnical documentation, technical documentation, bridge and tunnel design. 4.5
Risk Related to Construction Process
The next group of risks is related to construction process. In the construction process, risk related to construction site, equipment and materials could appear. The poor accessibility and poor organization of construction site can contribute to works delay. However, equipment and materials are essential risk elements which could largely contribute to the total project risk. The breakdown of equipment, delay of equipment delivery and increase in the cost of equipment are risks which could arise from equipment use. The poor quality of material, delays of materials supply and increase of material cost should be mitigated in order to avoid potential risks. 4.6
Risk Related to Staff and Management of the Project
The last group of risks is connected with human resources and management of the project. In this group, the lack of labor, poor management skills of project managers, lack of coordination between different sectors, poor team communication, inadequate quality control inspections, accident occurrence, and safety measures on the site are analyzed in order to efficiently manage the project. In some countries, there is a shortage of skilled labor on the market and unskilled workers could cause defects in construction works. Import of skilled workers cause the raise of project costs. During the construction work, construction workers are exposed to various types of injuryinducing hazards and poor safety management which could result in an accident [60]. The key causes of the highway construction accidents are: working environment changes frequently; during the construction the outdoor work which undertakes heavy
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amount and lasts for relatively longer time is influenced by the weather, temperature, wind, rain, and other natural conditions; the programs of the construction are of great changes; during the construction mechanical and blasting methods are utilized; and contractor’s unawareness of safe production [61].
5 Conclusion B&R Initiative represents infrastructure projects of international importance not only for China, but for all countries along the Silk Road. In this paper, the conceptual model of B&R project is proposed and developed. In addition, opportunities and risks in B&R projects are investigated. The results show that major opportunities in this Initiative for China and all countries along the Silk Road lie in different sectors: infrastructure, energy and resources, banking, transport and trade, agriculture, manufacturing, and education and culture. This information is of great interest for: Chinese enterprises planning to expand their business to B&R countries; investors; international companies which are planning to cooperate with Chinese companies; and countries and their governments which are planning to join B&R Initiative. In total, 43 different risks which can influence B&R construction projects are identified. Generally, these risks can be categorized into three different levels, B&R Policy, construction market and project. For further research, risk assessment on B&R projects can be perform by collecting data from different infrastructure projects in Asia, Africa and Europe in order to identify the critical risks and efficiently manage them. Acknowledgment. We are very grateful for research funds that supported this research: National Natural Science Foundation of China (project ID 71272088) and China Postdoctoral Science Foundation (grant number: 2017M622743).
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Developing a Fuzzy Evaluation Model of Safety Management for Urban Water Environment Rehabilitation Project Xingxiu Wang1, Zhengqiang Yu2, Tinglin Wang2, Jian Liu3(&), Zengwen Bu4, and Liu Ru3 1
College of Civil Engineering, Shenzhen University, Shenzhen 518060, China [email protected] 2 PowerChina Water Environment Governance Co., Ltd., Shenzhen 518060, China 3 Ecological Technology Institute of Construction Engineering, Shenzhen University, Shenzhen 518060, China [email protected] 4 Shenzhen Cenpoint Architects and Engineers Co., Ltd., Shenzhen 518060, China
Abstract. The construction safety management of the urban water environment rehabilitation project is more difficult than traditional projects safety management, because the rehabilitation project involves in many types of work and governmental departments, high requirements for surrounding environment and limited construction site. How to evaluate the construction safety management has become a key link to ensure the success of the urban water environment rehabilitation project. This study analyzed the four major factors that may lead to safety accidents during construction of urban water environment rehabilitation project, and established a safety evaluation index system including four first-level indicators and sixteen secondary indicators. An improved safety fuzzy comprehensive evaluation model was constructed on basis of Analytic Hierarchy Process and entropy weight method. This new model was verified with the safety management practice in the Maozhou River Rehabilitation Project in Shenzhen. Keywords: Rehabilitation project Safety management process Entropy weight method Evaluation model
Analytic hierarchy
1 Introduction With the advancement of China’s ecological civilization construction, there are more and more urban water environment rehabilitation projects. The urban water environment rehabilitation project is a complex system project, relating to various aspects such as urban traffic, resident’s life, construction noise control, and citizen safety management. Failure of safety management can lead to safety accidents, result in casualties and property losses, and even cause irreparable consequences to businesses and society. Therefore, for the safety management of construction site, it is necessary to seriously © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 341–352, 2021. https://doi.org/10.1007/978-981-15-3977-0_25
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identify the hazards and conduct a comprehensive assessment of the safety status on the construction site. For studies on safety status evaluation model, Rozenfeld et al. introduced the lean methodology into building construction safety management and achieved good management results [1]. Dagdeviren and Ihsan based on uncertain safety analysis, data processing fuzzy rules, and analytic hierarchy process (AHP), presented a safety assessment model for behavior-based safety management [2]. Leu et al., based on fault tree analysis, developed a Bayesian cybersecurity evaluation model, which can be used to quantify the risk probability of the system [3]. Li et al. used the Catastrophe Progression Method to evaluate the safety of building construction and verified it with the Longjinang Yunshan project in Fuzhou [4]. In the evaluation of building safety, Chen et al. determined the first-level weight coefficient according to the statistical data of construction accidents and used the entropy weight in information theory to define the second-level weight coefficient. This method provides a reference for the safety evaluation of other projects [5]. Zhao et al. used fuzzy comprehensive evaluation model to evaluate the status of water environment safety in Nanjing [6]. However, little research has been conducted on the evaluation of safety status on construction site of urban water environment rehabilitation projects. Therefore, this study describes a safety fuzzy comprehensive evaluation model based on AHP and entropy weight method, and its application to the Maozhou River rehabilitation project in Shenzhen.
2 Safety Fuzzy Comprehensive Evaluation Model The fuzzy comprehensive evaluation method was proposed by Zadeh, an American cyberneticist. Based on the theory of fuzzy mathematics, the method applys the principle of fuzzy relation synthesis to quantify some factors that are not clearly defined and difficult to quantify, and to comprehensively evaluate multi-factor and multi-level complex problems [7]. Analytic hierarchy process and Entropy weight method was combined to determine the comprehensive weight of each evaluation index, and a safety fuzzy comprehensive evaluation model was established by using the fuzzy comprehensive evaluation method. The basic principle of this model is that: defining the index set of the evaluated objects, determining the weight of each indicator and the evaluation scale set, constructing a fuzzy membership matrix, then calculating the evaluation index, and finally obtaining the fuzzy comprehensive evaluation result. 2.1
Defining the Evaluation Index Set
For the urban water environment rehabilitation project, the four major causes of safety accidents during the water environment construction process were analyzed by using the accident causation theory [8]. An index system of safety status evaluation including four first-level indicators of objects, people, management and environment, and sixteen secondary indicators impacting on construction site safety status evaluation was established, as shown in Table 1.
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Table 1. Evaluation factors for AHP method Construction site safety status evaluation index system (U)
Objects (U1)
Human (U2)
Management (U3)
Environment (U4)
2.2
Safety control of machinery (U11) Safety protection and monitoring equipment (U12) Equipment inspection and maintenance (U13) Material quality (U14) Security awareness of people (U21) The quality of people (U22) Technical level (U23) Construction procedures (U24) Implementation of safety regulations (U31) Setup of safety management organization (U32) Safety education and training (U33) Safety inspection and accident handling (U34) Safety investment (U35) Natural environment (U41) Construction environment (U42) Living environment (U43)
Determining the Weight Set
2.2.1 Determining the Weight by AHP The AHP is a subjective weight determination method. Its core principle is to use the fuzzy index quantification method to derive the relative importance of the criteria in the hierarchy, replace complex decision systems with interdependent hierarchical models, and then to determine the weight of each indicator in the multi-plan optimization decision [9]. The basic steps are as follows: Building hierarchical structure model The step analysis the interactions between the various factors that affect the evaluation object, layers and organizes the complex system composed of various factors, and then establishes a hierarchical structure model including the target layer, the criterion layer, and the indicator layer. Constructing a pairwise comparison judgment matrix By comparing the importance of each factor in each layer with respect to the previous layer and using the 1–9 scale method, the judgment matrix A = (aij)mxn is framed, Where aij represents the ratio of importance of element i to element j, as shown in Table 2.
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Meaning i and j counter the same way as achieving the objective i is slightly more relevant than j i is moderately more relevant than j i is more relevant than j i is definitely more relevant than j Intermediate values
(1) Calculating weight vectors According to the feature vector method, the corresponding weight of each index wi is built, as defined in Eq. (1): AW ¼ kmax W
ð1Þ
Where, W is a weight vector, kmax is the largest eigenvalue of the judgment matrix A = (aij)mxn. (2) Consistency test The formula for calculating the consistency ratio is given as Eq. (2), calculating consistency ratio CR, when CR < 0.10, meeting the consistency test. CR ¼
CI RI
ð2Þ
n Where, CI is the consistency indicator, CI ¼ kmax n1 , and RI is the average consistency indicator. Specific index values are listed in Table 3.
Table 3. Average Random Consistency Index Matrix order 1 2 3 4 5 6 7 8 9 RI 0 0 0.58 0.89 1.12 1.24 1.32 1.41 1.45
2.2.2 Determining the Weight by Entropy Weight Method The Entropy weight method is a objective weight determination method. In 1948, Shannon introduced information entropy for the first time to describe the uncertainty of the source signal, which is a measure to the degree of order of the system. Entropy weight is determined by the amount of information conveyed to decision makers by evaluation factors. If the appraiser has a large difference in the valuation of an evaluation factor, the entropy is smaller and the weight is larger [10]. The basic steps are as follows:
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(1) Standardizing the initial data matrix There are m items to be evaluated, n evaluation indicators, and the initial matrix is defined as X′ 2
0
0
x11 6 x0 0 6 21 X ¼6 . 4 ..
x12 0 x22 .. .
xm1
xm2
0
.. .
0
3 0 x1n 0 x2n 7 7 .. 7 . 5 0
xmn
Then standardizing the initial matrix X′ to get matrix X = (xij)mxn, as defined in Eq. (3): 0 0 0 0 xij min x1j ; x2j ; ; xmj xij ¼ 0 0 0 0 0 0 max x1j ; x2j ; ; xmj min x1j ; x2j ; ; xmj
ð3Þ
0
where, xij is the raw score data value of evaluation item i and evaluation indicator j, xij is the normalized value of evaluation item i and evaluation indicator j. (2) Defining the weight of each item under each indicator The proportion of the index value of the i item under the j evaluation index as pij is defined as Eq. (4): xij pij ¼ P m xij
ð4Þ
i¼1
(3) Defining entropy of the index The entropy value of the i evaluation index is defined as Eq. (5): Hi ¼ k
m X
pij ln pij
ð5Þ
j¼1
where, the constant k is related to the value of m, k ¼ ln1m, k 0, Only when pij ¼ 0,pij ln pij ¼ 0. (4) Defining entropy weight of the index Based on the defined entropy of the index i, its entropy weight is defined as Eq. (6): gi wi ¼ P n gi i¼1
where, gi ¼ 1 Hi .
ð6Þ
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2.2.3 Determining the Combination Weight by AHP-Entropy Weight Method AHP focuses on subjective preferences of decision makers, the Entropy weight method focuses on mining the objective information contained in the data itself, therefore, in order to obtain a more scientific weight, this study considers both subjective and objective weights, and based on AHP-entropy weights [11], develops the combination weight optimization model as Eq. (7): WC ¼ kWA þ ð1 kÞWB ¼ k
n X
wAi þ ð1 kÞ
i¼1
n X
wBi
ð7Þ
i¼1
According to expert’s opinion, this study takes k as 0.5, and defines the formula of the combination weight as Eq. (8): WC ¼ 0:5ðWA þ WB Þ
ð8Þ
where, WA is defined by AHP, WB is defined by entropy weight method. 2.3
Fuzzy Comprehensive Evaluation
2.3.1 Defining the Evaluation Scale Set This study divides the safety assessment results into 5 levels, which is p = 5. V is defined as vague language, which is V = {definitely safe, safer, safe, dangerous, definitely dangerous}. 2.3.2 Fuzzy Comprehensive Evaluation of Safety Status On the basis of expert’s evaluation information for each indicator, a membership matrix is established as Ri = R(rij)nxp. The fuzzy comprehensive evaluation model is defined as Eq. (9): B i ¼ Wi R i
ð9Þ
Where, “” is fuzzy operator, and defines it as M ð þ ; Þ operator. Corresponding to the above evaluation index system U, the first-level indicators fuzzy comprehensive evaluation vector is defined as B, the secondary indicators fuzzy comprehensive evaluation vectors are defined as B1, B2, B3, B4, and B = (B1, B2, B3, B4)T. To quantify the evaluation indicators, this study defines definitely safe as 9 scores, safer as 7 scores, safe as 5 scores, dangerous as 3 scores, definitely dangerous as 1 scores, which is V ¼ f9; 7; 5; 3; 1g. The safety status evaluation grade model is defined as Eq. (10) [12]: m P
Ap ¼
p¼1
Bkp Pi
m P p¼1
100% Bkp
ð10Þ
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Where, Bp is the evaluation object’s degree of membership on the p evaluation level, k is weighted coefficient, and takes k as 2. When Ap 2 ð8; 10, Ap 2 ð6; 8, Ap 2 ð4; 6, Ap 2 ð2; 4, Ap 2 ½0; 2, it is considered that the system’s safety status evaluation level is respectively as Class I - definitely safe, Class II - safer, Class III - safe, Class IV - dangerous and Class V - definitely dangerous. The safety status of each item is determined according to the graded results calculated by the safety status evaluation grade model.
3 Model Application 3.1
Project Overview
The fuzzy comprehensive evaluation model of safety management was verified with the safety management practice in the Maozhou River Environmental Rehabilitation Project in Shenzhen.
Fig. 1. The Maozhou River
The Maozhou River, as the largest river in Shenzhen, originates from the north of the Yangtai Mountain in Shenzhen. The total length of the main stream is 31.29 km, and the drainage area is 388.23 km2. In the Bao’an District, it covers two administrative areas, Songgang and Shajing, with 19 river surges and a total length of 96.56 km [13], as shown in Fig. 1.
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Along with the progress of reform and opening up and industrialization, the Maozhou River is facing serious problems of water pollution and siltation. The water quality of the main stream and 15 main tributaries are worse than Class V of National Surface Water Environmental Standard, and ammonia nitrogen, total nitrogen and total phosphorus are seriously exceeded. In view of the serious environmental problems in the Maozhou River, the Shenzhen Government commissioned the PowerChina Water Environment Governance Co., Ltd to carry out the comprehensive water rehabilitation work of the Maozhou River Basin (Bao’an district) in 2016. The project is an integrated urban water environment rehabilitation project with a total area of 112.65 km2 in the the Maozhou River Basin (Bao’an district), including the drainage project, the pipeline project, the river comprehensive rehabilitation project, and dredging and sediment disposal project. It is related to the lives of millions of residents, therefore, more requirements need to be placed on safety management on construction site of the urban water environment rehabilitation project [13]. 3.2
Indicator Weight Determination
The safety evaluation index system for the construction site of the urban water envi ronment rehabilitation project is set as U ¼ fU1 ; U2 ; . . .Un g, Ui ¼ Ui1 ; Ui2 ; . . .Uij , Ui is the first-level indicator, and Uij is the secondary indicator. This study determines the subjective and objective weights of safety evaluation indicators for urban water environment rehabilitation project by respectively applying AHP and Entropy weight method, and then calculates comprehensive weight of each index, as shown in Table 4. 3.3
Fuzzy Operation and Fuzzy Comprehensive Evaluation
The evaluation indicators considered are mainly qualitative factors in this study. According to the practical experience of 10 experts and managers, the degree of membership of each factor for the safety evaluation level was determined to construct the membership matrix. The safety status evaluation result of the drainage project, the pipeline engineering, the river comprehensive rehabilitation project and the dredging and sediment disposal project are obtained, as shown in Table 5. 3.4
Result Analysis and Discussion
Using the safety fuzzy comprehensive evaluation model to calculate comprehensive evaluation results of each item, this paper got each item’s safety status evaluation level value, as shown in Table 5, the evaluation level values of the drainage project, the pipeline project, the river comprehensive rehabilitation project and the dredging and sediment disposal project are 7.35,6.68, 6.23 and 6.61. The overall comprehensive evaluation rating of each item is ClassII-safer. Among them, the safety score of the drainage project is the highest, and the safety score of the river comprehensive rehabilitation project is relatively low. The main reason is that the river comprehensive rehabilitation project requires many processes, such as bored piles, gravity retaining
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Table 4. Combination weight for safety evaluation index First-level Indicators
Subjectivity Weight WA
Objectivity Weight WB
Combination Weight WC
Secondary Indicators
Subjectivity Weight wAi
Objectivity Weight wBi
Combination Weight wCi
U1
0.1571
0.2841
0.2206
U2
0.3011
0.2435
0.2723
U3
0.4575
0.2096
0.3336
U4
0.0844
0.2628
0.1736
U11 U12 U13 U14 U21 U22 U23 U24 U31 U32 U33 U34 U35 U41 U42 U43
0.2895 0.0965 0.2047 0.4094 0.4617 0.3038 0.1023 0.1333 0.4252 0.0814 0.2442 0.1074 0.1417 0.5936 0.2493 0.1571
0.1623 0.4261 0.2572 0.1544 0.2953 0.2764 0.1339 0.2944 0.1146 0.0888 0.2952 0.3002 0.2012 0.3343 0.2566 0.4091
0.2259 0.2613 0.2310 0.2818 0.3785 0.2901 0.1181 0.2138 0.2699 0.0851 0.2697 0.2038 0.1715 0.4639 0.2530 0.2831
Table 5. Safe rank comparison of safety assessment results of various projects Project name
Definitely Safe
Safer
Safe
Dangerous Definitely Dangerous
Drainage Project
0.3619
0.3440 0.2715 0.0229
0
Pipeline project
0.2760
0.3047 0.3274 0.0854
0.0044
River Comprehensive Rehabilitation Project Dredging and sediment disposal project
0.1932
0.3253 0.3373 0.1124
0.0321
0.2400
0.3431 0.2907 0.1153
0.0112
Ap
Evaluation Rank
7.35 Class safer 6.68 Class safer 6.23 Class safer 6.61 Class safer
Order
II -
1
II -
2
II -
4
II -
3
walls, ecological retaining walls, and gentle slope embankments, which is difficult to establish standardization and large-scale construction during the construction process. Furthermore, affected by the flood season and surrounding environment, the construction of the river comprehensive rehabilitation project takes a short period of time, and the construction intensity is high, resulting in an increase in the difficulty of management. Therefore, compared with the other types of projects, the management level of the river comprehensive rehabilitation project still has room for improvement. In addition, the actual condition of each type of project is consistent with the evaluation results of the model built in this paper, which shows that the evaluation model is practical and reasonable. From the above results, it can be seen that the overall evaluation of the four types of sub-projects in the Maozhou River rehabilitation project is Class II-safer, and can be concluded that its safety management work on the construction site is done in place. Therefore, the advanced safety management experience adopted in the Maozhou River rehabilitatin project is summarized as follows [13]:
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Setting up a safety education and training experience hall on the construction site. Some of the common safety incidents that may occur at the construction site are materialized so that the construction workers can feel and experience intuitively, and they can have a deeper understanding of the process and consequences of the accident. Implementing QR code safety management system. Everyone on the construction site wears a helmet with a QR code, the QR code is generated by the personal information of each worker, this will be easy to identify and control the safety education and personal basic conditions of workers on the construction site. Using video surveillance system. Managers can keep track of the actual situation on the construction site through video surveillance, realize dynamic management, and enable to carry out remote monitoring and management of the construction site. Using information management tools. A mobile phone APP is developed to realize information management. Workers can keep abreast of all types of information and documents of the construction site by using the APP. In addition, if they find some hidden dangers or accidents, they can use the APP to report to the leadership in time.
4 Conclusions In this study, an index system of safety status evaluation of the fuzzy comprehensive evaluation model was presented in consideration of the characteristics of the construction site of urban water environment rehabilitation project. The evaluation index system included in four first-level indicators of object, human, management and environment, and sixteen secondary indicators such as safety control, safety protection for mechanical equipment and monitoring equipment. Then the model was verified with the safety management practice of the Maozhou River rehabilitation project. The weight of each evaluation index was determined by AHP and entropy weight method and each item’s safety status evaluation level value was determined by the fuzzy comprehensive evaluation model. The result shows that the safety fuzzy comprehensive evaluation model has certain scientificity and practicability in the safety status evaluation of the construction site of urban water environment rehabilitation project, which can provide a certain reference for the safety management evaluation of the construction site of urban water environment rehabilitation project and improve the safety management level of urban water environment rehabilitation project. In order to carry out more effective safety management, the following measures should be executed: (1) Implementing incentive system. If the project safety managers can comprehensively and accurately predict the safety hazards on the construction site, the probability of safety accidents will be greatly reduced. Corporate leaders can combine safety performance with the salaries of managers, and implement incentive systems that can stimulate project safety managers to efficiently complete management tasks.
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(2) Strengthening the control of on-site machinery and materials. Comprehensive safety management of mechanical and equipment should be implemented, from procurement to operation and retirement. The materials entering the construction site must be strictly controlled and checked for a series of certificates such as the factory certificate and the factory acceptance report. In addition, new materials must be equipped with corresponding instructions before entering the site, and provided the qualified acceptance review of the new material. (3) Standardizing safety management. For each project, it should establish a sound safety management system, all workers see this system as a standard, and make it involves safety production responsibility system, safety technical measures management methods, safety accident management methods, emergency management methods, safety production assessment management methods, safety production training methods and other aspects. According to various safety management systems, all tasks can be promoted smoothly. Also they can prevent works from arbitrarily simplifying the affairs according to subjective wishes, which can reflect the superiority of standardized management. (4) Strengthening environmental protection. In order to ensure the safety of pedestrians and vehicles around the construction site, safety signs and warning signs should be set up in places where dangers are likely to occur. In addition, in response to the phenomenon of strong winds, heavy rain, lightning, floods, etc., we must take precautions at all times and strive to minimize the losses caused by the environment. Acknowledgments. The research was supported by Fund of the PowerChina Water Environment Governance Co., Ltd. for Study on Quality, Safety and Environmental Management of Urban Water Environment Rehabilitation Projects (Contract No. SHJ-JY-2017-024).
References 1. Rozenfeld, O., Sacks, R., Rosenfeld, Y., et al.: Construction job safety analysis. J. Safe. Sci. 48(4), 491–498 (2010) 2. Deviren, M., Ksel, M.: Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management. J. Inf. Sci. 178(6), 1717–1733 (2008) 3. Leu, S.S., Chang, C.M.: Bayesian-network-based safety risk assessment for steel construction projects. Acci. J. Anal. Prevent. 54(2), 122 (2013) 4. Li, X., Lai, J.Y.: Safety evaluation of building construction based on catastrophe progression method. J. Fujian Agri. Forest. Univ. (Natl. Sci. Ed.) 41(5), 557–560 (2012) 5. Chen, Z.Y., Zhou, L.J., Yang, S.Q., Ruan, C.F.: Application of fuzzy entropy weight in construction safety evaluation. J. Ind. Safe. Environ. Protect. 11, 56–58 (2008) 6. Zhao, J., Zang, Y.P., Zhang, L., Xu, X.D., Wang, L.C., Wu, H.: Water environment safety evaluation based on fuzzy comprehensive evaluation——taking nanjing city as an example. J. Jiangsu Water Conserv. 12, 4–11 (2016)
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7. Passino, K.M., Yurkovich, S.: Fuzzy Control. Addison Wesley, Menlo Park (1998) 8. Li, N., Huang, W., Chen, Y., Liu, J., Bu, Z., Luo, K., Guan, S.: Total Safety Management Practice in an Urban Water Environment Rehabilitation Project. In: CRIOCM2018 23rd International Symposium on Advancement of Construction Management and Real Estate, Guiyang, 24–27 August (2018) 9. Saaty, T.L.: Analytic Hierarchy Process. McGraw Hill, New York (1980) 10. Shannon, C.E.: A mathematical theory of communication. J. Bell Syst. Tech. J. 27(4), 379– 423 (1948) 11. Tian, L.G., Ma, C.G., Wang, X.: Fuzzy evaluation of owner risk of water conservancy projects based on AHP-entropy weight method, J. Yellow River, 39(12),117–122+130 (2017) 12. Zhang, M.X.: Research on the Influencing Factors and Evaluation Models of Safety Management in Construction Projects, China University of Mining & Technology (Beijing) (2009) 13. Shenzhen University. Report to the Study on Quality, Safety and Environmental Management of Urban Water Environment Rehabilitation Projects, Shenzhen (2018)
Total Safety Management Practice in an Urban Water Environment Rehabilitation Project Na Li1, Weidong Huang2, Jian Liu3(&), Yunchu Chen2, Zengwen Bu4, Kejun Luo2, and Shujie Guan2 1
2
4
College of Civil Engineering, Shenzhen University, Shenzhen, China [email protected] PowerChina Water Environment Governance Co., Ltd., Beijing, China 3 Ecological Technology Institute of Construction Engineering, Shenzhen University, Shenzhen, China [email protected] Shenzhen Cenpoint Architects & Engineers Co., Ltd., Shenzhen, China
Abstract. Considering the characteristics of the safety management of urban water environment rehabilitation project, a new total safety management model, Search-Tell-Check-Control (STCC) was proposed in this study. STCC was used in the safety management of the Maozhou River Rehabilitation Project in Shenzhen. The hazard sources of the construction site of the Maozhou River Rehabilitation Project were identified by the Fishbone diagram. AHP was used to analyze the four major causes of safety accidents during the construction. The result shows that management factors have the greatest impact on safety among the four factors of objects, people, management, and environment. Keywords: Safety management Water environment Fishbone diagram Search-Tell-Check-Control
Hazard source
1 Introduction With the rapid development of social economy and the intensification of human activities, china is facing a serious problem of water pollution. Deterioration of water environment has become a major constraint on the sustainable development of social economy. In response to these problems, china has formulated and implemented a series of policies, such as the “Water Pollution Prevention Action Plan”, “Guidelines for the Urban Black-smelly Water Remediation Work” and “Opinions on the Full Implementation of the River Chief System”. Water environment rehabilitation projects are totally different from traditional engineering projects. They always involve wide range and various types of projects, complicated technology, difficult operating conditions and last for a long period, resulting in increase of the risk of construction and the possibility of accidents during construction, all of these emphasize the importance of safety. Therefore, we must actively control and strengthen safety management to reduce the occurrence of security accidents and achieve the purpose of effectively avoiding risks. The key to preventing accidents is to figure out the mechanism of accidents, identify the inevitable and © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 353–364, 2021. https://doi.org/10.1007/978-981-15-3977-0_26
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accidental causes of accidents, then minimize the probability of accidents by eliminating inevitable causes and scientifically controlling accidental causes. In this study, the total safety management practice in the Maozhou River Rehabilitation Project was described by introducing a new total safety management model, Search-Tell-Check-Control (STCC).
2 The Maozhou River Rehabilitation Project As the largest river in Shenzhen, the Maozhou River originates from the north of the Yangtai Mountain in Shenzhen, the total length of the main stream is 31.29 km, and the drainage area is 388.23 km2. The Guangshen Highway to the Maozhou River estuary is the border river between Shenzhen and Dongguan. It flows from the southeast to the northwest of Shenzhen through Shiyan, Gongming, Guangming Farm, Songgang, Shajing, then it enters the Zhujiang Estuary in the Shajing Democratic Village. The location of this area is shown in Fig. 1. In recent years, the pollution of the water bodies in the Maozhou River Basin is serious. The water quality of dry tributaries is worse than V-type of National Surface Water Environmental Standard, and the water ecological environment needs to be improved urgently.
Fig. 1. Location of maozhou river
In view of the serious environmental problems in the Mazhou River, the Shenzhen Government commissioned the Power China Water Environment Governance Co., Ltd to carry out the comprehensive water rehabilitation work of the Maozhou River Basin (Bao’an district) in 2016. The project is an integrated water environment rehabilitation project with a total area of 112.65 km2 in the Maozhou River Basin (Bao’an district), including the drainage project, the pipe network project, the river comprehensive rehabilitation project, and dredging and sediment disposal project, total investment of
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the project is 15.2 billion yuan. It is related to the lives of millions of residents and is a comprehensive project that benefits people’s livelihood. Therefore, more requirements are placed on safety management [1]. This paper discusses the safety management practices of the Maozhou River Rehabilitation Project.
3 Search-Tell-Check-Control 3.1
Concept of STCC
According to the unique characteristics of water environment treatment project safety management, a new total safety management model, STCC (search-tell-check-control), is put forward based on the classic PDCA cycle and 5S management method. It is generally divided into four steps to implement. First is search stage, which means actively collecting security management data, conducting safety analysis, then formulating safety measures. The second is tell stage, informing all personnel of hazard factors and safety management measures in advance. The third is check stage, the security managers should regularly check the safety hazards on the construction site and find problems as soon as possible before safety accidents occur. The forth is control stage, taking risk control measures is to eliminate the adverse consequences of potential accidents as much as possible. In the safety management activities, in accordance with the STCC cycle, the success method or experience is incorporated into the safety management standard, and unsuccessful step is left for the next cycle to be solved. The process of the STCC cycle is shown in Fig. 2.
Search
Tell
NO
Check Control
Under control?
YES
Experience standardization
Fig. 2. STCC management model
3.2
Steps of STCC Cycle
As is shown in Fig. 2, the new total safety management model has four steps, the concrete work of these four stages are summarized as follows.
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3.2.1 Search: Actively Collect Safety Management Information Searching information is the most important step in security management. Managers need to actively collect daily data on the construction site, analyze and sort out safetyrelated data and grasp the safety conditions at the scene. Safety is a concept of fuzzy mathematics, there is neither absolute safety nor absolutely danger [2]. According to fuzzy mathematics, danger is a membership grade of safety, when the risk is reduced to a certain degree, it can be considered safe. The relationship between the two is expressed in Eq. (1). Therefore, research on safety can be transformed into research on sources of danger. S¼1D
ð1Þ
where, S is safety; D is danger. The KYT theory can be adopted to identify major hazards, then analyze all unsafe factors that may exist on the construction site and the triggering factors of each type of hazard, distinguish main and secondary causes, find out the main hazards, conduct safety assessments, and formulate safety measures in advance. KYT (Kiken Yochi Training) originated from the factory of Sumitomo Metal Industries Co., Ltd. in Japan, and was later promoted by “All-Participant Safety Campaign” launched by the Mitsubishi Heavy Industries Corporation and Nagasaki Shipyard. It has been developed technical methods widely used throughout the company [3]. The KYT management model aims to improve the level of corporate security management, control the occurrence of various types of accidents, and improve employees’ self-protection capabilities and awareness. The safety assessment of the identified hazards is performed, and effective control measures and management plans are formulated accordingly. 3.2.2 Tell: Conduct Safety Education and Training In the first stage, we have already made predictions on possible dangerous sources. In the second stage, we should inform safety management methods to the on-site construction personnel from top to bottom, such as the implementation of safety responsibility rules, engineering safety management system, and on-site personnel safety management, responsibility and specific division of labor, engineering safety delivery book, safety control at each stage of control points, stop points and a series of safety management related systems, norms, operating points. What’s more important is to carry out safety education for on-site employees, conduct regular safety training, strengthen the safety awareness of operators, and promote safety culture. 3.2.3 Check: Inspection of On-Site Production Activities Safety managers should regularly go to the construction site to inspect safety production activities and review the implementation of safety management activities and measures in the preceding stages. This is a relatively important stage of the cycle. The purpose is to find out the difference between the actual operation and the expected effect in the construction process, which is helpful for managers to take measures to control the accident in the early stage of germination. From this process we can see that
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the STCC management model has dynamic and feedback, which is similar to the traditional dynamic control principle in the progress control of engineering projects. 3.2.4 Control: Keep Security Issues Under Control The final step is to reduce or eliminate the unsafe behavior or state of production factors through the specific state control of production factors, without causing security accidents. Then managers should to summarizes and evaluates the safety management experience and lessons learned in stages, consolidates existing achievements, handles errors, transfers unresolved issues to the next management cycle as the safety information to ensure the realization of the benefit objectives of the project.
4 Hazards Risk Assessment and Accident Prediction Model Hazard sources are the premise of safety accidents in water environment rehabilitation projects and the energy subjects of safety accidents, it’s also the first step in STCC security management model. Only by identifying various energetic substances and behaviors in the production process, analyzing these energy conversion processes, conversion conditions and triggering factors can we control the energetic substances and behaviors from overflowing and losing control and prevent the dangerous sources from being converted into accidents. Therefore, the identification of hazard sources, risk assessment and accident prediction on the construction site are important prerequisites for construction enterprises to improving the level of safe production management. The process is shown in Fig. 3.
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Fig. 3. Hazard identification, risk assessment and accident prediction process
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Causes of Accidents on the Construction Site
Hazard identification is a process of using scientific methods to conduct research and comprehensive analysis of the nature of potential risk factors, trigger factors, possible consequences and severity of the production process, making scientific judgments, and providing reliable control of safety accidents. Because of the nature of a potentially insecure source of hazards, the identification of hazards requires an objective and
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thorough scientific study of the entire system. The job of identifying hazard sources is to identify the source of the hazards through comprehensive analysis, determine the conditions at which the hazards occur, describe the characteristics of the hazards, and determine the degree of impact of the hazards. Further correspond to the requirements of safety management standards and related laws and regulations, determine whether the potential hazard source has reached the requirements of the relevant standards, whether it has been effectively controlled, and achieve the purpose of avoiding safety accidents from the source. According to the characteristics of the construction site, through the continuous understanding of the theory of accident causes, the fishbone diagram method is used to analyze the incentives that may lead to safety accidents during construction of the water environment. Four factors for the occurrence of safety accidents in the construction of water Environment rehabilitation projects, shown in Fig. 4.
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Management Lack of safety education Insufficient safety investment Insufficient management system Wrong decision-making by managers
Physical defect Lack of safety awareness Violation of production laws Insufficient technical capacity Safety
Chemical factors Physical factors Biological factors Geographic factors
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Fig. 4. Fishbone diagram analysis of the causes of accidents on construction sites
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Safety Evaluation on the Construction Site
The safety assessment of hazard sources is to analyze the dangers and possible harm consequences and degrees of the system, and then develop effective control measures and management schemes to improve the safety management level. Risk is the composition of the probability and consequences of a particular dangerous situation. The risks and dangers are related to the possibility of the potential status becoming a reality. Since the danger from the potential state to the reality must be stimulated, the risk is related to the frequency, intensity, and duration of the triggering time. Evaluating the risk that a hazard may bring can be more intuitive to describe the hazard. The purpose of risk assessment is to evaluate and classify the risks brought about by the dangerous sources in the organization stage, and carry out targeted risk control according to the results. In order to ensure the rationality of safety assessment, based on the characteristics of the water environment rehabilitation construction project, the analytic hierarchy process (AHP) was used to evaluate the factors that affect the construction site safety of the Maozhou River rehabilitation project [4]. Its core principle is to use
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the fuzzy index quantification method to derive the relative importance of the two or more criteria in the hierarchy, and to replace the complex decision-making system with an interrelated hierarchical model, so as to determine the weight of each indicator in the program optimization decision [5]. 4.2.1 Evaluation Factors System Based on the analysis of the causes of safety accidents on construction sites in the previous step and the results of the questionnaires, an index system of safety evaluation including four first-level indicators of objects, people, management, and environment, and 16 secondary indicators impacting on construction site safety assessment of the Maozhou River rehabilitation project was established, shown in Table 1. Table 1. Evaluation factors for AHP method Construction site safety evaluation index system
Objects (U1)
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Environment (U4)
Safety control of machinery (U11) Safety protection and monitoring equipment (U12) Equipment inspection and maintenance (U13) Material quality (U14) Security awareness of people (U21) The quality of people (U22) Technical level (U23) Construction procedures (U24) Implementation of safety regulations (U31) Setup of safety management organization (U32) Safety education and training (U33) Safety inspection and accident handling (U34) Safety investment (U35) Natural environment (U41) Construction environment (U42) Living environment (U43)
4.2.2 Results and Discussion In order to ensure the evaluation results being scientific and objective, 10 experts including managers of safety and environmental protection department as well as experienced project managers, engineers, construction managers, technical managers, and supervision engineers at the construction site engineering department were invited to determine to weight of each indicator. The average of the 10 experts is used as the
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final score of each indicator. Based on this result, a level analysis is performed to determine the weight assignments of the two indicators. At the same time, a consistency check was performed on the weighted results to prove the reliability of the results. The assessment results are shown in Fig. 5.
0.5 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0
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Fig. 5. Results of AHP assessment
As is shown in Fig. 5, management factor accounts for the largest proportion in this case study, followed by people factor. Therefore, accidents in this project is more likely to be caused by management defects. The results can be used as a scientific basis for project managers to take measures. Based on the results, the managers need to focus on strengthening the implementation of management measures to avoid the occurrence of safety accidents. 4.3
Accident Prediction Model Based on BP Neural Network
From the above analysis, we can know that the factors affecting the security situation in this project can be summarized into four categories, including people, objects, environment, and management. These factors also include several sub-factors that are related to each other. The accident prediction model on the construction site can establish a BP neural network prediction model through the comprehensive system of safety prediction composed of the 16 factors, and the artificial neural network based on time series can be applied to accident prediction to avoid complex mathematical derivation process. The model can be used to predict accidents by investigating past accidents. This section describes the method. BP neural network is a kind of artificial neural network consisting of input layer, hidden layer, and output layer. The BP algorithm consists of two parts, the forward propagation of information and the back propagation of errors [6]. In the forward propagation process, information is passed from the input layer to the output layer, processed by the hidden layer. If the output does not match the desired output, it goes to the back-propagation phase of the error, sending the error signal back along the original connection path to modify the weights of the neurons at each layer. This is a
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repeated process until the error of the network output is reduced to an acceptable level, or until a preset number of learning’s. Assigning the previously defined inputs to trained models can be used for accident prediction. Through the analysis of the factors that affect accidents, combined with the comprehensive index system of accident prediction for construction projects established in the previous step, the above 16 prediction index systems are used as inputs of BP neural networks to construct an accident prediction model for water environment treatment projects, so the number of neurons in the input layer is N = 16. The output is the number of casualties, so the number of neurons in the output layer is L = 1. There is only one hidden layer, the number of neurons in the hidden layer can be determined by the empirical formula Eq. (2). The hidden layer activation function takes the Sigmoid function, shown in Eq. (3). The output layer activation function takes a linear function. M¼
pffiffiffiffiffiffiffiffiffiffiffiffi N þLþh
ð2Þ
where, M is the neurons number of hide layer; N is the neurons number of input layer; L is the neurons number of output layer; h is a positive integer with a value ranging from 3 to 7. fðxÞ ¼ 1=ð1 þ ex Þ
ð3Þ
In this case, the calculated value of M is 8. Therefore, the three-layer BP network structure diagram of accident prediction is obtained, as shown in Fig. 6 above. The specific calculation process can be realized by programming, which is omitted here. 4.4
Pre-control Measures for Security Accidents
The previously analyzed hazard identification and safety assessment can be a powerful support for managers to make decisions. The effective method of controlling security accidents is to prevent problems before they occur, that is, to use “pre-control” solutions to eliminate hidden dangers and insecure factors in the initial stage. According to the analysis results of the previous AHP assessment, the project team has taken some measures from the management and people factors to strengthen comprehensive safety management [7]. 4.4.1 QR Code Security Management System The company has developed a two-dimensional code security management system. The QR code logo is made of a car sticker with a size of 3 3 cm, and it is attached to the top of the helmet. Through the QR code management system, the project management staff of the project office inspects the safety education and personal basic information at anytime and anywhere by scanning the code on the helmet of the operator. A QR code that contains all the information of the operator is created for each
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People factors
Objects factors Casualties Environment factors
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Fig. 6. BP network structure
worker through a code system. Each bid must ensure that the code can be identified by a smart phone in order to obtain open information. 4.4.2 Video Surveillance System In addition to the QR code security management system, a video surveillance system also is adopted to improve the level of security management. Video surveillance system refers to the collection of video signals at the construction site transformed to the company’s video surveillance center through the network and information processing to achieve 24-h uninterrupted remote monitoring and video on the construction site. At the same time, through the video monitoring system, the basic situation of the construction site, the change of image progress, the safety dynamics of the project construction and the control of major hazard sources can be reflected in a timely manner so as to realize multi-level remote network monitoring and management of the construction site. 4.4.3 Building an Information Management Platform In terms of security management, the company attends to use “control security” APP for security management. Each security manager and operator are required to install the “controlling security” APP on their mobile phones and follow relevant regulations and procedures to ensure daily safety. The “controlling security” APP will integrate existing resources, including video surveillance systems, vehicles, personnel positioning systems, etc. Besides, five major special libraries, such as laws and regulations, emergency plans, emergency resources, early warnings, and typical accident cases will also be built. With the weather forecast at any time to grasp, timely notification notice received, view; laws and regulations, emergency plan online preview; hidden reporting,
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rectification, timely processing; immediate incident response, integration of on-site and surrounding security emergency resources and other functions. For safe construction and emergency disposal, efficient and convenient management methods are provided to improve work efficiency. The system will have the following functions that can provide efficient management methods for construction and emergency disposal and improve work efficiency. (1) Master the weather forecast, receive and check notification in time; (2) Browse laws, regulations and emergency plans online; (3) Report and handle safety hazards in time; (4) Immediate response to accidents, integration of on-site and surrounding security emergency resources. 4.4.4 Strengthening Safety Education and Training According to the previous analysis results, the lack of safety awareness is one of the important causes of accidents. Therefore, it is necessary to conduct safety education and training so as to improve the professionalism of the operators. Especially in recent years, with the constant emergence of new technologies and new equipment, the technical quality requirements of the front-line operators have been continuously improved, but the reality is completely incompatible with the situation. In particular, migrant workers are weak parts in the work safety education and training of China’s construction companies [8]. There are many reasons for this situation. The first is that the level of cultural knowledge of migrant workers is low, the ability to accept is poor, and their acceptance of new technologies is insufficient. Second, migrant workers are more mobile. The company mainly carried out training for construction workers, technical director, security officer and managers, mainly including safety production ideological education, safety knowledge education, safety skills education, and assessment according to relevant national laws and regulations.
5 Conclusions A new total safety management model, STCC cycle was put forward as combined with the actual safety management of the Maozhou River rehabilitation project. Based on the new STCC management model, intensive research is mainly focused on hazard identification and evaluation on the construction site in the search stage. A safety evaluation index system including four primary indicators of objects, people, management and environment, and 16 secondary indicators was constructed. The results of the AHP analysis indicated that the management factor had the most important influence on the safety of the construction site. Therefore, management measures should be emphasized for accident prevention. Finally, the control measures and safety management experience of this project were generalized for other similar projects as a reference.
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Acknowledgments. The research was supported by Fund of the PowerChina Water Environment Governance Co., Ltd. for Study on Quality, Safety and Environmental Management of Urban Water Environment Rehabilitation Projects (Contract No. SHJ-JY-2017-024).
References 1. Shenzhen University: Report to the Study on Quality, Safety and Environmental Management of Urban Water Rehabilitation Projects, Shenzhen (2018) 2. Smith, S.D., Carter, G.: Safety hazard identification on construction projects. J. Constr. Eng. Manage. 132(2), 197–205 (2006) 3. Wang, X., Yu, Z., Wang, T., Liu, J., Bu, Z., Ru, L.: Developing a safety fuzzy evaluation model ofor safety management for urban water environment rehabilitation project (2018) 4. CRIOCM2018 23rd International Symposium on Advancement of Construction Management and Real Estate, Guiyang, August 24–27 (2018) 5. Al-Harbi, A.S.: Application of the AHP in project management. Int. J. Project Manage. 19(1), 19–27 (2001) 6. Lin, J., Yao, S., Di, J.: Financial security evaluation in power production industry based on BP neural network optimized by genetic algorithm. In: International Conference on Automation, Mechanical Control and Computational Engineering (2015) 7. Liu, R.: Research on Hazard Source Identification and Safety Evaluation of Construction Site of Water Environment Treatment Project. Shenzhen University, Shenzhen (2018) 8. Chunhai, S.: On the necessity and ways of carrying out construction safety education and training. Building Safety 21(11), 54–56 (2006)
Application of Causal Analysis Method in Quality Management of the Maozhou River Rehabilitation Project Min Dong1, Huaxiang Zhao2, Kejun Chen2, Xiaoling Qin1, Jian Liu3(&), Gang Wang1, and Jun Wang2 1
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College of Civil Engineering, Shenzhen University, Shenzhen, China [email protected] PowerChina Water Environment Governance Co., Ltd., Beijing, China 3 Ecological Technology Institute of Construction Engineering, Shenzhen University, Shenzhen, China [email protected]
Abstract. This paper addresses the total quality management experience of the Maozhou River Rehabilitation Project in Shenzhen, China. The causal analysis method was introduced from six factors of man, machine, material, method, environment and measurement. The causes of the construction quality problems were analyzed and the level of the project quality management was improved duo to double quality management and new technology use. Keywords: Rehabilitation Causal analysis method Quality management The Maozhou River
Fishbone diagrams
1 Introduction The Maozhou River is the largest river in Shenzhen, originating from the north of the Yangtai Mountain in Shenzhen. The total length of the main stream is 31.29 km, and the drainage area is 388.23 km2. In the Bao’an District, it covers two administrative areas, Songgang and Shajing, with 19 river surges and a total length of 96.56 km [1]. Along with the progress of reform and opening up and industrialization, the Maozhou River is facing serious problems of water pollution and siltation. The water quality of the main stream and 15 main tributaries are worse than Class V of National Surface Water Environmental Standard, and ammonia nitrogen, total nitrogen and total phosphorus are seriously exceeded. In view of the serious environmental problems in the Mazhou River, the Shenzhen Government commissioned the PowerChina Water Environment Governance Co., Ltd to carry out the comprehensive water rehabilitation work of the Maozhou River Basin (Bao’an area) in 2016. The comprehensive rehabilitation works mainly include pipe network engineering, drainage engineering, river regulation engineering and water quality improvement engineering. The whole rehabilitation project adopts EngineeringProcurement-Construction model.
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 365–375, 2021. https://doi.org/10.1007/978-981-15-3977-0_27
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Compared with the general construction projects, the quality management of the Maozhou River rehabilitation project has the following characteristics: There are multiple sub items, implementation procedures in this project, and exist changeable conditions, extensive involvement, and complicated cooperation relations. Project quality involves safety, applicability and cost control, have strong concealment and difficulty of evaluation. After completion of construction, the internal quality of the project cannot be tested by simple disassembly or destructive inspection as other industrial products. This paper discusses the quality management of the Maozhou River Rehabilitation Project.
2 Quality Management of the Maozhou River Rehabilitation Project In response to the characteristics of the quality management of the Maozhou River, PowerChina Water Environment Governance Co., Ltd has strictly followed the thought of PDCA (plan - do - check - action) and total quality management (TQM) in the process of project management. Informationization and grid quality management, quality responsibility tracing system, factory supervision system, model introduction system, CCTV pipeline inspection are employed to heighten the management level. The management process is divided into the three stages of pre-control, in-process control, and post-control. The six elements of man, machine, material, method, environment and measurement are under key control. Through this comprehensive and multi-level management, the project quality management level has been significantly improved. At the same time, the PowerChina Water Environment Governance Co., Ltd implemented “Double Quality Management”, which was managed and controlled by both the project department and the platform company. This Double Quality Management solved problems such as inefficient communication and delayed coordination in the past, made the objectives and instructions clearer, and made the execution more efficient. The timely quality inspection and feedback ensure that the quality objectives are achieved, greatly improving the reliability of quality management. The highly institutionalized and streamlined process between the two levels makes the communication objects and processes clearer. Through information communication and close cooperation, it achieves high-efficiency self-control and monitoring at the internal management and control level, which enables the PDCA to operate in a closed loop and improve communication quality.
3 Application of Causal Analysis Method Causal analysis method is a method of making predictions based on the causal relationship between the development and change of things. By grasping the relationship between the main contradiction and the secondary contradiction, established a mathematical model to predict. The deliverable of causal analysis method is the causal analysis diagram.
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In a causal analysis diagram, the various causes are grouped into categories and the causes cascade from the main categories, flowing towards the effect, forming what resembles a fishbone appearance, so it is also called fishbone diagram. The fishbone diagram is a simple root cause analysis tool that is used for brainstorming issues and causes of particular problems and can and often is used in conjunction with the 5 Whys tool. Fishbone diagrams are great for analyzing processes and identifying defects in them. They are a great way to visualize causes and their effects [2]. In the quality management of water rehabilitation projects, a large number of project quality analysis and quality evaluation problems are often encountered. The causal analysis method can clearly express the relationship between the causes and the results, and turn the analyzed problems into structural graphics that is very intuitive and clear (Fig. 1). Through causal analysis diagram to analysis and control construction quality, equivalent to control the six factors: man, machine, material, method, environment and measurement, to achieve the goal of qualified quality. Six factors are “causes”, and quality is “result”. Pre-control and active control can be achieved through this method.
Fig. 1. Factors affecting project quality
From the above causal analysis diagram, we can clearly see six factors: man, machine, material, method, environment and measurement, which affect the quality of engineering. There are many reasons for each factor. Therefore, we can take the remedy to the case and take effective measures, eliminate or reduce quality problems and accidents to a minimum. 3.1
Personnel Management
As the biggest factor affecting the quality of engineering construction, the rational and effective management of personnel quality is of utmost importance. People are the most active and unstable factors in quality control, for they are both the main body and the controlled objects in control procedure. As the main body, we should fully mobilize the enthusiasm of people and play the leading role of them. As a controlled object, we should avoid making mistakes as much as possible [3].
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Establish a Sound Post Responsibility System
Post responsibility system is the basis of comprehensive, whole process and all staff quality management. Only by establishing a sound post responsibility system, clearly defining the responsibilities of each post and avoiding the phenomenon of shirk responsibility can we reduce the quality problem from the source. The post responsibility system of the construction quality management should include the management responsibility of project manager and project technical officer, the supervision responsibility of quality personnel, and the direct responsibility of construction staff. 3.3
Staff Education and Training
The construction quality depends on good quality of the relevant personnel, and the improvement of quality lies in education, especially the managers and operators who play a key role in quality management [4]. The purpose of education and training is to enhance quality awareness, standardize quality behavior, and improve project quality. With the constant emergence of new technologies and the constant updating of standards, training should be a continuous process. Through continuous training, it is possible to raise the level of knowledge of relevant personnel, as well as to sum up previous experience and lessons, and finally achieve the goal of improving the level of quality management. The training in the construction process is divided into general training and special technical training. The content mainly includes the quality control of the key locations, key processes, and special processes. The general training should do the following work: implement the quality education and training deployment of relevant personnel of the project headquarters, communicate and train the quality management personnel, key position personnel and labor personnel of each subcontractor; during the construction process, master the key measures or inspection standards of the project quality control and the common problems of quality management; study and implement new standards, new specifications, and “four new” technologies (new technologies, new processes, new materials and new equipment); carry out technical training before and during the post for special work and engineering professional work, and timely solve the practical quality control problems in the field. For the water rehabilitation project, special technical training includes testing training and pipeline CCTV inspection training. In addition, the one-month quality month activity held in September each year is also an important activity and measure to increase employees’ quality awareness. 3.4
Personnel Qualification Management
All construction teams who undertake construction tasks in the project department must have valid qualification certificates and have complete admission procedures. Before entering the venue, staff qualification declaration forms and relevant supporting documents must be prepared, and all obligations stipulated in the contract must be strictly observed.
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The entry personnel must remain relatively stable, and various types of work must be supported. According to the progress of the project, sufficient labors are ensured to meet the needs of production. 3.5
Construction Machinery Management
Machinery generally includes construction machinery equipment and production machinery equipment. The water rehabilitation project is generally based on construction machinery equipment. Construction machinery and equipment is the material basis for the implementation of construction projects and is an indispensable equipment for modern construction. The selection of construction machinery and equipment should implement the principles of application, advanced and reasonable, and combine the layout of the project, structure type, construction site conditions, construction procedures, construction methods and construction techniques, to control the choice of construction machinery type, main performance parameters and the use of machinery, set up corresponding operating system and strictly implemented. The performance of construction machinery will affect the worker’s efficiency, psychology and work quality, and will also have a certain impact on the quality of the engineering entity. At the same time, the quantity and quality of construction machinery inputs reflect the performance capacity, construction strength and construction level of construction companies. Construction companies should encourage use new technologies and new machinery to increase construction efficiency, ensure construction quality, and reduce construction disturbance to the surrounding environment. For example, soils in soft soil areas have “three high, three low” characteristics: high water content, high void ratio, high compressibility, low bearing capacity, low shear strength, low permeability coefficient, which have brought a lot of impact to the project construction. In view of this situation, the static pile pressing machine can be used to push the pile body slowly (as shown in Fig. 2), which is low noise, no vibration, no pollution, and can show the pile resistance, easy to guarantee construction quality.
Fig. 2. Construction by static pile pressing machine
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Material Management
The materials include various pipes, steel materials, cements and various finished products, semi-finished materials used in construction projects. The material is the material basis of the project and it is an integral part of the engineering project entity. Qualified materials are the premise and basis for guaranteeing the quality of project construction. In order to regulate the quality management of raw materials, the quality of the project should be controlled from the source, and the phenomenon of using unqualified materials in project construction should be eliminated. Pipes are the most common materials in the water rehabilitation project and are the key link in quality control. 3.6.1 Material Selection Before the official start of construction, we should select the best raw material suppliers and strictly control the material supply channels. In order to ensure quality, the material bidding customization system can be carried out when necessary, that is, the relevant technical parameters of the material are clearly defined in the project bidding documents, as well as the requirements of production capacity, scale, quality inspection ability and credentials of material suppliers. In the bidding stage of raw materials, the quality requirements of materials are raised, and raw material technical indexes higher than the national standard are proposed to exclude the errors that produced by the instability of production process, thoroughly eliminate the unqualified raw materials. 3.6.2 Factory Supervision System When purchasing the main materials (such as pipes), company can carry out factory supervision system, strengthen the quality control of the main raw materials, intermediate products and finished products used in the material production process. The factory supervisors shall check the quality certification materials such as the material factory qualification certificate, performance inspection report and user manual, as well as the basic information such as the factory quantity and delivery time. Before leave factory, supervisor shall sign and confirm those informations. In this way, not only can realize the whole process and all-round quality control of materials, but also ensure the material production and delivery quality. 3.6.3 Material Storage The necessary material identification plates shall be set up for the on-site storage of materials. Material should be stacked in a flat, solid site with no accumulated water and have sufficient carrying capacity. The stacking must be stable to prevent rolling, sliding, collapse, and stacking height is in compliance with relevant requirements. In the process of custody, handling, lifting and installation of materials, necessary protective measures shall be taken, in particular the protection of the pipe spout, so as to avoid material damage, rust or deterioration. The material breakdown caused by improper storage or handling, hoisting and installation in the course of construction should be cleared out of construction site in time to prevent the occurrence of hidden quality
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Construction Methods and Management Measures
3.7.1 Construction Method The construction method mainly refers to the construction organization design, construction scheme, construction technical measures and construction technology of the project. The construction method directly influences the quality formation of the project and whether the construction scheme is reasonable, which not only affects the construction quality, but also has an important impact on the construction progress and cost. Therefore, in the process of quality management, we should combine with the actual situation of the project, from the aspects of technology, organization, management, economy, etc., to conduct a comprehensive analysis and argument. This method can ensure the construction scheme is technically feasible, economically rational, advanced and easy to operate, which can not only guarantee the quality of project items, but also speed up construction progress and reduce cost. 3.7.2 Management Measures According to the quality policy of water rehabilitation project and the overall quality goals of construction projects, and on the basis of relevant laws and regulations, the construction project should establish quality management system which conforms to the characteristics of project, set up professional management department and personnel, effectively manage the construction quality according to the PDCA (plan-docheck-action.). The “quality management measures” shall beprepared, and project management department implements them strictly, formulate examination methods for quality assessment, and carry out on-site inspections regularly and irregularly. Strengthen the training of business personnel to better adapt to the water rehabilitation project management model. 3.8
Environmental Management
During the construction of the project, environmental factors are constantly changing, such as temperature, humidity, precipitation and wind force. The former process provides the construction environment for the latter process, and the environment of the construction site is also changing. The changing environment will affect the quality of the project to varying degrees. There are many environmental factors that affect the project, which can be summed up in two aspects as follows: (1) Engineering natural environment. The environmental factors considered during the construction mainly refer to the natural environment of the project. It mainly includes engineering geology, topography, hydrogeology, engineering hydrology, meteorology and other factors. These factors are complex and changeable, which have great influence on the construction quality of the project. For example, engineering geology and hydrology affect the quality of foundation pit construction. High temperature weather not only affects the performance of concrete and other materials, but also affects the safety and health of construction workers. In summer, the eastern region is a typhoon prone area. It is necessary to pay attention to the drainage of foundation pit ditch, protection of slope, waterproof treatment of materials and semi-finished products, and emergency evacuation of personnel.
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(2) Engineering management environment. Engineering management environment mainly refers to the quality management system, labor environment and so on. One of the conditions for effective control of quality management is the guarantee of system. The basic work of quality management is the quality management system, including the establishment, perfection and implementation of system. The main quality management systems include education training system, model introduction system, quality inspection system, construction technology disclosure system, etc. The working environment includes labor combination, labor tools, the working area of the construction environment, underground pipeline adjacent to the project, the protective facilities, ventilation, lighting and communication conditions of buildings or structures, etc. These are the guarantee that the operator can work normally. To improve the management environment, enterprises need to adjust the management department, clearly specify the responsibilities and authorities of the relevant management departments, ensure that the functions of the enterprise management department are set up, actively use advanced management methods, formulate system management mechanisms, guarantee the project management also varies according to the construction conditions. Comprehensively implement the quality management system, so as to continuously improve management results. 3.9
Test and Inspection
In order to strengthen quality control, self-inspection, mutual inspection and special inspection should be carried out for the raw materials, semi-finished products, quality control process and the quality of engineering entity in the process of construction. The quality inspection and supervision activities also shall be fully involved. 3.9.1 Establish “Three-Level Inspection System” Establish a three-level self-inspection system for working team, full-time quality inspectors and manager department, and adhere to the three-level inspection system combining self-inspection, mutual inspection, and special inspection, accept the quality inspection of supervision engineer and social quality supervision. Self-inspection is a kind of “self-checking”. Operators conduct self-inspection of their own construction procedures or completed inspection batches and sub-projects, and play a self-monitoring role to implement “self-control”, eliminate abnormal factors in time, and prevent unqualified product flows into the next process; mutual inspection is the form in which the operators perform mutual inspections of the completed processes or sub-projects, and plays a role of mutual supervision, mutual exchange, and complement each other; special inspection is conducted by professional inspectors, and is the objective requirement of the division of labor in modern large-scale production. It cannot be replaced by mutual inspection and self-examination. To implement the “three-level inspection system”, we must reasonably determine the scope of self-inspection, mutual inspection, and special inspection. Under normal circumstances, the inspection of raw materials, semi-finished products and finished products is mainly performed by full-time management personnel such as material personnel, laboratory technicians, and quality inspectors. The inspection of each process in the production process is based on the self-inspection and mutual inspection of
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the professional technicians and operating workers in the construction site, supplemented by the special quality inspectors touring inspection, and the quality of the finished product must be checked and accepted accordingly. 3.9.2 Raw Material Detection Material is the direct material that constitutes the engineering entity, which directly affect quality of the project, as well as the safety and quality of subsequent operations. Therefore, it is particularly important to strictly control the inspection of materials and carry out timely quality inspections to find and remove unqualified materials as soon as possible. The purpose of quality inspection of raw materials is to verify the quality of materials in a timely manner through scientific inspection methods and meet the engineering quality requirements. The raw materials and semi-finished products entering the construction site of the project shall be strictly controlled to ensure that any materials that have not been inspected or unqualified may not be put into use or put into production. Raw material testing should do the following four things: (1) Check, accept and record all quality certificates and specifications for purchasing raw materials. (2) The new materials, special materials and substitute materials used for the first time must be tested, trial-produced and appraised before they can be used by the relevant units. (3) The raw materials with qualified certificates shall be re-inspected, and the reinspected materials shall be used after review. (4) The material department shall mark the unqualified raw materials for reinspection, stop using and clear the construction site. 3.9.3 Spot Inspection It is necessary to organize spot inspection and sampling inspection on the production process, the quality of the main raw materials and their products, so as to ensure the quality of the project. Spot inspections shall include data verification, appearance and quantity inspections, quality inspections, sample inspections, etc., and fill in relevant records. During the spot inspection, the supervision unit and the construction unit shall be notified to participate. Spot inspection of materials and construction should pay attention to technical conditions, test procedures, and third-party testimony, and ensure their uniformity and fairness. The competent engineer and the supervising engineer of project department, need to verify whether the qualification of the spot inspection unit and the experimental unit is in accordance with the relevant regulations. 3.9.4 Pipeline Inspection For the water rehabilitation project, the pipeline inspection is a key task. In the Maozhou River Project, for the underground pipelines in the pipeline network project, CCTV and QV endoscopy technologies are used to timely determine the types, grades, and quantities of defects in the pipeline, supervise the construction party to carry out the rectification in time, achieve post-control. It will be the first pass for the project acceptance and handover, and will meet the acceptance standard. When analyzing
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defects, relying on the collected data to conduct process analysis and standardization analysis, explore the main causes of the construction process, and carry out targeted rectification. Through data visualization, the actual situation of construction is presented in an image, trend of quality management of quality implementation units is analyzed, and the quality early warning is put forward in time. In the process of data analysis, an important tool is the Pareto chart, which is a common and effective analysis tool. It is also known as an arrangement diagram, primary and secondary maps, and is a special histogram sorted by frequency of occurrence. It ranks the quality problems that appear in order of importance, and can be used to analyze quality problems and indicate how many results are caused by reasons has confirmed type or category [5]. In pipeline inspection, Pareto charts can be used to show how many pipe defects are caused by each identified cause, and the purpose of ranking is to take corrective actions with emphasis. Figure 3 is a Pareto chart drawn from the specific data of the pipe network project in the Maozhou River project.
Fig. 3. Pareto chart
We can see from Fig. 3 that the Pareto diagram conforms to the Pareto rule (two eight rule), which verifies that 80% of the defects come from 20% of its causes. As far as Fig. 3 is concerned, fluctuation, leakage and deformation, the three defect types, are the few key factors, and play a decisive role that need to spend time, energy and cost. Using Pareto chart, the construction unit can put a lot of energy and funds into the few categories that can cause most of the pipeline defects. Under the limited energy and funds, the final purpose of pipeline detection can be realized, thus improving the quality of project and the work efficiency of construction units.
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4 Conclusions In Maozhou River project, PowerChina Water Environment Governance Co., Ltd. firmly adheres to the idea of PDCA, innovates the double quality management mode, and realizes total quality management from the two levels of platform company and project department. In the course of construction, in view of the many factors affecting the quality of the project in different construction stages, the causality analysis diagram method is adopted to analyze the six aspects of man, machine, material, method, environment and measurement, emphasizing eliminate of quality problems before formation of the “cause”. Innovative methods such as static pile pressing method and CCTV pipe endoscope are used to improve management level. In this comprehensive and multi-level quality management model, through the innovative quality theory and specific management methods, the purpose of controlling the quality of the Maozhou River project is achieved, and the occurrence of quality accidents has been eliminated fundamentally. By May 2018, the water quality of Maozhou River has improved significantly, and the main stream water quality has reached the standard of non-black and non-odor. Some sections of the river have reached the target of class V of National Surface Water Environmental Standard [6]. This also indicates that the quality management methods and measures of Maozhou River are successful, which provides a model for the quality management of water rehabilitation projects in China.
5 Acknowledgments The research was supported by Fund of the PowerChina Water Environment Governance Co., Ltd. for Study on Quality, Safety and Environmental Management of Urban Water Rehabilitation Projects (Contract No. SHJ-JY-2017-024).
References 1. Shenzhen University: Report to the Study on Quality. Safety and Environmental Management of Urban Water Rehabilitation Projects, Shenzhen (2018) 2. Mu, R.L.: Application of causal analysis in construction quality control. Sci. Technol. Inf. 11, 53–55 (2009) 3. Zhang, N.: Discussion on the quality control of the construction process of building engineering. Gansu Sci. Technol. 19, 136–137 (2008) 4. Fu, C.H.: On the five factors affecting the construction Quality of waterway engineering. Port Science and Technology Development, (12) (2004) 5. Xiang, X.W.: The application of causality analysis graph in the analysis of the cause of engineering construction attachment. Shanxi Architecture, (32) (2008) 6. Yang, K.Q.: Governance sample of Shenzhen’s longer river-Secretary responsible, twenty billion return old account. Southern Weekend, 2018.5.24 (2018). http://www.infzm.com/ content/136014
Environmental Management Scheme of EPC Model for Water Environmental Treatment Project Dongjie Chen1, Yunchu Chen2, Ningkang Li2, Hui Zhang3, Huabo Duan1(&), Jian Liu1, and Peiwen Sun1 1
School of Civil Engineering, Shenzhen University, Shenzhen 518060, China {1426510211,843878498}@qq.com, {huabo,liujian}@szu. edu.cn 2 China Power Construction Water Environment Treatment Technology Co., Ltd., Shenzhen 518060, China [email protected] 3 School of Chemistry and Environmental, Wuhan Institute of Technology, Wuhan 430205, Hubei, China [email protected]
Abstract. ISO14001 international standard is a powerful decision support tool in project management, while it rarely been applied to analyze environmental impacts of construction projection. In the study, on the basis of a case of water environment comprehensive treatment project (EPC mode), we established an environmental management scheme process system based on ISO140001 by investing the environmental management model of 11 sub projects. The environmental management system consist of four parts: (1) determine the type of construction; (2) Identify the environmental impact factors; (3) Prevention and contaminated control scheme: (4) Implementation and evaluation of the scheme. The research results can provide ideas and references for environmental management model of construction project, especially for complicated water environmental treatment projects. Keywords: Field investigation ISO14001 Water environment management system Construction project
1 Introduction With the rapid urbanization of China, a series of infrastructure and industrial facilities were produced, which means massive construction projects across the country, in particular in some megacities. The construction activities of these projects would inevitably bring out some environmental problems e.g., to destroy the vegetation of the soil surface, to affect air quality owing to the dust in truck transportation, construction noise, the disposal of solid waste resulted from construction activities, etc. [1, 2], which mean a significant negative impact on the sustainable development of the environment and society [3]. However, the environmental problems produced in the process of construction have become increasingly prominent, which has become a widespread © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 376–389, 2021. https://doi.org/10.1007/978-981-15-3977-0_28
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concern in the world, consequently, the sound environmental management during construction activities is of importance, in particular in some megacities. Shenzhen City is situated in a rapidly industrializing region in China with a 100% of urbanization rate. It represents a national eco-civilized city and low carbon city. As a forerunner of China’s booming economy, the megacity has been confronted with a multitude of environmental challenges of construction activities, sound environmental management measures or scheme is the necessary and urgent. Water environmental protection is a significant issue in the development of our national economy. Since the reform and opening up, China’s water environment has gradually deteriorated, and has become a constraint factor in social and economic development. Water environment governance has reached an urgent need [4]. The implementation of urban water quality improvement projects plays a vital role in the city’s economy and environment. For key river basins, the national development and Reform Commission encourages and supports local policies to adopt franchise management and other project management and operation modes. Some complex largescale projects, such as the urban water environment comprehensive treatment project (urban water quality control project), have the characteristics of large investment, long period of time, many working procedures, complex construction conditions, high technical specifications and great environmental impact, so the EPC model is the best management mode suitable for such projects. EPC project general contract mainly refers to the owners who contract all links of investigation, design and equipment procurement and transportation in the construction project to a contractor with general contracting qualifications and a construction model that is later transferred to the owner as a whole when the owner’s requirements are reached [5]. Because of the emphasis and full play of the leading role of the design in the whole construction process of the project, the EPC model can effectively overcome the advantages of the contradiction between design, procurement, construction and mutual disintegration, and more and more are applied to in the f construction projection [6, 7]. At present, the study on environmental management of construction projection mainly focus on three respective separate aspects, including policy formulation and promulgation, the specific prevention and control management of environmental contamination, and the management method and theory of the project environment management [8–10]. So far, there still are scare for scientific and systemic environmental management scheme of water environmental treatment project, especially for the water environmental treatment project based on EPC model. Thus, taking Shenzhen City as a case study, the aim of this study was to puts forward its sound environmental management scheme in construction activity. ISO14001 international standard is a powerful decision support tool in project management, while it rarely been applied to analyze environmental impacts of construction projection and its management scheme, this study firstly will establish a sound environment management scheme on EPC mode of water treatment project in a megacity such as Shenzhen City.
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2 The Object, Method and Content of Field Investigation In the present study, 11 sub projects of ten tenders for comprehensive water treatment projects were investigated by field investigation. River regulation, waterlogging, pipe network, water supplement, wetland and landscape engineering are more or less ecological damage, such as vegetation destruction, biodiversity reduction, ecosystem function reduction, landscape destruction, soil erosion, but not the main environmental problems. In spite of the large amount of excavation, filling and material stacking, abundant rainfall in the area of the project and frequent rainfall in summer, the vast majority of the residual soil has been treated with no slag and land, which will not produce serious soil erosion and erosion of the ground. In addition, a series of ecological environmental impacts, such as vegetation destruction, the reduction of biodiversity (such as the decrease of plant diversity) and the decrease of the function of the ecosystem, are required to take appropriate ecological compensation and recovery measures at the end of the construction and in the operation period. As a whole, the environmental management team has no further investigation and analysis of the ecological environment problems at the construction stage, mainly investigating the pollution sources and management measures of the following environmental factors, including air pollution, water pollution, noise (vibration) pollution, solid waste impact, landscape destruction, risk sources, and traffic impact. This research mainly adopts the method of inquiring and combining the environmental condition monitoring with the construction workers, technicians and environmental managers. Through the introduction of the display board and the on-site staff, the operation time and the main construction technology related to the environmental impact, as well as the construction stage, the main construction machinery, the pollutant discharge methods of reducing and avoiding the environmental impact, the implementation of environmental management measures, etc. Portable measuring instruments such as noise instruments and dust instruments are used to monitor and record the noise values and particulate matters at the scene. For example, Table 1 and Table 2 are the contents and results of the on-the-spot investigation.
Table 1. Field research content Project name
Regenerative pump station project of sewage treatment plant Reclaimed water rehydration project- pipe jacking construction of sewage treatment plant Wastewater treatment plant reclaimed water replenishment project- excavation project
Object of investigation Dust Water Noise √
√
√
Solid waste √
Risk
Traffic
√
√
√
√
√
√
√
√
√
√
√
√
√
√
(continued)
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Table 1. (continued) Project name
Object of investigation Dust Water Noise
Comprehensive renovation project √ √ Storage Lake Water comprehensive renovation √ √ project - retaining wall project Comprehensive water regulation √ √ project at - channel silting Wetland Engineering √ √ Tunnel engineering √ √ Waterlogging project √ √ Sediment treatment plant ╳ √ Landscape demonstration section √ √ Note: “√” indicates that the investigation has been carried
Risk
Traffic
√
Solid waste √
√
√
√
√
√
√
√
√
√
√
√ √ √ ╳ √ out.
√ √ √ √ √
√ √ √ ╳ √
√ √ √ ╳ √
Table 2. Field survey results of each sub project Project name Main types of pollution Regenerative pump station project Noise pollution, air of sewage treatment plant pollution, solid waste and water pollution Noise pollution, solid Reclaimed water rehydration project-pipe jacking construction waste of sewage treatment plant Wastewater treatment plant Solid waste reclaimed water replenishment project- excavation project Comprehensive renovation Noise pollution, air project - Storage Lake pollution Water comprehensive renovation project - retaining wall project Comprehensive water regulation project at - channel silting Wetland Engineering Tunnel engineering Waterlogging project Sediment treatment plant
Landscape demonstration section
Noise pollution, air pollution Noise pollution, air pollution Noise pollution, air pollution, solid waste Noise pollution, air pollution, solid waste Noise pollution, air pollution Pollution of water quality, solid waste pollution —
Measures taken on the spot Environmental monitoring system, sprinkler dust, car wash pool Purification of mud water, separation of mud and water and recycling of water Three stage precipitation, spray system, sand soil cover Fog gun machine, car wash basin, water quality monitoring, seeded slope protection Use of machinery with less noise Sow grass and plant grass Solid Waste Management — Solid Waste Management Purification treatment and recycling of sediment Clean energy use
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3 Analysis of the Environmental Management Model of Present Project According to the field investigation and the related data in the construction process, the four characteristics of the effluent environmental treatment project are summarized, such as large scale, wide range, many projects, high social attention, strong engineering system, complicated professional connection, high requirement of interface management, tight project time period, many uncontrollable factors and large construction intensity. Resource dynamic management requires high level, civilized construction and high environmental protection requirements. 3.1
Characteristic of ISO14001 in Application of Project Management
In the ISO14001:2015 environment management system, the basic content of the management system consists of 5 first level elements and 17 two level elements. The 5 first level elements include environmental policy, planning, implementation and operation, inspection and management review. 17 first level elements are: environmental policy, environmental factors, laws and regulations and other requirements, objectives, targets and plans, resources, functions, responsibilities and powers, ability, training and awareness, information exchange, documents, file control, operation control, application preparation and response, monitoring and measurement, compliance evaluation, no compliance Corrective actions and preventive measures, record control, internal audit and management review. Table 3 is the elements of the environment management system. Table 3. Description of two grade level of factors lists ISO14001 international standard Factors lists
The first grade factors (一) Environmental policy (二) Plan
(三) Implementation and operation
(四) Check
(五) Management review
The second grade factors 1. Environmental policy 2. Environmental factor 3. Laws and regulations and other requirements 4. Objectives, targets and tasks 5. Resources, roles, responsibilities and powers 6. Ability, training and awareness 7. Information exchange 8. File 9. File control 10. Operation control 11. Emergency preparedness and response 12. Monitoring and measurement 13. Compliance evaluation 14. No conformity, corrective measures and preventive measures 15. Record control 16. Internal audit 17. Management review
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Analysis of Environmental Management Model Related to the Project
According to the combination of ISO14001 international standard and the results of investigation, some problems was observed in the present environmental management model of construction project during construction stages, which can be concluded as following: (1) Possibly because of the inefficiency of supervision and inspection, some environmental management measures were not well implemented; (2) The impact resulted from construction activities, which posed on environmental medias such as air, water and soil, etc. varied with construction condition, while environmental impact factors were identified before construction activity by a report on environmental impact assessment (EIA), which was published by official agencies such as local Environmental Protection Agency (EPA); (3) We found some unreasonable content related to environmental management targets and policies, as well as the corresponding management measures and its exam indexes, which were put forward to a great extent based on empirical judgment, even worse, the quantitative evaluation indicators of environmental management were not insufficient; (4) No sound and effective plans were put up, namely plans of inspection and supervision system, and perfection of sound management measures.
4 Environmental Management Scheme Process System Based on ISO14001 To solve the questions above mentioned, in view of the water environment management project, the process system of environmental management of the effluent environmental treatment project is summarized, including the construction type, the identification of environmental factors, the influence and the scheme control, and the implementation and evaluation. As shown in Fig. 1. 4.1
Determine the Type of Construction Project
In order to make better plans and implementation plans of environmental management, the characteristic of construction project firstly should be analyzed, including the types of construction, the detailed construction progress and various construction phases, and further analyze their respective environmental factors from those type of sub projects. In the present study, water environment control projects consist of four types of sub projects, e.g., rain and sewage network, river regulation, sediment dredging and landscape upgrading. The project of rain and sewage pipe network is subdivided into the pipeline transformation project, municipal road engineering, pipe network
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Fig. 1. Water environment management project environment management process system
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improvement project and water supplement facility project, etc. the river treatment projects are subdivided into waterlogging project, water quality improvement project, ecological restoration project, river sewage interception project, flood control renovation project and so on. Subdivision of sediment dredging projects is subdivided into such projects as river dredging and sediment disposal; landscape upgrading projects are divided into wetland projects, water intake and water replenishment projects, image enhancement projects, and landscape construction projects. 4.2
Identification of Environmental Impact Factors
On the basis of various type of construction sub projects and theirs’ characteristics of the project, further we can identify the different environmental impact factors resulted from various project construction activities mentioned above in the first step. According to field investigation, environmental factors can be classified into these two ones: the first grade one and the second grade one, presented the impact on environmental media such as air contamination, waste water, as well as wide conception factor such as noise pollution, solid waste pollution, ecological damage and traffic problem. However, the second ones refer to the detailed environmental impact factors resulted from the construction process (the first step), e.g., the corresponding one at the second level was some detailed factors, e.g., the transportation dust, the mechanical noise, construction waste, river sediment. Here, our results overcome the shortcoming of empirical judgment according to previous a report on EIA. Regarding the quantitative analysis of these two grade factors can be conducted by a combination of investigation method and model such as LCA or analytic hierarchy process (AHP) [9, 10]. In a word, investigation method is a simple and typical methods of EPI for construction project. 4.3
Prevention and Control Scheme of Environmental Contamination
After analyzing different environmental impact factors, especially for main factors, the prevention and control measures should be given accordingly. As is shown in Fig. 1, the pollution prevention and control scheme can be divided into two types of ones, normal scheme and special scheme. The normal one is used for all construction projects, including prevention and control measures aimed at air contamination, waste water contamination, construction noise and solid waste problem; while the special one is fit for the water treatment project which is similar to present study, e.g., civilization construction, green construction, risk management and etc. for example, green construction mean that four saving measures for water, electricity, materials and other natural resources such as land resource, one environmental protection [10]. In recent year government and construction management agencies pay more attention to green construction, with a purpose to improve environmental sustainable development and energy saving, the construction management is meaning for the development of ecocity or low carbon city.
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The specific measures in the normal and other special control schemes were involved in the following: discharge of the wastewater after treatment and the field sprinkled, solid waste and materials are 100 per cent covering, sound insulation, within reasonable operation time, classification and disposal of solid waste, classification and recycling, prohibition of rain day excavation, promotion of construction of green building materials, closed storage of chemical materials, timely recovery of chemical materials, and etc. 4.4
Implementation and Evaluation of the Scheme
To efficiently conduct the prevention and control scheme for environmental contamination, we set up a series of continued scheme one by one, e.g., the implementation scheme, the inspection and supervision scheme, evaluation and improvement scheme. These schemes presented the dynamic management model for construction project, namely PDCA management model in ISO14001 international standard, including four typical period such as plan, do, check, act (improve). Here, to overcome the shortcoming of unreasonable content related to environmental management targets and policies, some quantitative evaluation indicators were drawn from the laws, regulations and rules; for instance, the target of prevent and control scheme related to construction dust indicator (PM2.5) is should be set as below mean value of 33.5 g/m3 annually. In addition, the environmental management model makes perfection of institutionalization management, which is helpful for the implement of some system, including three simultaneous system, environmental protection target liability system, pollution control system, environmental protection publicity and education system, environmental management regular report system, reward and punishment system, and etc. In a word, this is a sound and efficient management scheme, it can promote the implement of some environmental measures well.
5 An Example of Quantitative Evaluation Scheme Based on AHP 5.1
Description of AHP Model
5.1.1 Establishment of Evaluation Index System According to the specific situation of the construction project and its exam requirement, the evaluation index system of environmental management is constructed by three hierarchy layers, namely, target layer (A), standard layer (B) and index layer (Fig. 1), detailed items related to these three layers see Fig. 2.
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Fig. 2. Establishment of evaluation index system
5.1.2 Weight Determination In order to quantify the judgment, it is mainly to make qualitative or quantitative judgment or description on the degree of influence of two different schemes on a criterion. We construct and judge the matrix with the scale method of 1–9 [11]. After constructing the matrix, then the consistency of matrix should be checked. And the consistency of pairwise comparison matrix has to be validated by means of consistency indicators (CI) and checkout ratio (CR). When the value of CR is below 0.10, the judgement matrix is acceptable consistency. The calculation process and the description of other indexes was similar the reference [12]. In the present study, the results of weight from target layer to index layer were documented in Table 4, 5, 6, 7, 8 and 9.
Table 4. Target-standard layer judgement matrix A B Target-standard layer Institutionalized environmental management A 1 1 General environmental management measures B 1 1 Professional environmental management measures C 2 3/2 The impact on society D 5/2 4/3 kmax ¼ 4:1798, CI: ¼ 0:0599, RI: ¼ 0:89 CR: ¼ 0:0673\0:10
C
D
Weight
1/2 2/3 1 4/5
2/5 4/3 5/4 1
0.1127 0.2616 0.3415 0.2842
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A1 A2 A3 A-Ai layer Three simultaneous system A1 1 1/2 1/3 Environmental goal responsibility system A2 2 1 3/4 Pollution source control system A3 3 4/3 1 Education and training system on A4 1/3 1/5 1/7 environmental protection Supervise and inspect system A5 5/3 2/3 4/5 Periodic work report system A6 2/3 1/3 1/4 Accident reporting and handling system A7 1/2 1/4 1/5 kmax ¼ 7:0314, CI: ¼ 0:0052, RI: ¼ 1:36 CR: ¼ 0:0038\0:10
A4 A5 A6 A7 Weight 3 5 7 1
3/5 3/2 5/4 1/5
3/2 3 4 1/2
2 4 5 3/4
5 1 5/2 3 2 2/5 1 2 4/3 1/3 1/2 1
Table 6. B-Bi judgment matrix B1 B2 B3 B4 Weight B-Bi layer Air pollution B1 1 3 1 2 0.3445 Water pollution B2 1/3 1 1/3 1/2 0.1069 Noise pollution B3 1 3 1 3 0.3813 Solid waste pollution B4 1/2 2 1/3 1 0.1673 kmax ¼ 4:046, CI: ¼ 0:015, RI: ¼ 0:89 CR: ¼ 0:017\ 0:10
Table 7. C-Ci judgment matrix C1 C2 C-Ci layer Ecological protection C1 1 3/4 Green construction C2 4/3 1 Environmental risk control C3 1/2 1/2 Traffic problem C4 2 2 kmax ¼ 4:0104, CI: ¼ 0:0035, RI: ¼ 1:12 0:10
C3 C4 Weight 2 1/2 0.2066 2 1/2 0.2385 1 1/4 0.1110 4 1 0.4439 CR: ¼ 0:0039\
Table 8. D-Di judgment matrix D-Di layer Environmental protection complaints D1 Administrative penalty D2 Administrative bulletin D3 Internal bulletin D4 Media exposure D5 kmax ¼ 5:0466, CI: ¼ 0:0117, RI: ¼ 1:12
D1 D2 D3 D4 D5 Weight 1 1 1/2 2 4 1 1 2/3 4/3 5 2 3/2 1 3 9 1/2 3/4 1/3 1 4 1/4 1/5 1/9 1/4 1 CR: ¼ 0:0104\0:10
0.2135 0.2162 0.3862 0.1409 0.0432
0.1127 0.2306 0.2917 0.0407 0.1888 0.0810 0.0545
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Table 9. Summary of weight of the index The first grade Index Institutionalized environmental management
Weight 0.1127
General environmental management measures
0.3415
Professional environmental management measures
0.2616
The impact on society
0.2842
5.2
The second grade Index Three simultaneous system Environmental goal responsibility system Pollution source control system Education and training system on environmental protection Supervise and inspect system Periodic work report system Accident reporting and handling system Air pollution Water pollution Noise pollution Solid waste pollution Ecological protection Green construction Environmental risk control Traffic problem Environmental protection complaints Administrative penalty Administrative bulletin Internal bulletin Media exposure
Weight 0.1127 0.2306
Summary of weight 0.0127 0.0260
0.2917
0.0329
0.0407
0.0046
0.1888
0.0213
0.0810 0.0545
0.0091 0.0061
0.3445 0.1069 0.3813 0.1673 0.2066 0.2385 0.1110 0.4439 0.2135
0.1176 0.0365 0.1302 0.0571 0.0540 0.0624 0.0290 0.1161 0.0607
0.2162 0.3862 0.1409 0.0432
0.0614 0.1098 0.0400 0.0123
Quantitative Evaluation Index System Based on AHP
In order to evaluate the effectiveness of environmental management measures, an example of quantitative evaluation scheme based on AHP was given. The scheme based on AHP model overcome the shortcoming of empirical judgment of exam indexes. As is shown in Table 10, which is obtained by the value in Table 9 multiplying by 100, according to the score of these indices in Table 10, the different management measures were quantitatively evaluated.
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Table 10. Evaluation index of environmental protection in construction period (total score is 100 points) Institutionalized environmental management
Score General environmental management measures
Score Professional environmental management measures
Score The impact on society
Score
Three simultaneous system
1
Air pollution
12
Ecological protection
4
6
Environmental goal responsibility system Pollution source control system Education and training system on environmental protection Supervise and inspect system Periodic work report system Accident reporting and handling system
2
Water pollution 4
Green construction
5
Environmental protection complaints Administrative penalty
3
Noise pollution 13
7
Solid waste pollution
6
Administrative bulletin Internal bulletin
11
1
Environmental risk control Traffic problem
2
/
/
/
/
1
1
/
/
/
/
Media exposure /
1
/
/
/
/
/
/
2
6
4
/
6 Conclusion In the present paper, a field investigation method was used to analyze the shortcoming of the situation of environmental management related to construction project and tis shortcoming in construction process, further we established a scientific and systemic environmental management scheme process system based on ISO14001 international standard. The process system consist of four steps: (1) The types of construction projection and theirs’ characteristic are firstly in need of determination, which is the priority of the analysis on project’s environmental factors in construction activities. (2) Identification of the environmental impact factors at two grade level, the results overcome the shortcoming of empirical judgment according to previous a report on EIA. (3) Prevention and control scheme of environmental contamination, the scheme is meaning for the development of eco– city or low carbon city. (4) Implementation and evaluation of the scheme, including the implementation scheme, the inspection and supervision scheme, those presented the dynamic management model (PDCA model) in ISO14001 international standard; and the schemes overcome the shortcoming of unreasonable content related to environmental management targets and policies, some quantitative evaluation indicators, specially, an example of quantitative evaluation scheme based on AHP was given.
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Acknowledgements. This study was supported by Fund of the Power China Water Environment Governance Co., Ltd. for Study on Quality, Safety and Environmental Management of Urban Water Environment Rehabilitation Projects (Contract No. SHJ-JY-2017-024).
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Innovative Bioretention Facility for Siphonic Drainage System Zhan Yuan1, Jianying Pan2, Jian Liu3(&), Xiaolei Wang4, Zengwen Bu5, and Lingyi Wu3 1
4
College of Civil Engineering, Shenzhen University, Shenzhen, China [email protected] 2 Technology Management Center, Shenzhen Metro Group Co., Ltd., Shenzhen, China 3 Ecological Technology Institute of Construction Engineering, Shenzhen University, Shenzhen, China [email protected] Construction Management Headquarters, Shenzhen Metro Group Co., Ltd., Shenzhen, China 5 Shenzhen Cenpoint Architects & Engineers Co., Ltd., Shenzhen, China
Abstract. A new type bioretention facility that called as bioretention parterre was proposed to treat the stormwater of the siphonic drainage system in the Changzhen Depot of Shenzhen Metro. The connection point of the siphonic downspout and the inlet of bioretention parterre was calculated by corresponding calculation formula. The energy dissipation well and the outlet well are set at two sides of the bioretention parterre respectively. The outflow control device is set up in the outlet well to regulate the discharge. The innovative bioretention parterre provides new thought for sponge city construction of urban rail transit. Keywords: Siphonic drainage system Metro
Sponge city Bioretention parterre
1 Introduction With the rapid development of the economy and the acceleration of urbanization process, more and more various large-scale stadiums, stations and factories have been built in China. Traditional gravity drainage system often cannot meet the drainage requirements of large-area roofs. Therefore, the siphonic drainage system has been widely used in large-area roof rainwater drainage due to high drainage efficiency and less space occupation [1]. According to the Guiding opinions on promoting the construction of sponge city issued by the General Office of the State Council in October 2015, the sponge city construction should give attention to fully using the functions of vegetation, soil and other natural underlying surface for rainwater infiltration, wetland, water area for natural purification of water quality and the natural circulation of urban water [2]. The sponge city construction should be done by means of the natural ecological functions © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 390–396, 2021. https://doi.org/10.1007/978-981-15-3977-0_29
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and artificial intervention measures such as the implementation of source reduction, process control and system management. Thus, the objects such as the restoration of urban water ecology, conservation of water resources, enhancing urban waterlogging control ability, expanding effective investment of public facilities, improving the quality of new urbanization and promoting the harmonious development of man and nature could come true. During the sponge city construction, some comprehensive measures such as rainwater infiltration, retention, storage, purification, use and drainage shall be taken to minimize the impact of urban construction on the ecological environment, and 70% of the annual rainfall will be treated and used locally. More than 20% of the urban built-up areas shall achieve the objectives and requirements by 2020; and more than 80% of the urban built-up areas shall achieve the objectives and requirements by 2030 [3]. During construction of sponge city, the facilities such as rain garden, green roof, bioretention and the permeable pavement in the non-motorized lanes, sidewalks, car parks shall be widely used to implement rainwater collection, purification and utilization, and as a result, the pressure of the constructed municipal drainage system can be reduced. The construction of the sponge city has become an important development direction of urban drainage system in China. As of April 2016, the central government had selected 30 pilot cities of the sponge city construction. The roof runoff pollution is serious, especially the initial rainwater pollution is the most serious with muddy and larger Chroma [4]. The COD of the initial runoff water quality is more than 500 mg/l. To reduce the initial rainwater pollution, roof rainwater is often connected to the sponge city facilities. The siphonic drainage system is different from the gravity drainage system, therefore, how to connect the siphonic drainage system to the sponge city facility is needed to be solved. In this study, a new type bioretention facility was proposed to treat the stormwater of the siphonic drainage system in Changzhen Depot of Shenzhen Metro.
2 Outline of Changzhen Depot The Changzhen Depot in Guangming District, Shenzhen, is located on the west side of the Keyu Road, the south side of the Tongguan Road, the east side of the Dongchang Road, and the block enclosed by the side of the Guangqiao Road. The current status of the project site is mainly construction land, and an average 5 m wide open channel of the Ejing River passes through the west side of the site [5]. Changzhen Depot is planned to be used as residential land, commercial land, and supporting public service facilities (Fig. 1). The total land area is 24.94 hectares with a total construction area of 233,764.4 m2, including a single building area of 168,713.5 m2 and a projected area of 148,200 m2. Changzhen Depot is one of the important works in Shenzhen Rail Transit Line 6 project, and it is adjacent to the Changzhen Station. The Changzhen Depot is positioned as a car frame repair section and undertakes major overhaul and repair tasks for Metro Line 6 trains (Fig. 2). It also undertakes tasks such as train parking, maintenance, operation, overhaul, maintenance and repair of various equipment, and undertaking of material support [6].
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Fig. 1. Location of Changzhen depot
Fig. 2. Changzhen depot under construction
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3 Innovative Bioretention Parterre Bioretention technology first appeared in 1999 in Prince of Georgia, Maryland, USA [7]. Rainwater is infiltrated with groundwater through percolation of plants and medium soils, or through the permeable pipe set at the bottom of the system to the municipal rainwater pipe network or the follow-up treatment system. The top-down structures of bioretention facilities are: storage layer, vegetation cover, plant, planting soil, medium soil and gravel layer [8]. Overflow facilities should be installed in the bioretention facilities. The overflow vertical pipe, the grate overflow well or the rainwater outlet can be used to discharge the rainwater more than the facility disposal capacity in time. Due to the characteristics of large drainage flow rate at the end of the siphonic drainage system, large flow velocity and large pressure, it cannot be directly combined with the traditional structure of the bioretention facility. Therefore, it is necessary to design a new structure of bioretention facility suitable for siphonic drainage systems. The plan and section of bioretention parterre with energy dissipation well and outlet well are shown in Fig. 3, and the outflow control device in the outlet well which was used in the bioretention cells at Shenzhen University in 2012 is shown in Fig. 4 [9]. The storage capacity of the innovative bioretention parterre is determined according to Eq. (1) [2].
Fig. 3. The plan and section of the bioretention parterre
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Fig. 4. The outflow control device used in the bioretention cells at Shenzhen University
V ¼ 10HuF
ð1Þ
Where V is Storage volume, m3; His Design rainfall, mm; u—Rainfall runoff coefficient, it is 0.9 for grey roof and it is equal to 0.35 for green roof5; and F is Catchment area, ha. The outlet of the siphonic downspout cannot connected with the inlet of the bioretention parterre because of high pressure and large discharge. Thus, in the process of setting bioretention parterre, it is necessary to calculate the place of closure point which is the place zero pressure of siphonic system and to set the place of closure point under that point about 0.5 m. The closure point of the innovative bioretention parterre is determined according to Eq. (2). Etop þ Ptop þ
qm2top 2g
¼ E0 þ P0 þ
E ¼ q:g:H: X
qm2o X þ Z 2g
ð2Þ
1 a
Z ¼ Zj þ ZL
Where E is Water head, m; P is Pressure; q is Density of water, P 1,000 kg/m3; G is 2 Gravitational acceleration, 9.81 m/s ; a is Conversion factors, 100; Z is Total head loss of pipe; Zj is local head loss; ZL— is the head losses along the way; Subscript top means the surface; and subscript 0 means the bottom.
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The length, width and depth of the bioretention parterre are 5 m, 2 m and 1.6 m, respectively. The structure of the bioretention parterre from top to bottom is plants layer, medium soil layer, permeable geotextile and gravel layer. The closure pipe is connected to the energy dissipation well for dissipating energy and slowing water flow rate. The perforated pipe with a diameter of 200 mm is put in gavel layer though the energy dissipation well and outlet well. The outflow control device is built in the outlet well at the end of the bioretention parterre. An energy dissipation well is set in the bioretention parterre. While the water in the energy dissipation well overflow to the surface of bioretention parterre, then infiltrate medium soil and gravel layer. The perforated pipe in the gravel layer conducts the flow into the outflow control device in the outlet well. The outflow control device has two different openings at different elevations. When the flow is small, the water flows from lower opening, and upper opening will release when the flow become large. This outflow control device was firstly used in the bioretention cells at Shenzhen University in 2012 as shown in Fig. 4 [9].
4 Conclusions According to the actual situation of Changzhen Depot of Shenzhen Metro, the bioretention parterre suitable for sponge city construction of rail transit was put forward. This new sponge city facility has applied many new technologies, such as new medium soil, and outflow control device. The connection between spongy city facilities and the siphon drainage system was solved, and the corresponding calculation formula was given in the paper. The energy dissipation well and the outlet well are set at two sides of the bioretention parterre respectively. The outflow control device is set up in the outlet well to regulate the discharge. This innovative bioretention parterre provides a new solution for sponge city construction of the rail transit project. Acknowledgments. The research was supported by Fund of the Shenzhen Metro Group Co., Ltd. for Study on Application of the Sponge City Concept in Subway Construction (Contract No. DT306KY002/2018).
References 1. Lei, G.Z.: On rainwater discharge of architectural roof. Shanxi Architecture 44(09), 97–98 (2018) 2. Ministry of Housing and Urban-rural Development: Technical guide for sponge City Construction: Construction of rainwater system with low impact development (Trial implementation). China Building Industry Press, Beijing, China (2014) 3. Liu, J., Li, S.X., She, N., Chen, H., Wu, L.Y.: Case study of low impact development facilities in municipal roads. China Water and Wastewater 33(4), 14–19 (2017) 4. Cao, X.Q., Che, W.: Schematic design and analysis of rainwater collection and utilization system of urban roofs. Water Wastewater Eng. 28(1), 13–15 (2002) 5. Shenzhen University. Report to the study on application of the sponge city concept in subway construction, Shenzhen (2018)
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6. Liu, Y., Wang, X.L., Liu, J., Pan, J.Y., Bu, Z.W., Wu, L.Y.: Innovative design of the sponge city facilities in the Changzhen depot. In: 23rd International Symposium on Advancement of Construction Management and Real Estate, Guiyang, Aug. 24–27 (2018) 7. Hatt, B.E., Fletcher, T.D., Deletic, A.: Treatment performance of gravel filter media: implications for design and application of stormwater infiltration systems. Water Res. 41, 2513–2524 (2007) 8. Davis, A.P., James, H.S., Eliea, J., Kim, H.: Hydraulic performance of grass swales for managing highway runoff. Water Res. 46, 6775–6786 (2012) 9. Lucas, W., She, N., Liu, J.: Advanced LID experimental array: Shenzhen University, Guangdong. Province, 2012 World Water & Environmental Resources Congress, Albuquerque, New Mexico, USA, May 20–24 (2012)
Estimating the Redistribution Effect of Affordable Housing on Income Distribution: Case Study of Nanjing Junjie Li(&) School of Management Engineering, Zhengzhou University, People’s Republic of China [email protected]
Abstract. During the past 20 years, China has provided large scale of government subsidized housing in order to improve the housing conditions for moderate and low-income households. In order to examine the effectiveness of housing security policy, this paper assesses the benefits and redistributive effect of affordable housing on income distribution. Hicksian income equivalent variation model (EV) is applied to measure benefits of low-income housing tenants and adopts Gini coefficient to examine the income inequality. Using a large micro dataset collected from 2011–2013 in Nanjing, this paper estimates empirically the benefits and income redistribution effect of affordable housing during three years. Empirical result shows that the provision of affordable housing can alleviate the income inequality problem. However, the result also indicates that the benefits of high-income families are often higher than that of low-income families, which generate another new inequity. It is necessary for the policy-makers to review the housing policy and some related suggestions are also put forward to improve housing policy in China. Keywords: Affordable housing EV model Housing benefits coefficient Income redistribution effect China
Gini
1 Introduction China is with the most population in the world, thus how to tackle the housing problem has been a major social concern facing the Chinese government. Before the implementation of the housing system reform, housing in China is regarded as the basic life materials which should be free of charge and provided by the government, forcing the government, the enterprises and institutions as a whole to build and allocate the houses to the urban employees, and residents only need to pay a small portion of nominal rent to obtain it (Hui and Wong 2006). Along with China beginning to establish a socialist market economic system gradually, Chinese housing policy has also witnessed a fundamental change during the past. Officially launched in 1998, the Chinese government decided to end physical welfare housing distribution system, substituted by implementing the marketization and monetization of housing reform, establishing and perfecting multi-level urban housing supply system which gives priority to the provision of affordable houses. As a result, China’s housing system there has been a © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 397–411, 2021. https://doi.org/10.1007/978-981-15-3977-0_30
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fundamental shift, and began to gradually establish a housing system with Chinese characteristics, namely the high income families solve the demand for housing via market, and the middle-income families are provided by the government with affordable houses, and impoverished families are aided by low-rent houses by government. After 2010, the Chinese government has introduced the new employment and urban migrant workers of public rental housing. Affordable housing, low-rent housing and public rental housing in China all known as affordable housing, is geared to the needs of different groups. Economical and applicable houses have long been the main body of China’s affordable housing supply, for its far below the market price. The government sell it to the low-income families, and ensure the families can get housing property. Therefore, compared with the other types of affordable housing, economical and applicable housing enables low-income families to have more housing welfare, making the income redistributive effect more significant. Although China’s housing system, to a certain extent, has solved the many lowincome families housing problem, the excessive marketization also poses a serious threat to the widening gap between the rich and poor (Wang and Murie 2011). China’s Gini coefficient was 0.39 in 2000, and the Gini coefficient of urban residents is 0.3171, while China’s Gini coefficient rose to 0.448 in 2010, and the Gini coefficient of urban residents increased to 0.3535 (Chotikapanich et al.), and both the overall Gini coefficient and urban Gini coefficient are still in the rising trend. Housing plays a crucial role in widening gap between the rich and poor. According to the initial housing policy of China’s government, affordable housing should account for 70% of the housing market supply, but because of local governments willing to increase revenue by selling land, lack of motivation to supply affordable housing, even in the peak time of affordable housing in 2000, the actual supply of affordable housing only took up about a quarter of the housing market supply. Then as the unusually prosperous real estate growth, it stimulates the rapid rise in house prices, making the houses an important approach for people to amass wealth in a short term. As housing prices soared in recent years, the high income group can get more benefit from ownership of assets, which even has exceeded the wage income, whilst the low-income groups are getting more difficult to afford housing, leading to the gap between the rich and poor. As the value of housing is rising, the housing assets play more crucial role in affecting the inequality among income distribution (Li Shi, Zhao Renwei.). For the government, it is by all means significant to research the income redistributive effect of affordable housing to whether set up housing policy or income redistributive policy, which is also the logical starting point of this paper. Toward that end, the redistribution effect of affordable housing on the income distribution is estimated in order to evaluate the implementation effect of affordable housing policy and further improve the domestic research in this field in China. Hicksian income equivalent Variation (EV) model is introduced to measure the income change of eligible household pre and post-obtaining affordable housing, which can transform the housing benefits obtained by eligible households into monetary value. In order to make EV more precise, Hedonic price model is also adopted to measure the market price of affordable housing without subsidy. The result of redistribution effect will be got by transforming EV obtained into Gini coefficient.
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In view of the great difference of affordable housing policy in different cities in China, Nanjing, a relatively developed city in the east of China, is chosen as a case. According to the micro data of affordable housing households collected from 2011 to 2013 data in Nanjing, the empirical analysis of redistribution effect of affordable housing is carried out in this paper. Based on the results obtained by empirical analysis, relevant policy suggestions are also put forward in the conclusion part of this paper. Nanjing as a relatively developed city in the eastern part of China, the price of housing is increasing at a astonishing rate in recent years. In the list of all countries in China, the average housing price in Nanjing was the ninth, leading heavier pressure in payment. In order to solve the housing problem of the low-income groups, Nanjing began to construct affordable housing from 2002, and enhanced the construction of the housing by launching a new round of large-scale housing construction, in which the most are affordable housing. As a city with heavy population, high housing price and large-scale affordable housing system, studying the income redistributive effect of Nanjing plays a typical role for people to understand the whole background of China in this issue. This paper is organized as follows. In Sect. 2, the literature referring to the relation between housing and income inequality are reviewed. The theoretical framework is introduced in Sect. 3, and Sect. 4 discusses the methodology and analysis process. Based on the theoretical model built in this paper, the income redistribution effect of affordable housing in Nanjing during 2011–2013 is analyzed in Sect. 5. Section 6 concludes the paper and proposes some policy suggestions.
2 Literature Review Public housing programs are often supplied by government to mediate and low-income households at a subsidized price or rent. Although the original purpose of housing security policy is to reduce the cost of decent housing for poor people, they have also become an important way to redistribute income (Fack 2006). Housing accounts for a large part consumption of the consumer owing to its asset attribute. When the eligible households obtain subsidized housing at below market price or rent, they get additional housing welfare relative to other people, which will affect the social income distribution structure obviously. From the point of welfare, the low price of affordable housing represents a transfer-in-kind to eligible households, and the supply of affordable housing could create a great reduction in income inequality (Olsen and Barton 1983; Wong and Liu 1988; Robinson et al. 1985; Dayioglu and Baslevent 2006; Antoninis and Tsakloglou 2001). There is a widespread conception that the affordable housing may result in equilibrium allocation of income (Gans and King 2003; Marical et al. 2006). Empirical studies of some developed countries and regions have indicated that the public housing program for low-income families could increase households’ benefits, improve their consumption ability, and reduce income inequality and Gini coefficient of the whole society significantly. For example, Dayioglu and Baslevent (2005, 2006) find that home-ownership has an equalising effect on income distribution in the urban areas of Turkey, which is attributed to the fact that many low income families reside in squatter housing built at the outskirts of large cities. Fack (2006) evaluates the impact of the housing subsidy on the level of rents in France. The results indicate that for every euro of
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housing benefit only leads to an increase of 22 cents consumption for the low income household. Lui (Lui 2007) demonstrates that the provision of public housing alleviates the income inequality problem in Hong Kong. Frick et al. (2010) analyze the income distribution of imputed rents in five European countries (Belgium, Germany, Greece, Italy and the UK). The results suggest that in almost all cases, housing subsidy policy leads to a decline in measured levels of inequality, despite widespread differences in the rates of home ownership and subsidization. Saarimaa (2011) analyses the effects of imputed rental income and its tax treatment on income distribution in Finland. It is found that imputed rental income has a major effect on homeowners’ well-being as it constitutes on average almost 10 per cent of homeowner households’ disposable income. In the process of China’s market-oriented reform, the widening trend of income gap arises (Li and Zhao 2011). Housing system reform, which is an important part of the market-oriented reform, aggravates the income inequality because of the unfair distribution. More seriously, with the rising of housing prices in recent years, the income gap has been widened further (Ning 2009). Providing government subsidized housing to low-income families becomes an important ways to reverse income gap (Zhang et al. 2013). In the 1990s, China began to establish the housing guarantee system. During the past 20 years, China has provided large scale of government subsidized housing in order to improve the housing conditions for moderate and low-income households. The government has proposed the magnificent goal of 36 million of affordable housing units during “the 12th Five Year Plan Period”. By the end of the coming 2015, the housing guarantee system will cover twenty percent of the population. As more and more low-income families qualify housing security, it will play an important role on improving China’s income distribution structure, and housing security policy has currently become an important way to adjust income distribution in China. It is very necessary to analyze the redistribution effect of public housing on income distribution, which will benefit not only housing security policy but also income distribution policy. However, the research on the effects of housing security policy on income redistribution is absent in China. Although more and more scholars are beginning to realize that the housing could have an important impact on income distribution and social equity with the housing problem arising public attention in recent years, the related research mainly concentrated in two fields. Some researchers focus on examining the effect of house price fluctuations on the income gap. For example, Feng and Wang (2010), Zhang (2014) analyze the relationship between house price fluctuations and income distribution. The results show that the rising of housing prices lead to a further widening of income gap. Others give attention to the influence of property tax on the income distribution. For instance, Li and Xiang (2013), Huang (2014) estimate the impact of property tax policy on income distribution in Shanghai and Chongqing, both of which are pilot cities of property tax in China. They find that the effect of current property tax on the income distribution is limited. However, in the field of the effect of housing security policy on the income distribution, domestic related studies are deficient in China. Although some scholars have also concerned this problem, they only think the income distribution will be affected by housing security policy from the point of qualitative analysis. Few people adopt quantitative method based on scientific theory and methodology to examine the extent of actual impact of affordable housing on the income distribution and social equity. This topic has received less attention than it deserves in China, while the purpose of this paper is to fill this gap.
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3 Theoretical Framework Housing benefit in the paper refers to the difference between total amount and structure of property to eligible households. Households of affordable housing pay a lower price (or rent) than the market price (or rent). Studies abroad have gone through three stages in terms of the measurement of the benefit of housing assistance. In the first phase, housing benefits are simply determined by the difference between the market housing rents and security housing rents, which, however, ignores consumers’ preferences (Hammond 1987). The second stage is based on the calculation method of Marshall’s consumer surplus theory, with which Aaron (1971) and Bish (1969) made estimates on the benefits of public rental housing tenant households. This approach allows the further improvement of housing security benefits estimation. Yet the extremely strict assumption in Marshall’s consumer surplus theory, that is, the income elasticity is “zero”, has been widely questioned. For example, Olsen & York (1984) did empirical researches on controls of New York public housing and rents in 1965, finding that it could not draw the correct conclusions about the redistributive effects with rental difference and Marshall’s theory. Later, more and more scholars, for instance, De Salvo (1975), Olsen and Barton (1983), Yoon and Kim (1997) and De Borger (1986, 1987) attempted to take advantage of Hicksian EV to measure the income of public housing tenants. From the perspective of public housing tenants’ earnings, Hicksian EV refers to the income support the tenants need in order to achieve the same utility level of housing price subsidies. This method takes into account both the income effect and the price effect, which, therefore, is extensively recognized and used by numerous scholars. By transforming the utility change into the income change, the benefits change of tenants pre and post entering the housing security system can be measured by monetary form as is shown in Fig. 1.
.
..
Fig. 1. Housing benefit for households who enter the housing security system
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The analysis starts from the hypothesis in which there just is housing service and other goods in the consumption of households. As Fig. 1 shows, the horizontal axe and vertical axe represent respectively demands for housing and other goods. Before entering the housing security system, the household’s optimal behavior is to maximize his/her utility in the consumption of housing service and other goods under a given income (I0 ) and housing price (PM ). That is I0 ¼ PM H þ X. It is defined the cut-off point E0 (I0=PM , X0 )as the indirect utility function which shows the maximum utility level that the household can get with given income (I0 ) and housing price (PM ). As the household obtaining the housing security, the price paid for housing service fall, while housing prices of other goods remained. In order to achieve a higher level of utility, the household will increase the number of housing consumption, and then income budget line moves to the right side. Then the optimum consumption point in this case becomes E1 (I0=PS , XS ). Therefore, income equivalent variation EV is calculated from the difference between the utility on the commodity bundle at E1 and the expenditure on the commodity bundle at E0 , which is denoted by DU ¼ US U0
ð1Þ
The compensated budget line is an analytical tool to express the monetary change to keep the actual utility level of household unchanged, which can be introduced to calculate the income difference between the utility. The compensated budget line CD, which stands for the level of income IE, as Fig. 1 shows, is parallel to the line AB while it remains tangent to the indifference curve Us. the level of income IE is equal to the level of income to keep the utility level under the housing guarantee system, and it satisfies this constraint: IE ¼ PM H þ X . Therefore, income equivalent variation EV can be indicated as follows: EV ¼ UE U0 ¼ IE I0
ð2Þ
4 Methodology of Estimating Housing Benefits Utility function is an important tool to describe consumer’s preferences in Western economics. As described using indifference curve above qualitatively, a utility function is established to estimate the housing benefits change of households quantitatively. (1) Initial consumption combination of households To obtain the theoretically correct utility in the market, it is assumed that the price of housing in the housing market is PM . The consumer’s optimal behavior is to maximize his or her utility in the consumption of housing service and other goods under a given income (I0 ). The utility function is as follows: MaxUðH; XÞ s:t: I0 ¼ PM H þ X
ð3Þ
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The variable H is defined as the demand for housing area and X is the non-housing expenditure in the basic living expenses. By solving the above utility maximization model, the optimum consumption combination ðH0 ; X0 Þ and the maximum value of utility U0 are obtained: H0 ¼ HðI0 ; PM Þ
X0 ¼ XðI0 ; PM Þ
U0 ¼ UðH0 ; X0 Þ ¼ U½HðI0 ; PM Þ; XðI0 ; PM Þ
ð4Þ
(2) Consumption combination of households who acquire the housing security As the household enter the housing security system, the price PS that paid for housing service always meets the following constraint: PS \ PM . Naturally, the optimum consumption combination ðHS ; XS Þ and the maximum value of utility US can be described as follows: HS ¼ HðI0 ; PS Þ
XS ¼ XðI0 ; PS Þ
US ¼ UðHS ; XS Þ ¼ U½HðI0 ; PS Þ; XðI0 ; PS Þ
ð5Þ
(3) Formulating the consumption combination of households based on EV The level of utility (UE ) based on EV is equal to the actual level of utility (US ), and the cut-off point (E2) where the compensated budget line CD remains tangent to the indifference curve (UE ) is the optimum consumption combination that the household obtain. UE ¼ US ¼ U½HðI0 ; PS Þ; XðI0 ; PS Þ ¼ U½HðIE ; PM Þ; XðIE ; PM Þ HE ¼ HðIE ; PM Þ XE ¼ XðIE ; PM Þ
ð6Þ
(4) The utility function form The Cobb–Douglas function, the CES function or the Stone–Geary function are often used as an explicit form of utility function. In comparison, the Stone–Geary function is more suitable for analysis in measuring EV in the view of the fact that it is more flexible in the income elasticity limit, and there are no special requirements on the minimum consumption level. Therefore, this paper adopts the Stone–Geary utility function. The above formula is modified as follows: UðH; XÞ ¼ ðH hH Þc ðX hX Þ1c
ð0 c 1; hH H; hX XÞ
ð7Þ
In the equation above, c represents the marginal propensity to spend on housing. The EV can be derived from applying Eq. (7): EV ¼ PM hH þ hX þ ðPM =PS Þc ðI0 PS hH hX Þ I0
ð8Þ
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5 Empirical Analysis 5.1
The Data
(1) Estimation of market price The market price is the required price keeping the same quality of the commodity housing from the housing market in the absence of subsidy, which can be estimated by the Hedonic price model. The basic principles of Hedonic price model is to decompose housing prices into different characteristics of aggregation (such as size, location, environment, etc.), and then explore the relationship between housing price and these characteristics. Since Rosen (1974) introduced the Hedonic price theory into the housing market analysis, many scholars have put it into the research in the field of public housing (Antoninis, Tsakloglou, 2001; Marial, Vaalavuo, Verbist, 2006; Frick et al. 2010). According to the Hedonic price theory, the relationship between housing price and its characteristic factors is analyzed by multiple regression model and semilogarithm function in this paper. In this model, the house price is dependent variable, and structure characteristics (including areas, building ages, orientation, degree of decoration, number of living-rooms, number of bed-rooms), neighborhood characteristics(including hospitals, schools, parking spaces, property fee), location characteristics (including distance from the CBD, traffic facilities) are independent variables, which contain a total of 12 indicators. According to the 1084 commercial housing transaction data collected from the online real-estate database of Nanjing, the regression coefficients of Nanjing commercial housing characteristics are obtained as is shown in Table 1.
Table 1. Hedonic price regression coefficient of sample Coefficients
Standard error
t
3.093
.065
47.500
.000
Areas
.066
.010
12.308
.000
Number of Bedrooms
.059
.017
3.451
.001
Number of Living-rooms
.082
.020
4.166
.000
Building Ages
.001
.001
1.765
.078
Decorate Degree
.082
.011
7.678
.000
Orientation
.246
.034
7.172
.000
Parking Spaces
.462
.052
8.885
.000
Independent (Constant)
Sig.
Property Fee
.345
.017
19.700
.000
Hospitals
.012
.008
1.500
.034
Schools
.052
.010
4.983
.000
Transportation Facilities
.017
.055
3.570
.000
.018
.011
19.766
.000
Distance from CBD
R2
.810
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From Table 1, the determination coefficient R2 is 0.810, which shows that the model fits very well with a strong linear relationship between independent variable and dependent variable. Based on the regression results above and the data of affordable housing family collected from Nanjing Housing Administration during 2011–2013, which concludes a total of 26 affordable housing district, 9468 households, the average market price of these affordable housing are calculated as shown in Table 2. Table 2. Estimation for the Market Price of Affordable Housing Number
Average Market Price
Number
Average Market Price
11626.69
14
16451.79
9824.28
15
10391.64
3
8830.15
16
9046.74
4
9415.72
17
7741.67
5
9353.93
18
8894.16
6
12104.19
19
9094.55
7
11115.37
20
14142.93
8
12517.87
21
8080.74
9
6475.74
22
13564.81
10
13295.81
23
11955.85
11
14585.81
24
9202.09
12
11933.33
25
12774.76
13
13529.09
26
10581.40
1 2
(2) Estimation of the actual price The real price of affordable housing is determined by the local government. In general, the department of housing management should announce the affordable housing prices publicly. Thus, the data can be acquired from the government website. According to the data announced by the Nanjing government, it shows that the real price of affordable housing is 5200 RMB/m2, ranging from 40 m2 to 160 m2. (3) The marginal propensity of housing consumption The marginal propensity of housing consumption is the willingness of income proportion spent on the housing expenses, which can be estimated by Eq. (9). CH ¼ b þ cI
ð9Þ
Where, CH is the average housing consumption expenditure of urban residents, I is per capita disposable income of urban residents, b is the constant and c is the marginal propensity of housing consumption.
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According to the data collected from the national bureau of statistics during 2003– 2012, the regression analysis is implemented by adopting the household expenditure as the dependent variable and the disposable income as independent variable. The results are shown in Table 3.
Table 3. The marginal propensity coefficient of housing consumption Independent (Constant) Disposable income
R2
Coefficients
Standard error
t
Sig.
1282.655
156.251
8.209
.000
.188
.010
19.327
.000
.979
According to Table 3, it shows that the marginal propensity of housing consumption for town resident is about 0.188 in China, that is to say, a household is willing to spend RMB 18.8 on housing expenditure when the income is RMB 100. (4) The minimum level of housing consumption The minimum level of housing consumption is the minimum standards that should meet the basic need of family housing consumption, which can be represented by the required minimum standard of urban residents by the government. According to the current living standard of Nanjing, the minimum housing area of residents is 15 m2. (5) The minimum level of non-housing consumption The minimum level of non-housing consumption can refer to the income level of urban impoverished population (Stone 2006; Kutty 2005). In China, the level can be represented by the subsistence security standards of urban residents in each city. According to the data announced by the civil affairs bureau of Nanjing, the subsistence security standard is RMB 540 per person in 2013. (6) The income of tenants The income data is collected from affordable housing household during 2011–2013 located in main urban area in Nanjing. The number of sample is 9468, including 2404 in 2011, 3506 in 2012, 3558 in 2013. The income distribution is mainly concentrated between the RMB 1000 to RMB 4000. 5.2
Distribution of Benefits
In order to analysis the benefits difference of household with varying income levels, the tenants is divided into five groups, which are under 500, (500,1000], (1000,2000], (2000,4000] and above 4000. The distribution of benefits among different groups is estimated and the results are shown in Table 4.
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Table 4. The distribution of benefits among different groups during 2011–2013 in Nanjing Year Income (RMB) 2011 Under 500 (500,1000] (1000,2000] (2000,4000] Above 4000 Total 2012 Under 500 (500,1000] (1000,2000] (2000,4000] Above 4000 Total 2013 Under 500 (500,1000] (1000,2000] (2000,4000] Above 4000 Total
5.3
Number 148 460 1105 640 51 2404 161 567 1581 1087 110 3506 151 775 1308 1165 159 3558
Proportion 6.16% 19.13% 45.97% 26.62% 2.12% 100.00% 4.59% 16.17% 45.09% 31.00% 3.14% 100.00% 4.24% 21.78% 36.76% 32.74% 4.47% 100.00%
Average 357.52 257.98 322.72 744.14 1350.34 586.82 376.91 436.98 554.32 750.15 1005.25 602.01 356.42 409.73 585.91 784.74 1087.54 633.8
Maximum 681.05 737.85 1164.52 1348.87 1991.09 1991.09 774.78 891.25 1126.33 1572.05 1643.01 1643.01 798.93 826.51 1182.11 1593.69 2615.83 2615.83
Minimum 214.5 428.77 556.97 476.74 761.29 214.5 209.69 253.11 308.86 346.71 620.89 209.69 262.45 324.21 401.65 514.97 760.3 262.45
The Change of Gini Coefficient
To analyze the income redistribution effect of affordable housing, the Gini coefficient index is adopted. Based on the housing benefits estimated above, the Gini coefficient change of pre and post-obtaining affordable housing is analyzed. The results are shown in Table 5.
Table 5. Gini coefficient of pre and post-obtaining affordable housing Category Gini coefficient Pre-G 0.2893 Post-G 0.2075
5.4
The Results
According to the data results analyzed above about the distribution of benefits among different groups and Gini coefficient of pre and post-obtaining affordable housing during 2011–2013 in Nanjing, some important results can be got as follows. According to the Gini coefficient’s change of the pre and post-obtaining affordable housing, it shows that affordable housing play a positive role adjusting the income effect. In the absence of housing security, the Gini coefficient is 0.2893, while after
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obtaining affordable housing, the Gini coefficient is 0.2075. That is to say, the Gini coefficient of Nanjing is reduced by 28%, which shows that affordable housing policy is beneficial to reduce the income gap of residents. The empirical analysis show that the average benefits of affordable housing tenants is about RMB 600 in 3 years recently. The income change caused by housing security benefits accounts for about a quarter of their income, which means that the income of eligible households can be increased by 25%. This shows that the income effect of housing security policy is very obvious, which plays a very important role in improving residents’ income and increasing household wealth. It can be observed that the proportion of the income group between 1000 and 2000 obtained housing benefits is highest, which account for nearly forty percent of affordable housing tenants. However, the income group between 2000 and 4000 has a rising trend, which suggests that the range of housing security is expanding gradually and more household with higher income are able to enjoy the benefits brought by affordable housing. The benefits obtained by affordable housing household in different years are increasing gradually. The results show that the average welfare is about RMB 586.82 per month in 2011, RMB 602.01 per month in 2012, while has risen to RMB 633.80 per month in 2013. The phenomenon of this change is mainly attributed to a wider range of eligible households with higher income. They have a higher consumption ability to purchase a larger area of housing. It can be found that there are gaps in the absolute values of the benefit among different income groups. The results indicate that the benefits obtained by the higher income group are more than the lower one. For example, the benefits gained by the highest income group (above RMB 4000) are three times more than the lowest income group (below RMB 500). The results show that the income distribution effect of affordable housing is different for different eligible households, which indicate that it will give rise to the new inequalities among affordable housing tenants. The reason for which is that high-income family can afford to buy a larger areas of housing, and thus get more benefits. The housing welfare gained from subsidies of affordable housing for those sheltered families is mainly from the gap between the real market price and the price of affordable houses. For those applicants, regardless of their financial status, the price of affordable houses is the same. Considering the condition that higher-income families are able to afford to buy bigger houses than that of low-income families, the inequality then arises.
6 Conclusion In this paper, Hicksian EV model and Gini coefficient are adopted to estimate the redistribution effect of affordable housing on the income distribution in China. The results of empirical analysis show that affordable housing policy play a significant role on income redistribution, which is of great significance to narrow the income gap. Faced with a stern fact that the income gap is widening increasing since its reform and opening up in China, the implementation of affordable housing policy, it will be of great realistic significance obviously to alleviate the income gap of residents.
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However, the research results indicate that the benefits of housing security among different income groups are different in this paper. The benefits obtained by the higher income group are more than that lower one. That is because the eligible family with higher income can choose to buy a large area of affordable housing, while lowerincome families can only buy the small one due to the limitation of housing price and affordability, which causes the difference of housing welfare occurred among different income groups, and then a new unfair come into being. That is to say, the affordable housing policy will induce new inequity among tenants, which suggests that the current housing policy cannot achieve the goal of vertical equity. Therefore, it is necessary for the government to adjust the current housing policy. Firstly, the standards of affordable housing should be limited. When the standards of affordable housing are different, the houses with better standards are often acquired by higher income families. While restricting the standards of affordable housing, the phenomenon that the subsidized households get different housing benefits can be avoided. In the case of unified housing standard, it will ensure that every household obtain the similar benefits, and thus the income gap among subsidized households can be narrowed. Secondly, it is necessary for the government to adjust the current housing policy in order to make a change from in-kind subsidies to monetary subsidies. In the case of inkind subsidies, the same housing subsidies are obtained by different income families on account of the immobility and inalienability of housing, which is not conducive to realize the aim of vertical equity. While in the mode of monetary subsidies, different household can get different subsidies according to their household income and housing circumstance. The higher income they have, the lower subsidy they obtain, and vice versa. In this way, it will increase the benefits of low-income households by providing more subsidies, which will be beneficial to promote the realization of vertical equity. At the last but not least, the scope of housing security should be expanded further. With the rising of housing prices, the households with home-ownership housing will get more and more richer, which will further wide the income gap between families with home-ownership housing and families without home-ownership housing. From the view of income distribution, it is necessary for the government to enlarge the benefits of housing security policy. Only then can the widening trend of polarization between the rich and poor be reversed at a greater degree in China. Not only it helps to realize the goal of vertical equity but also achieve the goal of horizon equity. Acknowledgement. Funding Statements: Humanities and Social Sciences Fund Project of Henan Province Education Office (2017-ZZJH-527); Innovation Development Fund of Management Engineering College at Zhengzhou University (20170613).
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Research on Relationship Between the Real Estate Prices and Technological Innovation Through Human Capital in China Zhang Hong1(&), Chen Yingying1, and Li Vera2 1
Center for Urbanization and Industrial Development/Hang Lung Center for Real Estate, Tsinghua University, Beijing 100084, China [email protected] 2 Department of Accountancy, Hang Seng Management College, Shatin 999077, Hong Kong
Abstract. This article mainly researches on the direct and indirect path of impact of the real estate prices on technological innovation through human capital. Then we build the theoretical impact model of the real estate prices on technological innovation through human capital utilizing the Cobb Douglas production function. Finally, we select panel data of 30 provincial administrative regions in China in 2006–2016 and use the fixed effect model to empirically test the impact of real estate prices directly and indirectly on technological innovation through human capital. This research shows: the real estate prices significantly inhibit the technological innovation directly and indirectly through human capital, based on which this article gives several suggestions on the real estate policy, the city and the industrial structure, the quality of human capital and the cities highly relying on importation. Keywords: Real estate prices
Human capital Technological innovation
1 Introduction China’s reform and opening to the outside world not only has brought about rapid development, it also has raised the housing price, which caused some social problems paid wide attention, including the effect of high house prices on the extrusion of human capital. Particularly, in 2016, an article of the People’s Daily Commentary on high house prices and personal struggles [1] caused a heated discussion on the relationship between human capital and house prices. Actually, the discussion of the inhibition effect of high house prices on young people has long been discussed. One well known example is that a Ph. D graduate from top2 university can’t afford to buy a house and leave Beijing to a second-tier city. The reason for this phenomenon is that the price of real estate is much higher than the income of residents, making it difficult for residents to buy one. Foundation item: National Natural Science Foundation of China (Grant No. 71373143) © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 412–425, 2021. https://doi.org/10.1007/978-981-15-3977-0_31
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In 2016 and 2017, there are 9 cities in China with a price-to-income ratio up to 10 (internationally considered 4–6 as a reasonable range). What’s worse, this mismatching is still increasing. And it need to be paid attention that on the one hand high real estate prices increase government revenue to enhance the level of technological innovation investment in research and development [2] and on the other hand they also raise the cost of the laborer living, corporate office and the labor cost. It will result in an employment decrease of technological innovation, which force the human capital face enormous negative constraints. Economic transformation and upgrading have become the only way for China to enter the new normal economic situation. Therefore, technological innovation has become the core driving force for economic and social development. However, with the global competitiveness continuously improving and the technological innovation making rapid progress [3], there is a problem of low conversion rate of scientific and technological achievements. At the same time, the enterprises which occupy more than 70% of the research and development (R&D) investment are facing the situation of difficult financing. Moreover, technological innovation itself has features of high risk, long return cycle, complexity and high uncertainty, which has limited the technological innovation process in China. Scholars at home and abroad have studied the impact housing prices having on technological innovation relatively comprehensively. The widely recognized theory about real estate prices abroad is the financing mitigation effect [4] and the crowdingout effect [5, 6] to other investments based on the real estate bubble theory, while domestic research generally studies the impact of real estate price on technological innovation from the aspect of the crowding-out effect [7–12]. And researchers abroad study the impact of the real estate price on human capital and the impact of human capital on technological innovation. However, few directly research on the role of human capital between the two impact mechanisms. By contrast, the domestic research on the impact of real estate prices on technological innovation through human capital is mainly from the two aspects of the scale and structure of employment. Few scholars have directly incorporated the transmission function of human capital to analyze the impact of real estate prices on technological innovation. When selecting index of the explanatory variables, most researchers use the technological production as the agent variable of technological innovation ability, seldom considering the input. When selecting index of the explanatory variable, most use the education year method to measure the human capital not considering the role human capital play in the relationship of real estate prices and the technological innovation. When selecting control variables, the variables selected by different researchers are also different. If we can reveal the relationship among the real estate prices, human capital and technological innovation, we will be able to find the inner mechanism of real estate prices directly and indirectly impact on technology innovation through capital. And basing on this, this article uses 30 provincial administrative region panel data in 2001– 2016 to empirically test the impact of real estate prices directly and indirectly having on technological innovation through human capital, by means of the fixed effects model, to verify this direct and indirect effects of path.
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2 Research Method The research method of real estate prices impact technological innovation through human capital is: 1. Analyze the relationship among the real estate prices, human capital and technological innovation to obtain the transmission path of the impact. Firstly, this paper studies the relevance of the rising real estate prices and human capital from the influence of the rising real estate prices on human capital, the effect theory of the national economic development and the changes of the three parts. Then basing on the relevance we establish the game model between the enterprises and the laborers, we analyze the influence of the rising real estate prices on technological innovation through human capital. Finally, the transmission path of the real estate price, human capital and technological innovation is obtained. 2. Construct a theoretical model based on Cobb Douglas function. According to the transmission path, the function relationship between the real estate price and the technological innovation ability is derived and then the theoretical model is designed. 3. Select data to do empirical analysis. The panel data of 30 provincial administrative regions in China in 2006–2016 years are used for empirical analysis and robustness test.
3 Theoretical Analysis 3.1
Relevance Analysis
The rise in real estate prices, on the one hand, will lead to higher living costs which makes people flow to areas with lower real estate prices. On the other hand, the rising real estate prices will also increase the human costs and office costs which leads enterprises to choose to settle in another more attractive city, thus triggering the flow of human capital [13]. At the same time, rising real estate prices will lead to inflation, and thus transmit to other national economy fields, bringing about an increase in the cost of technological innovation [14]. And it will bring different effects according to the different roles real estate plays in economy. Firstly, the real estate as a financing tool has the financing effect. That is, the rising real estate prices increase the valuation of the enterprises and brings more credit resources. Secondly, as an investment channel, the real estate is a department without technology spillover (nonproductive assets). So the rise of real estate price will generate crowding-out effect to the departments with technology spillover (productive assets) [6], which has an inhibitory effect on the technological innovation of the enterprises. Thirdly, the difference of the marginal technical substitution rate of the two departments input factors causes the changes of the substitution effect of the financing effect to the crowding-out effect, which will lead to the promotion or inhibition of the real estate price rise to the technological innovation [7]. Lastly, the real estate as a production factor and the price rise will cause direct cost
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effect and indirect cost effect to the technological innovation. On the one hand, the price rise has an inhibitory effect on the enterprise technological innovation by raising the office cost. On the other hand, it leads to the increase of human cost and raw material price and triggers inflation and the related influence, which will finally limit the development space of the enterprises. As shown in Fig. 1, the rising real estate prices (P1 to P2) lead to the cost of the innovation departments for the rental plant and other office places and the cost of human capital (C1 to C2). So under this premise, the profit space of the manufacturers is squeezed. Moreover, because the general innovation activity is long-term, then based on the hypothesis of the maximization of the profit of the manufacturers, the manufacturer will reduce the innovation investment in the short term. Eventually it will lead to the movement of innovation input (including human input and capital input) from I1 to I2, which will affect the speed of the level of technological innovation.
Fig. 1. Relationship of real estate price and enterprise cost ad innovation investment
The growth rate of R&D input growth rate represents technological innovation and the rate of wage growth represents the level of human capital. Figure 2 shows the relationship of real estate prices, human capital wage and R&D input. As can be seen from the graph, the growth rate of real estate price and the intensity of R&D expenditure are positively correlated. The growth of high wage level may inhibit the R&D input. 25.00% Wage growth rate 20.00% Real estate price growth rate
rate
15.00%
R&D input growth rate
10.00% 5.00% 0.00% 2007
2008
2009
2010
2011
2012
2013
2014
2015
year
-5.00%
Fig. 2. Relationship of real estate prices, human capital wage and R&D input
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Therefore, the rapid rise of the real estate price increases the living cost of the residents, forcing the enterprises to pay higher salary, which leads to the increase of the human cost of the enterprises. In summary, the cost of the technological innovation of the enterprise rises with the rise of real estate prices, and the technological innovation activities are inhibited. 3.2
Relevance Analysis
On the one hand, the rise of real estate prices leads asset appreciation, bringing additional benefits to enterprises, which promotes technological innovation to a certain extent. On the other hand, it also has a direct impact on the cost of social and economic operation. For individuals, it has improved the living cost so some choose to mitigate to low price areas which reduces individual innovation and entrepreneurship activities. For enterprises, it has improved the operating cost of enterprises and has a negative impact on the technological innovation of region and enterprise. Human capital is the core factor for enterprise production. It is the carrier from materials to production and service, which is related to the fundamental problems of the survival and development of the enterprises [15]. So its cost rise has a direct negative impact on the technological innovation activities of the enterprise. Therefore, enterprises need to continuously expend the cost to support the technological innovation of human capital, and transform the operating cost into value output through the technological innovation of human capital. The rise of real estate prices will promote technological innovation on the one hand, and on the other hand, it will have a negative impact on the workers and the operation of enterprises. The appreciation in asset value brought by the rising real estate price makes the investors gain more credit funds to increase the investment in technological innovation. At the same time, the steady rise in real estate price will create laborers’ long-term expectation of the rising of living cost, which encourages the laborers to improve their own ability to improve their innovation efficiency. But the rise of real estate prices will also force some workers to work and live in lower price cities at the expense of the work quality because of the increase of the living cost. This crowdingout phenomenon causes the waste of human capital [16] and distorts the normal population flow [17]. Besides, the rising real estate prices also affect the workers’ preference for innovation and entrepreneurship, and make them incline to choose a stable career. This employment structure is not conducive to the development of technological innovation [18]. And high house prices will also force the residents to invest most of their savings to buy a house, thus reducing the resources for innovation and entrepreneurship [19]. From the view of the enterprise management, the rise of real estate price will also bring enterprises’ short-term management behavior and make the enterprise innovation power insufficient. It also has a negative impact on the structure of the enterprise’s position supply. In addition, the enterprise’s operating cost increases, resulting in the rise of total cost, so the expected return rate and the acceptable risk of the enterprise are reduced. Finally, the investment of high risk innovation projects is suppressed. Meanwhile, enterprises can face the problem of insufficient human capital reserves for the flow of laborers.
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In order to characterize the transmission relationship between real estate prices, human capital and technological innovation, we make the following assumptions: 1. Workers accordance with the rational human hypothesis. 2. The enterprise seeks for the maximization of the interests. The impact of real estate prices on technological innovation of enterprises is generated by the intermediary role of human capital. It is assumed that the living cost of real estate prices is raised to Cs(X), the living cost is raised to Cj(X), and the development cost of worker X is raised to Cf(X). The workers’ expected growth rate of normal income is l, removing the impact of real estate prices. And the impact of other risk factors is e (regarded as a coefficient). Then under the condition that real estate prices are rising rapidly, workers’ expected compensation for income (expected income) is: EðxÞ ¼ ðCsðXÞ þ CjðXÞ þ Cf ðXÞ þ lÞe
ðFormula 1Þ
The conditions for the enterprise Y to satisfy the workers’ income are as follows: UðYÞ ¼ RðXÞ EðxÞ Cc [ 0
ðFormula 2Þ
Among them, Cc is the other production cost of the enterprise (regarded as constant) and R is the labor output of the laborer (the labor income gained by the enterprise). The Stackelberg game model is built as follows: UðYÞ ¼ RðXÞ EðxÞ C [ 0 s:t: EðxÞ ¼ ðCsðXÞ þ CjðXÞ þ Cf ðXÞ þ lÞe
ðFormula 3Þ
Establish a simultaneous equation, and the first-order derivative results of X reflect the marginal impact of the enterprise on the satisfaction degree of the various parts of the workers’ expected income. Further analysis of the game strategy between enterprises and workers. The cost of the workers entering the enterprise is C, the cost of the enterprise is C(X), the condition of the enterprise to satisfy the worker is R(X) − C(X) > 0, and the gain of the laborer is E(X) − c. Otherwise, the gain of the laborer is -c, and the gain of the enterprise is –C (X). When the worker does not satisfy the condition of the enterprise supply, the enterprise is willing to accept the worker, then the income of the laborer is -c, the profit of the enterprise is -C(X). When the worker satisfies the payment condition of the enterprise, but the enterprise does not accept the worker, the income of the worker is -c, the profit of the enterprise is -C(X). When both sides are not satisfied conditions, there will be no contact between enterprises and enterprises, so the income of the laborer is – c and the profit of the enterprise is -C(X). To simulate the game behavior between workers and enterprises, the game matrix is as follows (Table 1): Therefore, the best strategy for an enterprise is to reach agreement with the laborers and raise the profits of the enterprises to meet the profit requirements through raising the output level of the laborers. In the end, the macro environment of rising real estate
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prices leads workers to demand high salaries, and enterprises can only passively pay them to meet workers, in order to maintain the normal operation of enterprises. And when workers’ incomes rise, they may further trigger higher housing prices, which will bring about the vicious circle. For the enterprises, the high cost of human resources will lead to the reduction of the labor use and the control of other departments’ expenditure, especially for the technological innovation department with high risk and high uncertainty. Finally, enterprises choose to employ less laborers and reduce the technological innovation. In the context of the rapid rise in real estate prices, the positive substitution rate of the value appreciation benefits is far lower than the negative effects of the impact brought by the impact of human capital on the technological innovation. Basing on that, we can draw the transmission path of real estate prices, human capital and technological innovation, as shown in Fig. 3.
Fig. 3. Transmission path of real estate prices, human capital and technological innovation
4 Model Building 4.1
Derivation of Transmission Path
According to Joseph Schumpeter’s technology promotion hypothesis, innovation is the combination of production factors and production conditions, which mainly depends on the degree of labor division of (the existing technical level), the accumulation of
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professional human capital and the investment of funds. So this paper derives the function relationship between the innovation ability and the real estate price through the capital variable and the human capital variable, which reflects the effect of the real estate price rising to the enterprise’s scientific research innovation and the decrease effect of the utility of human capital income. Assuming that scale returns remain fixed, the scientific output model of an economy is the Cobb Douglas function: Yt ¼ AKta L1a t
ðFormula 4Þ
Among them: Yt represents the quantity of scientific research output in the period of t. Kta represents the amount of the capital used for research and development in the period of t. L1a represents the number of scientific research laborers invested in the t period of t. A is a comprehensive technical level (regarded as constant). And the a is the elastic coefficient of capital output. Considering the crowding out effect of real estate investment to innovation investment and the amount of labor depending on the wage rate provided by the society, assume the crowding-out fund as M Prt , of which Prt is the long-term price level of real estate. And the real estate prices and the crowding-out effect have a 0 r positive relationship, that is, M ðPt Þ [ 0. c represents the elastic coefficient. W repjt
jt
resents nominal wage level of j research department in t period. Prt represents the longterm real estate price level of r region in period t. Then we get: Wjt 1a r a Yt ¼ A Kt M Pt cjt r Pt
ðFormula 5Þ
On the partial derivation of Prt for Y: @Y K M a1 a2 ¼ A P ð1 aÞ ðK M Þ aM 0 ðPÞ\0 @Pr cW It can be seen that the real estate price is negatively correlated with the output of scientific research through the crowding-out effect and the declining effect of human capital income utility. Based on the above theoretical analysis, the following two basic assumptions are made: H1: the faster the real estate price goes up, the slower the technological innovation level will be. H2: real estate prices rise through the extrusion of human capital investment, thereby inhibiting technological innovation.
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4.2
Model Design
Based on previous research hypotheses, this paper is based on empirical models of different regions: TIit ¼ a0 þ a1 HPit þ a2 HCit þ a3 HPit HCit þ dZ þ eit
ðFormula 6Þ
Among them, HCit represents human capital investment of i area in t period, and HPit HCit is a crossing item between real estate price and human capital. 4.3
Variable Design
Taking innovation output and input as the key variable to measure technological innovation ability and technological innovation level, the comprehensive index of regional per capita patent award and the proportion of regional R&D input to GDP is selected as the explained variable (TI). In the selection of explanatory variables (HP, HC, HP*HC), the proportion of R&D to the population of the area is chosen as the variable of human capita. And the real estate price of newly built residential commodity is selected as the variable of the house price. The control variable vector Z includes: 1. The actual per capita GDP (PGDP) in the region is the ratio of GDP to population in the region. 2. The regional industrial structure (IS) is the proportion of the second, third industries to the GDP of the region. 3. Open export level (EL), is the proportion of regional exports to GDP. 4. Open import level (IL), is the proportion of regional imports to GDP.
5 Empirical Analysis This paper selects panel data from 30 provinces in China (data of Tibet is eliminated) in 2006–2016 to conduct an empirical analysis, with a total sample size of 330. These data come from the EPS database. The descriptive statistical analysis of the main variables is as in Table 2. The statistical analysis shows that the panel data varies widely. The difference in different factors is huge, no matter in the overall scale, or between and within the groups. The difference among cities is because the economic and technological development of different cities has a great diversity. The difference in different years is because the economic and technological development and the focus of policy are in flux. The relevance analysis is done as the following Table 3: From the relevance analysis, we can find that most of the factors are highly relevant. Particularly, the housing price, human capital, crossing item between housing price and human capital and per capita GDP are highly relevant to the technological innovation ability of different regions. Based on this phenomenon, we can infer that
Research on Relationship Between the Real Estate Prices and Technological Innovation Table 2. Descriptive statistical analysis Variable TI Overall Between Within HP Overall Between Within HC Overall Between Within HP*HC Overall Between Within PGDP Overall Between Within IS Overall Between Within EL Overall Between Within IL Overall Between Within
Mean 3.70
Std. Dev. 4.58 3.89 2.51 5.14 3.69 3.22 1.89 21.75 23.00 22.30 6.86 183288 393770 360209 171019 38679.63 22827 18582 13647 0.97 0.53 0.50 0.20 3.86 7.58 4.13 6.40 3.59 8.41 5.22 6.66
Min 0.25 0.75 −5.86 1.58 3.03 −3.79 1.45 4.94 −4.46 4609 16056 −843357 5787 17614 −617 0.50 0.61 0.21 0.22 0.52 −3.48 0.12 0.27 −8.17
Max 26.12 14.38 15.45 28.49 16.30 17.33 116.58 109.61 45.63 3321357 1802370 1702275 118198 84446 74652 4.17 3.31 1.87 74.03 15.96 61.93 89.73 23.27 74.57
Table 3. Relevance analysis TI HP HC HP*HC PGDP IS EL IL
TI 1 0.825 0.865 0.807 0.821 0.535 0.506 0.563
HP
HC
HP*HC PGDP IS
1 0.845 0.918 0.817 0.77 0.484 0.734
1 0.904 0.824 0.691 0.386 0.593
1 0.733 0.822 0.374 0.728
EL
IL
1 0.483 1 0.482 0.209 1 0.565 0.597 0.721 1
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there exists some certain relationship among these factors. And the correlation coefficients of industrial structure, open export level and open import level to technological are all greater than 0.5, which can be studied to find if there are relationships among them. Besides, some of these explanatory variables are also high relevant, such as housing price and human capital, per capita GDP and housing price, per capita GDP to human capital, industrial structure and human capital, industrial structure and housing price, open import level and housing price, and open import and open export level. Based on the panel balance test, autocorrelation test, heteroscedasticity test and unit root test, the model form test is conducted and finally determine the fixed effect model for empirical analysis. The empirical test of the relationship between real estate price, human capital and regional technological innovation is as in Table 4.
Table 4. Empirical test Dependent Coef. P > |t| Dependent Coef. P > |t| variable: TI variable: TI HP −0.3018*** 0.1044 Cons. −1.8980*** 0.4116 HC 0.1320*** 0.0168 F 230.15*** HP*HC 9.61E − 06*** 9.24E − 07 P 0.0000*** PGDP 4.69E − 05*** 1.09E − 05 R2 Within 0.8461 IS 0.8183* 0.4232 Between 0.7775 EL 0.0560*** 0.0154 Overall 0.7531 IL −0.0849*** 0.0176 Note: *, ** and *** respectively indicate that the coefficient estimates are significant at the level of 10%, 5% and 1%.
The results of the empirical test show that: 1. There is a negative correlation between China’s housing price (HP) and technological innovation (TI). The acceleration of house price growth will slow down the growth of technological innovation. 2. There is a negative correlation between human capital (HC) and technological innovation (TI). The promotion of human capital will bring the improvement of technological innovation capability. 3. The cross effects of human capital and housing prices (HC*HP) are positively related to technological innovation (TI). 4. The per capita GDP (PGDP), the proportion of the second and third industries (IS) and the open level of exports (EL) have positive correlation to technological innovation. And there is a negative correlation between import level (IL) and the technological innovation (TI). So the research shows that: 1. The impact of real estate prices on technological innovation can be conducted through human capital, and the improvement of human capital can significantly promote technological innovation.
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2. The increase in housing prices leads to a reduction of laborers of technological innovation and it generates a significant inhibition effect to technological innovation. The rising real estate price forces laborers to ask for higher wage for higher living cost expectation, resulting in the rise in labor force cost of the enterprises. Then some enterprises have to turn to employ less laborers and pay more expenditure on other essential productive factors to eliminate the negative effect of laborer decrease. In the end, it causes the human capital flow from technological innovative industries to other industries and among different cities, which brings about the redistribution of industries and human capital and the inhibition of technological innovation. 3. The regional per capita GDP (PGDP), industrial structure (IS) and open export level (EL) are positively related to technological innovation, indicating that regions of the better the economic development, the higher the proportion of second and third industry, the higher the level of the open export will have the higher the technological innovation ability. The open import level (IL) has a negative correlation with technological innovation ability, indicating that the regions of higher import dependence will have lower technological innovation ability. Replace the housing price variable (HP) with the average price (HP1) of all commercial real estate to do following robustness test (Table 5): Table 5. Robustness test Dependent variable: TI Coef. P > |t| Dependent variable: TI Coef. P > |t| HP −0.3034*** 0.003 Cons −1.8583*** 0 HC 0.1252*** 0 F 225.7200*** HP*HC1 0.0098*** 0 P 0 PGDP 0.0000*** 0 R2 Within 0.8436 IS 0.8149* 0.057 Between 0.7715 EL 0.0509*** 0.001 Overall 0.7466 IL −0.0748*** 0 Note: *, ** and *** respectively indicate that the coefficient estimates are significant at the level of 10%, 5% and 1%.
Research shows that: 1. The impact of real estate prices on technological innovation can be conducted through human capital, and the improvement of human capital can significantly promote technological innovation. 2. The increase in housing prices leads to a reduction of laborers of technological innovation and it generates a significant inhibition effect to technological innovation. The rising real estate price forces laborers to ask for higher wage for higher living cost expectation, resulting in the rise in labor force cost of the enterprises. Then some enterprises have to turn to employ less laborers and pay more expenditure on other essential productive factors to eliminate the negative effect of laborer
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decrease. In the end, it causes the human capital flow from technological innovative industries to other industries and among different cities, which brings about the redistribution of industries and human capital and the inhibition of technological innovation. 3. The regional per capita GDP (PGDP), industrial structure (IS) and open export level (EL) are positively related to technological innovation, indicating that regions of the better the economic development, the higher the proportion of second and third industry, the higher the level of the open export will have the higher the technological innovation ability. The open import level (IL) has a negative correlation with technological innovation ability, indicating that the regions of higher import dependence will have lower technological innovation ability.
6 Conclusions This paper analyzes the relationship between real estate prices, human capital and technological innovation, and thus derives the transmission path of their impact. Then we derive the function relationship between the technological innovation ability and the real estate prices. In the end, we select the panel data of the 30 provincial administrative regions in 2006–2016 to carry out empirical analysis and do robustness test. The research shows that rising real estate prices have negative effect on technological innovation while human capital has positive effect on it, and the effect on technological innovation by real estate prices can be transmitted by human capital. In order to minimize the negative impact of the rising real estate prices on technological innovation, the paper suggests that: 1. When making the real estate policy, the urban development and industrial planning should be considered to promote the rational flow of human resources among different industries. 2. It is necessary to optimize the allocation structure of the industries among different cities so as to achieve a reasonable match between industrial structure and human resources. 3. Our education system and enterprises should pay attention to improve the quality of human capital training and improve the value creation ability of human capital. 4. Attention should also be paid to improving independent technological innovation in areas with high import dependence. There still exit some weaknesses in this paper. Although this paper has chosen different variables to value the relevant factors, the variables still can not totally represent the factors which can be studied further. And for lack of data before 2005, the panel data elected is not big enough in time, so the data needs updating to test the results.
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References 1. Li, Z.: If we lose our struggle, we will be homeless even with many housings (in Chinese). People’s Daily Commentary (2016) 2. Chang, Z.Z.: The real estate bubble, the financial crisis and the adjustment of China’s macroeconomic policies (in Chinese), application of BOT system for infrastructure projects in China. Rev. Econ. Res. 07, 69–76 (2010) 3. An, T.L., Fang, Y., Alcorta, L.: Obstacles and Countermeasures of technological innovation in Chinese manufacturing enterprises – Based on the questionnaire survey of manufacturing enterprises in Jiangsu Province (in Chinese). Econ. Theor. Bus. Manage. 07, 41–46 (2005) 4. Tirole, J.: Asset bubbles and overlapping generations. Econometrica 53(5), 1071–1100 (1985) 5. Miao, J., Wang, P.: Sectoral Bubbles and Endogenous Growth. Meeting Papers, Society for Economic Dynamics (2012) 6. Chaney, T., Sraer, D., Thesmar, D.: The collateral channel: how real estate shocks affect corporate investment. Am. Econ. Rev. 102(6), 2381–2409 (2010) 7. Li, K.K.: Research on the impact of rising housing prices on enterprise innovation efficiency – Taking 16 cities in the Yangtze River Delta as an example (in Chinese). Market Weekly 10, 35–36 + 44 (2017) 8. Wang, J.Z.: Research on the impact of real estate industry on Chinese enterprises’ independent innovation activities – based on the analysis of Provincial Panel Data (in Chinese). Mod. Ind. Econ. 10, 30–39 (2013) 9. Wang, W.C., Rong, Z.: Housing boom and firm innovation: evidence from industrial firms in China. China Econ. Q. 02, 465–490 (2014) 10. Yu, Y.Z., Zhang, S.H.: Urban house price, limited purchase policy and technological innovation. China Ind. Econ. 06, 98–116 (2017) 11. Wang, R., Zhang, S.D.: Analysis of the impact of urban innovation capability on commercial housing prices (in Chinese). Shanghai J. Econ. 12, 113–119 (2016) 12. Li, P., Zhang, Y., Yang, L.N., Jiang, Q.: The evolutionary path of China’s real estate bubble to macroeconomic impact (in Chinese). Inq. Econ. Issues 4, 37–42 (2015) 13. Chen, B.K., Jin, X., Ou Yang, D.F.: Housing price, resource mismatch and productivity of Chinese Industrial Enterprises (in Chinese). J. World Econ. 04, 77–98 (2015) 14. Chen, L.J., Xu, B.: Human capital, technological innovation and structural adjustment of manufacturing industry – taking Ningbo as an example (in Chinese). Special Zone Econ. 10, 49–51 (2010) 15. Wu, A.H., Su, J.Q.: Human capital specificity, innovation capabilities and new product development performance. Stud. Sci. Sci. 30(06), 950–960 (2012) 16. Zhang, C.Y.: Labor mobility, housing price rise and urban economic convergence: an empirical analysis of the Yangtze River Delta (in Chinese). Ind. Econ. Res. 03, 82–90 (2016) 17. Wang, X.Z., Luo, Y.M.: On the relationship between the promotion of human capital and the rise of housing prices (in Chinese). Mod. Econ. Res. 04, 24–27 + 80 (2014) 18. Wu, X.Y., Wang, M., Li, L.X.: Is China’s high house prices a hindrance to entrepreneurship? (in Chinese). Econ. Res. J. 49(09), 121–134 (2014) 19. Li, X., Li, X., Wu, Y.: Housing price and entrepreneurship in China. J. Compar. Econ. 42(2) (2014)
Research on the Commercial House Price of Supply and Demand Elasticity Based on the Panel Data of China’s Four Municipalities Yanming Lyu1(&) and Mengxue Chen2 1
Department of Engineering Management, Sichuan Agricultural University, Ya’an, China [email protected] 2 School of Sichuan Agricultural University, Ya’an, China
Abstract. Based on the panel data from 2000 to 2016 of China’s four municipalities, this paper constructs a dynamic cobweb model that includes the price of real estate, per capita disposable income, interest rate, and other variables. Then, an empirical analysis of the price elasticity of China’s commercial housing supply and demand is conducted. The results show that for the supply side, the supply of residential real estate has a positive correlation with the real estate prices in the previous period and is insensitive to changes in the benchmark lending rates. For the demand side, the demand for residential real estate is positively correlated with the per capita disposable income of urban residents in the current period, and is negatively correlated with the real estate price in this period. However, the demand of residential real estate is not sensitive to price changes. This result may be due to the fact that the four municipalities are China’s economic and cultural centers. There are a large number of people are flooding into these cities. The increase in demand brought by the population boom far exceeds the decline in demand caused by rising prices. At the same time, the purchase restriction policy has played a certain role in suppressing speculative demand arising from price increases. Keywords: Commercial housing market model Supply and demand balance
Price elasticity Dynamic cobweb
1 Introduction With the rapid development of China’s economy, the real estate has become an important pillar industry for the development of China’s national economy thanks to its high relevance and strong driving force [1]. The average price of commercial housing in China rose from 1948 yuan per square meter in 2000 to 7203 yuan per square meter in 2016 [2]. The irrational soaring of housing prices in recent years has posed a potential threat to the sustainable development of China’s social economy [3]. The commercial house price elasticity not only can reflect the characteristics of supply and demand in the real estate market, but also can explain the change of commercial house © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 426–436, 2021. https://doi.org/10.1007/978-981-15-3977-0_32
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price. It plays an important role in measuring whether the real estate market is healthy or not, and it also can help decision makers to identify the regular of commercial house market, so as to formulate relevant policies. Muth R F’s research on “non-agricultural housing needs” in the paper “The Stock Demand Elasticities of Non-Farm Housing: Comment” is considered as the beginning of studies on housing demand in Western economics [4]. Thanks to the convenience of data acquisition, scholars from other countries have studied the demand and supply elasticity of the real estate market on the micro level. They not only consider the impact of income and price on housing demand, but also consider the effects of other factors such as different skin color, age, family size and income stability on the price elasticity of real estate demand. Polinsky A M and Ellwood D T selected relative sustained income and relative value of housing as independent variables, and conducted weighted least-squares method for housing price elasticity in 31 major cities in the United States [5]. Tong H L and Chang M K investigated the actual consumption area of housing in the United States. And they used panel analysis to study factors such as total income, relative housing prices, and characteristics of residents [6]. Carliner adopted the least square method and conducted an empirical study on the real income, the relative price of the house, skin color, gender, age and other factors by collecting the micro data of 4,565 consumers in the United States [7]. In recent years, scholars’ research on the real estate market is more and more novel. Liebersobn C J studied the regional changes in housing and consumption boom. The results show that the price effect of housing supply in non-elastic cities is stronger [8]. Based on theory and practice, Chen K S and Yang J J studied the relationship between housing price dynamics and demand for mortgages and reverse mortgages [9]. F Niu and W liu systematically discussed the spatial heterogeneity of urban housing price based on the interaction rules of urban activities [10]. The perspectives of Larson W D and Zhao W are novel. They studied the impact between oil prices and housing prices, and quantified the huge and differential risks of changes in oil prices between city and city [11]. China’s real estate market started relatively late, and its development history is only a few decades. It is an immature and fast-growing market. Before 1998, housing was allocated in kind. In other words, housing was a ration, not a commodity. In 1998, the State Council issued the “Circular of the State Council Concerning Further Deepening the Reform of Urban Housing System to Accelerate the Construction of Housing”, which unveiled the prelude of the reform of China’s comprehensive housing system. The government began to implement commercial housing supply model. Since then, real estate has become a commodity into the market, and has a real price [12]. Research on China’s real estate market can be roughly divided into empirical research and policy research. Empirical research: Jian Xiong and Chunyan Li studied the main influencing factors and characteristics of China’s real estate market demand, pointing out that the demand of China’s real estate market is mainly based on rigid demand [13]. Zan Yang, Huan Zhang and Siqi Zheng studied the demand elasticity of home housing in six provinces of China, and made qualitative and quantitative predictions about changes in the future demand and the trend of price [14]. Donghe Zhang and Wenwen Zhou estimated the overall and individual housing supply elasticity of 35 large and medium-sized cities in China, and considered that overall urban housing supply in China is inelastic [15]. From the perspective of population structure, Jianjun
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Zhou et al. analyzed the impact of demographic changes on the demand of real estate market based on provincial panel data [16]. Li Wang constructed a modified cobweb model by using the state space model to construct a variable parameter model for the demand function and supply function of Beijing real estate market. The results of the research show that the solution of the cobweb model is divergent, reflecting that the real estate price in Beijing has increasingly deviated from the equilibrium price in recent years, which requires the government to make it converge through macro-control [17]. Shuai Zhai and Yufei Yin added interest rates, per capita disposable income of urban residents and policy variables on the basis of the classic cobweb model, analyzed the supply and demand mechanism and price fluctuation characteristics of commercial housing in 35 large and medium-sized cities [18]. Policy research: Guozhen Chang divided China’s credit control policy into three phases and studied the cyclical impact of China’s credit policy on commodity housing prices [19]. Xiaoyan Shen studied the impact of China’s urban land supply policy on commodity residential stocks, theoretically analyzed the three channel effects of land supply policy on the real estate market, and tested the effectiveness of the three channels through empirical research [20]. Lu Li pointed out that “land finance” is closely related to housing prices. Through the analysis of the optimal model, it is concluded that the effective of controlling land supply to impact the housing price is far less than controlling land supply directly to impact the land revenues [21]. The existing literature has analyzed the fluctuation of house prices from the angles of real estate cycle, supply and demand mechanism, influencing factors, industrial linkage, and policy control. However, there are few studies on house price fluctuations in specific regions, and research based on the cobweb model is even less. The innovation of this paper lies in the fact that the per capita disposable income of urban residents and interest rates were added on the basis of the classic cobweb model, and the price elasticity of the real estate market of China’s four municipalities was studied in terms of supply and demand. The paper fully considers the characteristics of the real estate construction cycle and the lagging effect of the real estate market. Through the empirical analysis of the panel data of China’s four municipalities, it is of reference significance to measure the healthy development of the real estate market in China’s municipalities directly under the Central Government.
2 Model Construction 2.1
Dynamic Cobweb Model
The cobweb model is a dynamic analysis theory that introduces time into equilibrium analysis and uses elasticity theory to explain the different fluctuations in the occurrence when commodities with longer production cycle lose balance. It’s a classic model for analyzing dynamic equilibrium prices in microeconomics. The model is generally used to analyze the balance of products with long production cycles such as agricultural products, livestock products, and real estate [22]. Hypothesis 1: Current supply of commodities Qst depends on the price of the previous period Pt1 , namely the supply function for Qst ¼ f ðPt1 Þ. Hypothesis 2:
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Current demand of commodities Qdt depends on the current price Pt , namely the supply function for Qdt ¼ f ðPt Þ Through a brief introduction to the common cobweb model, this paper constructs the following cobweb model for the real estate market of municipalities directly under the Central Government: Supply function: Qst ¼ a0 þ a1 Pt1 þ a2 Rt þ e1
ð1Þ
Demand function: Qdt ¼ b0 þ b1 Pt þ b2 St þ e2
ð2Þ
When Qdt ¼ Qst , the spider model reaches equilibrium. In the formula, a0 and b0 are constant terms, an and bn are regression coefficients. Among them, Qst and Qdt represent the supply amount and demand amount in the t-th period, respectively. Pt is the current price, Rt express the current interest rate, and St represents disposable income of urban residents in the current period. Formula (1) means that the housing supply in this period depends on the price of the previous period Pt1 and the current interest rate Rt . Formula (2) shows that the demand for housing in this period depends on the current housing price Pt and disposable income of urban residents in the current period St . 2.2
Variable Description
2.2.1 Supply Variable Description Floor space completed refers to the completed commercial housing area that developers can directly input the market as supply. Floor space completed can intuitively reflect the change of supply, so this paper selects it to represent supply. Real estate price is the primary factor that affects the supply of real estate. In the case of constant construction cost, the higher the real estate price, the greater the profitability of real estate developers, and the more real estate supply. In the hypothesis of dynamic model, the real estate developers decide the supply quantity of real estate according to the real estate price of the last period. Due to the particularity of the real estate industry, the construction period is long, and this paper selects the completed area to represent supply, so the current price is not added into the model. The real estate industry is characterized by a long cycle and high investment. The developer’s funds are generally composed of its own funds and bank loans. The level of interest affects the profitability of developers in real estate development. Therefore, this paper adds the interest rate indicator to the supply model. In the model, interest rates are selected from the benchmark RMB interest rate (one-year period) of financial institutions issued by the People’s Bank of China. Because of the frequent changes in benchmark interest rates for several years, the author adopts weighted average method in data collection. In fact, the level of interest rate affects both the supply and the demand of real estate. This paper focus mainly on its impact on supply. 2.2.2 Demand Variable Description The level of sales can most intuitively reflect the people’s demand for real estate, so this paper selects residential commercial housing sales area to represent demand. And the
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real estate price is an important factor that people consider whether to buy property. In general, prices and demand change in the opposite direction. In the dynamic model assumptions, the demand for real estate in this period will be determined by the real estate price in this period. Disposable income is the decisive factor for people to consider whether to buy a house. It represents people’s purchasing ability. The per capita disposable income reflects the development level of the national economy. With the growth of economy, people’s income levels continue to increase. People’s demands for living environment and housing condition are getting higher and higher, and the demand for real estate increases accordingly. Therefore, the urban residents’ per capita disposable income index is added to the demand model in this paper.
3 Data Description 3.1
Sources of Data
This paper selects annual data for the period from 2000 to 2016. The average sales price of residential real estate in the country is taken from the “China Statistical Yearbook”. The floor space completed, sales area, annual average selling price, and per capita disposable income of urban residents in each municipality were taken from statistical yearbooks of municipalities directly under the Central Government. The benchmark interest rate for RMB loans of financial institutions (one year) comes from the official website of the People’s Bank of China. See the attached table for details: Table 1. Municipality panel data sheet City
Years Sales area (Ten thousand square meters)
Selling price (yuan)
Per capita disposable income (yuan)
Beijing Beijing Beijing Beijing Beijing Beijing Beijing Beijing Beijing Beijing Beijing Beijing
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
4557.00 4716.00 4467.00 4456.00 4747.14 6162.13 7375.41 10661.24 11648.00 13224.00 17151.00 15517.90
10349.70 11577.80 12463.90 13882.60 15637.80 17653.00 19977.50 21988.70 24724.90 26738.50 29072.90 32903.00
898.22 1127.50 1604.40 1771.10 2285.82 2823.65 2205.03 1731.48 1031.43 1880.45 1201.39 1034.96
Floor space completed (Ten thousand square meters) 1365.60 1707.35 1926.20 2080.75 2343.95 2841.42 2193.32 1853.95 1399.30 1613.23 1498.48 1316.13
Last year Interest rate sales (%) price (yuan)
4787.00 5.94 4557.00 5.94 4716.00 5.60 4467.00 5.49 4456.00 5.51 4747.14 5.76 6162.13 6.00 7375.41 6.32 10661.24 7.31 11648.00 5.40 13224.00 5.42 17151.00 6.36 (continued)
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Table 1. (continued) City
Years Sales area (Ten thousand square meters)
Selling price (yuan)
Per capita disposable income (yuan)
Beijing Beijing Beijing Beijing Beijing Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin Tianjin
2012 2013 2014 2015 2016 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
16553.48 17854.00 18499.00 22300.00 28489.00 3326.00 3658.00 4007.00 4989.00 5761.21 6698.00 7039.00 8253.00 8115.00 12364.00 14290.00 13565.83 13869.88 16192.00 16415.00 21501.00 25910.00 2274.00 2308.00 2414.00 2393.00 2950.34 3987.22 4649.25 5575.72 5598.00 6605.00 7940.00 8547.64 8009.58 8390.00 8828.00
36468.80 40321.00 43910.00 52859.00 57275.00 11718.00 12883.00 13249.80 14867.50 16682.80 18645.00 20667.90 23622.70 26674.90 28837.80 31838.10 36230.50 40188.30 43851.00 47710.00 52926.00 57692.00 8140.55 8959.70 9337.60 10312.90 11467.20 12638.60 14283.10 16357.40 19422.50 21402.00 24292.60 26920.90 29626.40 28980.00 31506.00
1483.37 1363.67 1136.53 1126.84 981.37 1445.87 1681.48 1846.40 2224.50 3059.53 2845.70 2615.49 3279.17 2007.48 2928.04 1690.82 1500.00 1592.63 2015.81 1780.91 2009.17 2019.80 378.34 514.59 538.30 720.60 796.09 1264.38 1332.49 1401.85 1135.35 1461.47 1302.61 1365.71 1511.40 1720.34 1483.64
Floor space completed (Ten thousand square meters) 1522.72 1692.04 1804.34 1378.22 1267.06 1643.62 1791.36 1708.10 2139.99 3076.19 2739.91 2699.11 2752.45 1801.45 1508.81 1396.05 1645.47 1609.13 1417.41 1535.55 1588.95 1532.88 583.51 690.48 673.00 750.67 1014.46 1270.96 1308.95 1398.61 1492.54 1580.82 1603.65 1645.10 1913.97 2117.66 2130.25
Last year Interest sales rate price (%) (yuan)
15517.90 6.42 16553.48 6.15 17854.00 6.14 18499.00 5.31 22300.00 4.75 3102.00 5.94 3326.00 5.94 3658.00 5.60 4007.00 5.49 4989.00 5.51 5761.21 5.76 6698.00 6.00 7039.00 6.32 8253.00 7.31 8115.00 5.40 12364.00 5.42 14290.00 6.36 13565.83 6.42 13869.88 6.15 16192.00 6.14 16415.00 5.31 21501.00 4.75 2157.00 5.94 2274.00 5.94 2308.00 5.60 2414.00 5.49 2393.00 5.51 2950.34 5.76 3987.22 6.00 4649.25 6.32 5575.72 7.31 5598.00 5.40 6605.00 5.42 7940.00 6.36 8547.64 6.42 8009.58 6.15 8390.00 6.14 (continued)
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City
Years Sales area (Ten thousand square meters)
Selling price (yuan)
Per capita disposable income (yuan)
Tianjin Tianjin Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing Chongqing
2015 2016 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
9931.00 12870.00 1077.00 1133.00 1277.00 1324.00 1572.56 1900.66 2081.31 2588.22 2640.00 3266.00 4040.00 4492.30 4804.80 5239.00 5094.00 5012.00 5162.00
34101.00 37110.00 6276.00 6721.00 7238.00 8093.70 9221.00 10243.50 11569.70 12590.80 14367.60 15748.70 17532.40 20249.70 22968.10 25216.00 25147.00 27239.00 29610.00
3.2
1674.78 2521.87 491.09 635.04 870.40 1133.00 1138.26 1792.41 2011.70 3310.13 2669.93 3771.22 3986.31 4063.42 4105.11 4359.19 4423.68 4477.71 5105.46
Floor space completed (Ten thousand square meters) 2182.99 2189.14 849.42 1020.63 1033.60 1231.75 1187.23 1713.55 1700.05 1769.19 1951.35 2384.51 2179.81 2826.78 3386.35 2867.45 2771.55 3185.90 3084.00
Last year Interest sales rate price (%) (yuan)
8828.00 9931.00 1080.00 1077.00 1133.00 1277.00 1324.00 1572.56 1900.66 2081.31 2588.22 2640.00 3266.00 4040.00 4492.30 4804.80 5239.00 5094.00 5012.00
5.31 4.75 5.94 5.94 5.60 5.49 5.51 5.76 6.00 6.32 7.31 5.40 5.42 6.36 6.42 6.15 6.14 5.31 4.75
Data Processing
In the context of panel data, there are fixed effect model and random effect model for common models. The biggest difference between the fixed effect model and the random effect model lies in its basic assumption, that is, whether the individual variables do not change over time is related to the predicted or independent variable. The HAUSMAN test value (p > 0.05) was obtained through data analysis. Therefore, the random effect model was chosen to perform regression analysis on the supply function and the demand function. In order to eliminate the influence of heteroscedasticity on the statistical results, the data has been processed logarithmically.
4 Regression Analysis This paper adopts stata12.0 software to perform regression analysis on supply and demand variables in the cobweb model (1) and (2). The stata12.0 software running results are shown in the following table.
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Table 2. Supply function regression results Variable Coefficient P > |z| 3.06 0.002*** Pt1 Rt 0.19 0.851 _cons 5.67 0.000*** R-sq 0.6475 Prob > chi2 0.0092 Number of samples 68 Note: ***, **, and * indicate significance levels of 99%, 95%, and 90%, respectively.
Table 3. Demand function regression results Variable Coefficient P > |z| −1.40 0.161 Pt1 St 2.40 0.016** _cons 0.84 0.403 R-sq 0.7217 Prob > chi2 0.0000 Number of samples 68 Note: ***, **, and * indicate significance levels of 99%, 95%, and 90%, respectively.
Supply function and demand function are: ln Qst ¼ 5:5510 þ 0:2015 ln Pt1 þ 0:0812lnRt
ð4Þ
ln Qdt ¼ 1:2577 0:5242 ln Pt þ 1:0826lnSt
ð5Þ
5 Conclusions and Discussion 5.1
Conclusion
Based on the panel data of 2000–2016 in four municipalities directly under the Central Government of China, the paper constructs a dynamic cobweb model that includes the price of commodity housing, disposable income per capita, and interest rate, etc. On this basis, the paper conducted an empirical analysis of the price elasticity of supply and demand in commercial housing in China. The results of the supply function regression are shown in Table 1. For the supply side, the supply of residential real estate is positively correlated with the price of real estate in the previous period, and it is significant at the 99% confidence level. For every 1 percentage point increase in housing prices, real estate supply rose by 3.62
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percentage points. With rising house prices, developers will find it profitable to increase supply. The central bank’s RMB-based benchmark lending rate is not significant for real estate, indicating that real estate supply is insensitive to changes in the benchmark lending rate. Interest rate adjustment may curb property supply in the short term, resulting in insufficient supply. However, in the long run it does not mean that interest rates can effectively curb property supply. The results of the demand function regression are shown in Table 2. For the demand side, the demand for residential real estate is negatively correlated with the real estate price in the current period. As the price increases, the demand declines. For every 1 percentage point increase in housing prices, real estate demand fell by 1.4 percentage points. However, the regression results are not significant. This may due to the fact that China’s four municipalities are the economic and cultural centers of China and a large number of people are flooding into these cities. The increase in demand brought by the population boom far exceeds the decline in demand caused by rising prices. Furthermore, real estate has its own characteristics as a commodity, which itself can also be used as an investment. In recent years, Beijing, Shanghai, and other economically developed cities have adopted a purchase restriction policy, so the speculative demand brought about by price increases has also been somewhat suppressed. In addition, the demand for residential real estate is positively correlated with the per capita disposable income of urban residents during the current period, and it is significant at the 95% confidence level. Per capita disposable income rose by 1 percentage point, and real estate demand rose by 2.4 percentage points. With the rapid economic growth, people’s income levels have continued to increase, their living standards have gradually increased, and people’s desire to improve their living environment has also increased. Thus, this has increased the demand for residential real estate (Table 3). Make Qdt ¼ Qst , the following conclusion can be drawn: lnQdt ¼ 5:5510 þ 0:2015 ln Pt1 þ 0:0812lnRt
ð6Þ
It can be seen that under the equilibrium conditions, the real estate market demand is positively correlated with the housing price in the previous period, indicating that the cobweb model of the real estate market in the four municipalities is divergent. There are many factors that make the cobweb model out of equilibrium. It is necessary for the government to introduce macro-control policies to rationally intervene in the real estate market. 5.2
Discussion
At present, China’s economy has entered a new normal and its economic growth has slowed down. Based on the study of the price elasticity of demand and supply in the municipalities directly under the Central Government, the following suggestions are proposed for China’s commercial housing. 1) Supply-side regulation should still be centered on increasing land supply. The lack of flexibility in the supply side of commercial housing in China’s municipalities directly under the Central Government is a major reason for land supply.
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Land control policies have a huge impact on housing prices. For municipalities with skyrocketing housing prices, such as Beijing and Shanghai, it is could be better to limit housing price, bids for land prices, and promulgate corresponding land control policies. 2) Supply-side regulation should vigorously promote the construction of affordable housing. China’s affordable housing has been relatively lacking. At present, housing prices have soared. Many low- and middle-income families cannot afford housing. The government should vigorously promote the construction of affordable housing. When necessary, the implementation of the public housing security system can be included in the performance evaluation system of local governments. 3) The demand-side regulation: The “restricted purchase” and “limited loan” policies are short-term effective tools for curbing housing prices. The “restricted purchase” and “limited loan” policies are major measures for China’s current adjustment of real estate demand. The result proves that these policies have also played a certain role, especially in suppressing real estate investment demand. 4) Improve the land market information release system and guide people’s reasonable expectations. A large part of China’s housing demand consists of speculative demand for investment. When people expect a higher level of real estate prices, they will increase investment and cause high prices. The government should promote the establishment of a land market information release system and guide people’s reasonable expectations. 5) Vigorously promote the concept of renting is as well as buying a house, and guide people to solve housing problems in multiple ways. Affected by traditional concepts, Chinese people are more inclined to buy a house when they choose a basic solution to solve the housing problem, leading to strong demand in China’s real estate market and high housing prices. The government should vigorously promote the concept of renting is as well as buying a house, guide people to solve the housing problem in a diversified way, and ease the pressure on housing demand in China. Due to the availability of data, the variables and parameters considered in this paper are incomplete. In general, there are many factors that affect the supply of real estate, such as: real estate prices, industry profitability, construction cost, land prices, interest rates, and national policies and so on. The more variable parameters, the more consistent the analysis results with the actual situation, and the more directivity will be. In future studies, it may be considered that adding construction cost and land prices as variables to the model. The price elasticity also can be explored in more depth. There are also many factors that affect real estate demand, such as real estate prices, per capita disposable income, population growth rates, people’s expectations of house prices, preferences for geographic locations, and so on. Similarly, in the later in-depth study, the rate of population increase can be added to make the analysis of price elasticity of demand more convincing.
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References 1. Xu, X., Jia, H., Li, Y., et al.: The role of real estate economy in China’s national economic growth. Chin. Soc. Sci. 1, 84–101 (2015) 2. China Statistical Yearbook 2017. China Statistics Press (2017) 3. Zhang, Z., Zhang, Y.: Current situation and sustainable development of China’s real estate market. Explor. Econ. Issues 8, 1–6 (2011) 4. Muth, R.F.: The stock demand elasticities of non-farm housing: comment. Rev. Econ. Stat. 47(4), 447–449 (1965) 5. Polinsky, A.M., Ellwood, D.T.: An empirical reconciliation of micro and grouped estimates of the demand for housing. Rev. Econ. Stat. 61(2), 199–205 (1979) 6. Tong, H.L., Chang, M.K.: Elasticities of housing demand. South. Econ. J. 44(2), 298–305 (1977) 7. Carliner, G.: Income elasticity of housing demand. Rev. Econ. Stat. 55(4), 528–532 (1973) 8. Liebersohn, C.J.: Housing Demand, Regional House Prices and Consumption (2017) 9. Chen, K.S., Yang, J.J.: Housing Price Dynamics, Mortgage Credit, and Reverse Mortgage Demand: Theory and Empirical Evidence. Real Estate Economics (2017) 10. Niu, F., Liu, W.: Modeling urban housing price: the perspective of household activity demand. J. Geogr. Sci. 27(5), 619–630 (2017). (in Chinese) 11. Larson, W.D., Zhao, W.: Oil Prices and Urban Housing Demand. Real Estate Economics (2017) 12. Department of Housing and Real Estate, Ministry of Construction: Question and Answer on the Current Housing System Reform Policy: “The State Council’s Policy on Further Deepening the Urban Housing System Reform to Accelerate Housing Construction” Policy Q&A. China Price Press (1998) 13. Xiong, J., Li, C.: Analysis of factors and characteristics of real estate demand in China. Stat. Decis. 12, 127–130 (2015) 14. Yang, Z., Zhang, H., Zheng, S.: Elasticity of housing demand for self-contained families. Stat. Decis. 14, 60–63 (2015) 15. Zhang, D., Zhou, W.: Calculation of housing supply elasticity in China and analysis of influencing factors. Stat. Decis. 7, 125–128 (2017) 16. Zhou, J., Dai, W., Yu, F., et al.: An analysis of the influencing factors of real estate prices based on spatial measurement. Take Hunan Province as an example. Theor. Pract. Finan. Econ. 2015(6), 114–119 (2015) 17. Wang, L.: An empirical study on the relationship between supply and demand in Beijing real estate market and the role of price mechanism. Econ. Manage. Res. 5, 61–66 (2008) 18. Zhai, S., Yin, Y.: Cobweb model analysis of real estate market price influencing factors—— based on central 6 provinces data. Res. World 05, 11–17 (2017) 19. Chang, G.: The periodical impact of domestic credit policy on prices of commercial housing. Price Month. 1, 51–56 (2017) 20. Shen, X.: Research on the Impact of China’s Urban Land Supply Policy on Commercial Residential Inventory. Nanjing University (2017) 21. Li, Y.: Housing prices, fiscal revenue stability, and optimal real estate regulatory policies. Stud. Finan. Econ. 02, 43–51 (2017) 22. Gao, H.: Western Economics, 3rd edn. Renmin University of China Press, Beijing (2005)
Capitalization of Urban Public Service Based on Urban Administrative Hierarchy: Evidence of Housing Prices from 281 Cities of China Junhua Chen(&), Siyu Chen, Dingwen Zheng, and Yanhui Hao School of Management Science and Engineering, Central University of Finance and Economics, Beijing, China [email protected]
Abstract. On the basis of Tiebout’s theory about optimal provision of public goods, the paper applies the hedonic approach to investigate the capitalization of public services in Chinese cities. We combine urban administrative hierarchy and the phenomenon of capitalization of public services, supplemented by empirical tests of 281 prefecture-level cities and higher. The sample cities were divided into municipalities, sub-provincial cities and general provincial cities. The three sets of data were tested empirically to examine the characteristics of capitalization effects of different grades of cities. The empirical results show that the phenomenon of capitalization of public services does exist, and it performs as follows. The capitalization effect of education and transportation can be proved positively. Furthermore, it is more effective in cities with higher administrative levels. Keywords: Public service
Capitalization Urban administrative level
1 Introduction Public service are non-competitive public goods provided by the government but can bring about economic benefits. When such economic benefits become continuous, they will enter into asset price, affected by the real estate market. That is the phenomenon of capitalization of public services that will be discussed in this paper. In recent years, China’s economic has been developing rapidly, and the process of urbanization is in full swing. In the process of urbanization, the total amount of public services provided by the government has increased substantially in order to meet the needs of more urban residents. Fortunately, it also allows us to accumulate enough data to analyzes and quantifies the capitalization of public services in urban development in China. Housing cannot be seen as research areas apart from the mainstream of urban economics [1–4]. In China, housing prices are rising rapidly as cities develop. In addition to the impact of rapid economic development, the lack of public service provision and its unbalanced spatial layout also led to higher housing prices in big cities. However, the cities with higher house price often have obvious advantages in administrative level. The administrative system of administrative levels in cities is strict in China. Political factors have a great influence on the development of Chinese cities (Fig. 1). © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 437–447, 2021. https://doi.org/10.1007/978-981-15-3977-0_33
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Fig. 1. The process of capitalizing public services to house prices
The provision of public services and the selection of public service structures have always been one of the concerns of urban economics. The existing studies on the capitalization of public services mostly involve the relationship between specific public service projects and house prices, such as education and medical care and so on. The theory of “voting with the feet” [5] emphasized the mechanism of the influence of factor mobility and jurisdictional competition on the local public service provision process. In China, public services are welfare and mainly provided by the government. However, public services can be capitalized into house prices or rents through processes of real estate sales or renting. We believe that the capitalization of public services does not conflict with its welfare feature. Therefore, the research on the capitalization of public services has practical significance for adjusting the structure of government’s public service supply. The different characteristics of capitalization of public services in different administrative grade cities enable the government to understand the capitalization effect more deeply and meticulously. Whether the capitalization of public services can motivate the government and real estate developers to spend on public services? The innovation of this research intends to provide a basis for investment in public services in the process of urban development in China. The highlight of this research in the empirical research part is that the panel data of 281 cities was used to verify the capitalization effect of public services. In addition, the cities in total sample has been divided to three groups, according to different administrative levels, to measure the capitalization phenomenon in different administrative hierarchy cities.
2 Related Literature Gleaser concerned [1] that differences in the nature of house across space were not only responsible for higher housing prices, but also affected how cities respond to increases in productivity. But Shen and Liu found [6] that the growth of housing prices could not be well explained by past information of economic fundaments and housing prices, which may need the policy makers and practitioners paid enough attention to. Liang
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compared [7] the fluctuations in house prices across the country and held that the fluctuations had obvious regional imbalances. Kuang examined [8] the impact of expectations and speculation on house prices. The empirical results showed that the expectation and its speculation had strong explanatory power on China’s urban house price volatility. Kuang’s research argued [5] that in cities where population growth was rapid, house prices fluctuated greatly. Some scholars have used cross-sectional data to conduct empirical research [9, 10] and concluded that differences in the level of public expenditure would gradually accumulate and capitalize into housing prices. MJ Holmes, J Otero and T Panagiotidis did a research on house price in Paris [11], their findings revealed that the half-life of a shock to long-run price equilibrium was affected positively by unemployment, distance and housing supply. The analysis suggested that smaller distances between Parisian districts were associated with a faster speed of adjustment back towards long-run equilibrium. However, researchers have produced some empirical evidence about capitalization [12, 13]. DM Brasington explored [12] the measures of public school quality on the housing market values with both the traditional hedonic house price estimation and the hedonic corrected for spatial autocorrelation. Other scholars have discovered the capitalization of traffic [13]. DP Mcmillen and J Mcdonald examined [13] the effect of the new rapid transit line from downtown Chicago to Midway Airport on single-family house prices before and after the opening of the line. They found that house prices were being affected by proximity to the stations in the late 1980s and early 1990s. In China, there were some authors who focused on incomprehensible high house prices. Tang Y. G. et al. [6] proved that transportation infrastructure could be capitalized to land premiums when land was transferred, while other public services could be capitalized to house prices in residential sales. Feng J.F. and Yang Q. [14] empirically analyzed the relationship between fiscal decentralization, transfer payments and urban expansion in current local governments. Their research showed that the “Chinese-style” fiscal decentralization system was an important cause of rapid urban expansion in China. There were obvious regional differences and cross-time differences in fiscal decentralization and transfer payment effects. According to relevant research by scholars all over the world on public expenditure and regional economic growth, some conclusions can be summarized as following: (1) Among the factors affecting the rise in house prices, some are manifested between cities. (2) China’s research in this area is currently limited to big cities and lacks an examination of general cities. (3) In addition, there are few articles examining differences about capitalization between urban administrative levels. Based on the above review, this paper combines urban administrative hierarchy and the phenomenon of capitalization of public services, supplemented by empirical tests of 281 prefecture-level cities and higher. The sample cities are divided into municipalities, sub-provincial cities and general provincial cities to investigating the characteristics of urban public service capitalization at different administrative levels.
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3 Data and Methodology The effects of public services have to be separated into specific types. In order to observe the feature in different administrative-level cities of the capitalization effect, with different types of public services, in terms of education, culture, medical care and transportation, panel data sample1 from 2005–2013 with 281 cities at the administrative level of prefecture or above was divided into three groups: both municipalities and subprovincial cities,16 other provincial capital cities except for sub-provincial, 246 general prefecture-level cities. The definitions and sources of the data are in Table 1 and the descriptive statistics are displayed in Table 2. Table 1. Variable definitions and sources Definition Source China Economic and Social hprice Average sales price of commercial housing Development Statistics Database (yuan/m2) Density Population density (population per square CEInet Statistics Database kilometer) Wage Average annual salary of employees CEInet Statistics Database M2/GDP The ratio of money supply M2 to GDP CEInet Statistics Database sbed Number of beds at the end of the year for CEInet Statistics Database hospitals and medical institutions sbus Public gas and tram operations CEInet Statistics Database sbook Public library collection CEInet Statistics Database eduex Local Public Expenditure_Education CEInet Statistics Database Note: Each variable, except the average selling price of commercial housing, is the data of municipal jurisdictions. As for the average selling price of commercial housing, it can be assumed that the urban housing prices could reflect the prices of jurisdiction.
Table 2 shows four groups of descriptive statistics of each dependent variable. In all urban city samples, the maximum value of each variable is the same as the maximum value of them in group 2, consisting of the cities with higher administrative level. This also shows that the administrative power has indeed played an important role in the development of the city. In cities with higher administrative levels, housing prices, wages, population density are higher, while public services are better.
1
14 district-level cities with incomplete data are omitted: Lhasa Sansha City, Bijie City, Tongren City, Haidong City, Turpan, Hami City, Bozhou City, Baoshan City, Pu’er City, Shanwei City, Chaohu City, Baoshan City, and Liupanshui City.
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Table 2. Descriptive statistics (1) 281 cities_all cities at the administrative level of prefecture or above Variable Obs Mean S.D. Min
(2) 19 cities_municipalities and sub-provincial cities Max
hprice density wage m2gdp sbed sbus sbook eduex
2529 3479 2814 394 45983 2529 428 343 5 3702 2529 29064 13616 6410 320626 2529 1.67 0.13 1.49 1.86 2529 13993 12107 940 113395 2529 1203 2549 22 30590 2529 1182 2369 3 28544 2528 154160 417613 70 6613913 (3) 16 cities_ provincial capital cities except for sub-provincial capital Variable Obs Mean S.D. Min Max hprice 144 4637 3763 1870 44181 density 144 459 260 124 1440 wage 144 459 260 124 1440 m2gdp 144 1.67 0.13 1.49 1.86 sbed 144 22609 11376 6301 63944 sbus 144 2727 1153 794 5745 sbook 144 3074 1713 290 9691 eduex 144 220080 178092 21207 861997
Obs
Mean
S.D.
171 7541 4194 171 845 569 171 845 569 171 1.67 0.13 171 42258 22671 171 8178 5940 171 7167 5258 171 1029935 1260390 (4) 246 cities_general prefecture-level cities Obs Mean S.D. 2205 3086 2259 2205 393 302 2205 393 302 2205 1.67 0.13 2205 11254 6757 2205 566 555 2205 598 869 2204 82233 100094
Min
Max
2135 184 184 1.49 6297 2437 562 87178
45983 3702 3702 1.86 113395 30590 28544 6613913
Min 394 5 5 1.49 940 22 3 70
Max 29867 2662 2662 1.86 49341 5449 10986 1100000
The hedonic model was used in this paper to test the research aim. The hedonic model holds that real estate consists of many different characteristics [15] and is determined by the utility of all the features that are brought to people. The price of real estate varies due to the different number and combination of different characteristics of the house. Therefore, if we can decompose the price influencing factors of real estate, we can find the price implied by each influencing factor. In different cities, the difference in the price of the house is possibly caused by the difference in public services reflected by the public service variables. The hedonic price model is specified as follows: lnhprice ¼ a0 þ a1 lndensity þ a2 ln
X M2 ak lnxkit þ u þ eit þ a3 lnwage þ GDP
Where the variables are defined as the following: xkit denotes the variables of public services in the t years of city i, including eduex, sbook, sbed, and sbus mentioned in Table 1. Sbusit is the actual number of buses for the city i at the end of the tth year, which represents the convenient level of transportation. The total amount of books defined as sbookit, for city i in the tth year, represents the degree of urban cultural development, and sbedit is the total number of hospitals and medical institutions for the year t of the city i, representing the medical level. Eduexit is the financial expenditure
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on education for city i in year t, ui is the individual heterogeneity that does not change with time, and eit is the random disturbance item. The average annual salary of employees and population density represent the general variables that affect house prices in different cities.
4 Results and Analysis The correlations among the independent variable and dependent variables are reported in Table 3, for 4 groups of regress: Table 3. Linear Regression Results (Interpreted variable is Inhprice) (1) (2) (3) * 0.13 0.172* lndensity 0.0371 (−2.51) (−1.36) (−2.07) lnm2gdp 0.881*** 0.315 0.775* (−10.33) (−1.31) (−2.04) lnwage 0.504*** 0.306* 0.625*** (−19.04) (−2.48) (−4.03) lnsbed 0.0364 .00000542* 0.0231 (−1.56) (−2.51) (−0.17) lnsbus 0.0499*** 0.380*** 0.0222 (−3.52) (−4.21) (−0.2) lneduex 0.130*** 0.232*** 0.0783 (−9.22) (−3.51) (−1.09) lnsbook 0.0131 0.0285 −0.0249 (−1.43) (−0.84) (−0.49) _cons −0.00479 −1.579 −0.71 (−0.02) (−1.61) (−0.52) N 2529 171 144 R2 72.84% 83.07% 71.98% t statistics in parentheses * p < 0.05, **p < 0.01, ***p < 0.001
(4) 0.0312* (−2.01) 0.953*** (−10.12) 0.494*** (−17.42) 0.0451 (−1.81) 0.186 (−1.34) 0.132*** (−8.85) −0.151 (−1.08) 0.159 (−0.67) 2214 72.20%
Table 3 shows that the regression result is significant and robust. The grouping in the regression model is the same as the grouping in the descriptive statistics. First of all, we use the panel data of 281 cities from 2005 to 2013 with a 2529 sample size2. In the first set of sample, the empirical results verify the existence of the capitalization effect of public services in Chinese cities. The second set of empirical test with the data of a total of 19 major cities (consisting of 4 municipalities and 15 sub-provincial cities) observe the feature of capitalization of public services of highest administrative-level
2
Including 19 municipalities and sub-provincial cities, 16 remove sub-provincial grades. Other capital cities, 246 cities in general prefecture-level cities.
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cities in China. And the third group of the test is other 16 provincial cities which are not the sub-provincial cities, representing cities with relatively good administrative resources in China. The fourth group is an empirical test of 246 other prefecture-level cities that always get the general administrative resources of China. 4.1
Analysis of All 281 Cities
From the results of the all cities analysis, the coefficients of education, health care, transportation and culture are all positively correlated with house price. The impact of traffic and education is significant. On the other hand, the coefficient of culture and medical care is positive, but not that significant. That may be related to the selection of proxy variables. For example, we choose the number of beds to represent the medical level of a city, but there are still some other key factors that are difficult to quantify, such as the doctor’s personal ability. Similarly, the cultural level of a city is also difficult to quantify. It may be one of the reasons that the utilization of libraries is different in sample cities. The results show that the public service level, represented by education and transport does have significant positive correlation with house prices at overall level. It also verifies that the average wage, population density, and policy have positive impact of housing prices, which can be considered as a result of the capitalization effect of public services. That is, the improvement of education and transportation levels could raise housing prices, the development of education and transportation has been significantly capitalized in the house price. Next, we focus on the characteristics of the capitalization effect of public services for cities of different administrative levels. 4.2
Analysis of Regression Results by Group
4.2.1 Sub-provincial Cities and Above The second set of results in Table 3 is an analysis of the 19 cities with the highest administrative levels in China, including 4 municipalities and 15 sub-provincial cities. In this group, only education and transportation show a strong correlation with house price. 1% increase in education expenditure increases house prices by 0.23%. Compared to national level, it is higher. Similar phenomena is present in the variable of traffic, obviously, 1% increase in the number of buses will give a premium of 0.38%. In addition, the reporting results of cultural variables are not significant, which shows that for cities with high administrative levels, the capitalization effect of culture on housing prices is not obvious. The rapid development of the economy is much attractive to talented people. In cities where high-quality talent gathers, the cultural level and cultural atmosphere of the city will inevitably increase. 4.2.2 Provincial Capital Cities Except for Sub-provincial Cities The third group in Table 2 corresponds to the results of 16 sub-provincial cities. It can be seen that in this group, the impact of education, transportation and healthcare on house prices is positive but not significant. This may be due to the limited number of samples and the fact that the variables do not show much difference in each city, which needs further study. The provincial capital city, with the highest administrative level,
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holds the greatest positive intervention in provincial capitals by the government. These cities are generally economically developed. The results of our regression also show that the average wage level per capita has a strong positive correlation with housing prices. The coefficient for the third group is 0.625, which is significant at the level of 0.001, from which we can conclude that the average salary is one of the most important factors affecting the housing price, particularly more pronounced in provincial capital cities. 4.2.3 General Prefecture-Level Cities Education in this group is much significant. Education spending increases by 1% will result in an increase in house price by 0.132%. This is similar to the result of the general regression of all 281 cities. In these 246 cities, medical care has a high correlation with house prices. This effect is not particularly large, but the p-value here is 0.07, indicating that the regression result is significant at the level of 10%. The medical service has a certain positive impact on housing prices. Cultural proxy variables exhibit negative coefficients in this set of data. The reasons have been talked about in previous part. Another point worth paying attention to is that, in addition to the several public service variables that the paper focuses on, the wage level, population density, and policy factors that affect house prices also show significant positive results, which also corroborate our opinion. This makes the results of the article more convincing. 4.3
Horizontal Comparison Analysis of Regression Results
WA horizontal comparison of the empirical results of public services was made according to the results of the regression shown in Table 3. For medical service, the agent variable is the number of beds in hospitals and medical institutions per year. Through the foregoing analysis, it can be found that medical treatment has not been robustly significant in this test. As a result, from the coefficient point of view, the absolute values of the coefficients of the total sample, group two, group three and group four were all very small. The regression coefficient for Group 2 is close to zero, and this result is significant at the level of 5%, indicating that in the 19 largest cities with the best administrative resources, medical service has nothing to do with housing prices. This does not seem to be consistent with our experience. As for the traffic variable, the number of public steam trams was chosen as the proxy variable. The reason why the total amount was chosen as the proxy variable instead of the per capita level was because when people judge a city’s public service level, they often concern about the total amount of public services, like Beijing. With the rapid population’s turnover rate in recent years and urbanization process, public service tends to have a time lag buffer. Therefore, the per capita level does not have strong representativeness. In the linear regression of traffic variables, the level of transport services can be very significantly capitalized into housing prices, with a coefficient of 0.05, which means that 1% increase in the level of transport services will bring about 0.05% of real estate. Although the confidence level of the regression is not very high, we convincingly proved the capitalization effect of transportation on house prices. In the results of
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the analysis of 19 large-scale cities with high administrative levels and administrative resources, the traffic shows a very significant and larger positive coefficient. It can be seen that the advantage of administrative resources makes traffic capitalization even more pronounced. For the 19 large cities with high administrative levels, the development of transportation will bring a high premium to housing prices. So that we can make such an assumption that for the group of cities with the highest administrative levels, the provision of public transport can bring about high marginal returns which were capitalized into real estate value. It also shows that there is still much room for improvement in the development of their transportation systems. The third public service variable is education that shows a significant positive effect in the overall linear regression and the group 2 regression. It means that education has a greater influence in municipalities and sub-provincial cities. It is consistent with our experience and perception that education is an important factor for house buyers. The more microscopic evidence is a crazy premium for the Beijing school district, which is consistent with the ideas expressed in our regression results. For the general prefecturelevel cities, the capitalization effect of education on house price is also positive, and it is logical to be similar to the results of the regression of 281 cities. The last variable of public service is culture. In this part, the correlation is not very obvious. Cultural variables are difficult to quantify. In addition the improvement of cultural level is sometimes with the pooling of talents.
5 Conclusions and Implications The primary message of this paper is that in different administrative cities, capitalization of public services shows different characteristics. In fact, this effect is more pronounced in higher administrative grade cities. They need a more complete public service system to meet the rising demand of the population. In the development of Chinese cities, administrative forces have always played a very important role. The imbalance in the supply of public services is caused by the advantages of the administrative level. The paper discusses the capitalization effect of public services and its feature in different administrative levels of cities. Through the empirical analysis, we can draw the following conclusions: first, the phenomenon of capitalization of public services does exist, which is manifested by the relationship between supply and demand in the real estate market. Second, for the public services, education, transportation, medical care and culture, the capitalization effect of education and transportation can be proved positively, but the effect of medical treatment and culture needs further study. Third, the capitalization effect of education on house prices is significant, robust, and highly influential, while the effect is among municipalities directly under the central government and sub-provincial cities is the strongest. Lastly, the capitalization effect of the transportation development exists, and the effect exhibited by municipalities and sub-provincial cities is stronger. The existence of the phenomenon of capitalization of public services, especially the significant effects of education and traffic capitalization, can indicate that while developing the economy, paying attention to the provision of public services, especially the increase in the quantity and quality of education and transport, can promote
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the rise in real estate. Especially for the municipalities directly under the central government and sub-provincial cities, they gathered good administrative resources and attracted a large number of people. The premium on education for these cities has reached a premium of 0.23. It is not difficult to find that the development of real estate and the linkage development of various industries brought about by the development of real estate played a significant role in promoting the economic development of the city. An important reason why the premium is so high is that the existing education supply is still far away from the level required by the residents. These cities should use their administrative resources and pay attention to the balance between the amount of demand and structure provided by education, so as to increase the efficiency of the use of administrative resources and promote the healthier development way of city. Concerning the connection between house prices and land prices, government expenditures on public services can be converted into returns on fiscal revenue. Although it is unhealthy for fiscal expenditure to be overly reliant on land sales, it does exist. As mentioned above, this paper believes that the capital maximization effect of municipalities directly under the Central Government and sub-provincial cities is due to the severe imbalance between supply and demand. In these cities, the provision of public services is not enough. A large part of the demand has not yet been met. In other words, its population concentration is far greater than its public service capacity for the population. To this end, we propose that the public service system of municipalities directly under the Central Government and sub-provincial cities should continue to be optimized. Therefore, from the perspective of improving development efficiency, public services in big cities should be forward-looking and meet the needs of existing and potential populations. Furthermore, the government should improve its forwardlooking nature. Through adequate public service provision to prevent major urban diseases, the city will develop healthier and the people will live better. Finally, due to the availability of data, although 281 large samples were used to analyze the capitalization of public services, the selection of specific variables still has room for improvement. It is not sufficient to use a single variable to represent a certain level of public service. For example, for the study of the variable of traffic, the number of cars can only represent the level of land traffic in the city. It does not conclude rail transit and other external traffic such as aviation and railways. Worse situation occurs in the selection of cultural variables as mentioned above. Although the model is robust and significant, the selection of cultural variables still needs to be found again.
References 1. Glaeser, E.L., Gyourko, J., Saks, R.E.: Urban growth and housing supply. J. Econ. Geogr. 6 (1), 71–89 (2006) 2. Jr, H.W.H.: Who benefits from state and local economic development policies? Econ. Geogr. 68(2), 214–216 (2010) 3. Mills, E.S.: An aggregative model of resource allocation in a metropolitan area. Am. Econ. Rev. 57(2), 197–210 (1967)
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4. Landis, J.D., Guhathakurta, S., Huang, W., et al.: Rail Transit Investments, Real Estate Values and Land Use Change: a comparative analysis of five California rail transit systems. University of California Transportation Center Working Papers (1995) 5. Tiebout, C.M.: A pure theory of local expenditures. J. Polit. Econ. 64(5), 416–424 (1956) 6. Yue, S., Liu, H.: Housing prices and economic fundamentals: a cross city analysis of China for 1995—2002. Econ. Res. J. (2004) 7. Liang, Y.: Empirical analysis on real estate price fluctuation in different provinces in China. Econ. Res. J. 8, 133–142 (2007) 8. Weida, K.: Expectation, speculation and urban housing price volatility in China. Econ. Res. J. 9, 67–78 (2010) 9. Tang, Y., Chen, Q., Man, L.: Capitalization, fiscal incentives and the provision of local public services: evidence from 35 large and medium sized cities of China. China Econ. Q. 2016(1), 217–240 (2016) 10. An Empirical Analysis Based on Provincial Panel Date. Urban Stud. 19(8) (2012) 11. Holmes, M.J., Otero, J., Panagiotidis, T.: A pair-wise analysis of intra-city price convergence within the paris housing market. J. Real Estate Finan. Econ. 54(1), 1–16 (2017) 12. Brasington, D.M.: Which measures of school quality does the housing market value? J. Real Estate Res. 18(3), 395–414 (1999) 13. Mcmillen, D.P., Mcdonald, J.: Reaction of house prices to a new rapid transit line: Chicago’s midway line, 1983–1999. Real Estate Econ. 32(3), 463–486 (2010) 14. Zong, J., Yang, Q.: The Public Financial Incentives of Chinese Urban Expansion 15. Goodman, A.C.: Hedonic prices, price indices and housing markets. J. Urban Econ. 5(4), 471–484 (1978)
Overseas Social Security Housing Construction Pattern and Its Enlightenment to China Zou Run-yan, Huang He, Wen Jia-ming, Ying Qian-liang, Li Hong-yi, and Dan Cheng-long(&) Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang, China [email protected]
Abstract. The purpose of this paper is to analyze and review of foreign patterns of social security housing construction. Methods of documentation and comparative analysis are employed. The results show that constructions of social security housing in USA and Germany are dominated by market and in Singapore and South Korea is dominated by government. Furthermore, this paper summarizes the characteristics of social security housing construction in developed countries from the perspectives of financial support and legislation, and reviews the development stages of social security housing in USA and Singapore. This paper concludes that Chinese government can improve the social housing construction by establishing a housing institution, innovating the incentive policy, perfecting laws and regulations and making detailed provisions on social security housing construction in all respects. Keywords: Social housing construction Enlightenment
Patterns Characteristics
1 Introduction Social security house, closely in correlation to immediate interests of people, has become a hot issue in China and abroad. Providing more social security houses is an effective mean for solving the housing problems of citizens in China. Since “National Housing Project Implementation Plan” promulgated in 1995, China has formed a housing security framework that supports low-cost house, affordable house, house of two limits, and policy-based rental house [1]. According to the data from the Ministry of Housing and Urban-Rural Development, 40.13 million sets of social security housing projects had been built during the “12th Five-Year Plan” period. However, due to the late start of China’s social security housing project; there have been many problems in the practice of social security housing construction. Learning from the successful experience of foreign social security housing construction will help China’s further improvement in the construction of social security house. At present, Chinese scholars have conducted research on affordable housing in European countries such as the United States [2], Germany [3], and Canada [4] and Asian countries such as Japan [5], Korea [6], and Singapore [7]. However, its perspective is most focused on the development and evolution of social security housing © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 448–456, 2021. https://doi.org/10.1007/978-981-15-3977-0_34
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construction policies. There is relatively little research on social security housing construction. Particularly, there is still relatively little research on the models and characteristics of foreign social security housing construction. Chinese government has introduced a series of measures to speed up the development of the housing rental market. At the same time, Chinese government promotes the construction of social security housing with public rental housing as the mainstay. Therefore, it is necessary to continue to explore the mode of social security housing construction that suits China’s conditions. At the end, this article takes countries such as the United States, Germany, Singapore, and South Korea that have relatively improved housing security as examples, and summarizes and sorts out the basic conditions, models, and characteristics of the construction of social security housing in order to provide reference and guidance for China’s social security housing construction.
2 Model of Affordable Housing Construction Abroad The construction of social security housing in developed countries based on housing social security, land social security, and promoting social fairness. It has implemented under the conditions of regional social supply and demand conflicts, irrational use of land, and gaps in household income levels leading to inadequate housing demand. Its primary aim has changed from meeting the housing demand of low-income residents to realizing social and environmental aims such as eliminating community isolation, increasing employment rates, promoting energy saving and emission reduction [8]. It shows mainly as two forms. 2.1
Government-Led Model
The government-led model refers to various activities such as financing, construction, and management of government-sponsored housing construction and management. The typical representatives of this model are Singapore and South Korea (Table 1). The Singapore government led the development and construction of HDB flats. First of all, when the self-government government was established in 1959, it placed priority on the settlement of residential housing issues. It considered building flats as a basic national policy and formulated the “Housing Development Law”. In 1960, the law established the Housing Construction Development Bureau [9]. The Housing Construction Development Bureau is the government’s responsibility for the planning and management of the construction of affordable housing, and it is also the largest real estate developer responsible for housing construction, rental and sales. The Singapore government provided a low-interest loan for the Housing Development and Development Bureau to support its various expenses. The central provident fund system established in 1955 provided substantial funds for the construction of affordable housing in Singapore. So far, 86% of the total population of Singapore has lived in the government. The building of the HDB [10]. The Korean government initially did not directly intervene in the construction of social security housing, and the supply of housing was provided by the private sector, which resulted in serious housing shortage problems [11]. Since the beginning of 1989, the Korean government began to build and
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provide social security housing in urban areas [12]. The Ministry of Land, Infrastructure and Maritime Affairs of Korea, the land and residential communes of central and local governments, and other public departments [5] mainly lead the construction of social security housing. In terms of source of funds for social security housing construction, national and local fiscal revenues and national housing funds account for the major part, and households and land residential communes bear a small part of the construction funds. To date, Korea has developed various forms of affordable housing, covering more and more families [13].
Table 1. Government led mode of public housing construction in developed countries Country Institution Administrative composition Organization
Construction Bodies
HDB
Capital Source
Central Provident Fund, Government Financial Subsidies “Home Ownership” Program, Five-year Housing Plan
Program
2.2
Singapore HDB
Korea Ministry of Land, Transport and Maritime Affairs Land and Residential Commune National and Local Finance, National Housing Fund
Feature Functions related to all aspects of affordable housing construction The government sets up a separate agency or a stateowned company to take charge of the construction The government bears the main part of the funds for affordable housing construction
Public Housing The government has planned Construction construction of affordable Plan housing
Market-Oriented Model
The market-oriented model, which emphasizes the market plays a leading role in the construction of social security housing, does not advocate direct government intervention. The government hopes that the participation of the private sector can improve the efficiency of social security housing construction [14]. The typical representatives of this model are United States and Germany (Table 2). The establishment of US market-oriented model has experienced a long period. Early as 1933, the U.S. government provided real estate development companies or individuals with low-interest loans to build social security housing on their own, and Congress hoped to increase the employment rate of workers by social security housing construction [15]. The Enactment of the Housing Act of 1974 encouraged developers to use part of the housing they developed for social security housing leases and gave
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developers certain policy preferences. Thereby this increased the stock of public housing and stimulated the enthusiasm of real estate developers to build social security housing. In respect of housing guarantees for low-income families, the U.S. government also implemented a market-oriented housing supply mechanism. Within the framework of the market mechanism, the government increased the housing affordability of low-income groups through personal tax deductions and rental vouchers. Social security housing construction had been used as the main means of housing policy in Germany for a long time [16]. Due to the serious house shortage experienced by Germany after the Second World War, the German government issued a large number of 30-year low-interest or interest-free loans to build a great number of rentonly and unsold loans in order to involve private individuals and enterprises into the construction of social housing. Low-rent social security housing effectively solved residents’ housing problems [17]. The construction of social security housing in Germany has been continuing in recent years. However, due to the privatization of housing and fiscal burden reduction, the number of social housing has gradually decreased. The German government is no longer directly involved in the construction of social housing. Private real estate companies and residential cooperatives are main force of the social security housing construction, while the government actively participates in social security housing construction through the market mechanism, the use of policy support, tax deductions, interest rates and other forms of subsidies [18].
Table 2. Market led mode of public housing construction in developed countries Country Institution Administrative Composition Organization
America HUD
Germany BMU, Department of Conservation, MOC, DNS
Construction Bodies
Real Estate Developer
Financing Mode
Private Financing, Mortgage Loan, Bond Offer LowInterest Loan, Tax Incentive and Other Measures
Private Property Company, the Housing Cooperative Society, Pastoral Ministry House saving, Saving Reward
Government Participation
Offer Low-Interest Loan, Tax Concession and Other Measures
Feature Management agencies do not directly participate in affordable housing construction Most of the direct builders of affordable housing are private sectors
Various ways to encourage and absorb private capital participation Encourage private and non-profit organizations to participate in affordable housing construction
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3 Characteristics of Social Security Housing Construction in Developed Countries The construction of social security housing in developed countries shows relatively consistent characteristics in the context of their own political systems, economic and social development stages, urbanization levels and cultural integration, which are mainly reflected in the following aspects. 3.1
Financial Support for Social Security Housing Construction
The construction of social security housing is a costly and systematic project that requires sufficient funds to ensure high efficiency. Different countries have different fiscal and tax incentives for the construction and financing of social security housing, which can fully guarantee the construction of social security housing. Germany grants subsidies to social security housing by non-profit housing companies, such as residential cooperatives, to obtain government-supplied interest-free loans that account for 50% of construction costs, with a repayment period of 25 years [8]. At the same time, the German government also encourages new private houses to solve the housing problems, and through tax deductions to reduce the burden on building houses, in order to reduce the income of building owners should be included in the tax [19]. In Singapore, the HDB built a closed housing construction financing system around the central provident fund. The public paid a reserve fund at a certain rate to the Central Provident Fund Bureau. Then the government used the government bonds to absorb the central provident fund to provide loans to the HDB [20]. In addition, the government also provides low-interest loans for the HDB. To make up for its deficits, it also provides additional subsidies each year from the budget. The HDB itself can also issue public debt. 3.2
Relevant Legislation of Social Security Housing
The construction and supply of social security housing plays an important role in stabilizing the housing market, relieving social conflicts, and promoting the sustainable development of the social economy, which also determines the public characteristics of it. Countries that have a comprehensive system of social security housing development have established relevant laws and regulations. Germany passed the first Residential Construction Act in 1950. The government began to adopt low-interest or interest-free loans, credit guarantees, and providing low-cost land in various ways to promote the construction of social security housing. The second Residential Construction Act of 1956 further allowed individuals to own housing property rights [21]. The housing rental market composed of social security housing and private housing is also wellestablished. The German government has issued the “Resident Protection Act” to protect the interests of lessees [14]. The 2013 Rental Law stipulates that within 3 years of sufficient supply of rental housing, The rent increase cannot exceed 15%. In 2015, the housing market that exceeds supply is allowed to rent. The rent can be increased by 10% above the government rent guidance price [22]. The United States’ social security housing construction activities are also conducted under the premise of legal support.
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In 1937, the first public housing legislation passed by the United States, the Housing Act, established the “US Protection of the Housing Department,” and the House of Defense issued in 1965. The Urban Development Act stipulates the establishment of the Department of Housing and Urban Development (HUD) as the management agency responsible for the overall construction of affordable housing. Its responsibilities include “providing social security housing and high-quality, low-cost rental housing” [23]. In response to the subprime mortgage crisis in 2008, the Housing and Economic Recovery Act was introduced. By 2016, the Ministry of Housing and Urban Development’s rent assistance program has covered 9.8 million people [24]. 3.3
Diversification of Affordable Housing Construction and Supply
The supply of social security housing in developed countries is not static, and various countries have adopted various types of social security housing supply methods to meet the housing needs of people with different economic status and spending power. From the perspective of diversification of social security housing construction, German builders of social security housing include urban housing companies, public housing organizations, real estate developers, and various other types of investors [25]. Judging from the multiple supply of social security housing, in South Korea, low-and middleincome families living in cities and with certain purchasing power can purchase smallsized public housing for sale. Most of their housing area is controlled less than 85 square meters, and the price is 50 percent of the market price. For the urban minimum income group, the Korean government has built permanent leased housing to solve its housing problem. Long-term rental of houses is a unique renting method in Korea [26], and the protection target is people whose income is less than or equal to the average income of urban residents.
4 Inspiration for the Construction of Social Security Housing in China After nearly 20 years of practice, China has initially formed a system of social security housing for rent, sale, and change. For low-income and middle-income groups with certain purchasing power, the government will reduce or exempt taxes and fees, land transfer fees, and real estate companies will be responsible for the development and construction of affordable housing and house of two limits. For urban residents with housing difficulties, the government directly invests or support institutions to build public rental housing to solve the problem of housing for newly employed workers [27]. For low-income and middle-income households in urban shantytowns and urban villages, the government has improved housing conditions through shanty towns and old homes. The construction of affordable housing in China has made some positive achievements. At the same time, there are also many problems [28]. On the one hand, local governments lack of the enthusiasm of affordable housing construction; real estate companies and developers show a low degree of participation of social security housing construction, on the other hand, China lacks specific laws to regulate the construction of social security housing and the guarantee system involving planning,
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capital, and post-management is still not perfect. Developed country has a long history of social security housing construction, it can provide reference for the construction of social security housing in China in the following aspects. 4.1
Establishing an Executable Housing Security Agency
Singapore’s “House Construction Development Law” and the United States’ “Housing and Urban Development Law” all have clear provisions for the establishment of social security housing construction agencies. At present, the Housing Security Department under the Ministry of Housing and Urban-Rural Development in China has undertaken the guarantee. The responsibility for the management of housing is to formulate relevant policies, prepare and supervise housing security development plans, but there is no independent execution force [29].Therefore, first of all, China needs to establish a housing security agency with execution power, and the law clearly defines its responsibilities and obligations in the construction of social security housing. Secondly, at the local level, an executive agency should be established at the administrative level to take responsibility for the implementation of housing security policies and the planning, construction, distribution, and maintenance of social security housing construction. From the experience of the above developed countries, we can see that the government’s involvement in the construction of social security housing has obvious stage characteristics. At present, China needs to participate in the construction of social security housing through the government, and at the same time, the participation of market mechanisms and social forces is also indispensable. 4.2
Perfecting Laws and Regulations System
Drawing on the experience of Singapore, South Korea and the United States, there are relevant legal supports for different levels of housing security. For example, the German Housing Construction Law provides detailed provisions for the construction of social security housing, as well as the Rental Law and Residential Subsidies Law and other special regulations. First of all, China should set up a “Residential Law” to determine and protect citizens’ right of residence through the law and return the housing to the nature of its residence. Secondly, China should also step up its efforts to issue special laws on the construction of social security housing, such as the “Housing Security Law,” which stipulates the task of local governments in the construction of social security housing, and specifies the construction standards, guarantee targets, and scope of protection. Guide the practice of construction of social security housing, and strive to put the relevant work into practice. 4.3
Provisions for the Construction of Social Security Housing
The important feature of the construction of social security housing in every country of the world is to standardize the construction of affordable housing through a series of rules and regulations. Thus, in accordance with various types of construction such as affordable housing, low-rent housing, public rental housing, the transformation of old urban housing and shantytowns, China clearly defines the financing, development and
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construction, distribution, post-management and some other parts. Formulating a unified standard for affordable housing units is a fabulous example. Secondly, all localities should determine the scale of social security housing in combination with actual conditions and carry out the selection of sites for the construction of affordable housing, land requisition, determination of the volume ratio, and building density, and reflect them in the overall planning of urban planning and land use [30]. In the process of housing construction, access mechanisms for tendering, design, construction, and supervision must also be established to improve the quality of housing construction.
5 Conclusion This paper draws lessons from the models and characteristics of social security housing construction in developed countries, sorts out and summarizes them from a new perspective, and understands more clearly the mode and characteristics of these countries’ social security housing construction and comprehensively grasps the experience of developed country’s social security housing construction. It proposes the establishment of a housing guarantee agency with executive power, improvement of relevant laws and regulations, and fine-grained all aspects of the construction of social security housing to improve and standardize the construction of social security housing in China. However, in the specific implementation, it is necessary to combine the characteristics of different social security housing construction in different regions, and consider China’s regional differences and other factors, establish laws and regulations and technical specifications suitable for China’s construction of social security housing, and further clarify the construction of social security housing. The main body and funding sources to ensure its feasibility and operability. Acknowledgement. This research was supported by grants from the National Science Foundation of China (No. 41561049), the Natural Science Fund for Distinguished Young Scholar of Jiangxi Province (No 20171BCB23049), and the Science and Technology Project of Jiangxi Provincial Education Department (No GJJ150481).
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Research on Demand Forecast of Social Pension Facilities: A Case Study of Chongqing Yu Zhao(&), Jiuxia Tan, and Yang Chen School of Economic and Management, Graduate Student of Chongqing Jiaotong University, Chongqing, China [email protected]
Abstract. With the deepening of the aging process and the gradual weakening of the family’s endowment ability, the demand of institutional endowment facilities will be increasing in the future. In the face of the present shortage and unreasonable allocation of endowment facilities in Chongqing, this paper combines field investigation with Leslie Matrix model to forecast the demand of the facilities of the aged in Chongqing. Firstly, this paper analyzes the current situation of the aging of Chongqing population and the endowment institution, then the population growth and population structure change of Chongqing during the next 10 years are forecasted and analyzed by using Leslie Model based on the relevant data of Chongqing in the “China’s fifth census” “China’s six census”, so as to forecast the number of old-age beds and the nursing staff needed in the pension institutions in Chongqing. The results show that Chongqing will reach an aging peak in 2019 of which Dadukou District peaking in 2020 and other districts peaking in 2019. At the age of the aging, if the number of old-age beds is allocated according to 8%, the biggest gap of the number of the old-age beds is Wanzhou District with a total gap of 2527 and the smallest district is Dadukou District with a total gap of 257. If the provision of care provider in accordance with the 1:10 ratio, the total number of elderly nursing staff 37290–42147 are needed during the peak period of Chongqing. At the same time, according to the results of the research data, this paper asks the corresponding old-age facilities construction suggestion combined with the actual situation of Chongqing. The research results can provide constructive suggestions for the development of the endowment service in Chongqing and help to promote the efficient and reasonable construction of the endowment facilities in urban institutions. Keywords: Social pension facilities
Demand forecast Chongqing
1 Introduction With the deepening of the aging and the approaching of the peak of the elderly population, population aging has become a common trend in the world. China has entered the rapid development stage of population aging. In 2015, the population aged 60 and over was approximately 1.4 million in Chongqing’s main urban area, accounting for 21% of the elderly population in Chongqing, which was 5.56% points higher than the national population aged 60 and over. Compared to 2014, the data © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 457–475, 2021. https://doi.org/10.1007/978-981-15-3977-0_35
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increased by 0.54 and 1.01 respectively. The degree of aging is deepening year by year. It is reported that the elderly population will be more than 8 million people by the year 2020, which will account for 24% of the total population. It can be seen that with the dramatic increase of the number of elderly people, it is urgent to solve the demand of Chongqing endowment facilities; In 2015, the number of beds per 1,000 old people possess in Chongqing was only 16, which was far from the 35 of international standards that shows there is a serious shortage of the number of the old-age facilities; In addition, the existing small-scale family structure model [1] and the increasing demand for elderly care services by the elderly population have increased the demand for the number and quality of nursing staff in the care facilities for the aged. The traditional family pension in China is transitioning to social endowment at a very fast rate. Therefore, this paper takes Chongqing as an example to analyze the characteristics and existing problems of aging population and endowment facilities. Based on the population data in 2010, the population distribution and changing trends of the elderly population in Chongqing in 2011–2025 will be forecasted by using Leslie Matrix model. The number of beds needed by the city’s old-age care institutions and the nursing staff needed by the organization will be made reasonable predictions to address the current situation of the inadequate and large-capacity, so as to provide a reference for the planning of the endowment facilities in Chongqing [2].
2 Research Review In the related research of institutional endowment service facilities, most of them study the endowment facility resource allocation by analyzing the present situation of endowment facilities. In these studies, most are qualitative studies and quantitative studies are relatively deficient, less research on demand forecast. Among them, Tang, taking Zhejiang province as an example, the supply and demand analysis were carried out from the respects of the quantity and development level, type structure, spatial distribution, utilization situation and service level of the old-age facilities and combined the four spatial levels of the province, urban and rural areas, regions and cities respectively [3]; Xu Haiyan deeply dug into the existing problems of the pension institutions in Shanghai through the comprehensive analysis of the characteristics of the aging situation in Shanghai, the challenge of the family endowment, the disposition of the endowment facilities, the service object and the employees and based on the study of the relevant theories and practical cases, the author combined with field investigation to forecast the demand of the facilities of the aged in Shanghai [4]; according to the target of 10% of elderly population to the institutional endowment to retire in the year of 2045 in Shanghai, Lu Jinfei taking Shanghai, a city with a severe population aging in China, as the population scale forecast benchmark to forecast the number of beds for the future pension institutions in Shanghai, the funds required for pension institutions and the needs of doctors [5]. Therefore, what the most important task is to study the planning and construction of endowment facilities and combine with the trend of the elderly population and the actual demand of old people.
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3 Current Situation of Population Aging and Pension Institutions in Chongqing 3.1
Current Situation of Population Aging
According to《the “13th Five-Year Plan” for the development of old-age career development and old-age care system in Chongqing》, at the end of the “Twelfth FiveYear Plan” period, the city’s elderly population aged 60 or over accounted for 20.09% of the city’s total population, which was 3.99% higher than the national average level. During the “Thirteenth Five-Year Plan” period, the city’s aging population will still be in a fast-rising channel, the old-age elderly, disabled old people, elderly people living alone and other elderly care service object will increase significantly. The elderly, as a socially disadvantaged group, will be neglected in the provision of market services. In particular, the construction of public welfare facilities are often crowded out by other for-profit facilities and the demand for old-age care services will be even more prosperous [6]. The aging of the population in Chongqing has characteristics of large-scale, rapid growth, aging, regional differences obviously. The aging of Chongqing mainly has the following characteristics: 3.1.1
The Aging Degree Deepens, the Population of the Old Age Is Increasing Every Year
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China's fifth census
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Fig. 1. Age difference table
The number of people aged 0–14 in 2010 decreased by 0.26% points compared with 2000, while the population of 14–64-year-old and 65-year-old and above had increased
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by 0.07 and 1.32% points respectively (Fig. 1). Obviously, the older population grown faster than the younger population. The reasons for this status quo may be: (1) The state implements the family planning policy strongly and controls the birth rate strictly; (2) The economic level is increasing and the social environment is comprehensive year by year, so that the survival rate [7] of the elderly population increases year by year. According to the “China’s fifth census” and “China’s six census”, the life expectancy in 2000 and 2010 were 71.9 and 75.7 respectively. In terms of the natural life cycle, the body’s skills will deteriorate and morbidity, disability rate will increase after the age of 70, then the population aged 70 and over need more daily care, living health and social services. 3.1.2 The Aging of Population and the Coexistence of Old Age Chongqing has entered an aging society earlier. According to the data from the civil affairs department’s website, the population aged 60 and over has broken through 6.5 million, of which the empty nest elderly has 1.66 million. The elderly population has accounted for 18.61% of the city’s registered population, which higher than the national average level. As of 2015, the population aged 80 and over has 650,000 people, accounting for 18% of the population aged 65 and over. The aging population and the elderly population of the coexistence of the current situation forced Chongqing must speed up the planning and layout of endowment facilities and implement the construction of endowment facilities as soon as possible so as to avoid the restriction of the elderly population pension service. 3.1.3 The Difference in the Number of Elderly Population Is Obvious This study divides Chongqing into five functional areas: urban function core areas, including Yuzhong District, Shapingba District and other areas within the inner ring region; urban function expansion area, including Beibei District and other areas outside the inner ring; new urban development areas, including Jiangjin District, Yongchuan District and other 12 districts; ecological conservation and development area in northeast Chongqing, including Wanzhou District, Fengdu County and other 11 districts and counties; ecological protection and development area of southeast Chongqing, including the Qianjiang District, Xiushan County and other 6 districts. From the distribution of the elderly population in each district (Fig. 2), at the end of 2016, the largest number of elderly people in Chongqing is Wanzhou District, which located in the northeast of Chongqing ecological conservation development area with 386,000 people; The second are Hechuan and Jiangjin District, which located in the new urban development area; the least of which is Chengkou that only with 43900 of elderly population. From the population ratio of the elderly, Yuzhong District is the highest proportion of the elderly population region, accounting for 31%, which located in the urban function expansion area; the following area is Beibei; Youyang and Qianjiang are the least one that only accounted for 26%. Obviously, the spatial distribution of the elderly population in various districts of Chongqing is uneven, the regional differences are obvious.
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Total population
Wanzhou District
Hanjiang District
Fuling District
Nanchuan District
Hanjiang District
Tongliang District
Southern District
Laoshan District
Dadukou District
Yuzhong District
Jiangbei District
Beibei District
South Bank area
Shapingba District
Fengdu County
Changshou District
Banan District
Rongchang District
Dianjiang County
Yunyang County
Wuxi County
Shuyang County
Pengshui County
Wulong District
Chengkou County
Jiulongpo District
Liangping District
Zhongxian
Fengjie County
Yongchuan District
Yu Bei District
Jiangjin District
Hechuan District
Elderly population aged 60 and above
Wanzhou District
Hanjiang District
Fuling District
Nanchuan District
Hanjiang District
Tongliang District
Southern District
Laoshan District
Dadukou District
Yuzhong District
Jiangbei District
Beibei District
South Bank area
Shapingba District
Fengdu County
Changshou District
Banan District
Rongchang District
Dianjiang County
Yunyang County
Wuxi County
Shuyang County
Pengshui County
Wulong District
Chengkou County
Jiulongpo District
Liangping District
Zhongxian
Fengjie County
Yongchuan District
Yu Bei District
Jiangjin District
Hechuan District
Fig. 2. The number of elderly people aged 60 and above in each district of Chongqing in 2016 (Source: Chongqing statistical information network)
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60 years and above account for the population of the district
Wanzhou District
Hanjiang District
Fuling District
Nanchuan District
Hanjiang District
Tongliang District
Southern District
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Yuzhong District
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Beibei District
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Shapingba District
Fengdu County
Changshou District
Banan District
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Dianjiang County
Yunyang County
Wuxi County
Shuyang County
Pengshui County
Wulong District
Chengkou County
Jiulongpo District
Liangping District
Zhongxian
Fengjie County
Yongchuan District Yu Bei District
Jiangjin District
Hechuan District
Fig. 2. (continued)
3.2
Spatial Distribution and Existing Problems of Elderly Care Institutions in Chongqing
3.2.1 Spatial Distribution of Pension Facilities in Chongqing The pension institutions refers to an institution that provides elderly people with comprehensive services such as daily food, cleanliness and life care [8]. The pension institutions surveyed in this research including nursing homes, elderly apartments, nursing homes and old-age care centers [9]. The spatial distribution of pension institutions in Chongqing is studied from three aspects: the number of pension institutions, the number of beds available and the number of beds per 1,000 elderly people possess. This is mainly reflected in the following three aspects:
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Number of pension institutions
Wanzhou District
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Fuling District
Nanchuan District
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Tongliang District
Southern District
Laoshan District
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Yuzhong District
Jiangbei District
Beibei District
South Bank area
Shapingba District
Fengdu County
Changshou District
Banan District
Rongchang District Dianjiang County
Yunyang County
Wuxi County
Shuyang County
Pengshui County
Wulong District
Chengkou County
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Bed number
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Hanjiang District
Fuling District
Nanchuan District
Hanjiang District
Tongliang District
Southern District
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Dadukou District
Yuzhong District
Jiangbei District
Beibei District
South Bank area
Shapingba District
Fengdu County
Changshou District
Banan District
Rongchang District Dianjiang County
Yunyang County
Wuxi County
Shuyang County
Pengshui County
Wulong District
Chengkou County
Jiulongpo District
Liangping District
Zhongxian
Fig. 3. Parameters of pension institutions in various districts in 2015 (Source: Elderly-related websites (www.yanglao.com.cn))
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Number of elderly people aged 60 and above
Wanzhou District
Hanjiang District
Fuling District
Nanchuan District
Hanjiang District
Tongliang District
Southern District
Laoshan District
Dadukou District
Yuzhong District
Jiangbei District
Beibei District
South Bank area
Shapingba District
Fengdu County
Changshou District
Banan District
Rongchang District Dianjiang County
Yunyang County
Wuxi County
Shuyang County
Pengshui County
Wulong District
Chengkou County
Jiulongpo District
Liangping District
Zhongxian
Thousands of elderly people have beds
Wanzhou District
Hanjiang District
Fuling District
Nanchuan District
Hanjiang District
Tongliang District
Southern District
Laoshan District
Dadukou District
Yuzhong District
Jiangbei District
Beibei District
South Bank area
Shapingba District
Fengdu County
Changshou District
Banan District
Rongchang District Dianjiang County
Yunyang County
Wuxi County
Shuyang County
Pengshui County
Wulong District
Chengkou County
Jiulongpo District
Liangping District
Zhongxian
Fig. 3. (continued)
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3.2.2 The Spatial Distribution of Endowment Facilities Are Different As shown in Fig. 3, from the perspective of the spatial distribution of pension institutions in each district, the number of the pension institution in Yubei District is up to 43, followed by Shapingba District and Fuling District, but the number of the pension institution in Qianjiang District and Fengdu County that located in the outskirts of the urban area are smaller, which only with 3 and 2 respectively; Judging from the total number of old-age institutions in the “five functional areas,” by the end of 2015, the number of old-age institutions in new urban development districts was the largest, with a total number of 252, followed by the urban functional core area, and the ecological protection and development area of southeast Chongqing was the least, which only with 23. From the perspective of the overall interior of the “five functional areas,” the distribution of endowment facilities is also very irrational. For example, in the urban function core area, the number of old-age institutions can reach up to 42 in Shapingba District, but there are only 7 in Jiangbei District. It can be seen that the spatial distribution of endowment facilities in Chongqing is unevenly distributed, the total number of old-age institutions in urban centers is much larger than that in the peripheral area and there is a tendency to decrease from the interior to the periphery. The spatial distribution difference is very significant. 3.2.3
The Imbalance Between Supply and Demand of the Pension Institutions and the Small Size of Pension Facilities By statistics, the total number of beds in Chongqing’s pension facilities in 2015 amounted to 42706, the number of beds in most pension institutions were between 50– 100 and the size of pension institutions was small. According to the number of beds per 1,000 elderly people should possess, the number of beds per thousand elderly people possess in Shapingba District reached 21.21, Dadukou District and Nanan District ranked second and third, Fengdu County and Hanjiang District were the least only with the number of beds 0.19,1.67 respectively. Thousands of elderly people in 80% of the region had no more than 10 beds, which was far from the international standard (35 beds per thousand old people should possess) [10]. It can be seen that the development level of the endowment facilities in Chongqing is extremely uneven. The number of beds in each district is extremely lacking. The contradiction between the number of old-age beds and the needs of the elderly are increasingly serious. In addition, the supply and demand of the endowment facilities is unbalance, the development of oldage care services has a long way to go.
4 Study and Application of Forecasting Method for Elderly People in Chongqing 4.1
Research Methods
The changing trend of the elderly population is mainly affected by natural growth and mechanical movements [11]. This study uses the Leslie model to predict and analyze the future population growth and population structure changes in Chongqing based on the “China’s fifth census”, “China’s six census” and other relevant data [2]. The
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research idea of the model is to predict the population number of the Nth 1 age group in the first M 1 years by using the population quantity of the nth age period of the first M. In this study, the data in 2010 is used as benchmark data to predict the number of elderly population in Chongqing from 2011 to 2025. According to the Leslie model, this study makes three basic assumptions: (1) Social stability, there will be no major natural disasters and wars, birth and death rates do not change over time or changes so little that can be ignored; (2) Over a long period of time, the population migration of Chongqing is mainly urban and rural population migration, regardless of the impact of migration on the total population; (3) In a relatively short period of time, the average age change is small and can be considered unchanged; 4.2
Model Establishment
In order to improve the accuracy of the prediction, the study divides age into 18 age groups at 5 intervals, 0–4 years old as the first group, 5–9 years old as the second group and so on, 90-year-old and above for an age group. Since the population grows through the reproduction of female individuals, the number of female individuals is considered as the basic research object [12]. This study has forecasted the total population of Chongqing form 2011 to 2025, including the total female and male population. Therefore, on the basis of the female Leslie Matrix, the model is modified to obtain the model of the total number of the gender population: (1) The predicted starting point population number vector p (0), the specific expression is: T 0 0 0 0 0 pð0Þ ¼ p0 ; p5 ; ; p80 ; p85 ; p90 þ ; p0 ; p5 ; ; p80 ; p85 ; p90 þ Among them, PX indicates the number of female population in all age groups, and P ‘x indicates the number of males in all age groups. 3 2 0 0 ... 0 0 .. 7 6s 7 6 0 . 6 .. 7 .. (2) Survival matrix S ¼ 6 . 7 s5 . 7, 6 7 6 . 5 4 .. s85 s90 þ 3 2 0 0 ... 0 0 . 7 6 0 7 6 s0 .. 7 6 . . 6 0 .. 7 .. S0 ¼ 6 7, among them, Sx indicates the survival rate of s 5 7 6 7 6 .. 5 4 . 0 0 s85 s90 þ
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females of each age group (x, x + 5), and S’x indicates the survival rate of males of each age group (x, x + 5). 2 3 b0 b5 b90 þ 6 0 0 0 7 , bx represents the fertility rate of each (3) Birth Matrix B ¼ 6 .. 7 .. 4 ... . 5 . 0 0 0 age group (x, x + 5). (4) Leslie matrix: 0
L¼
L B0
B B B B B B B B B 0 ¼B 0 B S B B B B B B B @
b0 s0
b5 .. . s5
b00 0 .. .
b05 0 .. .
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..
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.. . .
s85 b085 0 .. .
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Among them, b’x indicates the birth rate of the male population in each age group (fertility rate of women of childbearing age * proportion of male infants in the newborn); bx indicates the birth rate of female population in each age group (fertility rate of women of childbearing age * proportion of female infants in newborns); (5) The total population number after 5 years: pð5Þ ¼ Lð0Þ pð0Þ !T 9X 0þ 9X 0þ 0 0 0 0 0 0 0 0 ¼ bi pi ; s0 p0 ; ; s85 p85 þ s90 þ p90 þ ; bi pi ; s0 p0 ; ; s85 p85 þ s90 þ p90 þ i
i
If P(n) is the starting point for prediction, the total population after five years is p (n + 5) = L(n + 5)p(n). 4.3
Result Analysis
The relevant data after processing is substituted into the Leslie model and Matlab software is used to predict the trend of the elderly population in Chongqing in the future. Given the realistic factors such as the rapid development of economic and social, the change of the old people’s concept and the support of the national policies [13], this paper only predicts the changing trend of the elderly population in Chongqing in the future of 2011–2025.
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AGEING TRENDS IN CHONGQING 1600.00 1400.00 1200.00 1000.00 800.00 600.00 400.00 200.00 0.00 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Population aged 60 or above
Population aged 80 and above
Fig. 4. Forecast of ageing and ageing trends in Chongqing
As shown in the forecast results (Fig. 4), the resident elderly population aged 60 and above exceeded 10 million in 2015 and peaked at 14.3212 million in 2019. From 2014 to 2018, the increase of the elderly population is relatively large. 2018–2023 is the peak interval of the elderly population. The highest peak value of the elderly population is as 3.85 times as the initial year of 2011, the elderly population will show a downward trend in 2020–2025, but the elderly population in 2025 with 8.576 million elderly people is also as 1.69 times as the initial year of 2011. It can be seen that the growth rate of the elderly population shows an upward trend. At the same time, the number of senior citizens aged 80 and above with a breakthrough of 4 million in 2016 is also rising rapidly. The proportion of senior citizens in the elderly population will exceed 47% in 2019, reaching a peak of 7,515,100 in 2022, which accounts for 57% of the elderly population and takes as 8.65 times as the starting year. It can be seen that the senior citizens in Chongqing is increasing in proportion to the elderly population in the year, which is the main reason for the rapid increase of the elderly population in Chongqing [2]. Therefore, there will still be the coexistence of the problem of the elderly population and the senior citizens during the next 10 years, the planning and construction of endowment facilities is imminent. All districts will reach a peak in 2019 except Dadukou that will reach the peak of the elderly population in 2020. Among them, the four districts with the largest elderly population are: Wanzhou District, Fuling District, Hechuan District, Jiangjin District, which are located in the “ecological conservation and development area in northeast Chongqing” “urban functional expansion zone” and “new urban development zone” respectively. As far as the five function areas are concerned, the new urban development area has the most elderly population, which ups to 6.5055 million people; followed by the ecological conservation and development area in northeast Chongqing with the
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elderly population of 4.2396 million people; ecological protection and development area of southeast Chongqing has the least number of elderly people. It can be seen that the density of the elderly population in the middle circle in Chongqing is relatively large. Because the area of inner circle zone (urban functional core area is about 297.5 km2, the urban development new area is about 2.32 km2, etc.) is generally too small, the total number of elderly people in it is less than the middle circle. In addition, the density of the elderly population in the central district of Chongqing is declining. Most of the elderly population is distributed in the peripheral areas and the degree of aging is higher. The research result shows that the aging degree of the central district will gradually deepen in the future and the population density of the elderly population in urban function development areas will increase, followed by urban function expansion area, while the density of elderly population in new urban development areas will show a downward trend. But generally speaking, the aging problem of Chongqing mainly concentrates on the urban development area and the urban function expansion district. According to the area, the endowment facility development space of the urban function core zone and the urban function expansion district are bigger, which will become the key area of Chongqing endowment facility construction [14].
5 Forecast on the Demand for Elderly Care Facilities in Chongqing In order to solve the status pension quo of “hard-to-find, low-volume, high-demand” of Chongqing, this paper hope to provide constructive advice for the development of the elderly care service in Chongqing and promote the efficient and rational construction of urban institution endowment facilities. This study forecasts the demand of the number of old-age beds and the number of nursing staff based on the total number of elderly people in 2010. 5.1
Demand Forecast of the Number of Old-Age Beds Based on the Total Population
First, according to national designated standards, the number of beds per 1,000 elderly people possess should be 35 by 2020. According to it, the number of the old-age beds in Chongqing are obtained, the expression is as follows: Y ¼ 35x=1000 Y: The actual number of beds to be allocated in various regions of Chongqing in 2011 to 2020. X: The predicted number of elderly population in various regions of Chongqing in 2020. According to calculations, the number of beds and the number of required beds in various regions of Chongqing in 2020 are shown in Fig. 5:
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The number of beds and required beds in various regions of Chongqing in 2020 40000
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Bed number in 2010 Number of beds in 2020 under international standards Peak ageing population Calculate the number of new beds in 8% forecast year
Fig. 5. The number of beds and the number of required beds in various regions of Chongqing in 2020
According to the international standards that per thousand elderly people should possess 35 beds, in 2020, the largest gap of the old-age beds is Wanzhou District, Jiangjin District followed by. The number of newly-added old-age beds per year in Chongqing is forecasted based on the ratio of 8%, the first 5 counties with the largest number of endowment beds gap in Chongqing are Wanzhou, Hechuan, Jiangjin, Yunyang and Yongchuan respectively. Among them, the largest gap in the number of old-age beds is still in Wanzhou District with a total gap of 2527; followed by Hechuan District and Jiangjin District, which the number of gaps is 2290 and 2143 respectively; the least gap in the number of old-age beds is Dadukou District with a total gap of 257. Looking at the five function core areas, the number of newly-added old-age beds per year of the “new urban development area” will be 16,585, ranking first; the “ecological conservation and development area in northeast Chongqing” followed by, which needs the number of 11098 of newly-added old-age beds per year. While the “urban function development area” and “urban function core area” require less than 9,000 new beds per year, but the two
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function areas have a relatively large area of about 5587.86 km2. Therefore, in allocating endowment facilities, it can adjust the spatial layout of the endowment institution, which is closely related to the regional development space and prospect of two functional regions. At the same time, according to the forecast results, the number of required beds is consistent with the predicted results of the elderly population. At present, there are still a large number of gaps in the number of old-age beds in large-scale care facilities of Chongqing. More than 90% of the endowment facilities belong to small and medium-sized pension scale, which have the number of old-age beds between 150–200. In addition, the physical equipment of major endowment facilities can be equipped according to the actual conditions of the service objects in terms of appearance, quality, floor space and performance. While increasing the number of old-age beds, it is also necessary to consider the actual area utilization rate of the old-age care institutions. At present, the actual floor area of most old-age care institutions is not enough to meet the need for configuring the number of newly-added old-age beds. Therefore, in order to avoid the phenomenon of “more beds less land”, new construction or reconstruction of existing buildings may be considered. 5.2
Forecast of the Number of Nursing Staff Based on the Total Number of Elderly Population
With the rapid development of economy and society and the gradual improvement of people’s living standards, the old people’s demand for the quality of old-age service is increasing gradually, there will be a great demand for the elderly care. Therefore, how to determine the reasonable proportion between elderly people and nursing staff is one of the important measures to standardize the management and service standards and improve the management efficiency of the elderly care facilities in Chongqing. According to the Chongqing Municipal Civil Affairs Bureau’s notice regarding the issuance of the “Standards for the Management of Chongqing’s Aged Care Institutions (Trial)”, the proportion of nursing staff and elderly population should be: the proportion of nursing staff and self-care elderly is not less than 1:10; the proportion of nursing staff and the elderly population whose living behavior dependent on facilities is not less than 1:5; the proportion of nursing staff and the elderly population whose living behavior dependent on others assistant is not less than 1:3. Among them, the self-care elderly people are selfcareers who are able to take care of their daily life and do not rely on the help of others. In other words, they are under the age of 80 and the ability of them is assessed as normal. The second type represents the elderly people who rely on crutches, walking aids, and other people’s help for life behavior, or the elderly people aged 80 and over. The ability of them is assessed as mildly disabled. The third type refers to those who are dependent on the care of others for life behavior and are characterized by mildly disabled thinking function, or the elderly people aged 90 and over. The ability of the elderly is assessed as moderately disabled. According to the investigation of the elderly care institutions and health institutions in Shapingba District of Chongqing and the proportion of nursing staff and elderly population in the “Standards for the Management of Services for the Aged Institutions in Chongqing”, the proportion of nursing staff and elderly population in this study is 1:10 (i.e. one nursing staff takes care of 10 elderly population.). The number of newly-added nursing staff per year in Chongqing in 2019 and 2020 is shown in Fig. 6:
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Demand for Nursing Staff in Nursing Agencies of Various Districts and Counties in Chongqing in 2019 and 2020 600
500
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Total number of nursing staff needs in 2019
Total number of nursing staff needs in 2020
Fig. 6. Demand for nursing staff in 2019 and 2020
At present, the small-scale family pension structure can no longer meet the life care, medical care and spiritual care of the elderly, which needs the help of nursing staff care [15]. According to the forecast results at the ratio of 1:10 (i.e. one nursing staff takes care of 10 elderly population.), the demand of the number of the nursing staff in Wanzhou District, Jiangjin District, Hechuan District, Yongchuan area are larger than other districts. Among which, the demand of the number of the nursing staff in Wanzhou District is the most. According to the results, the “new urban development area” is the area with the largest demand for nursing staff among the five major function areas, followed by “urban function expansion area”. The total number of newly-added geriatric nursing staff in Chongqing is 37290–42147 from initial year to peak year. In 2020, there is a slight decline in the number of the elderly population compared with 2019. Therefore, 36430–41245 newly-added geriatric nursing staff are needed in Chongqing in 2020. The analysis shows that the elderly population in Chongqing will reach a peak of 14.3212 million in 2019, the number of which is as 2.82 times as that of the older population in the initial year. On the basis of this population base, according to the forecast, there need 498091 newly-added old-ages beds under the international standard of 2020, however, the number of old-age beds in the first year of 2010 was only 42706. According to statistics, the current number of the old-age beds in Chongqing are
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only 212,000, which is far from the international standard. It’s can be seen that the supply and demand of the old-age beds of Chongqing now is extremely imbalance. So, at the ratio of 8%, there need 36428 newly-added old-ages beds per year. At present, the total number of the elderly nursing staff reaches to 25147 in Chongqing and there is a gap of 15000 nursing staff in Chongqing, The forecast results show that as of 2020, the total demand of newly-added aged nursing staff in Chongqing is 36430–41245. It can be seen that both the number of old-age beds and the elderly nursing staff are imbalance between supply and demand, the future endowment service will be a huge demand industry. Accelerating the professional development of institutional pension services is an important part of the pension facilities development in Chongqing. The development of old-age facilities requires the services of medical rehabilitation and spiritual comfort. In addition, the provision of these services requires a certain degree of expertise, which needs to increase the entry threshold for practitioners, to provide regular training to existing practitioners, to receive new methods and skills from training and to improve the professionalism of older service practitioners.
6 Conclusions and Discussion 6.1
Main Conclusions
At present, the endowment facilities in Chongqing are still deficient in quantity, old-age beds, high-quality nursing personnel and unreasonable distribution. In this paper, the Leslie model is used to predict the changing trend of the aging population in Chongqing in the next 15 years. The results show that Chongqing will reach the peak of aging in 2019 except Dadukou District, the changes in the ageing population of the counties are roughly in similar trend. Based on the projections of the elderly population, the number of old-age beds per 1,000 elderly people possess in Chongqing and the need for nursing staff are forecast. The forecast results show that the population density of Wanzhou, Jiangjin, Hechuan, Yongchuan, Shapingba, Yubei, Banan and so on is large, the number of beds and the demand of nursing staffs are bigger compared with other districts, the number of old-age beds and the elderly nursing staff of the care facilities are imbalance between supply and demand. The demand forecast in the central urban area is significantly higher than that in the outer region, which is closely related to the level of economic and social development in the central city. However, considering the excessive population density of the elderly has a certain inhibitory effect on urban development and the fact that the available area of the central city is relatively small, the actual factors we may consider that the endowment facilities should be planned in the outer regions so that the land resources will be used to the maximum in the construction of endowment facilities. In the future, the problem of population aging in Chongqing will still exist, the proportion of it will be far higher than that in 2010. To avoid the situation of “difficult to find” and “supply less than demand”, Chongqing should start to improve the policy guarantees for the endowment facility construction: (1) Perfecting land supply policies, rationally planning land for endowment facilities and establishing effective land use mechanisms; (2) Improving investment and financial policies, paying attention to
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structural adjustment and management business methods, guiding social capital and private enterprises capital to establish large-scale comprehensive pension institutions; (3) Perfecting tax incentives, increasing the enthusiasm and initiative of social capital and non-governmental organizations in establishing old-age care facilities, fully embody the government’s pension security policies and social pension support capabilities [16]. 6.2
Research Prospects
This study focuses on the prediction of the total population of the elderly in Chongqing and on the basis of it to predict the number of old-age beds and the needs of nursing staff. There are still some deficiencies. (1) Because of the difficulty of data collection and the limitation of objective factors such as research level, data collection and processing have some subjectivity. In future studies, there need to collect more reliable data as far as possible and further improve the data. (2) The population data of all ages of the Chongqing used in this paper are obtained through data processing of all ages of the whole country, which results in a certain gap between the predicted population data of the number of the old people and actual data, so that the prediction value of the number of the old people is higher than actual value. In future studies, more accurate information should be collected or more scientific and reasonable methods should be used to process the data in order to reduce the error between the predicted value and the actual value. (3) This article focuses on predicting the number of old-ages beds and the amount of nursing staff of pension facilities of Chongqing, but considering that different age groups have different needs for endowment facilities, in future studies, the actual needs of older people should be taken into account in the demand forecast.
References 1. Zhanlian, F., Heying, Z., Xinping, G., et al.: The rise of urban aged care institutions in China: development and equity issues. Popul. Dev. 18(6), 16–23 (2012) 2. Xu, H., Wang, X., Zhou, R., et al.: Demand forecast of regional endowment facilities in Shanghai. Urban Probl. 10, 60–66 (2014) 3. Tang. Study on supply and demand analysis and planning strategy of endowment facilities in Zhejiang Province. Zhejiang University (2011) 4. Haiyan, X.: Forecast and analysis on the demand of endowment facilities in Shanghai’s aging peak period. Fudan University (2014) 5. Jinfei, L.: The demand for endowment facilities and medical facilities in the peak age of China’s aging–take Shanghai as an example. ECNU (2013) 6. Liwei, C., Yi. Y.: Problems existing in the construction of elderly care facilities in Chongqing and their planning suggestions. In: Expert Forum on Sustainable Development of Mountainous Cities and Towns (2013) 7. Wu, Y., Wu, Y.: A study on the accommodation degree of the space for the aged real estate —taking Wuhan City as an example. J. Jishou Univ. 39(1), 73–78 (2018)
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8. Xin, X., Yuan, Z.: Spatial distribution pattern and accessibility evaluation of elderly care facilities in nanjing: a two-step mobile search method based on time cost. Mod. Urban Res. 2, 1–11 (2017) 9. Zhuolin, T., Yang, C., Teqi, D.: Evaluation of spatial reachability of the elderly facilities in Beijing. Adv. Geogr. 33(5), 616–624 (2014) 10. Li, L., Zhang, J., Qiu, B., et al.: Research on the optimization of the allocation of endowment facilities in large-scale safe residential districts: a case study of Nanjing City. Mod. Urban Res. 2016(6), 11–15 (2016) 11. Chengdong, Y., Chun, Z., Shuping, W., et al.: Study on spatial distribution and change of older population in Beijing from 2000 to 2010. Urban Dev. Res. 21(2), 66–71 (2014) 12. Zhaoyi, Z.: Analysis of population forecast and aging trend in Hubei based on Leslie model. Sci. Technol. Inf. 15(29), 180–183 (2017) 13. Chen Fei. Research on the development of elderly care in Chongqing under the aging trend. Urban Hous. 23(4) (2016) 14. Yayi, S.: Research on the planning of the aged facilities in shanghai based on the growth of the elderly. World Geogr. Stud. 25(5), 121–130 (2016) 15. Wei, Yu., Baihui, L.: The construction of elderly care service system in China and forecast of demand—taking Shanghai as an example. J. Popul. Sci. 4, 3–13 (2012) 16. Defu, W., Xueyan, T.: Study on the demand and spatial distribution of urban endowment facilities: a case study of Nanning. Guangxi Soc. Sci. 1, 21–25 (2017)
An Evolutionary Game Analysis on the Choice of Urban Housing Purchase Restriction Policy Guancen Wu(&), Shanshan Xi, and Huan Chen School of Management, Shanghai University, Shanghai 200444, China [email protected], [email protected], [email protected]
Abstract. High-growth housing prices have prompted the city’s local government to continue to introduce a series of housing purchase policies aimed at regulating market demand. This paper explores the evolution of the decisionmaking process of the central city and the sub-central city from the perspective of evolutionary game theory, obtains the evolution law and behavior evolution of the two cities according to the replicated dynamic equation, and analyzes the influencing factors of the policy of housing purchase restriction in different types of cities. The results show that different types of city property purchase restrictions on the execution closely relates to the purchase discount policy benefits, spillover effect, the purchase of the implementation of the purchase cost, restriction of increased social welfare, unlimited increase in social risk, economic gains without restriction, value-added benefits of mutual restriction between cities, and the risk of collective irrationality caused by the mutual restriction between cities. Finally, some corresponding recommendations of urban housing purchase restriction have been put forward for the local government to formulate reasonable housing control polices. Keywords: Urban housing purchase Evolutionary game stabilization strategy Central city Sub-central city
Evolutionary
1 Introduction Since the “State Council on Resolutely Curbing the Rapid Increase of House Prices in Some Cities” proposed in 2010, “the local people’s government can take temporary measures to limit the quantities of housing purchases within a certain period of time according to the actual situation”, some cities, such as Beijing, Shanghai, Guangzhou and Shenzhen, have successively introduced a series of housing purchase policies to curb the rapid rise in housing prices. In September of the same year, the country again identified the cities that can implement the purchase restriction policies as cities with over-high house prices, rapid rises, and tight supply. Therefore, a total of 16 first and second-tier cities introduced their own housing purchase restriction policies. The “Notice on Relevant Issues Concerning Further Improvement of the Real Estate Market” in January 2011 also pointed out that cities with direct municipalities, separate plans, the provincial capital, and excessively high house prices and rapid growth need to formulate and implement housing purchase restriction measures. Around August of © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 476–492, 2021. https://doi.org/10.1007/978-981-15-3977-0_36
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the same year, the Ministry of Housing and Urban-Rural Development also issued the standards for the housing purchase of second- and third-tier cities. Thus, the scope of the city that introduced the housing purchase restriction policies continued to expand, and the cities that have implemented the housing purchase restriction basically did not give the specific time for the housing purchase restriction policies. After the housing purchase restriction policies expired, most cities chose to continue to maintain purchase restrictions according to the instructions of the Ministry of Housing and Urban-Rural Development. As China’s economy has entered the new normal and destocking strategies for housing, some cities have temporarily adjusted or cancelled the housing purchase restriction policies. When the urban housing market became more and more fragmented and some real estate prices returned to rise, the national real estate control strategy turned to classified control and city-based governance, and there was no reunification of housing purchase restrictions. The result is that in addition to Beijing, Shanghai, Guangzhou, and Shenzhen, which have consistently insisted on housing purchase restriction policies, new cities have successively introduced housing purchase restriction policies. These cities include not only economically developed areas in the Bohai Bay region, the Yangtze River Delta region, and the Pearl River Delta, but also other second-tier cities in the provincial capital, and even some third- and fourth-tier cities such as Zhangjiakou, Ganzhou, Jiashan, Baoding, and Chuzhou. What is more special is that due to the formal establishment of the Xiong’an New District in 2017, Bazhou, Wen’an, Renqiu and other places have also initiated housing purchase restriction policies. With the increasing number of cities that have joined the list of housing purchase restriction, the differences between the policies for restricting purchases in these regions and the areas for restricting purchases have also increased. This article hopes to discuss the behavioral interaction mechanism of related entities in the implementation of the housing purchase restriction policies in the new context, analyze in depth the main factors that influence the government’s introduction of the housing purchase restriction policies in each city, and judge the development trend of the housing purchase restriction policies as a whole, so as to provide a reference and evidence for local governments to rationally formulate housing control policies. Although research of domestic and foreign scholars on real estate policies is relatively abundant, there is rare to see many restrictions on housing purchase policies that involve the entire city. Due to the special nature of the housing purchase restriction policies, there is no more thorough and systematic research abroad. As far as the domestic situation is concerned, the discussion on the housing purchase restriction policies mainly focuses on the rationality of the purchase restriction policy, the interpretation of legitimacy, and the effectiveness of the purchase restriction [1–9]. In terms of rationality, most scholars tend to use the special housing purchase restriction policies as a transitional institutional arrangement under China’s special national conditions, which is reasonable and can effectively suppress the overheated real estate speculative demand [10–12]. The more tangible effect of the housing purchase restriction policies is that they will undoubtedly limit the investment demand and influence the real estate market from the demand side. However, the effectiveness of the housing purchase restriction policies on housing price control has some controversy among the various cities and even the regional effects of cities [13–23].
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With the housing purchase restriction policies as a housing control policy tool, the connection between its launch and implementation intensity and the local government’s own interest appeals and considerations has become increasingly close. Cao Qingfeng and others believe that the supervision and non-supervision of the central government, the maximization of local government fiscal revenues and official performance, and the country’s consideration of social stability and harmony and overall economic restructuring will affect the introduction and implementation of the housing purchase restriction policies [24]; Han Yonghui expanded the theory of single-center and doublering city model into central cities and small- and medium-sized cities, and added the constraints of housing purchase restriction policies. He analyzed that city heterogeneity decided the dialectical choice of real estate purchase restriction policies, and the purchase restriction policies reduced the investment demand of the rich and caused housing prices to fall in large, medium and small cities. However, the decline in housing prices in small and medium-sized cities is larger than that in large cities [25]. On the basis of previous studies, Cao Qingfeng studied that the “proximity effect” of local governments in space also affected the housing purchase restriction policies of local governments. Since the housing purchase restriction policies had a negative impact on the development of the local real estate market, if the purchasing intensity of the local government in a certain region was higher than that of the neighboring region, which caused housing investors and consumers to flow to the neighboring regions with lower purchase intensity [26]. It is precisely owing to the increasing autonomy of the urban government in the formulation and introduction of the housing purchase restriction policies, this paper has considered the motivation of the introduction of the housing purchase restriction policies from the perspective of the local government on the basis of past research, and established an evolutionary game model of the central city (it refers to a relatively firstline or central city with strong appeal and influence) and the sub-city and sub-central cities (It refers to the first-tier or second-tier cities that have certain attraction but are easily affected by the central city), which analyzed exhaustively the increase and decrease of the cost of benefits after the introduction of the housing purchase restriction policies by each local government and the external spillover effect of the housing purchase restriction policies, and taking into account the effect of the housing purchase restriction intensity and the effect of different types of cities after the purchase restriction. From the point of view of dynamic evolution, the paper investigates the evolutionary stability strategies and the influencing factors of the implementation of housing purchase restriction policies in different types of cities.
2 Research Methodology 2.1
Problem Description
At present, most of the housing purchase restriction policies are central cities where house prices have risen too fast. They are subject to the overheating effects of their own real estate market and have had to implement housing purchase restriction policies. However, due to the obvious difference in the scale of cities and the different
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development goals and starting points of the city itself, the central cities and sub-central cities have considerable gaps in the introduction and formulation of the housing purchase restriction policies, coupled with different levels of awareness of the housing purchase restriction policies, and even sometimes the unclear positioning of their own economic development, therefore, various cities still have some differences in the introduction and intensity of the housing purchase restriction policies. Generally speaking, the housing purchase restriction policies as a tough administrative measure will inevitably destroy the balance of the housing market, and reduce the taxes and land transfer revenue directly related to the local government and the real estate industry, which may lead to the loss of the benefit of investment consumers. However, the implementation of the housing purchase restriction policies can control housing prices by curbing the investment of local residents and foreign workers and the demand for speculative housing purchases, which in turn promotes a rational return of house prices, alleviates social conflicts as a whole, and stabilizes the macro economy. According to the economic externality theory and the geographical proximity effect, the activities of an economic entity will have some impact on others and society, and the housing purchase restriction policies will be also like this. For a central city that is subject to restrictions on housing purchase and its neighboring regions, restrictions on housing purchase may reduce the attractiveness of these places to the outside world, increase the pressure on the residents of the city to buy houses, and exert a certain negative impact on the real estate market, thereby slowing down economic development; If some sub-central cities are not limited to housing purchase, they will likely attract talents and industries in neighboring cities, and the economy will also develop as the wealth effect of housing increases. Of course, because of the government’s pressure, there are also sub-central cities learning to imitate big cities, and then implement the housing purchase restriction policies. Moreover, if these cities don’t have enough public services, there will also be problems of excessive social burden and insufficient bearing capacity of infrastructure. In general, the development of the internal housing market in each city also has a correlation effect with other industries. The implementation of the housing purchase restriction policies will have a certain negative impact on the overall GDP growth of the city through its linkage effect. At the same time, owing to the flow of population, the close social and economic exchanges between cities and cities, and the proximity effect, there are still certain mutual influences on the policies for restricting the housing purchase of cities. Nevertheless, after the local government promulgated the housing purchase restriction policies, the evolutionary game between the city and the city will lead to an overall development and change of the housing purchase restriction policies in cities where the supply and demand of the housing market does not match, and will influence the trend of future housing control policies and the socio-economic development of each city. Therefore, in the evolutionary game model of housing purchase restriction policies, this article defines the game participants as the center city and the sub-center city, and their strategy sets are {restricted purchase, not restricted purchase}. The study hypothesize that the central cities self-executing housing purchase policy is more rapid in responding to the surge in housing prices in the housing market, and for the healthy development of the city and the stability of the housing market as a result of their stronger economic strength and housing market risk forecasting ability. Despite the
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normal economic benefits will be cut down, social welfare will increase. When the analysis finds that the unlimited purchase can also control the housing market, it may choose to cancel the purchase in accordance with the actual situation. Despite the economy will increase, there is great social risks. When the central cities implement the housing purchase restriction policies, it will have a certain degree of influence on the sub-central cities, prompting it to implement purchase restrictions. Sub-central cities’ normal economic returns after purchase restrictions may be reduced thanks to administrative interference, and may even decrease the benefits of undertaking the central cities, but social welfare will increase. If the sub-central cities do not implement purchase restrictions at this time, in addition to their normal returns, they will also undertake some benefits from the central cities, but they will have some social risks. Of course, when the central cities execute the housing purchase restriction policies, and the sub-center cities may also carried out or not considering their own situations. General speaking, when central cities and sub-central cities all actualize the housing purchase restriction policies, it can improve the overall social benefits for the overall housing market, achieve win-win effects, and increase certain additional comprehensive income. And when neither of them executes purchase restrictions, they are not only confronted with social risks, but also increase the collective irrational risks. 2.2
The Construction of Evolutionary Game Model of Housing Purchase Restriction Policies
Evolutionary game theory takes the game participants’ bounded rationality as the premise, and regards the adjustment process of group behavior as a dynamic system. It breaks through the limitations of the classical game theory rational hypothesis, and can systematically examine the participants’ behavioral evolution rules and stability strategies [27]. Considering the bounded rationality of central cities and sub-central cities and the progressiveness of their tactical adjustment process, the paper uses the copy dynamic mechanism to simulate the two-sided repeated game process. Since neither the center cities nor the sub-center cities can find the optimal strategy through a game, they try to find a better strategy through trial and error, summarization and imitation, and finally forming a stable strategy. In this case, the Nash equilibrium under static games does not make a true description of the behavioral characteristics of the central cities and the sub-central cities, but based on the evolutionary game theory, the behavioral strategies of the central cities and the sub-central cities will be more consistent with actual situations. According to the above basic settings, considering 2 2 asymmetric repeated games, the payment matrix of the stage game is shown in Table 1. Table 1. City stage and sub-center city stage game payment matrix The central cities
The sub-central cities
Purchase restriction Not purchase restriction
b1 E1 þ Q1 C 1 þ h1 W b1 E2 þ Q2 C2 þ h2 W b1 E1 þ Q1 C 1
Purchase restriction
c1 E1 þ b2 E2 N 1
Not purchase restriction
b 1 E 2 þ Q2 C 2
c2 E 2 þ b2 E1 N 2
c1 E1 N 1 h1 T c2 E 2 N 2 h2 T
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Symbol Description
Among them, E 1 is the normal economic income of the central cities without executing the housing purchase restriction policies; E 2 is the normal economic return of the subcentral cities without executing the housing purchase restriction policies; b1 is the benefit discount ratio after the implementation of the housing purchase restriction policies; b2 is the proportion of profit spillovers after implementing the housing purchase restriction policies,. In order to simplify the problem, whether the central cities and sub-central cities choose to implement the housing purchase restriction policies or not, the study is based on the assumption that the economic benefits discount and value-added ratio are assumed to be the same, and assume that b1 þ b2 ¼ 1; c1 is the ratio of income appreciation of central cities that do not implement housing purchase restriction policies; c2 is the ratio of income appreciation of non-restricted purchase policies in sub-central cities; C1 is the implementation cost of housing purchase restrictions in central cities; C 2 is the implementation cost of housing purchase restrictions in sub-central cities; Q1 is the overall social benefits after the implementation of the housing purchase restriction policies and improvement of the housing market in the central cities; Q2 is the overall social benefits that the sub-central cities improving the housing market when implementing the housing purchase restriction policies; N 1 is the social risk that the central cities may undertake when purchased independently; N 2 is the social risk that the sub-central cities may undertake when purchased independently; W is the value-added social benefits that is increased when both types of cities limit purchases; T is the collective irrational risk cost that may be borne when both types of cities are not limited to purchases; h1 is the coefficient of increase and decrease of income about a limit-to-purchase or unlimited purchase of central cities when both types of cities are limited to purchases; h2 is the coefficient of increase and decrease of income in the sub-central cities with limited or no-order purchases. Also for the sake of simplicity, this paper presumes the increase and decrease coefficients of value-added income and collective irrational risks for various types of cities are the same. All symbol values are greater than zero.
3 The Evolutionary Game Analysis of the Housing Purchase Restriction Policies in Central Cities and Sub-centers 3.1
Game Model Replication Dynamic Equation
If the proportion of central cities that choose to implement a housing purchase restriction strategy is x, the proportion that choose not to implement a housing purchase restriction strategy is 1 x; the proportion of sub-central cities that choose to implement a housing purchase restriction strategy is y, and the proportion that choose not to implement a housing purchase restriction strategy is 1 y.
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For central cities, the expected benefits of implementing the housing purchase restriction policies are: U 1 ¼ yðb1 E 1 þ Q1 C 1 þ h1 WÞ þ ð1 yÞðb1 E 1 þ Q1 C1 Þ ¼ b1 E 1 þ Q1 C 1 þ yh1 W
ð1Þ
The expected benefits of not implementing the housing purchase restriction policies are: U 2 ¼ yðc1 E1 þ b2 E 2 N 1 Þ þ ð1 yÞðc1 E1 N 1 h1 T Þ ¼ c1 E1 N 1 h1 T þ yðb2 E2 þ h1 TÞ
ð2Þ
The average expected return of the central cities is: ¼ xU 1 þ ð1 xÞU 2 U
ð3Þ
The replication dynamic equation of the central cities’ implementation of the housing purchase restriction policies is: dx Þ ¼ x½U 1 xU 1 ð1 xÞU 2 ¼ xð1 xÞðU 1 U 2 Þ ¼ xð U 1 U dt
ð4Þ
Taking U 1 and U 2 into the copy dynamic equation gives: F ð xÞ ¼
dx ¼ xð1 xÞ½b1 E 1 þ Q1 C1 c1 E1 þ N 1 þ h1 T þ yðh1 W b2 E 2 h1 T Þ dt ð5Þ
For sub-central cities, the expected benefits of implementing the housing purchase restriction policies are: V 1 ¼ xðb1 E 2 þ Q2 C 2 þ h2 W Þ þ ð1 xÞðb1 E 2 þ Q2 C2 Þ ¼ b1 E 2 þ Q2 C2 þ xh2 W
ð6Þ
The expected benefits of not implementing the housing purchase restriction policies are: V 2 ¼ xðc2 E 2 þ b2 E 1 N 2 Þ þ ð1 xÞðc2 E 2 N 2 h2 T Þ ¼ c2 E 2 N 2 h2 T þ xðb2 E 1 þ h2 TÞ
ð7Þ
The average expected return of sub-central cities is: ¼ yV 1 þ ð1 yÞV 2 V
ð8Þ
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The replication dynamic equation of the implementation of the housing restriction policies in the sub-central cities is: dy Þ ¼ y½V 1 yV 1 ð1 yÞV 2 ¼ yð1 yÞðV 1 V 2 Þ ¼ yð V 1 V dt
ð9Þ
V 1 and V 2 are brought into the replication dynamic equation [12] to get: Fð yÞ ¼
dy ¼ yð1 yÞ½b1 E 2 þ Q2 C 2 c2 E 2 þ N 2 þ h2 T þ xðh2 W b2 E1 h2 T Þ dt ð10Þ
Combining Eqs. (5) and (10) will result in replicating dynamic systems for subcentral cities and central cities:
F ð xÞ ¼ dx dt ¼ xð1 xÞ½b1 E 1 þ Q1 C 1 c1 E 1 þ N 1 þ h1 T þ yðh1 W b2 E 2 h1 T Þ dy F ð yÞ ¼ dt ¼ yð1 yÞ½b1 E 2 þ Q2 C 2 c2 E 2 þ N 2 þ h2 T þ xðh2 W b2 E1 h2 T Þ ð11Þ
3.2
Equilibrium Point and Stability Analysis of Game Model
The strategy combination corresponding to the equilibrium point of the replication dynamic system (11) is an equilibrium of the evolutionary game, which is referred to as evolutionary equilibrium. If the trajectory starting from an arbitrarily small neighborhood of an equilibrium point in the system eventually evolves toward this equilibrium point, the equilibrium point is said to be locally asymptotically stable, that is the evolutionary stability point. Using the local stability analysis method of Jacobian matrix, the local asymptotic stability of the equilibrium point can be analyzed, and the evolution stability point and its corresponding evolution stability strategy (ESS) are obtained. To find the partial derivative of the replicated dynamic equations in the system, the Jacobian matrix is [12]:
ð12Þ The determinant of matrix J is: det J ¼ ð1 2xÞ½b1 E1 þ Q1 C 1 c1 E 1 þ N 1 þ h1 T þ yðh1 W b2 E 2 h1 T Þð1 2yÞ½b1 E2 þ Q2 C2 c2 E 2 þ N 2 þ h2 T þ xðh2 W b2 E 1 h2 T Þ ðh1 W b2 E 2 h1 T Þðh2 W b2 E 1 h2 T Þxð1 xÞyð1 yÞ ð13Þ
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The trace of matrix J is: tr J ¼ ð1 2xÞ½b1 E 1 þ Q1 C 1 c1 E 1 þ N 1 þ h1 T þ yðh1 W b2 E2 h1 T Þ þ ð1 2yÞ½b1 E 2 þ Q2 C2 c2 E 2 þ N 2 þ h2 T þ xðh2 W b2 E1 h2 T Þ ð14Þ In the system (11), let Fð xÞ ¼ 0 and Fð yÞ ¼ 0 to obtain the equilibrium point 2 c2 E 2 þ N 2 þ h2 T O(0,0), A(1,0), B(0,1), C(1,1), D(x*,y*) where x ¼ b1 E2 þ Qb 2EC , 1 þ h2 Th2 W 2
1 c1 E 1 þ N 1 þ h1 T y ¼ b1 E1 þ Qb 1EC . Substituting the value of the equalization point, the 2 2 þ h1 Th1 W expressions of matrix determinants and traces are shown in Table 2.
Table 2. Expressions of matrix determinants and traces corresponding to the equilibrium point of the system (11) The equilibrium point
det J
tr J
(0,0)
(b1 E1 þ Q1 C1 c1 E 1 þ N 1 þ h1 TÞðb1 E 2 þ Q2 C 2 c2 E 2 þ N 2 þ h2 TÞ
(b1 E 1 þ Q1 C1 c1 E 1 þ N 1 þ h1 TÞ þ ðb1 E 2 þ Q2 C2 c2 E 2 þ N 2 þ h2 TÞ
(1,0)
ðb1 E 1 þ Q1 C 1 c1 E 1 þ N 1 þ h1 TÞðb1 E 2 þ Q2 C 2 þ h2 W þ N 2 c2 E 2 b2 E1 Þ
ðb1 E1 þ Q1 C1 c1 E 1 þ N 1 þ h1 TÞ þ ðb1 E 2 þ Q2 C 2 þ N 2 þ h2 Tc2 E 2 Þ
(0,1)
ðb1 E 1 þ Q1 C 1 þ h1 W þ N 1 c1 E 1 b2 E2 Þðb1 E 2 þ Q2 C 2 c2 E 2 þ N 2 þ h2 TÞ
((b1 E 1 þ Q1 C1 þ h1 W þ N 1 c1 E 1 b2 E 2 Þ ððb1 E 2 þ Q2 C2 c2 E2 þ N 2 þ h2 TÞ
(1,1)
(b1 E1 þ Q1 C1 þ h1 W þ N 1 c1 E 1 b2 E 2 Þðb1 E 2 þ Q2 C 2 þ h2 W þ N 2 c2 E 2 b2 E1 Þ
ðb1 E1 þ Q1 C1 þ h1 W þ N 1 c1 E1 b2 E 2 Þ ðb1 E 2 þ Q2 C 2 þ h2 W þ N 2 c2 E2 b2 E 1 Þ
(x*,y*)
0
In the expression, making p1 ¼ b1 E 1 þ Q1 C 1 c1 E1 þ N 1 þ h1 T, p1 is the difference between the net income of the executed restricted purchases and the net income of the non-executed restricted purchases in the central cities when the subcentral cities are not limited to purchase. p2 ¼ b1 E2 þ Q2 C2 c2 E 2 þ N 2 þ h2 T, p2 is the difference between the net income of the sub-central cities in the implementation of purchase restriction and the net income of non-restricted purchases when the central cities are not limited to purchase. p3 ¼ b1 E1 þ Q1 C1 þ h1 W þ N 1 c1 E 1 b2 E 2 , p3 is the difference between the net income of the central cities in the restrictedpurchase implementation and the net income of the non-execution of the restricted purchase when the sub-central cities are limited to purchase. p4 ¼ b1 E2 þ Q2 C2 þ h2 W þ N 2 c2 E2 b2 E 1 , p4 is the difference between the net income of the sub-central cities in the implementation of purchase restriction and the net income of the non-restricted purchase when the central cities are limited to purchase. According to the evolutionary game theory, the equilibrium points simultaneously satisfied det J [ 0 and tr J\0 are as the evolutionary stable points of the system. Obviously, there is tr J ¼ 0 at the local equilibrium point D(x*,y*), so the local equilibrium point D(x*,y*) is not ESS. Therefore, only the remaining four equilibrium points need to be considered.
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According to the system (11), the values of the determinants and traces of the equilibrium points of the Jacobian matrix J can be obtained, and the local stability can be determined. Due to the different values of the parameters, the final determination of the local stable points is different. For the 16 cases with different values of p1 ; p2 ; p3 and p4 , the previous four cases are analyzed as examples. The local stability determination methods in other cases are consistent. No longer elaborate exhaustively. Case 1: p1 [ 0, p2 [ 0, p3 [ 0, p4 [ 0 When the central cities and the sub-central cities are equal to or greater than zero in the difference between the net income of the purchase restriction and the non-execution limit purchase, the equilibrium point of the game is C(1,1), which is the evolutionary stability point. The corresponding evolutionary stability strategy is {restricted purchase, restricted purchase}, that is, the center cities and sub-central cities tend to choose to implement the housing purchase restriction strategy (Table 3). Table 3. Local stability analysis of equilibrium points (Case 1, 2, 3, 4) The equilibrium point
Case 1 det J
Case 2 tr J
Stability
+
Unsteady
det J
(0,0)
+
+
(1,0)
−
Indefinite
Saddle point
−
(0,1)
−
Indefinite
Saddle point
+
(1,1)
+
−
ESS
−
Case 3 tr J
Stability
+
Unsteady
Indefinite
Saddle point
−
ESS
Indefinite
Saddle point
det J
Case 4 tr J
Stability
tr J
Stability
+
+
Unsteady
det J +
+
Unsteady
+
−
ESS
+
−
ESS
−
Indefinite
Saddle point
+
−
ESS
−
Indefinite
Saddle point
+
+
Unsteady
Case 2: p1 [ 0, p2 [ 0, p3 [ 0, p4 \0 When the difference between the net income of the executed restricted purchases and the net income of the non-executed restricted purchases in the central cities in the case that the sub-central cities are not limited to purchase is greater than zero, the difference between the net income of the sub-central cities in the implementation of purchase restriction and the net income of non-restricted purchases when the central cities are not limited to purchase is greater than zero, the difference between the net income of the execution purchase restriction or not in the central cities while the sub-central cities are not to limit purchase is greater than zero, and the difference between the net income of the execution purchase restriction or not in the sub-central cities while the central cities are not to limit purchase is less than zero, B(1,0) is the evolutionary stable point in the equilibrium point of the game, and its corresponding evolutionary stabilization strategy is {restricted purchase, not restricted purchase}, that is the central cities tend to choose to implement the housing purchase restriction strategy, and the sub-central cities tend to choose not to implement the housing purchase restriction strategy (Table 3). Case 3: p1 [ 0, p2 [ 0, p3 \0, p4 [ 0 When the difference between the net income of the executed restricted purchases and the net income of the non-executed restricted purchases in the central cities in the case that the sub-central cities are not limited to purchase is not greater than zero, the
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difference between the net income of the sub-central cities in the implementation of purchase restriction and the net income of non-restricted purchases when the central cities are not limited to purchase is greater than zero, the difference between the net income of the execution purchase restriction or not in the central cities while the subcentral cities are not to limit purchase is less than zero, and the difference between the net income of the execution purchase restriction or not in the sub-central cities while the central cities are not to limit purchase is great than zero. A(0,1) is the evolutionary stable point in the equilibrium point of the game, and its corresponding evolutionary stabilization strategy is {not restricted purchase, restricted purchase}, that is, the central cities tend to choose not to implement the housing purchase restriction strategy, and the sub-central cities tend to choose to implement the strategy (Table 3). Case 4: p1 [ 0, p2 [ 0, p3 \0, p4 \0 When the difference between the net income of the executed restricted purchases and the net income of the non-executed restricted purchases in the central cities in the case that the sub-central cities are not limited to purchase is not greater than zero, the difference between the net income of the sub-central cities in the implementation of purchase restriction and the net income of non-restricted purchases while the central cities are not limited to purchase is greater than zero, the difference between the net income of the execution purchase restriction or not in the central cities while the subcentral cities are not to limit purchase is less than zero, and the difference between the net income of the execution purchase restriction or not in the sub-central cities while the central cities are not to limit purchase is less than zero. B(1,0) and A(0,1) in the equilibrium point of the game are evolutionary stable points. The corresponding evolutionary stability strategy is {restricted purchase, not restricted purchase} and {not restricted purchase, restricted purchase}, that is one of the central cities and sub-central cities tends to choose to implement the housing purchase restriction strategy, and the other party chooses not to implement it (Table 3). Based on the above analysis, if the central cities and sub-central cities adopt the {restricted purchase, restricted purchase} strategy, both p1 and p2 are greater than zero, that is. b1 E 1 þ Q1 C 1 c1 E1 þ N 1 þ h1 T [ 0, b1 E2 þ Q2 C2 c2 E 2 þ N 2 þ h2 T [ 0 and b2 E 1 þ h2 T h2 W [ 0, the replication dynamic equation for the central cities 2 c2 E 2 þ N 2 þ h2 T (10), if x ¼ b1 E2 þ Qb 2EC , then Fð yÞ ¼ 0, 0\x \1 is the mixed equilib1 þ h2 Th2 W 2
b1 E 2 þ Q2 C 2 c2 E 2 þ N 2 þ h2 T , then Fð yÞ [ 0, b2 E 1 þ h2 Th2 W b1 E 2 þ Q2 C 2 c2 E 2 þ N 2 þ h2 T If x\ , Fð yÞ\0, b2 E 1 þ h2 Th2 W
rium point. If x [
y ! 1 is the evolutionary
stability strategy. y ! 0 is the evolutionary stability strategy. The replication dynamic equation for the sub- central cities (5), if 1 c1 E 1 þ N 1 þ h1 T y ¼ b1 E1 þ Qb 1EC , then Fð xÞ ¼ 0, 0\y \1 is the mixed equilibrium point. 2 þ h1 Th1 W 2
b1 E 1 þ Q1 C 1 c1 E 1 þ N 1 þ h1 T , then Fð xÞ [ 0, x ! 1 b2 E 2 þ h1 Th1 W b1 E 1 þ Q1 C 1 c1 E 1 þ N 1 þ h1 T strategy. If \ , then Fð xÞ\0, x b2 E 2 þ h1 Th1 W
If [
bility strategy.
is the evolutionary stability ! 0 is the evolutionary sta-
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In the 2 2 strategic space of the central cities and the subcentral cities, the stability of the replicated dynamic Eqs. (5) and (10) is comprehensively considered. The evolutionary phase map is shown in Fig. 1. There are five equilibrium points in the graph, which O(0,0) and C (1,1) are evolutionary equilibrium points, points A(1,0) and B (0,1) are unstable points, and the mixed equilibrium point D (x*,y*) is an unstable saddle Fig. 1. Evolutionary phase diagram point. When the central cities and sub-central cities adopt the {restricted purchase, restricted purchase} strategy, both p1 and p2 are greater than zero, that is b1 E1 þ Q1 C1 c1 E 1 þ N 1 þ h1 T [ 0, b1 E 2 þ Q2 C 2 c2 E 2 þ N 2 þ h2 T [ 0 and b2 E1 þ h2 T h2 W [ 0, the equilibrium result of the city purchase game is {not restricted purchase, not restricted purchase} and {restricted purchase, restricted purchase} is shown in Fig. 1. The specific evolutionary outcome depends on the initial state of the social system such as the concept of governance of the local government and the promulgation of the central government policy. When the initial point is in area I (quadrilateral OADB), the system will converge to point O. The two sides of the game will adopt {not restricted purchase, not restricted purchase}; otherwise, if the initial point falls in area II (quadrilateral ACBD), the system will converge to point C, at this time, the final action combination of the two sides of the game is {restricted purchase, restricted purchase}.
4 Analysis and Discussion of Influencing Factors of Evolutionary Stability Strategies In the process of housing purchases by local governments in different cities in the country, there are separate restriction purchase methods such as restricted purchases and unlimited purchases. According to the above model analysis, when the central cities and sub-central cities adopt the {restricted purchase, restricted purchase} strategy, both p1 and p2 are greater than zero, that is b1 E 1 þ Q1 C 1 c1 E1 þ N 1 þ h1 T [ 0, b1 E2 þ Q2 C2 c2 E 2 þ N 2 þ h2 T [ 0 and b2 E1 þ h2 T h2 W [ 0. There are multiple evolutionary stability strategies in the city purchase-restricted game {not restricted purchase, not restricted purchase} and {restricted purchase, restricted purchase}. The direction in which the final result evolves depends on the area SOADB of the area I and the area SACBD of the area II. If SOADB [ SACBD , the probability of unlimited purchase is greater than the probability of restricted purchase, the system will evolve along the DO path to the full unlimited purchase direction; if SOADB \SACBD , the
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probability of unlimited purchase is less than the restricted purchase probability, the system will evolve along the DC path to the overall purchase direction; if SOADB ¼ SACBD , both parties have the same probability of adopting two kinds of strategies, and the direction of system evolution is not clear. According to Fig. 1, the area of Area I is as follows: 1 b E 2 Q2 þ C2 þ c2 E2 N 2 h2 T b1 E1 Q1 þ C 1 þ c1 E1 N 1 h1 T þ Þ SOADB ¼ ð 1 2 h2 W b2 E1 h2 T h 1 W b2 E 2 h 1 T
ð14Þ Factors affecting the size of area I include: Q1 , C1 , Q2 , C2 , m1 , m2 , n1 , n2 , cT and bW, Its impact on the evolutionary direction of urban housing restriction purchases is shown in Table 4.
Table 4. Evolutionary influencing factors of urban housing restrictions Parameter Relationship with D
Evolution area of the phase change
Evolutionary direction
b1 E1
b1 E1 ", y #
SOADB #; SACBD " Restricted purchase
b1 E2
b1 E2 "; x #
SOADB #; SACBD " Restricted purchase
b2 E1
b2 E1 #; x #
SOADB #; SACBD " Restricted purchase
b2 E2
b2 E2 #; y #
SOADB #; SACBD " Restricted purchase
c1 E1
c1 E1 #; y #
SOADB #; SACBD " Restricted purchase
c2 E2
c2 E2 #; x #
SOADB #; SACBD " Restricted purchase
Explanation
The greater discount income the central cities obtain on purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater discount income the subcentral cities obtain on purchase restriction, the greater the probability that both parties choose to restricted purchase will be The smaller profit spillover effect the central cities acquire on purchase restriction, the greater the probability that both parties choose to restricted purchase will be The smaller profit spillover effect the subcentral cities acquire on purchase restriction, the greater the probability that both parties choose to restricted purchase will be The less the central cities receive increase revenue that don’t implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The less the sub-central cities receive increase revenue that don’t implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be
(continued)
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Table 4. (continued) Parameter Relationship with D
Evolution area of the phase change
Evolutionary direction
Q1
Q1 "; y #
SOADB #; SACBD " Restricted purchase
Q2
Q2 "; x #
SOADB #; SACBD " Restricted purchase
C1
C 1 #,y #
SOADB #; SACBD " Restricted purchase
C2
C 2 #,x #
SOADB #; SACBD " Restricted purchase
N1
N 1 "; y #
SOADB #; SACBD " Restricted purchase
N2
N 2 "; x #
SOADB #; SACBD " Restricted purchase
h1 W
h1 W "; y #
SOADB #; SACBD " Restricted purchase
h2 W
h2 W "; x #
SOADB #; SACBD " Restricted purchase
h1 T
h1 T ",x #; y # SOADB #; SACBD " Restricted purchase
h2 T
h2 T ",x #; y # SOADB #; SACBD " Restricted purchase
Explanation
The greater social benefits the central cities create in the implementation of purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater social benefits the sub-central cities create in the implementation of purchase restriction, the greater the probability that both parties choose to restricted purchase will be The less the central cities invest costs on the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The less the sub-central cities invest costs on the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater the central cities undertake the social risks that don’t implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater the central cities undertake the social risks that don’t implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater the value-added benefits of the central cities is when both cities implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater the value-added benefits of the sub-central cities is when both cities implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater the irrational constraint cost of the central cities is when both cities don’t implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be The greater the irrational constraint cost of the central cities is when both cities don’t implement the purchase restriction, the greater the probability that both parties choose to restricted purchase will be
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5 Conclusions and Policy Recommendations In view of the tense trend of the current housing purchase restriction policy, this paper takes the game party’s bounded rationality as the premise, uses the evolutionary game theory to analyze the evolution process of decision-making of central cities and subcentral cities during the implementation of the housing purchase restriction policy, and systematically examines different types of cities about the increase and decrease of the cost of earnings and the external spillover effect of the restriction purchase policy after the introduction of the purchase restriction policy, simultaneously, this paper studies the evolutionary stability policy and the influencing factors of the implementation of housing restriction purchase policy in different types of cities from the point of view of dynamic evolution. The results of the study indicate that different types of cities impose restrictions on the implementation of housing purchase restriction policies is closely associated with restrictions on purchase discounts, spillover effects, restriction purchase execution costs, increased purchase of social benefits, unlimited purchase of increased social risks, unlimited purchases of increased economic benefits, value-added benefits of restricted purchases between cities, and risk costs caused by mutual restriction between cities. Reducing the loss and overflow of profits caused by urban housing purchase restrictions, debasing the implementation cost of urban purchase restrictions, enhancing the social welfare effects brought about through purchase restrictions, increasing the value-added benefits of city purchase restrictions, and accurately predicting the risk of collective irrational constraints caused by the unlimited purchase will impel both parties to implement the housing purchase restriction strategy, so as to achieve the purpose of regulating market demand and residential prices. The overall study is based on the compatibility of other macro-control policies and home purchase restriction policies and the same goal. Based on the above analysis, this paper proposes that cities actively improve their attractiveness, influence and competitiveness, thereby debasing the loss and spillover of urban social economic benefits caused by changes in housing restriction purchase policies. All the cities should also pay attention to changing the concept of development and lay emphasis on the social welfare effects brought by the housing restriction purchase policies. Meanwhile, the research and analysis are based on the premise that cities and cities can learn from it and improve the formulation and implementation of housing restriction purchase policies. The study also doesn’t consider how concrete coordination between the housing purchase restriction policies and other control policies should be implemented. But overall, the local government should accelerate to establish a long-term effect mechanism of the housing development market that will contribute to the smooth and healthy development of the housing market in the context of the effective housing restriction policies.
References 1. Schmidt, C.: Are evolutionary games another way of thinking about game theory. J. Evol. Econ. 14(2), 249–262 (2004) 2. Weibull, J.W.: Evolutionary Game Theory. MIT Press, Cambridge (1997)
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3. Smith, J.M.: The theory of games and the evolution of animal conflicts. J. Theor. Biol. 47(1), 209–221 (1974) 4. Taylor, P.D., Jonker, L.B.: Evolutionary stable strategies and game dynamics. Math. Biosci. 40(1–2), 145–156 (1978) 5. Friedman, D.: Evolutionary games in economics. Econom. J. Econom. Soc. 59(3), 637–666 (1991) 6. Jia, Y.: Between autonomy and regulation: boundary and base for correction— cutting in from home purchase curb. Adm. Law Rev. 03, 51–59 (2011) 7. Zhang, Y., Xiong, Q.: A jurisprudential analysis of the justification of the “purchase restriction order” in China. Soc. Sci. 11, 98–101 (2012) 8. Zhou, J.: An exploration into the legitimacy of the home purchase restriction order and its relief approach. J. Hainan Univ. (Human. Soc. Sci.) 05, 92–99 (2012) 9. Han, Y., Huang, L., Zou, J.: The analysis on the effects of the housing restriction policy in China’s real-estate market. Econ. Manag. (04), 159–169 (2014) 10. Li, D.: Restriction has theoretical basis but belongs to transitional institutional arrangement. China’s Urban and Rural Financial Newspapers 2011-02-25(3) 11. Yin, B., Yin, C.: Limited purchase: a reasonable demand for the healthy development of the property market. Explor. Free Views 5, 53–55 (2011) 12. Wang, S., Peng, X.: An analysis of governmental regulation in real estate market in China: evaluation of legitimacy for “house buying limitation order.” J. Northwest Univ. (Philos. Soc. Sci. Ed.) 3, 148–153 (2011) 13. Chu, C., Zheng, J.: Research on the effect of housing restriction policy in China – concurrently study on the effect of housing restriction policy on urban differences. Price Theory Practice 08, 36–38 (2012) 14. Zhang, D., Zheng, X.: Is house purchase limit an effective policy to control housing price— an empirical study based on 70 upper medium cities. J. Quant. Tech. Econ. 11, 56–72 (2013) 15. Yu, Y., Zhang, S.: Urban housing prices, purchase restriction policy and technological innovation. China Ind. Econ. 06, 98–116 (2017) 16. Wang, M., Huang, Y.: The impact of restriction and property tax on housing prices: an analysis based on long term dynamic equilibrium. World Econ. 1, 141–159 (2013) 17. Zou, L., Gao, B., Zhao, F.: Housing speculation, price increase and the purchase restrictions: a natural experiment from China. Urban Dev. Stud. (6), 53–58 (2014) 18. Mi, J., Liu, C.: Residential housing purchase restriction and the fluctuation of urban house price. Shanghai Econ. Rev. 01, 101–111 (2017) 19. Zhang, H., Li, Y., Chen, X.: Simulation and evaluation of the home-purchase limit policy effect based on a search-matching model. J. Tsinghua Univ. (Sci. Technol.) 01, 68–73 (2015) 20. Zhang, J., Fang, C., He, F.: The impact of house purchase restriction: a regression discontinuity approach. Sci. Decis. Making 07, 1–23 (2015) 21. Liu, X., Xie, J., Zhao, H.: Empirical study on the effect of real estate market under the order of limited purchase. Stat. Decis. 04, 126–128 (2013) 22. Qiao, K.: Has house purchase limit policy taken effect—evidence from China 70 upper middle cities. Res. Econ. Manag. 12, 25–34 (2012) 23. Tao, Hu., Sun, Z.: Limited purchase policy and social welfare: a theoretical discussion. Econ. Sci. 06, 42–49 (2011) 24. Cao, Q., Wang, J., Chen, T.: what affects the housing purchase restriction decision of local governments—the game between central and local government considering policy heterogeneity. J. Public Manag. (4), 82–89, 156–157 (2015)
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25. Han, Y., Zhang, Z., Zou, J.: The analysis on the influence mechanism and policy perspective of the housing restriction policy on China’s urban housing prices—based on single centerdual cycle city model. Econ. Theory Bus. Manag. 07, 16–28 (2016) 26. Cao, Q.: The spatial neighborhood effects and the implementation of housing purchase restriction policy of local governments. Nankai Econ. Stud. 01, 77–89 (2017) 27. Xie, S.: Economic Game Theory, 4th edn. Fudan University Press, Shanghai (2016)
Multi-objective Optimization for the Portfolio Selection on Economic Prefabricated Component Y. H. Gao and C. Mao(&) School of Construction Management and Real Estate, Chongqing University, Chongqing, China [email protected]
Abstract. Off-site construction (OSC) has been proved to be an effective way to improve the quality and operative safety as well as to save labor and time. Nevertheless, present research usually examines only on the feasibility of the OSC, how to design and select the prefabricated components in generic project remains unclear and complex. This study aims to develop a feasible multiobjective algorithm based on genetic algorithm for optimizing the portfolio of prefabricated components, minimizing the cost and the total time of the project. The proposed algorithm has been tested under a generic construction project case and demonstrated that it can produce accurate and effective solutions. Pareto front solutions which are economic and time-saving are illustrated. These feasible portfolios of prefabricated component will help the stakeholders to address the challenge of cost-time trade-off. Keywords: Prefabricated component selection Multi-objective optimization Cost-time trade-off
1 Introduction Building and construction industry has too often failed to meet the needs of modern businesses that must be efficient and well-qualified, and rarely provides best value for clients for a long while. It has been facing great challenges such as long construction time, low efficiency, a large amount of construction defects and waste and environmental problems [1]. Off-site production/construction (OSP/OSC)has been considered to be an effective way to address the challenges above, whose advantages include speed of construction, lower cost, reduce energy using and the need of skilled labor reduce and achieve of zero defects [2]. It is a manufacturing process, generally conducted at a specialized facility, in which various construction materials are product to form a building component of the final installation on site [3]. The US’s National Research Council also identified OSP as an “opportunity for breakthrough achievement” to modern construction industry [4]. To the construction sector in the UK, OSP is also recognized as an approach to improve construction processes [1]. Likewise, the Australian construction sector identified OSP as a key © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 493–502, 2021. https://doi.org/10.1007/978-981-15-3977-0_37
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vision for improving the industry over the next decade [5]. The Hong Kong government has started to promote prefabrication techniques for improving buildability, quality and efficiency in public housing projects [6]. Despite the anecdotal benefits residing in the context of certain projects, the uptake of OSP in the construction industry is still relatively slow. It is as likely to see that the decision making process for prefabricated project is more complex when OSP is applied. Clients, for instance, need to collectively take into account several strategical and tactical factors such as, workflow, stakeholders collaboration, verification for modularization design, craftsmanship, expenditure, logistics, installation, site conditions, labor availability, and so on (Azhar et al., 2012). Otherwise, they would continue to have concerns over the security of their investment. Contractors also need to be informed of the relative profits of applying OSP rather than the traditional construction approaches before they decide to commit significant resources to the fabrication process (Nadim and Goulding, 2011). In addition, it is also unlike to see the industry to value OSP unless several questions are addressed, i.e., which stakeholders could make the most of the technique in terms of cost, time and quality; how to design the optimum prefabrication models given different project size and complexity; what is a set of standardised processes of applying the technique (replicability issues); and how about the effects of the technique on project procurement, teams, culture, professions (Blismas et al., 2005). To respond to the barriers obstructing the wider application of OSP, this paper starts with a review of literature and summarises a few key findings from the review as stated below. Chen et al. (2007) demonstrated automated designing making tools for the project stakeholders to work out optimal prefabrication strategies by which the project economic, social, and environmental performances could be better achieved compared with the traditional construction strategies. There strategies, when embraced as a part of the organizational philosophy, are favourable for eliminating its bureaucratic barriers such as extra reporting and management efforts, and improving business efficiency therein (Pan et al., 2012). Modularization is also perceived as an effective approach to reduce the project design cost and effort. As evidenced by Sered and Reich (2006), a standardization and modularization driven design process (SMDP) can provide the design professional with decision-making insight through contrasting diverse design probabilities and sifting the most cost-effective design scheme. Better economics, together with improved building quality and environmental performance are collectively argued as the potential incentive push for the statutory authorities to apply the OSP techniques to better fulfil project success factors in the long run (Chiang et al., 2006). Encouraging the utilisation of OSP at a greater scale should also justify the engagement and/or commitment issues of the government and industry, and require all the pertinent stakeholders to support the current movements towards a more flexible and market responsive system for integrating the OSP process, product and technology (Pan et al., 2007; Nadim and Goulding, 2011). In China, the semi-prefabrication construction method of precast concrete system (some building elements (e.g. slab, facades, staircases, beams and so on) are factory-built, while the remainder adopts cast in-situ) is prevalent in construction market. Since lack of enough experienced projects, it is difficult to assess whether or not to use prefabricated component, or what is best prefabricated portfolio. Most previous studies on the feasibility(do or not do) while few concerned about the tactical level of “how to do”.
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This paper presented a multi-objective optimization model based on generic algorithm, taking all feasible prefabricated components (including column, beam, slab, façade, staircase, balcony, and internal wall) into consideration, and concern with the cost and time. To this end, an illustrative real residential project is adopted to demonstrate the feasibility of the proposed approach. The remainder of this paper is organized into three sections. The next section presents proposed multi-objective optimization model. It is followed by the application of this model to a real case study. The last section is discussion and conclusion.
2 Multi-objective Optimization Methodology 2.1
Multi-objective Optimization Problem
This study presents the multi-objective optimization (MOO) of the selection strategies of prefabricated components. Considering to the clients’ general project expectation of offsite prefabrication, some principle should be kept: • Using prefabricated components with lower cost • Choosing prefabricated components which can save construction time • Using easy manufacturing components in factory-site To put it brief, the problem is how to minimize the construction cost and the time of the project in a feasible way. it requires the definition of appropriate decision variables, objective functions and constraints, and finally the selection of appropriate prefabrication strategies. We use the notation in Table 1 throughout this paper.
Table 1. The notation in this study Abbr. vti cti dit
2.2
Description Volume of PC component (cast-in-situ) PC component (cast-in-situ) construction fee PC component (cast-in-situ) construction duration
Unit m3 yuan/m3 yuan/m3
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Decision variable reflect the whole set of alternative choices that are available for construction methods or prefabricated components (e.g. column, beam, slab, facade, staircase, balcony, and internal wall). In this paper devote to the volume of PC components/cast-in-situ elements. t denote to the type of building elements/components, t = 1…7, denotes to column, beam, slab, facade, staircase, balcony, and internal wall respectively. i denotes to construction methods, i = 1 denote to cast in-situ construction, i > 1 denote to prefabricated construction.
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Objective Function
Given On the perspective of client, a fundamental and essential demand on construction selection is to save construction cost and faster completion. The construction cost of the whole project consists of each element/component’s construction fee (e.g. column, beam, slab, facade, staircase, balcony, and internal wall). Therefore, the total construction cost Cost(v) is descripted as the following equation: X X Cost(v) ¼ vt cti i t i Where cti – PC component (cast-in-situ element) construction fee per m3 vti – PC component (cast-in-situ element) volume The Total duration of the whole project consists of each element/component’s duration. The Total duration Tdu (v) is descripted as the following equation: Tdu(v) ¼
X X i
vt t i
dit
Where dit – PC component (cast-in-situ element) duration per m3 vti – PC component (cast-in-situ element) volume For the construction fee and the duration of the elements/components, according to the precast construction consumption quota which published by Chinese government, the data of the duration of each prefabricated component can be accessed, several studies has presented that prefabricated method can save construction time. The internal wall can save time by 10%, the staircase, facade, slab can save time by 3%, 1%, 7% respectively [7]. The construction cost of elements/components are accessed according to a large amount of generic programs in China. The available types of prefabricated components and its correspond duration and construction cost were listed in Table 2. 2.4
Objective Constraints P i
vti ¼ vt
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v t t
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Considering the above, the decision problem is formulated as follows: Min CostðvÞ Min TduðvÞ S:t: All constraints of multi-objective problem P i
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Matlab was used to solve the integer programming and detailed analysis is including in the following case study. The multi-objective genetic algorithm is used in this paper. Genetic Algorithm is based on the evolutionary ideas of natural selection, and it represents an intelligent exploration of a random search used to solve optimization problems. The basic techniques of the GAs are designed to simulate processes in natural systems necessary for evolution, specially those follow the principles first laid down by Charles Darwin of “survival of the fittest” [8]. The process of solving the multi-objective problem is briefly described in Fig. 1.
Create f.m document to initial the multi-objective function (2 objective)
Solve the problem: min f(X) subject to: A*X 1 High load 1 High load >1 High load >1 High load 1 High load >1 High load
2.1.4 The Comprehensive Evaluation of Ecological Carrying Capacity Load pressure index reflects the comprehensive evaluation of ecological carrying capacity, and there is a negative correlation between them. Based on the evaluation of support subsystem and pressure subsystem, the ecological carrying capacity of the city is evaluated comprehensively considering the impact of the two subsystems. The final comprehensive evaluation results are shown in Table 9 and Fig. 2.
Table 9. The comprehensive evaluation of the ecological carrying capacity in Chongqing from 2007 to 2016 Year The support index
The evaluation of support system
The pressure index
The evaluation of pressure system
The load pressure index
Index value
The evaluation of load pressure index
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Lower Lower Lower Low Low Low Low Lower Low Low
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Medium Lower Lower Lower Low Low Low Low Low Low
1.1288 0.8728 0.9730 1.2465 1.2153 1.1427 1.9566 0.5398 2.0700 1.8944
>1 1 >1 >1 >1 >1 >1
High load Low load Low load High load High load High load High load Low load High load High load
0.40 0.34 0.26 0.19 0.16 0.13 0.10 0.30 0.08 0.10
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Fig. 2. The comprehensive evaluation of the ecological carrying capacity in Chongqing from 2007 to 2016
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Analysis
As can be seen from Table 6, the support index of the ecological carrying system in Chongqing from 2007 to 2016 is relatively low, and it is declining year by year. In 2014, the support index of Chongqing increased, but it gradually declined after 2014. It shows that in 2014, Chongqing City adopted more effective measures, such as reducing the emission of pollutants and increasing production efficiency, making the supporting capacity of the Chongqing support system more effective. In general, during 2007– 2016, the support capacity of Chongqing’s support system showed a downward trend, indicating that Chongqing needs to take measures to increase the support capacity and alleviate the contradictions brought about by the sharp increase in population and insufficient resources. As can be seen from Table 7, the pressure on Chongqing’s ecological carrying capacity has been declining since 2007–2016. Especially, during the period of 2007– 2012, the pressure index of the Chongqing ecological carrying capacity dropped year by year. This shows that Chongqing achieved some achievements on environmental governance, and solved some problems about the environmental pollution, waste of resources, and insufficient resources due to economic growth. In general, the pressure on Chongqing’s carrying system during 2007–2016 has been on the decline. It shows that the damage to the environment in Chongqing is gradually decreasing. From Table 8, it can be concluded that the load pressure index in Chongqing was low during the period of 2008–2009, which shows under the background of population and economic growth at that time, its ecological environment capacity was relatively surplus. Except for 2014, the ecological carrying capacity was overloaded during the period of 2010–2016, which explained that due to a series of problems such as excessive resource consumption, waste generation and emission increase, the ecological environment of Chongqing was destroyed. However, the load pressure index gradually decreased, which shows that a series of measures such as energy saving, emission reduction, population control, and environmental protection planning in Chongqing slowed the pace of ecological environmental damage in 2014.
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From Table 9 and Fig. 2, we can see that in 2007–2016, the ecological support and pressure system in Chongqing beared relatively low support and pressure. Except for 2014, the ecosystem load in 2010–2016 is high and the ecological environment capacity is relatively tight. In 2014, a series of environmental protection measures were introduced and the seven ecological civilization reform tasks were implemented to improve the ecological carrying capacity of Chongqing.
3 Conclusion (1) Based on the comprehensive evaluation of the ecological carrying capacity in Chongqing, the ecological carrying capacity system is mostly under high load in recent years. The support subsystem has always been under a state of low load bearing, and the pressure on the pressure subsystem is mostly in a relatively low state. Therefore, Chongqing needs to increase the support subsystem and thus improve the comprehensive ecological carrying capacity. (2) Chongqing must adhere to the principle of paying equal attention to ecological protection and economic development, and regard improving ecological carrying capacity as the primary task. Actively change the economic development mode and adjust the industrial structure, and guide the urban planning and construction with the ecological concept, build the ecological economy system with the recycling economy as the core, build the ecological atmosphere with the guidance of the ecological civilization, attach importance to the development and application of ecological technologies, and strengthen the environmental pollution Comprehensive prevention and control, strictly control population growth. At the same time, it will increase the propaganda of ecological environment protection and enhance the people’s ecological awareness. From government to individuals, improve the overall ecological carrying capacity of cities from all aspects so as to achieve sustainable development. Acknowledgment. This study was supported by the National Planning Office of Philosophy and Social Science Foundation of China under Grant No. “17ZDA062”, “15BJY038” and “15AZD025”.
References 1. Costanza, R.: Economic growth, carrying capacity, and the environment. Ecol. Econ. 15(2), 89–90 (1995) 2. Ru, X., Wu, H., Zhangqing, Q.: Comprehensive evaluation for ecoIogicaI carring capacity of Jlnan. 26(01), 87–92 (2013) 3. Chen, H.S., Chen, C.Y., Chang, C.T., Hsieh, T.: The construction and application of a carrying capacity evaluation model in a national park. Stochast. Environ. Res. Risk Assess. 28(6), 1333–1341 (2014) 4. Yan, C., Zhang, Z.: Interspecific interaction strength influences population density more than carrying capacity in more complex ecological networks. Ecol. Model. 332, 1–7 (2016)
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5. Kang, P., Xu, L.: The urban ecological regulation based on ecological carrying capacity. Proc. Environ. Sci. 2, 1692–1700 (2010) 6. Yuan, B., Ren, S., Chen, X.: Can environmental regulation promote the coordinated development of economy and environment in china’s manufacturing industry?–a panel data analysis of 28 sub-sectors. J. Clean. Prod. 149, 11–24 (2017) 7. Mori, K., Christodoulou, A.: Review of sustainability indices and indicators: towards a new City sustainability index (CSI). Environ. Impact Assess. Rev. 32(1), 94–106 (2012) 8. Wang, J., Wei, X., Guo, Q.: A three-dimensional evaluation model for regional carrying capacity of ecological environment to social economic development: model development and a case study in China. Ecol. Indic. 89, 348–355 (2018) 9. Zhang, M., Liu, Y., Jing, W., Wang, T.: Index system of urban resource and environment carrying capacity based on ecological civilization. Environ. Impact Assess. Rev. 68, 90–97 (2018) 10. Peng, J., Yueyue, D., Liu, Y., Xiaoxu, H.: How to assess urban development potential in mountain areas? an approach of ecological carrying capacity in the view of coupled human and natural systems. Ecol. Indic. 60, 1017–1030 (2016) 11. Peng, J., Yueyue, D., Liu, Y., Xiaoxu, H.: How to assess urban development potential in mountain areas? an approach of ecological carrying capacity in the view of coupled human and natural systems. Ecol. Indic. 60, 1017–1030 (2016) 12. Li, Y., Zhou, G.J.: Construction of the Evaluation Model for Ecological Carrying Capacity of Shallow Mountain Area in Beijing. Proc. Environ. Sci. 11, 874–879 (2011) 13. Xu, L., Xie, X.: Theoretic research on the relevant concepts of urban ecosystem carrying capacity. Proc. Environ. Sci. 13, 863–872 (2012) 14. Wang, R., Cheng, J., Zhu, Y., et al.: Evaluation on the coupling coordination of resources and environment carrying capacity in Chinese mining economic zones. Res. Policy 53, 20– 25 (2017) 15. Jin Yue, L., Zhaohua, T.F., et al.: Assessment of ecological carrying capacity on the typical resources-based cities: a case study of Tangshan City. Acta Ecol. Sin. 35(14), 4852–4859 (2015) 16. Geng, W., Rui, D.: Dynamic evaluation and adaptive management countermeasures of ecological carrying capacity of the green transformation in Taiyuan city. Res. Ind. 20(2), 28– 35 (2018) 17. Ding, L., Kun-lun, C., Cheng, S., Wang, X.: Water ecological carrying capacity of urban lakes in the context of rapid urbanization: a case study of East lake in Wuhan. Phys. Chem. Earth 89, 104–113 (2015) 18. Liu, H.L., Shi, P.J., Zhang, S.W., Chen, L.: Research on the urban system scale structure in loess plateau based on the ecological carrying capacity — taking qingyang city as case study, vol. 5, pp. 6018–6023 (2012) 19. Navarro, J., Damian, I.M., Fernandez-Morales, A.: Carrying capacity model applied in coastal destinations. Ann. Tour. Res. 43, 1–19 (2013) 20. Peng, W., Chen, M., Yuan, S., et al.: Comprehensive evaluation of ecological carrying capacity in Wuhan city. Hubei Agri. Sci. 57(3), 37–40 (2018) 21. Ban, X., Wen, H., Song, B., et al.: Evaluation of ecological carrying capacity based on ecological footprint in Shijiazhuang city. resource. Dev. Mark. 26(12), 1074–1077, 1100 (2010)
Overview and Analysis on the Effectiveness of Indicator Systems for Evaluating Urban Carrying Capacity Zhi Liu(&), Yitian Ren, and Liyin Shen School of Construction Management and Real Estate, Chongqing University, Chongqing, China [email protected]
Abstract. With the rapid process of urbanization, the contradiction between resource environment and economic development is increasingly prominent. Correctly understanding and evaluating urban carrying capacity is urgent for promoting sustainable social progress. Although substantial studies of urban carrying capacity have been conducted, existing indicator systems still lack validation on the effectiveness and credibility. Accordingly, 47 indicator systems were selected to identify and compare the information from three aspects based on content analysis. The results from indicator analysis manifest that current assessment systems differ greatly in indicator selection and dimension division, indicating an obstacle for guiding urban planning. The deficiencies of indicator systems can serve as a motivation for researchers and urban planners to develop a holistic and effective evaluation system in order to attain coordinated sustainability. Keywords: Urban carrying capacity Effectiveness
Indicator systems Content analysis
1 Introduction The world has witnessed an unprecedented process of urbanization, which has induced widespread concerns. According to the data from World Urbanization Prospects, the world urbanization rate steadily increased from 31.49% in 1955 to 54.29% in 2016, with an average annual increasing rate of 2.45% (World Bank Open Data, 2018). This trend is much more prominent in those developing countries [1, 2]. For example, in China, the urbanization level has reached 56.78% in 2016 from 13.86% in 1955, while it remained stable in developed countries. Figure 1 illustrates the performance trend of urbanization in some typical countries. Moreover, it is reported that the urbanization level worldwide will continue to grow, reaching over 70% by 2050 [3].
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 869–887, 2021. https://doi.org/10.1007/978-981-15-3977-0_66
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The rapid process of urbanization is an impetus for economic increment and technological advancement. It is investigated that a higher level of urbanization is associated with more per capita income [4, 5]. However, some typical problems have been induced in line with the rapid urbanization process. For example, the low utilization of natural resources, the environmental degradation, the overcrowding of urban communities, etc. It is considered that urban areas are tend to be more vulnerable with the large scale of urban-rural migration and urbanization development activities [6–8]. These problems will be worsen if we ignore the carrying capacity of urban areas whilst only pursuing for the rapid urbanization development. Therefore, the fast urbanization leads to rigorous requirements of urban carrying capacity, which provides a foundation and guidance for sustainable social progress [9]. The National Plan on New Urbanization (2014–2020) published by the Central Committee of the Communist Party of China has addressed the importance of environment and resource carrying capacity in order to optimize the urban-rural layout and to achieve the sustainable urbanization development. With the increasing recognition of the need for enhancing urban carrying capacity, some scholars have made great efforts on this topic, including clarifying the connotation of UCC [10], modeling a conceptual framework [11], analyzing the application of UCC [12] and evaluating the performance of UCC [13, 14]. Indicator systems are imperative methods to visualize the UCC for urban planners and policy makers [15]. Nevertheless, plethora of UCC assessment systems lack sufficient validation on comprehensiveness and effectiveness, due to the differences in research perspectives, assessment units and evaluation methods. These assessment systems can assist policy makers to guide practice, only if they are comprehensive and effective. Furthermore, little researches have been conducted on the review of UCC indicator systems. Accordingly, analyzing the effectiveness of UCC evaluation indicators is indispensable to improve the accuracy of assessment.
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This paper thus aims to analyze indicator systems proposed in previous studies for evaluating urban carrying capacity, including the major components and the application effectiveness of these indicator systems. This holistic review can further provide convictive information on what missed in the previous indicator systems for better understanding and evaluating the urban carrying capacity, and help to improve the sustainability of future urbanization practice. Meanwhile, it can lay a theoretical foundation for the further evaluation study on urban carrying capacity.
2 Literature Review The concept of carrying capacity initially originated from ecology, and permeated into transportation [16, 17], population [18, 19], environment [20], economy [21] and urban construction gradually [22]. Malthus (1888) defined the human carrying capacity as the scale of population that the nature can support and coined a principle of “populationgrain-land” which has generated a profound effect on further research [23]. In the early 1980s, the term of resource carrying capacity was proposed by UNESCO, which means the capacity of indefinitely sustaining population and their activities at a better standard of living [24]. In order to improve development corresponding to carrying capacity, Wackernagel. M (1999) developed the ecological footprint model for assessing the amount of natural resources needed by people [25]. This is regarded as the initial form of natural ecological carrying capacity. On the basis of extending the scope of carrying capacity theory, Oh et al. (2005) pointed out that urban carrying capacity should be a natural and man-made system, including the level of physical development, population growth, land use and human activities [7]. In addition, Tehrani (2013) considered that urban carrying capacity refers to fulfill the requirements of various environmental loads [14]. The premise of this notion is that the environmental thresholds hypothesis exists [26]. Urban carrying capacity is also deemed to be an ensemble of resource carrying capacity, ecological environmental carrying capacity and geological environmental carrying capacity [27]. Although carrying capacity has obtained extensive attention and application, there remain ambiguities in its implication. Consequently, Wei (2015) carried out a review to integrate the existing concept of UCC that can be expressed as five dimensions, including environmental impacts and natural resources, infrastructure and urban services, public perception, institution setting, and society supporting capacity [28]. On the basis of previous studies and Triple Bottom Line sustainable principle, this paper defines urban carrying capacity as an aggregation of environment impact, economic development, social progress, resources supply and demand and some soft elements where culture, institution, spirit and openness are included in. Effective evaluation systems contribute to identifying the status of carrying capacity and monitoring sustainable urban practice. Substantial early researches focus on evaluating UCC by using single factors which is based on the urban short board theory [29]. From the perspective of human carrying capacity, Graymore (2010) estimated the sustainability of region by applying sustaining human carrying capacity model [30]. With considering the pressure that human activities impose on region, this model incorporated a complex interaction of ecological, social and economic phenomena and formed a major pressure categories to progress region management. According to the
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ecological sensitivity analysis and geographic information system, Jin (2017) evaluated urban land carrying capacity from topographic conditions, land use type, regional development intensity and eco-environmental sensitivity [31]. The results indicate that urban land carrying capacity in Hangzhou has allowance compared to current population. Analogously, Liu (2015) established the index system involving population, social economy development, and ecological environment. Water quality and quantity are closely associated with human life and urban development. Wang (2015) explored a method of dynamic assessment on water carrying capacity using PSR framework [32]. This study found that the co-development between social economy and water environment seems to be potential for coordination and sustainability. Furthermore, studies on single factors of carrying capacity are dedicated to marine carrying capacity [33, 34], disaster carrying capacity [35], cultural carrying capacity [36], ecological carrying capacity [36], public service carrying capacity and other critical factors that may limit the development of urban area. However, urban development is limited by the synergy of multi-elements. Subsequently, the study of urban carrying capacity has evolved from single factor to multifactor system, from carrying capacity based on natural resource endowments to comprehensive one covering natural resources and human development needs. Yuan (2018) measured comprehensive carrying capacity of the urban agglomeration in the Yangtze River Economic Belt from a dynamic perspective [37]. The results revealed that the four sub-systems of urban carrying capacity contribute differently and the spatial difference is significantly increasing. Lv (2008) constructed a supply-demand assessment model including water, land, transportation and environment for urban comprehensive carrying capacity, which provides a principle to select evaluation indicators for followup researches [6, 38, 39]. Wei (2015) selected 59 indicators to address environmental impacts and natural resources, infrastructure and urban services, institution, and society supporting systems of urban carrying capacity [23]. Yu (2002) built a regional carrying capacity evaluation system in which economic foundation, population, resources and environment, development potential, and interregional communication are the key dimensions [40]. Wang (2014) applied 41 indicators to examine the urban carrying capacity level which are grouped under land, water, environment, energy, transportation, infrastructure and society sections [41]. Given an abundance of consideration and discussion surrounding carrying capacity assessment, existing researches still lack a general overview and standardization for accurate UCC evaluation. Summers (2004) opined that some indicator systems have limited application due to the imprecision of urban carrying capacity, and efforts are needed to examine the applicability of indicators and set up a systematic assessment. Nevertheless, few studies have an overview, comparison and analysis of current evaluation model at present. To fill this gap, this paper is pursued to examine the differences among existing indicator systems from different aspects and provide theoretical basis for advancing studies.
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3 Methodology Content analysis is employed in this paper to review existing evaluation literatures on carrying capacity which can provide us digital information for comparing and analyzing, and to explore a suitable indicator system for urban planners and policy-makers. It is widely recognized that content analysis can identify the intrinsic characteristics and analyze explicit and implicit information of texts, which is suitable for the research in the field of management [42]. Figure 2 illustrates the major steps in the systematic research process. At the first part of the framework, literature search was implemented to acquire adequate articles relevant to carrying capacity from two databases. Thereafter results were filtered to conduct detailed analysis with three aspects in part two. The analysis from three different dimensions is expected to identify information of indicator systems on urban carrying capacity holistically. Ultimately, according to the analysis results from selected literatures, conclusion and research gap about structure and application of indicator systems were discussed to direct future studies. Simultaneously, suggestions on how to develop a suitable evaluation system of urban carrying capacity were proposed for improving sustainable urban development.
Derived from Two databases: Web of Science
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Fig. 2. Main process adopted in this research
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4 Data Collection Urban carrying capacity and resource environmental carrying capacity were applied as a keyword to retrieve literatures from two academic databases, the Web of Science and CNKI. These two databases comprehensively cover Chinese and foreign core journals and conference proceedings which can ensure the information will not be left out. From 2000 to 2018, there are 1456 literatures relevant to urban carrying capacity published on WOS, while 612 publications were searched out from various Chinese core journals in CNKI. Further literatures retrieval was then conducted to determine the number of papers related to evaluation systems of urban carrying capacity. After removing duplicated articles, a total of 553 papers were remained. Extensive preliminary literature review accomplished above is a foundation for literature selection. Accordingly, literatures screening was performed by reading abstracts and examining the content of the 553 literatures. Take into account the scope of study, this paper adopted the following principles to filter the results of preliminary information collection for elaborate analysis. (1) Evaluation indicator systems of carrying capacity can be divided into single factor assessment and comprehensive assessment [43]. The single factor evaluation systems were not the focus of this paper due to the complexity and systematicness of urban. (2) Some literatures that only lists the dimensions and criteria of evaluation, lacking specific indicators for comparative analysis are inappropriate and unacceptable. For example, Sun (2009) appraised comprehensive carrying capacity of urban agglomerations from land, water, transportation and environment aspects without specifying the indicators [29]. Obviously, this kind of paper cannot be utilized as the source material for analysis. (3) For those retrieved papers which are not relevant to urban construction but published in other areas like arts humanities were excluded. Conforming to these three selection criteria, the number of papers was reduced to 47 for data analysis. These literatures may not cover all urban comprehensive carrying capacity evaluation systems, but they are believed to reflect the current state of researches representatively. The results of preliminary literatures retrieval and targeted literatures selection are demonstrated in Table 1.
Table 1. Data collection results Database
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5 Data Analysis After the above sifting, altogether 47 evaluation indicator systems developed by scholars from various countries were identified in this study. Comparison and analysis from different dimensions will be carried out to completely comprehend the differences and deficiencies of existing indicator systems. 5.1
Overview of the Literatures on Urban Carrying Capacity Evaluation
In the process of literatures retrieval, it can be observed that papers on the assessment of urban carrying capacity in CNKI database were published since 2002, while the literature in WOS database were started in 1986. Zinyama (1986) critically estimated the changes of population distribution in Zimbabwe from the perspective of population carrying capacity [44]. It appears that the research on UCC evaluation is developed from population carrying capacity. Table 2 shows the number of selected indicator systems distributed annually. The number of literatures increased with fluctuation during the study period, peaked at 10 in 2014 and 2015. With the popularity of sustainable development awareness and the requirements of relevant policy documents, it can be predicted that the assessment of urban carrying capacity deserves further study in the future. The scope of literatures retrieval in this paper is limited to core journal articles and conference papers which accounted for 91.5% and 8.5% of the total selected papers respectively. The distribution of the journal titles is not listed here due to the scatteration of these papers. Moreover, comprehensive carrying capacity evaluation can be conducted at different area scales from micro- level to macro-level, which can be classified as villages and counties [45], cities [38], urban agglomerations [37], provinces [46] and countries [47]. Figure 3 displays the distribution of selected indicator systems at these five level. There are 22 indicator systems apply cities as assessment units and only 3 systems focus on the villages and counties level, causing a serious demand for researches to maintain their efforts on carrying capacity evaluation at provinces and countries level. The reason for this phenomenon may be due to the availability of the data. Table 2. Number of publications distributed annually Publication year Number 2002 1 2003 0 2004 0 2005 0 2006 0 2007 0 2008 1 2009 2 (continued)
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Fig. 3. Number of indicator systems at different area scales
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The Analysis on the Methodology of Selected Indicator Systems
The study on the evaluation of urban carrying capacity is mainly based on empirical research, combined with questionnaires, statistics and simulations [48]. A variety of method can be used to determine the value of carrying capacity, such as ecological footprint (Irankhahi, 2017), energy analysis [49], dynamic-based approach, and indicator systems selected for comparative analysis in this paper. Indicator system method is the most commonly used to measure the condition of urban carrying capacity. By constructing the index system and calculating the sub-index value, comprehensive urban carrying capacity is eventually obtained. As can be noticed in Table 3, the following various method can be combined with indicator system to assess and analyze the performance of urban carrying capacity, which helps to propose corresponding suggestions for urban development. These methods that originated from the summary of selected indicator systems can be regarded as a reference for method selection.
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Table 3. Summary of calculation method The main calculation method of urban carrying capacity indicator system Grey correlation Responsivity Surplus ratio Multidimensional vector Coordinated analysis model clustering development degree Standard deviation decision Multi-target linear function Entropy method Spatial correlation analysis Load model
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Catastrophe progression method AHP
State space approach
System dynamic Variation coefficient model method
Information entropy method
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Comparison Between Selected Indicator Systems
Comparison on indicators After analyzing the above two aspects, indicator analysis was conducted to examine the barriers and effectiveness of these established indicator systems. 1080 Indicators from 47 selected literatures are identified for comparison in the following discussion. Considering the availability and measurability of the data, modification is made to improve the applicability of existing indicator systems. Some indicators were removed from the list because they couldn’t be evaluated quantitatively. For example, “Transport dominance” in S18 is regarded as a qualitative indicator that cannot describe the level of institutional carrying capacity accurately. Although qualitative research is also a method to measure carrying capacity, it tends to rely on the experience and knowledge of the researchers, which is considered too subjective for guiding practice. For those indicators which focus on the detailed problem, a general terminology is employed. For instance, “The low-income fatalities and special social class including the elderly and the disabled can get access to living subsidies by government” in S15 is replaced by the term “The coverage rate of social security” for simplifying the data collection. Furthermore, according to the connotation of urban carrying capacity, some indicators are deemed avoidable for assessment and thus excluded from this study. For example, “Pass rate of spot check for key food safety monitoring” and “Pass rate of drug spot check” in S15 are removed as there is a weak connection between these two indicators and urban carrying capacity. On the other hand, the safety monitoring of food and drug is mandatory and the rate of these two indicator is close to 100% in China (State Administration for Market Regulation, 2016). After modifying these indicators extracted from the evaluation system, 993 indicators are remained for further analysis. As shown in Appendix, the number and dimensions of indicators vary dramatically in each system. With a thorough and comprehensive understanding of urban carrying capacity, some researchers created a compilation of the main factors for urban carrying capacity assessment that included 59 indicators. Conversely, only 9 indicators are adopted in S46, and the number of indicators in other evaluation systems hovered in
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this interval. Currently, there is no explicit requirement on the number of indicators for the evaluation system. Nonetheless, it is universally acknowledged that excessive or insufficient number of indicators is not conducive to the application and effectiveness of evaluation systems [50]. Accordingly, a suitable number of indicators should be determined to evaluate and guide urban sustainable development. It can be found from these remained indicators that some issues are involved in many different evaluation systems, where different expressions are often used. For example, “The ratio of sewage treated” is applied in S2 to explain the situation of environment treatment, while “The disposal and recycling rate of sewage” is used in S15. And two indicator systems S12 and S13 address the same issue of public health by using indicator “Medical funds accounts for proportion of financial expenditure” and “The proportion of the medical treatment and public health expenditure in each area” respectively. Table 4 lists some different indicator terms adopted for addressing the same issues. Various indicators are vital to provide valuable information and cover all urban carrying capacity related areas. However, inconsistent complicated index terms will lead to confusion for evaluation in practice. Therefore, for these indicators who assess the same issues but employ different expressions, a common terminology is used to merge them together. Table 4. Different indicator terms adopted for addressing the same issues Issue
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There are then altogether 165 indicators after distilled from original data by merging indicators which have same meaning. As can be seen from Fig. 4, the frequency on the application of these 165 indicators differs widely. It is surprising that no indicator is included in the all 47 evaluation systems, whilst 55 indicators are embodied in only one system. For example, the indicator “Number of fixed telephone users per 10,000 persons” is involved only in S2. The most frequently employed indicator is “Per capita water supply”, which has appeared 36 times. The reason for this phenomenon is not only that different concerns have been given in evaluating urban carrying capacity, but also that there is a lack of corresponding standards to guide indicator selection. The excessive dispersion of these indicators accounts for an obstacle to the effective application of current evaluation systems [1]. It makes sense to recognize this problem and then improve it.
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50 40 30 20 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 27 30 31 35 36 NUMBER OF SYSTEMS
Fig. 4. Number of indicator shared between different systems
Comparison on Dimensions The dimensional classification of reviewed 47 indicator systems can be divided into three categories approximately, as shown in Table 5. For the first category containing pressure indicators and carrying indicators, some improvements have been conducted to cover all aspects of the concept on urban carrying capacity. Based on the state space model, Li (2014) constructed an indicator system from pressure factors and pressure bearing factors [51]. Similarly, Guo (2015) analyzed the resource environmental carrying capacity of Beijing-Tianjin-Hebei region by established evaluation systems including pressure indicators, carrying indicators and potential indicators [52]. Besides, communication indicators in S16 is considered as an interpretation for the extensive concept of urban carrying capacity because it takes into account the two roles of city, as an individual and as an integral part of the urban agglomeration network (Steve Egger, 2006). The second category including society, resources, environment and economy is the most common one to measure urban carrying capacity. Under different circumstances, some minor adjustments are implemented finely, such as increasing agglomeration dimension in S10 and factor market dimension in S4, removing social and
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economic dimension in S3, decomposing the social dimension into infrastructure dimension and transportation dimension in S2, refining resources dimension to land dimension and water dimension in S27. The third category is composed of supply indicator and demand indicator, which is a further discussion to second one. For example, S35 applied supply-demand indicators to evaluate the urban comprehensive carrying capacity of Economic Belt of Tianshan North-slope. The evaluation results indicated that the contribution of supply factors to urban carrying capacity is greater than that of demand factors. Table 5. Number of indicator systems distributed by categories Category Pressure-carrying Society-economyresources-environment Supply-demand
Indicator system S1, S5, S16, S17, S28, S34, S37, S38, S39 S2, S3, S4, S6, S7, S8, S10, S11, S14, S15, S18, S19, S20, S21,S22, S23, S24, S25, S26, S27, S29, S30, S32, S33, S36, S40, S41, S42, S43, S44, S46, S47 S9, S12, S13, S31, S35, S45
Number 9 32
6
There is no explicit consensus on what is the most appropriate dimension division to estimate urban carrying capacity. Yu (2002) used a multi-vector Euclidian space to represent the concept of regional carrying capacity comprising environment, resources and human activities aspects [40]. According to this concept model, urban carrying capacity indicators are then divided into society, economy, resources, environment and nature properties, in which the nature properties is a specific description of the basic attributes for each assessment object. Table 6 and Fig. 5 demonstrate the distribution of 165 indicators under these five dimensions. Table 6. Number of indicators distributed by five dimensions Attribute Dimension Number Proportion Man-made state Society (D1) 65 39.39% Economy (D2) 25 15.15% Resources (D3) 32 19.39% Environment (D4) 37 22.42% Nature state Nature properties (D5) 6 3.64% Total 165 100%
From the data above, it can be observed that the number of indicators in social dimension is obviously larger than other dimensions. Subsequently, a more detailed division of social dimension was conducted to clarify its internal components. Referring to the conceptual equation proposed by Wei (2015), social dimension is divided into six parts in this paper, including infrastructure, population, transportation, technology, service, public perception and culture [28]. Figure 6 illustrates that the number of service indicators and infrastructure indicators is considerable, reaching 18 and 17
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Five dimensions
respectively, followed by the transportation indicators which is 15. However, there are only two indicators in perception part and culture part. This results indicate that little attention has been given to soft elements for evaluating urban carrying capacity in current studies [53]. Thus, it’s necessary to supplement soft factors on the basis of hardware elements studies so as to expand the implication of urban carrying capacity.
Number of indicators Fig. 5. Number of indicators in the five dimensions
Public perception, 2
Culture, 2 Infrastructure, 17
Service, 18
Population, 8 Technology, 3
Transportation, 15
Fig. 6. Number of indicators across six social parts
In referring to the 47 selected evaluation systems in this study, some indicators with the same meaning were divided into different dimensions in different systems. Typically, “Municipal district annual average population” is grouped in social dimension in S4 and S10 but classified into resources dimension in S23. And “Industrial wastewater discharged per 10,000 Yuan GDP” is considered as an environmental indicator in S2, while it is accounted as an economic indicator in S16 and a resource indicator in S6. It appears that the same indicators will be grouped in different dimensions due to the
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different perspective and mindset. Although this divergence has some impact on the effective application of existing evaluation systems, it’s hard to define which division is better. Some other typical indicators that are classified into different dimension are listed in Table 7. Table 7. The same indicators belong to different dimensions Indicator systems Term
S2
S4
S6
S10
S11
D4
D4
D3
D4
D4
D4
D4
D4
D4
D4
D4 D3
S19
S37
S43
D3
D4
D4
D4
D3
D4
D4
D4
D3
D3
D3
D3
D1
Industrial wastewater discharged per 10,000 Yuan GDP Per capita green area The converge ratio of greening in build area Forest coverage rate Water intensity pre GDP
D3
Unemployment rate
D2
D4
D3 D3
D3
D1
For a specific indicator, the frequency of its occurrence in each system can also be recognized as the importance of this indicator approximately [54]. Symbolically, the above statement can be described as shown in Eq. (1), where ni represents the number of times indicator i appears in selected evaluation systems, N is the total number of selected evaluation systems, m represents the number of indicators, i=1, 2, …, m. f ¼ ni=N
m X ni i¼1
N
ð1Þ
Consequently, the importance of remained 165 indicators can are calculated according to Eq. (1) in this paper, which can provide reference for selecting indicators of urban carrying capacity. After ordering the importance of indicators, only the top 15 indicators the importance of the first 30 evaluation indicators is shown in are listed in Table 8 due to the space limitation. Among these 15 indicators, there are 6 environmental indicators, accounting for 40%, which is higher than social indicators. It can be considered that although substantial social indicators are included in existing UCC evaluation systems, resources and environment are still the key factors restricting the development of urban.
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Table 8. The importance ranking of UCC evaluation indicators Indicator Per capita water supply Water intensity pre GDP Per capita constructive land GDP per capita The cultivated area per capita Per capita urban road areas Industrial wastewater discharged per GDP Per capita green area Energy intensity pre GDP The tertiary industry share of GDP The density of population The converge ratio of greening in build area The disposal and recycling rate of Solid waste The ratio of sewage treated The emission intensity of SO2
Frequency 36 35 31 30 27 23 22 22 22 21 20 19 19 19 18
Importance 3.63% 3.52% 3.12% 3.02% 2.72% 2.32% 2.22% 2.22% 2.22% 2.11% 2.01% 1.91% 1.91% 1.91% 1.81%
Dimension D3 D3 D3 D2 D3 D1 D4 D4 D3 D2 D1 D4 D4 D4 D4
6 Discussion From the perspective of research hotspots and research volume, existing studies are relatively mature to some extent. Nevertheless, there are still many deficiencies in defining the connotation of urban carrying capacity and establishing the evaluation systems (Sarma 2012). The results from above analysis reveal that current evaluation systems of urban carrying capacity differ greatly in indicator selection and dimension determination. These differences might contribute to the lack of comparability and credibility between research results, and also hinder urban planners to effectively apply the indicator system for guiding sustainable development. In terms of the research scope, some previous researches of carrying capacity evaluation usually select cities as study objects. A wider range of research should be carried out to take account of the unbalanced and uncoordinated development among cities [37]. Reviewing these selected indicator systems, on the one hand, it can be assumed that time series method and system dynamic model are employed gradually which can help evaluate the dynamic performance of urban carrying capacity rather than static assessment. It’s widely recognized that static evaluation is unable to identify urban performance duly. On the other hand, although method of calculating performance value is as diverse as the current evaluation model, few literatures have expounded the merits and limits of choosing calculation method. Thus, a dialectic analysis is required for applying method appropriately and providing support to assess in further research. Furthermore, the number of existing indicators in distilled systems is considerable, but the indicators are diversified in terminology and properties, demonstrating the lack of criteria for selecting indicators and the need for improving applicability and generality. And little existing research has considered public perception and culture
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indicators which are indispensable for understanding urban carrying capacity holistically. And there is a gap between study and practice due to the availability of data and the measurability of some indicators. Therefore, the above barriers indicate that the current indicator systems is slightly ineffective for application in practice. For visual convenience, a three-dimensional framework of evaluation systems is established to outline the research status quo, as shown in Fig. 7.
Fig. 7. Overall framework of selected indicator systems
7 Conclusion Urban carrying capacity should be a baseline for social development [55]. An effective evaluation system has momentous significance for identifying the level of urban carrying capacity accurately, helping to promote social progress, maintaining the quality of life, and guiding sustainable development. This paper reviewed the implication of urban carrying capacity and examined the effectiveness of distilled 165 indicators from 47 selected systems based on substantial literature reviews. The results of various comparison and detailed analysis demonstrate that present indicator systems are not sufficiently effective to guide practice and no standard evaluation system is applied by the official government. To develop a comprehensive and effective indicator system, future urban carrying capacity researches should highlight the soft factors and interregional flow of development elements, assisting urban planners and policy-makers to understand and improve urban carrying capacity. Acknowledgements. This study is supported by the National Social Science Foundation of China (Grant Nos. 17ZDA062, 15AZD025 and 15BJY038).
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Prediction on the Contribution of Green Building Development to Carbon Emissions Reduction: A Case Study of Chongqing Mengcheng Zhu1(&), Vivian W. Y. Tam2,3, Liyin Shen1, and Yu Zhang1 1
School of Construction Management and Real Estate, International Research Centre for Sustainable Built Environment, Chongqing University, Chongqing, China [email protected] 2 Western Sydney University, School of Computing, Engineering and Mathematics, Penrith, NSW 2751, Australia 3 College of Civil Engineering, Shenzhen University, Shenzhen, China
Abstract. Due to the severe problems caused by huge amount of carbon emissions generation, implementing effectively measures has become an emerging topic around the world. China has set up targets of reducing carbon emissions by 60−65% to 2005 in 2030 in Treaty of Paris. With expectations for energy saving and low carbon emission in construction industry, green building strategies have been conducted by lots of countries. However, limited studies were focused on the relationship between green building targets and carbonemissions targets. This paper represents an empirical study on Chongqing area to explore the relationship between the proportion of green building area and building carbon emissions intensity. Despite green building start in China is extremely recent, a logarithmic curve was adopted to measure the relationship based on the existing data. Corresponding to the carbon emissions target, the green building proportion should reach to 12.82% in 2030. The findings provide a good reference for governments to evaluate the influence of green building strategies to carbon emissions. Keywords: Green building
Building sector Carbon emissions Target
1 Introduction Vast amount of carbon emissions throughout the world had bought serious problems to us. Global warming is one of those problems which is threatening natural ecological system and human survival and development [1–3]. According to International Environment Agency, global carbon emissions had reached a historic high of 32.5 giga tonnes in 2017, a resumption of growth after three years of global carbon emissions remaining flat [4]. Construction industry is one of the main contributors of energy consumption and pollution emissions, which has become the focus of emissions reduction [5, 6], carbon emissions of buildings will reach up to 42.4 billion tonnes in 2035, adding 43% on the level of 2007 [7]. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 888–899, 2021. https://doi.org/10.1007/978-981-15-3977-0_67
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China has become the largest carbon-emissions country across the world since 2011, the carbon emissions of China in 2017 reached 9.1 giga tonnes, contributes about 28% of global emissions [4]. And 60% of carbon emissions in cities comes from maintaining buildings’ function in China [5]. To mitigating the growth of carbon emissions in China, Chinese state council announced a target that carbon emissions for every GDP unit should be reduced by 60–65% in 2030 compared to the 2005 level in Treaty of Paris. In order to reach this target, Chinese government has been devoting huge amounts of effects for reducing carbon emissions by implemented policies and took measures in recent years [5]. Green building is one of these major measures which is adopted by governments around the world for mitigating carbon emissions [8, 9], however, its contribution to carbon emissions has not been assessed. To assist the development of green buildings, a number of assessment tools have been composed including Leadership in Energy and Environmental Design (LEED, United States), BRE Environmental Assessment Method (BREEAM, United Kingdom), Green Building Council of Australia - Green Star (GBCA, Australia) (Zuo and Zhao, 2014). The start of green building is relatively late in China. In 2006, the first version of green building standard, Evaluation Standard for Green Building (GB/T 50378–2006), was published by Ministry of Housing and Urban-Rural Development of the People’s Republic of China, ESGB for short. And it was used to assess and approval of GB since 2008. The second version of ESGB was published in 2014, which increased the ranges of buildings and further refined the evaluation process into design evaluation and operation evaluation [10]. The green building assessment system has been composed in China for around a decade, the area had reached 5.23 * 108 m2 up to the end of August 2016. Chongqing Municipal Commission of Urban Rural Development (CMCURD) had also introduced many relative policies. The development of green building in Chongqing is not only on the leading position of western China, but also above the national average. There are 101 numbers of two-starts-above green building projects and the area attained to 1667.27 * 104 m2 area until April 2018 [11]. However, the effectiveness of implementing the strategies in carbon emissions have not been measured. Without evaluate the progress of green buildings, it is hard for the government to decide whether they should input additional strategies. Therefore, this paper aims to evaluate the quantitative relationship between carbon emissions of building sector and green building area in Chongqing, China. Recommendations will also be suggested for the required level of green buildings in order to achieve the carbon emissions target of the whole country.
2 Literature Review Carbon emissions has become a hot topic since the change of climate awaken the world. Thus numerous studies were focused on digging out the relative factors of carbon emissions. Li, et al. [12] explored the driven factors of the changes of national and regional carbon emissions. Shen, et al. [13] adopted the logarithmic mean Divisia index (LMDI) to decompose carbon emissions factors into five factors by introduced a city development-stage framework. Wang, et al. [14] used Granger causality tests the
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link between carbon emissions with economic structure, energy consumption structure, GDP and urbanization. Villoria-Sáez, et al. [1] used linear regressions to test the carbon emissions trend related to emissions penalties, and the optimal penalty was also found. Accounts for large part of the total carbon emissions, building sector plays a significant role in both low-carbon research and development. As for the boundary of building sector carbon emissions were not normally identified, the calculate method vary from different researchers. Zhang and Wang [15] proposed a hybrid input-output approach that account for supply-chain energy and emissions by China’s building sector, and the carbon emissions of building sector are analyzed by divided the lifecycle into construction, operation and disposal stages. Yang, et al. [16] developed a carbon- calculating methodology and used it to predict the future trend of carbon emissions in China’s building sector. Studies were mainly focused on the exploration of future trend, impact factors and targets set in carbon emissions of building sector. Tan, et al. [17] developed a model system to predict the future trend of carbon emissions in China’s building sector and this study also found that green buildings have a great influence on emission abatement in building sector. Enker and Morrison [18] examined the application of socio-technical transition theory to the building sector and underscored that building could make to a low carbon transition with appropriate policy settings. Wang, et al. [19] analyzed the main features and key challenges of carbon emissions in building sector, what’s more, the carbon emissions reduction target in global building sector is 32 Gt between 2010 and 2050. There were also extensive studies on green buildings which generally focused on the coverage and definition, costs and benefits of green building, and measures for achieving green buildings [7]. Also, some were concentrate on green building rating systems. Mattoni, et al. [20] analyzed the differences and similarities among five green building rating systems in detail. Illankoon, et al. [21] established key credit criteria based on eight green building rating tools. Ye, et al. [22] analyzed the development of green building standards based on 17 green building standards at country level and 50 green building standards in Chinese provinces. While Wu, et al. [23] evaluated construction waste management measures in five green building rating systems. Nevertheless, there were limited studies on the carbon emissions of green buildings. Roh, et al. [24] developed a building life-cycle carbon-emissions assessment program to support Korea’s Green Building Index Certification System. Erfu Guo [25] used lifecycle assessment to calculate carbon emissions of individual green building. Wu, et al. [10] compared carbon emissions between green buildings with non-green buildings based on several individual programs, the different carbon- emissions performance of commercial buildings and residential buildings were also identified. However, limited studies were conducted on the relationship between green building targets and carbonemissions target.
3 Research Methodologies Regression studies is one of the useful methods to examining the relationship [26, 27]. In this study, regression is adopted to measure the relationship between buildings’ carbon emissions intensity and the proportion of green building areas. The regression
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analysis is used for the prediction of future green building development corresponding to its carbon emissions target, both linear and non-linear curves are used, including linear, logarithmic. Data analysis is one of the functions of Microsoft Excel software, which is used to obtain the trend of green building proportion and building carbon emissions intensity in recent years. The green building proportion (GP) means the proportion of green building in new buildings which shows the green building development. The carbon emissions intensity (CI) is the carbon emissions per added value in construction industry which represents the carbon emission performance in building sector. In analyzing carbon emissions after green building strategy implementation, the data of carbon emissions in building sector in Chongqing is measured. Before examining the relationship between green building and carbon emissions, the data of building carbon emissions and green building development need to be collected and calculated. The first step is to identify the boundary of building carbon emissions. Yanfang, et al. [28] divided macro buildings’ carbon emissions into three parts: (1) carbon emissions from construction material; (2) carbon emissions in construction process; and (3) carbon emissions from operating process. All of those raw data used for calculating building carbon emissions could be found in China Energy Statistical Yearbook and Statistical yearbook of Chinese construction industry. Figure 1. Summarizes the research methodologies for this paper.
Fig. 1. Research methodologies flowchart.
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Feng [29] set up the following model to measure building materials carbon emissions (Phase 1) based on life cycle concept and the carbon emissions accounting method in IPCC: X Cb1 ¼ Mi bi ð1 2i Þ ð1Þ i¼1
Where Cb1 denotes the building carbon emissions of phase 1, Mi denotes the consumption of the material j in year t, bi represents the carbon emissions coefficient of material i and 2 represents the recovery factor of material j. As for the material like steel and aluminum, the recovery factor should be considered because they can be recovered after demolition. The recovery factor of steel and aluminum are 0.8 and 0.85 respectively. The values of carbon emissions coefficient of main building materials are listed in Table 1 [30–33].
Table 1. Values of carbon emissions coefficient of main building materials. Material Cement Steel Glass Aluminum Coefficient 0.822 1.789 0.966 2.600
Phase 2 can be calculated according to the following formula which is published in the IPCC Guidelines for National Greenhouse Gas Inventories [34, 35]. Phase 2¼
44 X j E LCVj CFtj Oj 12 j¼1 t
ð2Þ
Where Phase 2 denotes the building carbon emissions of construction process, 44 12 means the molecular weight ratio of carbon dioxide to carbon, Etj denotes the energy consumption of the fuel j in year t, and LCVj represents the lower calorific value of fuel j, CF represents the carbon emissions factors of the fuel j in year t, bi and Oj is the oxidation rate of the fuel j. The values of LCV, CF and O are listed in Table 2. Yanfang, et al. [28] divided building operating emissions into public building, residential building and heating depends on the energy consumption. In this study, we take the energy consumption and electricity consumption into consideration. The calculation rules for energy consumption of building operating are shown in Table 3, Eq. (3) was used to get the power consumption of transport, storage and post (Phase3 b) in Chongqing, what’s more, Eq. (2) was used to make a calculation of the rest (Phase3 a). Above all, building carbon emissions can be calculated as Eq. (4) [28]. Phase3 b ¼ 0:801kg=kwh Electricityconsumption
ð3Þ
Phase 3 ¼ Phase 3 a þ Phase 3 b
ð4Þ
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Table 2. Lower calorific value (LCV), carbon emissions factor (CF) and oxidation rate (O) of energy sources. Energy source Raw Coal Clean Coal Other Washed Coal Briquettes Coke Coke Oven Gas Crude Oil Gasoline Kerosene Diesel Oil Fuel Oil Other Gas Other Petroleum Liquefied Petroleum Refinery Gas Natural Gas a Data resource: [36]. b Data resource: [37]. c Data resource: [38].
LCV (GJ/t) Or (MJ/m3)a 20.908 26.344 8.363 21.636 28.435 16.746 41.816 43.070 43.070 42.652 41.816 5.227 41.816 50.179 46.055 38.931
CF (t C/TJ)b 25.800 27.680 25.800 33.600 29.410 14.000 20.080 18.900 19.600 20.170 21.090 14.000 20.000 17.200 18.200 17.200
Oc 0.918 0.918 0.918 0.900 0.928 0.990 0.979 0.986 0.980 0.982 0.985 0.990 0.980 0.989 0.989 0.990
Table 3. Calculation rules for energy consumption of building operating. Operating energy Public building
Residential building
Total Final Consumption Wholesale, retail trade and hotel, restaurants Power consumption of transport, storage and post Residential consumption
The items to reduce
Explain
Deduct 95% of the gasoline consumption and 35% of the diesel oil
95% of the gasoline is for service industry, 35% of the diesel oil is for the transportation
Deduct all of the gasoline consumption and 95% of the diesel oil
All of the gasoline and 95% of the diesel oil are of the transportation
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Building carbon emissions ðBCÞ ¼ Phase 1 þ Phase 2 þ Phase 3
ð5Þ
CI ¼ BC=added value inconstructionindustry
ð6Þ
4 Empirical Analysis There are four categories of data need to be collected or calculated for this study. One is the building carbon emissions in Chongqing, which was calculated based on the regional energy balance sheet from China energy statistics yearbook and building material consumption from Statistical yearbook of Chinese construction industry. In order to get the total building carbon emissions in Chongqing, Eq. (1), (2), (3) and (4) are referred. The data of green building area in Chongqing from 2010-2015 are given in the website of Chinese green building evaluation label. The added value of construction industry is known according to Chongqing statistical yearbook, which also contains the new building area every year in Chongqing. Considering the availability of data, the period of 2010–2015 were covered as Table 4. Table 4. Collected data of Chongqing from 2010–2015. Data 2010 2011 2012 2013 2014 2015 BC 5791.449 6299.676 5963.43 6584.322 6634.929 6640.169 AVC 634.55 690.31 743.78 1084.42 1265.85 1501.25 S1 12.8 27.2 66.49 147.07 339.11 601.31 S 8292 8989.56 11601.82 12240.32 12815.64 13542.58 X 0.15 0.30 0.57 1.20 2.65 4.44 Y 9.13 9.13 8.02 6.07 5.24 4.42 4 BC: Building carbon emissions (10 tn) AVC: Added value of construction industry (109 yuan) S1: Green building area (104m2) S: new buildings area (104m2) X: The proportion of green building area (X = S1/S)(%) Y: Building carbon emissions intensity (tn/105 yuan)
Fig. 2. Building carbon emissions in Chongq- Fig. 3. Building carbon emissions intensity. ing. (2003–2015) (2003–2015)
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Fig. 4. Green building area in Chongqing. Fig. 5. Green building area proportion in (2010–2015) Chongqing. (2010–2015)
The trend of building carbon emissions in Chongqing from 2003-2015 and building carbon emissions intensity are shown in Fig. 2 and Fig. 3 respectively. The area of green building and green building proportion which indicates the green building development in Chongqing from 2010-2015 are displayed in Fig. 4 and Fig. 5 respectively.
5 Results and Discussions As it can be seen from Fig. 2, the carbon emissions of building carbon emissions in Chongqing shows a slightly decline and went back in 2012, then it reached a plateau. Figure 3 displays a clear tendency of building carbon emissions intensity. It shows that the building carbon emissions intensity increased rapidly in the period of 2007–2011, then it continued to decline after 2011. Chongqing has experienced a sharply growth of urbanization in the few decades, lots of people move to cities brought the huge development of infrastructure and residential buildings construction. With the Fast development of economic, carbon emissions from building sector shows a soar skyrocket. Realizing the important of sustainable development, governments implemented kinds of strategies to control carbon emissions and environmental protection [39], green building is one of them which is aimed at building sector [40]. As you can see from Fig. 4 and Fig. 5, a dramatic growth of green building area and proportion during 2010–2015 can be observed. Both green building area and proportion showed a dramatic upward tendency. Thus, the carbon emissions from building sector is under the effective control after 2011. The relationship between the building carbon emissions and green building development is obvious from observation. To identify the reality of this relationship and explore the precise relationship quantitatively, regression analysis was used. The regression analysis of performance is conducted by using SPSS. Two curves were used to model the relationship, linear and logarithmic. The results are shown in Fig. 5. It can be seen that according to the growth of green building area, building carbon emissions intensity continued to decline. The values of coefficient of determination (R2) were used to identify fitting degrees of models with data. Regarding the F and Sig values of both the two curves from Table 5, the logarithmic displayed better correlation and fits the original data better
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than linear. Therefore, the logarithmic curve is used to represent the relationship between green building proportion and carbon emissions intensity. What’s more, Eq. 4 is used to approximate the relation between the green building area and building carbon emissions intensity. Y ¼ 1:539 ln x þ 6:745
ð7Þ
Table 5. Model summary and parameter estimation. R2 F Sig Constant b1 Linear 0.840 21.018 0.10 8.724 −1.110 Logarithmic 0.956 86.825 0.001 6.745 −1.539
Fig. 6. Relationship between building carbon emissions and green building area.
While Chinese government promised that reduced total carbon emissions per GDP by 60–65% in 2030 compared to the 2005 level, the building carbon emissions should be reduced at the same extent at least. According to previous calculate, building carbon emissions intensity is 7.05, that is to say, y should decline to (1–60%) * 7.05 = 2.82 in 2030. The corresponding green building area should reach to 12.82%. The findings in this paper provide a good reference for Chinese government to evaluate green building strategies affect carbon emissions. Green building strategies have been widely employed by many countries to achieve the common goal of energy saving and emissions reducing. However, “how much green building strategy affect carbon emissions” have not been measured based on province level. The logarithmic
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curve indicate that green building strategy contributes huge effects on carbon emissions reduction. The green building target correspond to total carbon emissions target were also be estimated. Therefore, the findings provide a good reference for governments to decide how much resource and effects should be investing to achieve the carbon emissions goals. The limitation of this study is data used. Because of the lately start of green building strategy in China, the available data of green building area is only from 2010– 2015. Better results are expected if there are additional original data can be obtained. Despite further studies and future research works need to be carried out in next few years. However, this paper develops a detailed method and a first estimation of the relationship between green building development and carbon emissions from building sector on city level. This study not only provided a useful reference for Chongqing government to review the contribution of green building strategies to carbon emissions reduction, but also offered a good example which will be useful for other parts of China and around the world.
6 Conclusion With the challenges of huge carbon emissions around the world, green building is considered as a strategy to create a sustainable environment of construction industry and reduce carbon emissions. The relationship between green building and carbon emissions has been studied by some researchers, with recent research finding of green building strategy efficiency in reducing carbon emissions based on several individual buildings. However, there are few studies based on regional level for evaluating the total contribution. This paper examined the relationship between green building development and carbon emissions intensity on province level, and the finding provide a logarithmic function to evaluate the relationship. With the carbon emissions targets of Chinese state council announced on the 2015 Paris world climate conference, the proportion of green building is measured to reach to 12.82%. This paper also developed equations for Chongqing government to select the level of carbon emissions intensity reduction required by increase to the corresponding green building area proportion. For the further study, the research model should be improved to achieve the better estimation and more influence factors should be considered. Acknowledgement. This research work is supported by the National Planning Office of Philosophy and Social Science Foundation of China under Grant Nos. “15AZD025”, “15BJY038” and “17ZDA062”.
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Evaluation of Low-Carbon City Construction Maturity—A Case Study of Chongqing Linyan Luo(&), Qingqing Wang, and Xiaoyun Du School of Construction Management and Real Estate, Chongqing University, Chongqing, China [email protected]
Abstract. The purpose of this paper is to build a low-carbon city construction maturity evaluation index system in five dimensions: low-carbon development, economic development, energy utilization, urban management and policy tools. The principle of Capability Maturity Model (CMM) was integrated with the index system. Fuzzy Analytical Hierarchy Process (FAHP) method and experts’ opinions were used to quantify the weight of each indicator. Based on the data of Chongqing from 2006 to 2016, this paper analyzes the development course of low-carbon city construction maturity in Chongqing. It was found that lowcarbon city construction maturity can be used to reflect the low-carbon construction level. The wide application of this method can put forward targeted improvement measures for cities at different maturity levels. By this way, lowcarbon city construction in China can be enhanced as a whole. Finally, this research can provide reference for other cities to promote low-carbon development. Keywords: Low-carbon city construction index system Chongqing
Maturity FAHP Evaluation
1 Introduction Global warming caused by carbon emission has been recognized as a threat to public health and welfare. Carbon emission reduction is therefore a necessary task for each country to address the severe challenges arising from global warming. Cities, where most resources are consumed and wastes are produced, emit 70% of global carbon emissions [1, 2]. Developing low-carbon city is a global strategy for achieving carbon emission reduction [3]. China has already overtaken the United States as the biggest emitter of CO2 [4]. Thus, low-carbon city construction has emerged as a key priority in China. China has set up 81 low-carbon pilot cities since 2010 to promote low-carbon city construction [5]. However, the CO2 reduction goals of low-carbon pilot cities haven’t been accomplished yet [6]. The main reason is that the different stages of development in different cities haven’t been taken into consideration when making relevant policies [7]. For better construction of low-carbon city, a lot of research about low-carbon city evaluation has been done. Yang and Li (2012) established a low-carbon city evaluation index system which included low-carbon production, low-carbon consumption, © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 900–917, 2021. https://doi.org/10.1007/978-981-15-3977-0_68
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low-carbon environment and low-carbon urban planning [8]. Du et al. (2016) established an evaluation index system of low-carbon urban construction based on the “input-output”, which can reflect the construction level and effort degree of low-carbon urban construction completely and systematically [9]. A book named Reconstruction of China low-carbon city evaluation indicator system: a methodological guide for application was published in 2013. It provides an overview of the low-carbon progress in various Chinese cities, and also aims to develop a vision, strategy, action plan and supervision system to promote low-carbon city construction, enabling best practice knowledge sharing and developing comprehensive, yet China-specific, low-carbon standards and management systems [10]. There is also some research about the relationship between city economic growth and low-carbon development. Based on the theory of urban development stage and decoupling theory, Lu et al. (2014) divided the development course of low-carbon city into 5 stages: the primary stage, the rapid rising stage, the locking stage, the unlocking stage and the advanced stage [11]. Lei and Wu (2014) used the quadrant method and divided the development course of low-carbon city into 4 stages: low economic growth-low carbon emission, low economic growthhigh carbon emission, high economic growth-high carbon emission and high economic growth-low carbon emission [12]. Chen et al. (2012) demonstrated the rationality of China’s carbon emission scale from the perspective of economic development stage [13]. Kang et al. (2014) divided the city development stage from economic perspective and found out that economic growth was the most important factor driving the increase in emissions, while energy efficiency improvements were primarily responsible for the decrease in emissions [14]. Through a literature review in this field, a problem was found that most of the existing research focuses on the relationship between economic growth and low-carbon development, while little has taken the cities’ stages of development into account from a comprehensive perspective. However, some factors, such as environmental governance and infrastructure construction, are essential for low-carbon development. It is of critical importance to integrate these factors and cities’ stages of development with low-carbon evaluation system. By this way, cities in different stages of low-carbon construction can take measures suitable for their own situation and the level of lowcarbon city construction in China can be improved as a whole. This paper aims to solve this problem. The CMM was used in this paper to establish a low-carbon city construction maturity evaluation index system. Firstly, the principle of construction of the index system was elaborated. Then, the low-carbon city construction maturity evaluation index system was established, which contains 5 first grade indicators, 13 sub-indicators and 38 specific indicators. FAHP was used to determine the specific indicators’ weights. Finally, Chongqing was taken as the study case. Through this empirical research process, the feasibility of applying the CMM model in the evaluation of low-carbon city construction was verified.
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2 Methodology 2.1
CMM
In September 1987, the Software Engineering Institute (SEI) released a brief description of the process maturity framework [15]. After four years of experience with the software process maturity framework and the preliminary version of the maturity questionnaire, the SEI evolved the maturity framework into the Capability Maturity Model for Software (SW-CMM) [16, 17]. SW-CMM dealt specifically with Software, Systems Engineering and Integrated Product Development [18]. The SW-CMM was designed to guide software organizations in selecting process improvement strategies by determining current process maturity and identifying the few issues most critical to software quality and process improvement. By focusing on a limited set of activities and working aggressively to achieve them, an organization can steadily improve its organization-wide software process to enable continuous and lasting gains in software process capability. The CMM is based on knowledge acquired from software process assessments and extensive feedback from both industry and government. In general, a CMM is a collection of practices that help organizations to improve their processes in a specific domain. “Maturity” refers to the degree of formality and optimization of the processes used in an organization. As shown in Fig. 1, maturity levels range from ad hoc, unpredictable practices (Level 1), to formally defined process steps (Level 3), to process improvement optimization (Level 5). The CMM presents sets of recommended practices (KP) in a number of key process areas (KPA) that have been shown to enhance software process capability [19].
Fig. 1. Maturity of processes in the capability maturity model [20]
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Table 1. The characteristics of each low-carbon city construction maturity level Level High carbon
Medium-high carbon Medium carbon
Medium-low carbon Low carbon
Characteristics Extensive economic growth, lack of energy saving and low-carbon deepen awareness, chaotic and aimless low-carbon development, large carbon emissions and energy consumption, irrational energy structure, serious urban pollution and very unsound infrastructure The necessity of low-carbon development is recognized; initial lowcarbon development strategy and policies are put forward; some lowcarbon projects are developed Government sectors carry out low-carbon development work continuously; strictly follow the requirements of low-carbon development index, and realize the standardization of low-carbon development Making quantitative management and assessment of low-carbon city construction work; encourage low-carbon development innovation; establishing the low-carbon construction evaluation index system The whole society is deeply aware of the importance of low-carbon development, and is committed to policy innovation, mechanism innovation and technological innovation; form a virtuous cycle of low-carbon development
Fig. 2. The structure of low-carbon city construction maturity model
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Based on the principle of CMM, this paper aims to identify the maturity level of low-carbon city construction. The CMM for low-carbon city construction would help to determine current low-carbon construction level and identifying the issues most critical to low-carbon construction level improvement. By focusing on a limited set of activities and working aggressively to achieve them, a city can steadily improve its low-carbon construction level to enable continuous and lasting gains. The CMM for low-carbon city construction rank from level 1 to level 5, namely, high carbon level, medium-high carbon level, medium carbon level, medium-low carbon level and low carbon level [21]. Table 1 shows the characteristics of each level Each level presents sets of KPs in a number of KPAs. Every KP needs to be implemented and goals of every KPA need to be achieved to reach a certain maturity level. In this paper, KPAs are coded by first grade indicator U and KPs are coded by sub-indicator A. Figure 2 shows the structure. The maturity level will be assessed by computing the R-score with specific indicator xi. The R-score, which expresses the maturity level of low-carbon city construction, can be calculated by the following equation: R ¼
n X
w i xi
ð1Þ
i¼1
If a < R b, then the maturity level is level 1; If b < R c, then the maturity level is level 2; And so on. where xi denotes standardized index value; wi represents the weight of corresponding index; and a, b, c are constants, which denote the interval boundaries and need to be determined by specific evaluation object. 2.2
FAHP
The Analytic Hierarchy Process (AHP), proposed by Saaty (1980), is a structured qualitative and quantitative technique for helping people deal with complex decisions [22]. The fundamental principle of the analysis is the possibility of connecting information, based on knowledge, to take decisions or previsions; the knowledge can be taken from experience or derived from the application of other tools [23, 24]. Nowadays, many researchers have used AHP in the personnel evaluation problems [25, 26]. However, this method still cannot really reflect the human thinking style [27]. For instance, it uses an exact value to express the decision maker’s opinion in a comparison of a pair-wise matrix, which is problematic [28]. Another, it is often criticized due to its use of unbalanced scale of judgments and its inability to adequately handle the inherent uncertainty and imprecision in the pair-wise comparison process [29]. Therefore, fuzzy AHP (FAHP) was developed to overcome these shortcomings, which is a combination of fuzzy sets theory and AHP. In this paper, FAPH was used to define the weights of specific indicators. A fivestep procedure is provided in Fig. 3.
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Fig. 3. The proposed methodology for FAHP
3 The Construction of Low-Carbon City Construction Maturity Evaluation Index System The purpose of index system construction is to convert the qualitative research into quantitative research. In this paper, the built low-carbon city construction maturity evaluation index system will take KPAs and KPs into account and measure low-carbon city construction maturity with data analysis. Through the comparison and matching between the current low-carbon construction situation and the KPAs in CMM of the city, its maturity level can be determined and evaluated. Therefore, the findings are expected to guide the low-carbon development reasonably and improve the low-carbon construction level. More importantly, this study will make contributions to building a low-carbon and environment-friendly society. 3.1
The Principles of the Construction of the Evaluation Index System
To make the index system more practical, the following three principles were considered: (l) scientificity: Index should be able to evaluate the object objectively. And the methods used would have scientific theories as support; (2) integrity: The choice of indicators could fully and systematically reflect the low-carbon construction level; (3) representativeness: The study could select the most representative integrated indicators and professional indicators. 3.2
Construction of Low-Carbon City Construction Maturity Evaluation Index System
Through a large number of literature review and screening, this paper has collected 21 low-carbon city evaluation index systems as research foundation. According to Evaluation index for construction of green low carbon key small towns (Trial Implementation) [30] and Pilot construction guidelines for low carbon communities in China
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[31], the five KPAs of low-carbon city construction are identified. They are low-carbon development, economic development, energy utilization, urban management and policy tools, respectively. Recommended practices in every KPA are regarded as KPs, which are listed in Table 2. Indicators, whose frequency of occurrence in the 21 index systems is above the median, are taken as the specific indicators to form the evaluation index system. Policy tools indicators of the evaluation index system in this study refer to the policy structure established by Luo et al. [32]. Meanwhile, the principles of index system construction and the requirements of FAHP are taken into account. Finally, the evaluation index system of low-carbon city construction maturity is established as shown in Table 3. The relationship between indicators and low-carbon city construction level is also shown in Table 3. The ‘negative’ means the low-carbon city construction level is reducing, while the corresponding indicator’s value is increasing. However, the ‘positive’ means the low-carbon city construction level is still increasing with the indicator’s value increasing. 3.3
Weighting Each Index Based on FAHP
3.3.1 Development of a Judgment Matrix Using Pair-Wise Comparisons In this study, three experts were invited as the decision makers. Concerning the type of experts, they are professor, young teacher and government environmental protection worker, respectively. Each decision maker was invited to do comparison in pairs on the same level of indicators through questionnaires. According to the relative importance of indicators, they give appropriate scores. The scores of pair-wise comparisons were collected and used to form pair-wise comparison matrices for each decision makers.
Table 2. KPs and KPAs KPA Low-carbon development
Code U1
Economic development
U2
Energy utilization
U3
Urban management
U4
Policy tools
U5
KP Carbon emission Carbon sink Production and consumption Industrial structure Investment in science, technology and environmental protection Urbanization Energy consumption Energy structure Pollution treatment Infrastructure Mandatory policy tools Mixed-type policy tools Voluntary policy tools
Code A11 A12 A21 A22 A23 A24 A31 A32 A41 A42 A51 A52 A53
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The fuzzy judgment matrix P can be gotten: 2
p11 6 .. P = 4. pn1
.. .
3 p1n .. 7 . 5 pnm
where pij denotes the relative importance of indicator i and indicator j; i, j = 1,…,n. Table 4 shows the reference value of the relative importance of indicators, and Table 5 shows the fuzzy judgment matrix expressed by one expert. 3.3.2 Construction of Fuzzy Consistency Matrices To simplify the calculation process, a fuzzy judgment matrix would, firstly, be converted into a fuzzy consistency matrix, which can be expressed as follows: 2
q11 6 Q = 4 ... qn1
.. .
3 q1n .. 7 . 5 qnm
And then qij can be computed by using following equation: qi ¼
n X
pij ; i ¼ 1; 2; . . .; n
ð2Þ
pij ; j ¼ 1; 2; . . .; n
ð3Þ
qi þ qj þ 0:5 2n
ð4Þ
j¼1
qj ¼
n X i¼1
qij ¼
Table 3. Low-carbon city construction maturity evaluation index system KPA U1
KP A11 A12
Specific Indicator Per capita carbon emission(ton/person) Carbon emission per GDP(ton/10000 yuan) Forest coverage rate (%) Urban area green coverage rate (%) Per capita area of parks and green land (m2 /person) Carbon sink estimation(10000 tons)
Code x1 x2 x3 x4 x5 x6
Relationship − − + + + + (continued)
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KPA U2
KP A21
Specific Indicator Per capita GDP(yuan) GDP growth rate(%) Per capita annual disposable income(urban residents) (yuan) Engle coefficient(%) A22 Proportion of the third industry’s added value in GDP(%) Proportion of high technology industry(%) A23 Protection in government expenditure(%) The proportion of R&D expenditure in GDP(%) A24 Urbanization rate(%) U3 A31 Elasticity ratio of energy consumption Energy consumption per unit of GDP(tons of SCE/yuan) Natural gas consumption per capita(cu.m) A32 Electricity consumption per capita(kw. h) raw coal consumption Per capita(ton) U4 A41 Decontamination rate of domestic waste (%) Rate of industrial solid waste comprehensively utilized (%) Rate of waste water treatment (%) Annual daily mean of NO2 concentration (mg/cu. m) Annual daily mean of SO2 concentration(mg/cu.m) Annual daily mean of PM10 concentration (mg/cu. m) A42 Per capita urban road area (m2 ) Number of public vehicles owned per 10000 persons(unit) U5 A51 Low-carbon city laws and regulations Assessment system of carbon emission intensity Technical guide for low-carbon city planning Total carbon emission control scheme A52 Tax and fee policy Carbon trading policy Subsidies and investment and financing policies A53 Low-carbon consumption guidance policy Clean energy consumption policy Information disclosure and public participation Note: The ‘–’ means the relationship is negative and the ‘+’ means the
Code x7 x8 x9
Relationship + + +
x10 x11
− +
x12 x13 x14 x15 x16 x17
+ + + + − −
x18 x19 x20 x21 x22
+ + − + +
x23 x24
+ −
x25 x26
− −
x27 x28
+ +
x29 + x30 + x31 + x32 + x33 + x34 + x35 + x36 + x37 + x38 + relationship is positive.
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Table 4. Reference value of the relative importance of indicators Three scales (0−1) Meaning 0−0.4 j is more important than i 0.5 i and j are equally important 0.6−1 i is more important than j
Table 5. The fuzzy judgment matrix expressed by one expert The fuzzy judgment matrix Sub-indicator A1 A2 A3 A1 0.5 0.6 0.5 A2 0.4 0.5 0.5 A3 0.5 0.5 0.5 A4 0.4 0.4 0.4 A5 0.5 0.5 0.5
A4 0.6 0.6 0.6 0.5 0.5
A5 0.5 0.5 0.5 0.5 0.5
3.3.3 Calculation of Weights Based on the fuzzy consistency matrix, fuzzy weights of the decision elements were calculated using the following procedures: • Calculate the sum of elements in each line exclude itself. Then calculate the sum of all elements exclude diagonal elements. li =
Xn j¼1
qij 0:5 ¼ 1; 2; . . .; n
li ¼
n(n 1) 2
ð5Þ ð6Þ
where li denotes the importance of indicator i. • Define the normalized importance weight wi of each indicator by using following equation: i
X
li 2nðn 1Þ
ð7Þ
where wi is a non-fuzzy number. The fuzzy judgment matrix shown in Table 4 was converted into the fuzzy consistency matrix shown in Table 6. Also, li and wi were calculated. The scores of the three experts were calculated using the method above and the results were integrated by using arithmetic mean method. When the three experts’ opinions are integrated into one opinion, the final weights of indicators were shown in Table 7.
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4 Empirical Study of Evaluating Chongqing’s Low-Carbon Construction Maturity 4.1
Study Area
Chongqing, which is located in western China, is selected as the study area. It is one of the municipalities and is critical for regional and even national economy development. As one of the 81 low-carbon pilot cities, Chongqing has been exploring on the path to becoming a low-carbon city and some productive measures have obtained initial success. By analyzing the low-carbon construction maturity of Chongqing, some valuable results can be obtained to guide the development direction and be used as a reference for other cities’ low-carbon construction. Together with Chongqing’s data availability and economic development, it is representative to select Chongqing as the case. Meanwhile, due to the limitation of data availability, we choose 2006-2016 as the surveyed period. Table 6. The fuzzy consistency matrix expressed by one expert The fuzzy consistency matrix expressed Sub-indicator A1 A2 A3 A4 A1 0.5 0.5 0.5 0.6 A2 0.5 0.5 0.5 0.5 A3 0.5 0.5 0.5 0.5 A4 0.5 0.5 0.5 0.5 A5 0.5 0.5 0.5 0.5
A5 0.5 0.5 0.5 0.5 0.5
li
wi
2.1 2 2.1 1.9 2
0.2 0.2 0.2 0.2 0.2
Table 7. The final weights of the specific indicators Specific indicator wi Specific indicator wi x1 0.0642 x20 0.0420 x2 0.0458 x21 0.0154 x3 0.0228 x22 0.0172 x4 0.022 x23 0.0168 x5 0.0228 x24 0.0157 x6 0.0225 x25 0.0157 x7 0.0115 x26 0.0155 x8 0.0109 x27 0.0256 x9 0.0124 x28 0.0300 x10 0.0138 x29 0.0193 0.031 x30 0.0199 x11 x12 0.0237 x31 0.0177 (continued)
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Table 7. (continued) Specific indicator wi Specific indicator wi x13 0.0283 x32 0.0171 x14 0.0231 x33 0.0217 x15 0.0473 x34 0.0195 x16 0.0437 x35 0.0238 x17 0.0535 x36 0.0213 x18 0.0352 x37 0.0227 x19 0.0339 x38 0.0188
4.2
Data Sources and Numerical Standardization
There are several kinds of attributes’ data sources in the study. Carbon emissions is computed using Eq. (8), in which Ck is coming from Chongqing Statistical Yearbook and Ik is coming from the Carbon Emissions Calculation Guide Default Value of IPCC [34]. Carbon sink is roughly estimated with the data of carbon dioxide absorption by forests, grasslands and crops and the corresponding carbon absorption coefficient [35, 36]. Data on energy structure is coming from China Energy Statistics Yearbook. Data on pollution treatment is coming from Chongqing Municipality State of the Environment. Data on policies are coming from the Chongqing low-carbon network.If there were policies relevant to the indicator being implemented, then the value of the indicator was defined as 1. If not, then the value of the indicator was defined as 0. Except these, data of other indicators are coming from the statistical database of CNKI. A ¼
8 X
Ck
ð8Þ
Ik k¼1 where Ck is energy consumption, Ik is carbon emission coefficient, and k denotes different forms of energy sources. This paper picks 8 forms of energy sources in this calculation. They are raw coal, crude oil, gasoline, kerosene, diesel oil, fuel oil, liquefied petroleum gas and natural gas. In the process of the low-carbon city construction maturity assessment, a primary step is to ensure a standardized measurement system for all indicators considered. In this paper, all the index values were normalized by using the following equations: • If the relationship of the indicator with low-carbon city construction level is positive, then the normalized index xij can be computed as follows: Xij ¼
xij minfxi1 ; . . .; xin g maxfxi1 ; . . .; xin g minfxi1 ; . . .; xin g
ð9Þ
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• If the relationship of the indicator with low-carbon city construction level is negative, then the normalized index xij can be computed as follows: Xij ¼
xij maxfxi1 ; . . .; xin g xij maxfxi1 ; . . .; xin g minfxi1 ; . . .; xin g
ð10Þ
• where i denotes the serial number of each indicator and j denotes that of each year. Every index value is greater than 0 after normalized. 4.3
Scales of R-Score for Each Maturity Level of Chongqing
Taking Chongqing as the evaluation object, this paper determined the interval boundaries of R-score by integrating the three experts’ opinions. The final scales of Rscore for each maturity level are as following Table 8. Table 8. The scales of R-score for each maturity level Maturity level High carbon Medium-high carbon Medium carbon Medium-low carbon Low carbon
Scale 0 R 0.5 0.5 0.85, 13 indicators were selected. The results are shown in Table 2.
Table 2. Key index score based on fuzzy mathematics Ranking 1 2 3 4 5 6 7 8 9 10 11 12 13
2.2
Coding CF17 CF3 CF22 CF27 CF26 CF28 CF5 CF38 CF18 CF32 CF39 CF4 CF36
Factor name Agricultural mechanization level Per capita income Average years of schooling Social security coverage Poor population ratio Public facilities land Infrastructure investment Domestic waste disposal Per capita cultivated area Number of doctors per thousand Sewage disposal Per capita expenditure Degree of financial self-sufficiency
k value 0.933 0.930 0.925 0.912 0.899 0.893 0.885 0.882 0.880 0.877 0.874 0.858 0.855
Evaluation Model
In accordance with the characteristics of entropy, entropy value can be used to determine the randomness and disordering degree of an event, and the entropy value can be used to judge the degree of discretization of an index. A great degree of the index corresponds to a great influence of the index on the comprehensive evaluation. A sustainability evaluation model of rural areas was established in five steps. Step 1: Standardize data processing The dimensions and units of each indicator are different and cannot be directly compared and calculated. This paper adopted the linear non-dimensionalized extreme value method to process data. According to the nature of indicators, indicators can be divided into positive, negative, and moderate indicators. The ideal value of positive indicators is max (rj), and the ideal value of negative indicators is min (rj).
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rij ¼
rij rjmin rjmax rjmin
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ð1Þ
When the indicator is a negative indicator, the normalized formula is 0
rij ¼
rjmax rij rjmax rjmin
When the indicator is a moderate indicator, the standardized formula is rij di 0 rij ¼ 1 maxrij di
ð2Þ
ð3Þ
To determine the standard value, min(rj) is the minimum value of the index j, and max(rj) is the maximum value of the index j. Step 2: Data translation Parts of the data are still negative after processing. Several index values may be smaller or negative after data standardization processing. For the sake of unity and convenience of calculation, the standardized values are translated to eliminate the above situation. The formula is as follows: 0 0 rij ¼ H þ rij (where H is the magnitude of the index translation, generally taken as (1) The result is as follows: 0
0
rij ¼ 1 þ rij
ð4Þ
By defining its normalized value as Pij, we calculate the proportion Pij of the sample index i value under the index j rij Pij ¼ P rij
ð5Þ
i¼1
The standardization matrix for data is p ¼ pij . Step 3: Calculate the entropy value e and the information utility value g under index j We calculate the entropy value under index j: ej ¼
n 1 X pij ln pij ln n i¼1
ð6Þ
The coefficient of variation g of index j is as follows: gj ¼ 1 ej ; j ¼ 1; 2; . . .; p
ð7Þ
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Step 4: Define the weight xj (entropy weight) of indicator j xj ¼
gj 1 ej ¼ ; j ¼ 1; 2; . . .; p p p P P gj p gj j¼1
ð8Þ
j¼1
The weight of the indicator is determined by the information utility value of the indicator. A great utility value of the indicator information corresponds to great importance of the evaluation and a great weight. Step 5: Calculate the comprehensive score of the evaluated index si ¼
m X
xj pij
ð9Þ
j¼1
3 Case Study This research takes Jiaxing City as the case study due to three reasons. First, Jiaxing has been experiencing rural community construction due to new socialist countryside construction for 10 years. Second, Jiaxing is implementing rural land rectification and actively changing land use methods in various ways to achieve sustainable use of land resources. Jiaxing has a high level of agricultural modernization and sustainable development, which promotes the sustainable development of rural communities. Table 3. Rural community coding diagram Village Coding Counties and towns Wuyuan Town, Haiyan County A1 A2 Wuyuan Town, Haiyan County A3 Ganpu Town,Haiyan County A4 Yuantong Town, Haiyan County Xitangqiao Town, HaiyanCounty A5 A6 Dingqiao Town, Haining County A7 Huangwan Town, Haining County A8 Chang’an Town, Haining County A9 Taozhuan Town, Jiashan County A10 Taozhuan Town, Jiashan County A11 Yuxin Town, Jiashan County A12 Dushangang Town, Pinghu City A13 Linhu Town, Pinghu City A14 Dushangang Town, Pinghu City A15 Lindai Town, Pinghu City A16 Chongfu Town, Tongxiang city A17 Wangjiangjing Town, Xiuzhou District
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Therefore, Jiaxing is a good case for investigating the sustainability of new rural communities. Moreover, the per capita disposable income level of rural residents in Jiaxing has ranked first in Zhejiang Province for 14 consecutive years, thereby providing insight into the sustainability assessment of new rural communities in the Yangtze River Delta, which has similar conditions. Table 4. Village sustainable development ability score A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17
2006 0.393 0.298 0.290 0.400 0.438 0.269 0.286 0.228 0.382 0.158 0.287 0.229 0.312 0.202 0.460 0.255 0.195
2007 0.400 0.296 0.273 0.398 0.406 0.275 0.297 0.255 0.395 0.171 0.311 0.239 0.330 0.212 0.347 0.256 0.201
2008 0.431 0.386 0.296 0.437 0.428 0.280 0.201 0.278 0.399 0.187 0.330 0.246 0.303 0.220 0.376 0.262 0.210
2009 0.446 0.449 0.300 0.473 0.455 0.295 0.293 0.264 0.413 0.203 0.382 0.252 0.316 0.227 0.363 0.276 0.216
2010 0.520 0.461 0.336 0.482 0.470 0.308 0.385 0.282 0.426 0.232 0.340 0.258 0.304 0.232 0.416 0.277 0.230
2011 0.601 0.477 0.349 0.498 0.491 0.354 0.416 0.283 0.441 0.286 0.320 0.309 0.352 0.237 0.395 0.309 0.241
2012 0.613 0.453 0.463 0.519 0.498 0.376 0.419 0.311 0.446 0.280 0.405 0.315 0.364 0.243 0.415 0.310 0.250
2013 0.562 0.494 0.351 0.534 0.499 0.403 0.424 0.311 0.453 0.302 0.475 0.326 0.404 0.310 0.351 0.309 0.258
2014 0.601 0.564 0.411 0.555 0.510 0.417 0.421 0.324 0.459 0.318 0.519 0.327 0.359 0.314 0.354 0.312 0.265
2015 0.645 0.542 0.414 0.511 0.546 0.499 0.447 0.357 0.476 0.328 0.548 0.334 0.411 0.319 0.355 0.315 0.272
2016 0.651 0.594 0.437 0.558 0.540 0.512 0.394 0.437 0.503 0.337 0.691 0.342 0.416 0.323 0.354 0.320 0.308
This paper adopted field investigation and questionnaire survey to collect information on indicators in Jiaxing. Twenty questionnaires were sent out to 20 villages, and 17 valid questionnaires were screened. The specific names of the investigated villages are hidden for unnecessary disputes brought to the relevant villages as shown in Table 3. With the use of formula (9), the sustainable development capacity of each rural community in different years was obtained. The results are shown in Table 4. Except for A15 (Xudong Village), the sustainable development ability of other villages been significantly improved, and A11 (Yongming Village) increased to 0.403. However, the capacity of sustainable development of villages is different, and the gap between villages’ sustainable development capacity increased after 10 years. As shown in Fig. 2, the sustainable development capacity of land remediation-type rural communities in various parts of Jiaxing continued to rise from 2006 to 2016. The probable reason is that with the gradual completion of China’s industrialization and urbanization, the country began to implement a large-scale process of “industry-feeding agriculture, urban back-feeding the countryside” and proposed a slogan for new rural construction. The Jiaxing municipal government actively responded to the call of the
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Annual average village sustainability score 0.5 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Fig. 2. Annual average village sustainability score
central government and actively launched a new rural construction campaign within the city. Abundant policy and economic resources began to flood into the new countryside to promote the construction of new rural areas. At the same time, the central and local governments are constantly exploring rural governance mechanisms. Continuous improvement of governance systems and integration of resources has injected vitality into the construction of the new countryside and driven its continuous development. While the capacity for sustainable development of rural communities in Jiaxing continues to increase, the differences between rural communities slowly expand in different regions. This difference may be due to the speed of economic development or the strength of governance systems. Cluster analysis is a generic term for a large collection of techniques designed to investigate multivariate data to determine whether the data consist of relatively distinct groups of similar individuals. Cluster analysis can directly compare the nature of things. Therefore, considering categorical variables (rural communities) and continuous variables (year-to-year scores) in the data, this study uses two-step cluster for exploratory clustering analysis. To further analyze the factors that affect the sustainable development capacity of land remediation-type rural communities in various parts of Jiaxing, this study uses SPSS system clustering to classify the samples as shown in Table 5. This clustering method can effectively classify samples from different variables, and the results can be clearly displayed on the corresponding clustering map. In addition, the results obtained by this method are more reasonable and comprehensive than those of traditional classification. The villages are divided into two types, with 11 villages in the first ladder and 6 villages in the second ladder. The two types have several differences. First, compared with the second-ladder rural communities, the collective assets of the first-ladder rural communities are relatively monolithic, that is, the collective assets of most first-ladder rural communities are in the form of collective land, and the income from land
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Table 5. Classification results Ladder Coding Rural name City and Construction district funds 1 A12 Jufu Pinghu 800 A16 Zhi Tongxiang 1130 A8 Xinmin Haining 1280 A14 Yousheng Pinghu 728 A17 Hongdian Xiuzhou 580 A10 Xiangsheng Jiashan 620 A3 Liuzhon Haiyan 1460 A13 Huafeng Pinghu 1320 A6 Hongjin Haining 1440 A7 Wufeng Haining 1500 A15 Xudong Pinghu 1368 2 A4 Xinxing Haiyan 5000 A5 Dianzhuan Haiyan 3300 A9 Jinhu Jiashan 2880 A2 Jianxin Haiyan 3300 A1 Shuangqiao Haiyan 14600 A11 Yongming Jiashan 18820 Note: The construction funds here refer to funds related community construction.
The main types of Average collective assets score Real estate 0.289 Collective land 0.291 Collective land 0.303 Collective land 0.258 Collective land 0.241 Collective land 0.255 Real estate 0.356 Collective land 0.352 Real estate 0.363 Collective land 0.362 Collective land 0.381 Real estate 0.488 Enterprise 0.480 Real estate 0.436 Real estate 0.456 Real estate 0.533 Real estate 0.419 to land remediation funds and rural
circulation is stable. Consequently, this situation leads to the lack of new engines for the income of the first-ladder rural communities and causes a lack of growth and an inability to provide stable financial support for follow-up maintenance, high-quality public services, and further development of the village industry. Second, the income and expenditure structure of the first-ladder are in single digits, and the income and consumption levels are low. According to the collected questionnaires, most firstladder rural communities are dominated by agriculture and employment, while the diverse income sources of farmers in the second-ladder rural community is closely related to the diversification of their industries. Therefore, in the process of constructing a new rural community, we must fully understand the importance of building a diversified industrial system for the construction of a new countryside. Third, a firstladder rural community, namely, Xudong Village, has not increased its sustainable development capacity. With the general improvement of the sustainable development capacity of rural communities in Jiaxing City, this situation is particularly worthy of attention. The sustainability capacity of Xudong Village fell from 0.46 in 2006 to 0.35 in 2016. The relevant survey found that the population of Xudong Village is small (only 216 people, far below the normal village population level). The village economy is declining due to the small population base and the large outflow of labor force.
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4 Discussion Jiaxing is in the Hangzhou-Jiaxing-Huzhou Plain, west of Hangzhou, east of Shanghai, south of Nantong, and north of Suzhou. With convenient transportation and relatively good economic foundation, Jiaxing has sufficient financial resources to carry out land rectification and community construction. Generally, new rural construction funds are closely related to the community’s sustainable development capacity [23]. With the increase in construction funds, the sustainable development capacity of rural communities is constantly increasing. Although the sustainable development capacity of rural communities in Jiaxing is increasing year by year, differences exist between them. First, compared with the second-ladder rural community, the first-ladder rural community has relatively little construction funds. Under the premise that the economic foundation and construction methods are not much different, the construction funds will have a profound impact on the level of rural community construction. Second, in the process of community construction, whether the community can make full use of government-related project funds to transform itself will be the key to realize the rapid development of rural communities. Several rural communities maximize their advantages, scientifically plan their industrial layout, and build their own modern agricultural industrial, production, and operating systems through construction funds to achieve their own “leap-forward” development. Third, online surveys and field interviews revealed that the strengths of grassroots and village committee organizations are closely related to the sustainable development of rural communities [24]. Village committees are the backbone of new rural construction. The quality of village committees directly affects the construction of rural communities. A strong and impartial village leadership team can effectively overcome conflicts between different groups in the village, coordinate village collective actions, reduce the risks and costs of new rural construction, and ensure the success of the new rural construction. Finally, regional conditions vary. The investigation process found that rural communities with a strong sustainable development capacity are mostly adjacent to the city’s traffic arteries. The superior location conditions have facilitated the economic development of rural communities, and communities with weaker regional conditions have been trapped, thereby posing challenges to their own development. Measures should be taken to solve the disproportion of rural development and facilitate the sustainability of new rural community construction. The sustainable development capacity of rural communities is closely related to the amount of funds they obtain, and the influx of financial or social funds will strongly promote the development of rural communities. Therefore, rural areas need to make full use of government-related projects to obtain the funds needed for the construction of rural communities. In the process of new rural construction, villages should vigorously develop related industries and enhance their economic and financial capabilities. A high-quality grassroots organization is the key to regional economic development. In the vast rural areas, powerful and effective grassroots organizations can effectively implement relevant policies of higher authorities and provide high-quality public
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services for the development of the new countryside. Therefore, rural areas should focus on strengthening their basic organizational system with the village committee as the core, improving the efficiency of the basic organization, and ensuring the effective use of funds and the smooth progress of rural construction. In addition, farmers are the main body of the new rural construction. The construction and development of the new countryside must rely on the people, and the results must be shared by the people. Therefore, various measures should be taken to ensure that the achievements of the construction will benefit all the villagers. For example, public services should be equalized, rights of the villagers should be guaranteed, and the living environment of the villagers should be improved. To effectively promote the sustainable development of new rural communities, rural areas must increase financial investment, vigorously promote the implementation of agricultural projects, introduce market forces, build a complex industrial system, develop modern agriculture, and implement a modern agricultural system. Furthermore, the communities must improve basic grassroots democracy and self-government, strengthen the grassroots legal system, and strengthen the capacity of rural basic organizations. Other changes can be made by increasing environmental governance, improving the living environment of the villagers, achieving equalization of public services, advancing the living conditions of the villagers, and continuously increasing the income of farmers.
5 Conclusion Land consolidation and rural community construction are important means to promote the sustainable development of the countryside. This research developed a model to evaluate the sustainability of new rural communities generated from land consolidation with a case study of Jiaxing, Zhejiang Province. Findings indicate that the sustainable development capacity of the new countryside in Jiaxing has been significantly strengthened through land consolidation and community construction. The rural communities of Jiaxing can be roughly divided into two categories. A certain gap exists within the sustainable development capabilities of the second type of rural communities, and this gap may be due to various factors such as governance systems and construction funds. The study provides references for local governments to monitor and take measures to improve sustainability of rural communities generated from land consolidation. However, it should be noticed that there are some limitations in the current study. Important but difficult-to-quantify factors was not integrated into the model, resulting in an incomprehensive evaluation of the sustainability of rural communities. The effects of certain difficult-to-quantify important factors should be explored, such as leaders’ personal style and villages’ cultural atmosphere and social
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network. In addition, more cases in other regions should be included for comparison in order to deepen understandings on rural communities generated from land consolidation. Acknowledgements. The work described in this paper was jointly supported by National Natural Science Foundation of China (Project No.: 71503228), Natural Science Foundation of Zhejiang Province of China (Project No.: LQ16G030006) and Qianjiang Talents Program of Zhejiang Province of China (Project No.: QJC1602006).
References 1. Xi, J.P.: Win the battle to build a well-off society in an all-round way and win the great victory of socialism with Chinese characteristics in the new era: report at the nineteenth National Congress of the Communist Party of China, CCP (2017) 2. Dudzinska, M., University of Warmia: “Community education and integrated organization of rural areas based on land consolidation processes in Poland”. Rural Environment, Education, Personality (2015) 3. Peng, Y., Zhu, X., Zhang, F., Huang, L., Xue, J., Xu, Y.: Farmers’ risk perception of concentrated rural settlement development after the 5.12 Sichuan Earthquake. Habitat Int. 71, 169–176 (2018) 4. Behera, B., Reddy, V.R.: Environment and accountability: impact of industrial pollution on rural communities. Econ. Polit. Weekly 37(3), 257–265 (2002) 5. Gao, M.X.: Coupling relationship between land consolidation and new rural construction and its model innovation. Doctoral dissertation, Shandong Agricultural University (2008) 6. Peng, Y., Shen, L.Y., Tan, C., Tan, D.L., Wang, H.: Critical determinant factors (CDFs) for developing concentrated rural settlement in post disaster reconstruction: a China study. Nat. Hazards 66(2), 355–373 (2013) 7. Yang, J., Wang, Z.Q., Yi, P., Jin, G., Hu, X.D.: Study on the spatial differentiation of land remediation project in Zhushan County and its coupling with new rural construction. China Land Sci. 28(7), 62–70 (2014) 8. He, D.J.: A coupled innovation model of land improvement and new rural construction based on the perspective of farmers’ participation. Urban Geogr. 10, 82–83 (2016) 9. Cai, F., Pu, L., Zhu, M.: Assessment framework and decision-support system for consolidating urban-rural construction land in coastal china. Sustainability 6(11), 7689– 7709 (2014) 10. Anush, Y., et al.: Development of the rural active living assessment tools: Measuring rural environments. Prev. Med. 50, supp-S (2010) 11. Song, W., Liu, M.: Assessment of decoupling between rural settlement area and rural population in china. Land Use Policy 39(39), 331–341 (2014) 12. Qu, F.T., He, J., Wu, H.J.: Indicator system, level of realization and regional comparison of new rural construction in Jiangsu province. Agric. Econ. Issues 2, 62–66 (2007) 13. Zhou, Y.M.: The construction of a new rural community quality assessment index system. Econ. Aspect (4) (2014) 14. Teng, M.L.: Construction of an evaluation index system for the “five in one” construction of new rural communities. J. Guangxi Univ. Finance Econ. 5, 90–94 (2015) 15. Zhao, Q.M., Liu, J.B.: The reverse between the goal of new rural construction and the reality: the dilemma of intellectual support for rural talents. Contemp. World Social. (1) (2008)
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Thinking on Spatial Restructuring of Traditional Villages in the Ancient Miao Territory Corridor Under the Ground of Rural Revitalization Dong Wang(&), Geng Ma, and Heng Liu School of Architecture and Urban Planning of Institute of Guizhou Technology, Guizhou, China [email protected] Abstract. The formulation of rural revitalization strategy creates opportunities for the development and protection of traditional villages, and the proposal of “The Ancient Miao Territory Corridor” means a new academic perspective on traditional villages in Southwest China. This paper, by integrating current politics focuses and academic hot points, analyzes and discusses the research status of traditional villages in “The Ancient Miao Territory Corridor” in china, proposes the orientation of space restructuring strategy for traditional villages in “The Ancient Miao Territory Corridor” based on the interpretation of the rural revitalization strategy and traditional village space relation, and affirms the innovation of the strategy from the aspects of research model, research content and research method. It is hoped to boost theory construction of rural revitalization strategy, protection and development of traditional villages in Guizhou province, and applying for the listing of world cultural route heritage of “The Ancient Miao Territory Corridor”. Keywords: Rural revitalization The Ancient Miao Territory Corridor Traditional villages Space restructuring
1 Introduction A new development idea of “implementing rural revitalization strategy” was put forward in the report of the 19th National Congress of the Communist Party of China, [1, 2] bringing a new historic opportunity for the protection and development of traditional villages in “The Ancient Miao Territory Corridor” that is an integral part of Southwest China. Along “The Ancient Miao Territory Corridor”, there are more than nationalities or ethnic groups, including Hmong people, Dong people, Bouyei people, Chuanqing people, Tunpu people, and a lot of densely-distributed traditional villages. In recent years, with rapid urbanization and industrialization, traditional villages in “The Ancient Miao Territory Corridor” are faced with problems such as space system degradation and culture root breakage due to exploitation-caused damage and people’s unawareness of the value of traditional villages, and there lacks appropriate and sustainable planning and design of spatial form and architectural style of villages. This is adverse to further image promotion of the villages and village culture tourism brand building. On account © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1172–1184, 2021. https://doi.org/10.1007/978-981-15-3977-0_90
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of the facts, this paper is to, with the definite research value and based on analysis of the research status and interpretation of rural revitalization strategy and space relation of traditional villages from the perspective of architecture, analyze the orientation of space restructuring of traditional villages in “The Ancient Miao Territory Corridor” and the innovation of this research.
2 Literature Review 2.1
Introduction of “The Ancient Miao Territory Corridor” and Traditional Villages
The academic concept of “The Ancient Miao Territory Corridor” was put forward by Professor Yang Zhiqiang in 2012, which caused widespread concern in the educational circles and political circles immediately. “The Ancient Miao Territory Corridor” starts from Changde of Hunan, runs through Guizhou transversely, and ends in Kunming of Yunnan. (Fig. 1) The corridor running through Hunan, Guizhou and Yunnan has been being a key military thoroughfare to be defended by the state since the Yuan Dynasty. Many historical events in southwest China were connected with the corridor. Thus, the corridor is also called “southwest state corridor”. So far, “The Ancient Miao Territory Corridor” has been listed in the five ethnic corridors in China (Tibetan-Yi Corridor, Nanling Corridor, Northeast Corridor and Wuling Corridor). Before the concept of “The Ancient Miao Territory Corridor” was put forward, there were scholars did researches based on the theory of cultural route. The national social science fund program titled Study on Lineal or Serial Cultural Heritages in Southwest China under the lead of Professor Wu Xiaoqiu discusses the value composition of courier routes in Guizhou, analyzes multiculture fusion along the courier routes, and puts forward suggestions on protection of cultural route heritage in Southwest China covering traditional villages [3]. The program titled Research and Development of “The Ancient Miao Territory Corridor” under the lead of Professor Yang Zhiqiang was fully affirmed and supported by the State Ethnic Affairs Commission. The “Forum on The Ancient Miao Territory Corridor and Guizhou Cultural Construction” was held in Guiyang in April 2012, attracting much attention from the provincial government of Guizhou, so that the provincial government convened the symposium on “reconstructing The Ancient Miao Territory Corridor” immediately to boost deep integration and development of Guizhou culture and tourism. The symposium on culture corridor in Southwest China under the background of the Belt and Road Initiatives and the seminar on cultural tourism planning of The Ancient Miao Territory Corridor of China were held in Guiyang in 2017 and 2018 successively, which raised concern from all circles nationwide. The researches on “The Ancient Miao Territory Corridor” are mainly about its connotation and extension, relate to academic value, formative factors, connotation, and characteristics [5–7], and cover its potential role in the historical development, cultural industry development, and tourism development of “The Ancient Miao Territory Corridor” and Guizhou [8, 9]. No one does special research on space restructuring of traditional villages in “The Ancient Miao Territory Corridor” yet. It is thus clear that this topic is completely innovative.
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Fig. 1. Picture of “The Ancient Miao Territory Corridor” in southwest China provided by Yang Zhiqiang
2.2
Value of Space Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor”
The study on space restructuring of traditional villages of “The Ancient Miao Territory Corridor” is the realistic need for boosting theory construction of rural revitalization, implementation of rural revitalization strategy, and application for listing “The Ancient Miao Territory Corridor” as world cultural route heritage. 2.2.1 Need for Theory Construction for Boosting Rural Revitalization Strategy There are about 300 Chinese traditional villages along “The Ancient Miao Territory Corridor”, and the cultural route heritages of “The Ancient Miao Territory Corridor” are mostly preserved in traditional villages. The cultural heritages reflect the survival wisdom and humanistic spirit of our ancestors, contain the cultural gene of ethnic groups in Southwest China, and reveal the regional characteristics of traditional villages in “The Ancient Miao Territory Corridor”. The study thereon will make for expanding and deepening theoretical researches related to rural revitalization of “The Ancient Miao Territory Corridor”. Since the proposal of “The Ancient Miao Territory Corridor”, it has been being attached with high importance in the educational circles at home and abroad, and related researches and research results received strong support and popularization by the provincial government of Guizhou. Being under the historical background of rural
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revitalization, from the perspective of architecture and based on the clues of cultural route, the study on space restructuring of traditional villages in “The Ancient Miao Territory Corridor” is an innovative academic study by integrating academic hot points and current politics focuses. For a long time, the researches on traditional villages in “The Ancient Miao Territory Corridor” have been focusing on humanities and social sciences, and few research results have been achieved and the results are scattered. Further efforts are to be made to combine related researches with the practice of rural revitalization. The writer, with “The Ancient Miao Territory Corridor” as the subject word, retrieved 65 papers on CNKI, 37 on academic journal, 25 on newspaper, 2 doctoral theses, and 1 other paper Table 1. Retrieve results with “The Ancient Miao Territory Corridor” as the subject word on CNKI Academic journal Master/doctoral thesis Conference paper Newspaper Other Total 37 2 0 25 1 65
(see Table 1). All the retrieved papers fall into the field of humanities and social sciences. This study will help boost the application of the regional architecture theory in researches on space system of traditional villages in “The Ancient Miao Territory Corridor”, expand and deepen researches on regional architecture or regional settlement in “The Ancient Miao Territory Corridor”, and promote traditional villages in “The Ancient Miao Territory Corridor” to become a shared research platform of architecture and anthropology. 2.2.2 Realistic Need for Boosting the Implementation of Rural Revitalization and Application for Listing as World Cultural Route Heritage The study on space restructuring of traditional villages in “The Ancient Miao Territory Corridor” will provide theoretical reference for the implementation of “rural revitalization”. Specifically, it is to provide theoretical reference for renovation of styles and features of traditional villages, village planning and construction, transformation and renovation of ancient buildings, restoration of ecological landscape of villages, restoration of cultural relics, and reservation of related cultural heritages along the corridor and decision basis for implementation of rural revitalization of “The Ancient Miao Territory Corridor” for the provincial government of Guizhou or related decisionmaking sections by analyzing common problems in space design of traditional villages in “The Ancient Miao Territory Corridor”. Experts, through research and argument, believe that “The Ancient Miao Territory Corridor” is comparable to “The Ancient Tea Horse Road” in the terms of importance. The provincial government and related decision-making sections of Guizhou plans to apply for listing “The Ancient Miao Territory Corridor” as world cultural route heritage, construct a “Long International Cultural Tourism Belt of The Ancient Miao
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Territory Corridor”, and build a cultural tourism brand for Guizhou, to boost the strategy of tourism insight and great poverty alleviation of Guizhou. The “seminar on cultural tourism planning of The Ancient Miao Territory Corridor of China” was held on January 6, 2018 to discuss the possibility, feasibility, importance and inevitability of applying for listing The Ancient Miao Territory Corridor as world cultural route heritage, at which it was insisted that “The Ancient Miao Territory Corridor” completely comply with the core indicators for listing as “world cultural route heritage”. This is a good opportunity for making overall planning of “The Ancient Miao Territory Corridor” to link traditional villages along the corridor with related heritages to realize interactive development of multiple industries. Surveys show that many historic ancient towns, ancient villages and ancient roads in Southwest China, and some sites that had been declared as world culture heritage such as Tusi Sites in Hailongtun Village, Zhenyuan Qinglong Cave of Guizhou National Architecture Museum and Huangguoshu Waterfalls Scenic Area (AAAAA) are situated along the corridor. Thus, exploiting culture heritage of traditional villages in “The Ancient Miao Territory Corridor” and paying close attention to space system restructuring of traditional villages along the corridor are, on one hand, to drive rural revitalization along the corridor and promote the development of cultural tourism industry in Guizhou and even Southwest China, and on the other hand, to provide theoretical foundation for the provincial government of Guizhou to apply for listing “The Ancient Miao Territory Corridor” as world cultural route heritage jointly with Hunan province and Yunnan province. 2.3
Review on Researches on Space System of Traditional Villages in “The Ancient Miao Territory Corridor”
Presently, no research achievement of traditional villages definitely covering “The Ancient Miao Territory Corridor” hits headlines, but the corridor is related to in other regional or integral researches at varying degrees. This paper is to review the trends of research on traditional villages at home and abroad from the aspects of “space system” and “space restructuring”, providing directions and ideas for researches on space restructuring of traditional villages in “The Ancient Miao Territory Corridor”. 2.3.1
Research Status
2.3.1.1. Research Status of Space System of Traditional Villages It is not difficult to found that space is the common starting point of researches on traditional villages of different fields by reviewing the academic history. In the general, such researches mainly relate to material space, cultural space, and “The Three Basic Spaces”. Researches on material space of traditional villages are usually made based on macrologic, madhyamaka philosophy, and micrologic. Macroscopically, material space relates to landscape and scenery pattern; in respect of madhyamaka, material space relates to village arrangement, street layout, and construction group; and microscopically, material space relates to the major form of buildings. Besides, the cultural significance contained in the space of traditional villages is covered, which is inferior to
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interpretations from the fields of humanities and social sciences, and architect in the terms of depth and extent. Yet it is quite the opposite for most achievements of research on traditional villages in Guizhou. The ones doing researches on traditional villages mainly are scholars of humanities and social sciences, who prefer to analyze village culture. Nationwide, the research achievements obtained in the field of architecture in Guizhou are unworthy of the cultural resources of abundant traditional villages in Guizhou, in both quantity and quality. Researches on cultural space of traditional villages mainly focus on protection and development of intangible cultural heritage. The achievements of such researches are mainly about interaction, fusion and relation between intangible and tangible cultural heritages, with a purpose to realize active inheritance of “intangible cultural heritage” by restructuring “intangible cultural heritage” space of traditional villages [10]. Some scholars classify cultural space of traditional villages into location-oriented type and time-oriented type, to greatly promote the formulation and implementation of protective measures for “intangible cultural heritage” in villages of national minorities from the aspects of composite multi-culture space, space transformation, space outside the stockade village gate, floaters in space, and “creolization” system of space [11–13]. The three basic spaces of traditional villages refer to production, life and ecology. It is thought that the three basic spaces can be driven to develop harmoniously only by integrating economic benefit, social benefit and ecological benefit and unifying concentricity and equilibrium [14]. Some scholars proposed an idea of integrating “The Three Basic Spaces, and to solve rural development problems by putting agricultural production facilities into human residential space with agriculture as the link [15]. However, most researches are on space restructuring from one or two aspects [16–18]. 2.3.1.2 Strategy of Space System Restructuring of Traditional Villages In recent years, village decay has attracted great attention from all circles. Scholars also do related researches from different perspectives. For rural planning oriented by new type urban-rural relationship, stress should be laid on transformation of “The Three Basic Spaces”. Specifically, for life space, stress should be laid on feature update and public space restructuring; for production space, stress should be laid on farmland agglomeration and endogenous growth; for ecological space, stress should be laid on authentic ecological right and ecological control [19]. Scholars have done researches on space restructuring strategy of traditional villages from the perspectives of social structure reengineering, multiple village link, tourism, and different planning and design ideas and strategies [20–23]. But there are few achievements of research on space restructuring of traditional villages made in Guizhou. This indicates that the research on space restructuring of traditional villages in “The Ancient Miao Territory Corridor” is a new field to be developed.
2.3.2 Review and Analysis on the Status Review on research achievements in China shows that there are few researches specific to traditional villages in “The Ancient Miao Territory Corridor”, and few people touch space system restructuring strategy. The present researches are mainly from the perspective of humanities and social sciences. Thus, more efforts should be made to
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produce more theoretical research achievements to guide the implementation of rural revitalization. Researches on cultural route heritage of “The Ancient Miao Territory Corridor” have become the academic frontier and a current politics hot topic in China. Since such researches begin late, they are only on macroscopic level at present. Only the importance of cultural route heritage covering traditional villages is pointed out in general terms, and there are few achievements of special research. Most research achievements are limited to, from the perspective of humanities and social sciences, collection and sort of cultural heritage, exploration of cultural value, and development of rural tourism, and, from the perspective of architecture, to spatial form. There are few results of research on space system restructuring strategy of material space, cultural space and “The Three Basic Spaces” of traditional villages, and such results are scattered. So far, there is no published achievement of overall research on “The Ancient Miao Territory Corridor”. The ones devoted to research on “The Ancient Miao Territory Corridor” are mainly from the circles of ethnology, anthropology, history, and tourism science. Comparing with the research results achieved by scholars of humanities and social sciences, the researches from the perspective of architecture are less noticeable, which is not in line with the features of integrity and liveliness of traditional villages. Thus, to expand the research perspective is an important development direction in the future. Besides, the present researches mainly focus on “study-type” basic theories. This research trend is not good for promoting “rural revitalization”, “protection and development of traditional villages”, and development and construction of “The Ancient Miao Territory Corridor”.
3 Research Content 3.1
Research Orientation of Space Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor”
Only the research orientation of space restructuring of traditional villages in “The Ancient Miao Territory Corridor” that is established by analyzing the research status to figure out the hitting-point and highly complies with the general requirements of rural revitalization strategy can be scientific, rational, and close to life. 3.1.1 Interpretation of Relationship Between the General Requirements of Rural Revitalization Strategy and Traditional Village Space This paper is to build a research framework based on the internal logical relationship (Fig. 2) between the general requirements of “rural revitalization strategy” and space system of traditional villages. Thus, the general objective of this research highly complies with the objectives of rural revitalization. Specifically, this research aims to conduct field study on traditional villages in “The Ancient Miao Territory Corridor”, absorb predecessors’ outstanding research results, summarize the problems of space system of traditional villages in “The Ancient Miao Territory Corridor” in the process of protection and development, be based on regional architecture theory, draw lessons from frontier achievements of space research, combine the general requirements of
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rural revitalization strategy, construct a traditional village space system containing material space, cultural space, and “The Three Basic Spaces”, and specially study a restructuring strategy of space system of traditional villages in Guizhou in combination with the realistic needs for protection and development of traditional villages in Guizhou, “rural revitalization”, and development and construction of “The Ancient Miao Territory Corridor”, with a hope to boost industrial development, livable ecology, civilized village spirit, efficient governance, and rich life.
Fig. 2. Internal logic relationship between space system of traditional villages and the general requirements of “rural revitalization strategy”
3.1.2 Contents of Space System Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor” (1) Material space system of traditional villages in “The Ancient Miao Territory Corridor” It is to determine the contents of material space restructuring with regional characteristics in combination with the feature of multiple styles of traditional villages in “The Ancient Miao Territory Corridor”. Researches on space restructuring of traditional villages usually will cover space function structure and development orientation. Firstly, it is to take overall consideration of natural heritage, culture heritage and industrial economy related to traditional villages and “The Ancient Miao Territory Corridor” based on the linear structure feature of “The Ancient Miao Territory Corridor”, geographic feature of karst, and different forms of villages, to build a space network linking “The Ancient Miao Territory Corridor” with traditional villages. Secondly, it is to identify the contents and features of space function of traditional villages of different ethnic groups, and classify villages according to density, scale, location, and form. Thirdly, it is to study the interactions and relationships among “The Ancient Miao Territory Corridor”, cities and towns, and industrial economic functions.
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(2) Cultural space system of traditional villages of “The Ancient Miao Territory Corridor” It is to determine the contents of cultural space restructuring of traditional villages in “The Ancient Miao Territory Corridor” according to the feature of multiethnic culture there. There are more than 20 nationalities or ethnic groups along “The Ancient Miao Territory Corridor”, and the restructuring of multiethnic culture space is to study the coupling mechanism between material elements and immaterial elements of culture space based on the feature of dependence relationship between material space and immaterial space and the isomorphism of traditional villages as dual carrier of tangible and intangible culture heritage. Studying the coexistence of preservation of “intangible culture heritage” in change and vanished spatial carrier is the key to space system restructuring. Specifically, it is to study the phenetic relationship between material space and immaterial space from macroscopic, madhyamika and microscopic level; figure out flexible and human-oriented cultural protection measures from the perspectives of management and implementation and push forward the construction of “village spirit and civilization” based on the consideration of the diversity of ethnic culture. (3) “The Three Basic Spaces” system of traditional villages in “The Ancient Miao Territory Corridor” It is to determine the contents of “The Three Basic Spaces” restructuring of traditional villages in “The Ancient Miao Territory Corridor” according to the requirements of “industrial development, livable ecology, and rich life” of rural revitalization strategy, and establish the core perspective of “The Three Basic Spaces” restructuring according to the requirements of “industrial development, livable ecology, and rich life”, the structural features of coexistence of “The Three Basic Spaces”, theories of multiple subjects, and important value orientation of ecological character of space theory. The main contents are: to solve basic bread-and-butter issue by restructuring production space; to balance and harmonize environment and human by restricting ecological space; to improve and enrich human’s living style and contents by restructuring life space. (4) Strategy of space system restructuring of traditional villages in “The Ancient Miao Territory Corridor” The strategy of space restructuring of traditional villages is put forward from the perspectives of material space, cultural space and the three basic spaces respectively. “Material space” is the basis and prerequisite of protection and development of traditional villages, “cultural space” is the core and key to protection and development of traditional villages, and “symbiotic space of the three basic spaces” is the objective and orientation of protection and development of traditional villages. It is to innovate and study restructuring strategy of physical space of villages based on material space of traditional villages in “The Ancient Miao Territory Corridor” and in combination with the bidirectional requirements for protection and development of traditional villages in “The Ancient Miao Territory Corridor”. The system architecture of the material space of traditional villages can be understood and grasped from spatial level (landscape ecological space, land-use space, and public space, etc.) and spatial element of village. The strategy of intangible heritage inheritance and utilization can be realized by means of modern “living-oriented” protection style. We aim to turn from
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production-oriented protection to living-oriented protection, to enhance the present “intangible culture heritage” protection idea greatly, and deepen study on “intangible culture heritage” from the perspectives of culture symbol and traditional meaning in life. As to cultural space of traditional villages, the protection and inheritance mechanism of “intangible culture heritage” can be studied from the aspects of human being, space and event, and the cultural space of traditional villages can be fully understood and rebuilt from the aspects of spatial element protection, inheritance path, and vitality of daily organizational management. This paper, based on the policy and system innovation of restructuring of “the three basic spaces” of traditional villages in “The Ancient Miao Territory Corridor”, aims to critically discuss the appropriateness and performance of current policies and systems relating to village space restructuring, and propose a system chain and policy support system for restructuring “The Three Basic Spaces” of traditional villages based on the orientation of cultural diversity protection and development. As to the three basic spaces of traditional villages, it is to dialectically integrate “The Three Basic Spaces” of traditional villages from the aspects of social governance, industrial development and ecological construction. 3.2
Innovation of Research on Space Restructuring of Traditional Villages in “The Ancient Miao Territory Corridor”
Professor Yang Zhiqiang emphasized the value of “The Ancient Miao Territory Corridor” when proposing the concept of “The Ancient Miao Territory Corridor”: “open a new perspective for research on territory and ethnic group in Southwest China methodologically, and provide a shared engagement platform for multiple subjects such as humanities and social sciences and natural science.” [8] This paper exactly follows this logic to target space restructuring of traditional villages in “The Ancient Miao Territory Corridor”, innovate the research model, expand the research content, and explore research method based on regional architecture theory. 3.2.1 Innovation of Research Model Review on the origin of and academic researches on traditional village shows that space is the core point and key word of discourse system of researches on this topic from the perspective of various fields. In this paper, by putting the research results about material space, cultural space and “The Three Basic Spaces” of traditional villages in different fields under the perspective of architecture, a research model of space system of traditional villages in “The Ancient Miao Territory Corridor” is built, which reflects the innovation of academic research model and creation of a new theoretical discourse system. 3.2.2 Innovation of Research Content This is the first time that special research on space system restructuring of traditional villages in “The Ancient Miao Territory Corridor” is proposed. Presently, there are few researches on traditional villages in “The Ancient Miao Territory Corridor” both at home and abroad, and most related researches are scattered. In this paper, the essential connotation of material space, cultural space and “The Three Basic Spaces” of traditional villages in “The Ancient Miao Territory Corridor” is studied deeply, spatial
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linkage is rebuilt by means of repairing landscape corridor and village landscape, mending street texture, innovating cultural inheritance mechanism, and optimizing social governance pattern to realize enrichment and development of space and continuation of vitality, and a strategy of space system restructuring for traditional villages in “The Ancient Miao Territory Corridor” is put forward to echo the rural revitalization strategy of the state and satisfy the needs of the time for protection and development of traditional villages in Guizhou. 3.2.3 Innovation of Research Method For a long time, the researches on traditional villages in Guizhou mainly take on a trend of point to area (scattered point), and seldom review the internal logic relationship between points. In a word, such researches bring only quantity accumulation rather than quality improvement. This objectively constrains the advancement of researches on regional settlement and regional architecture in Guizhou. In this paper, “The Ancient Miao Territory Corridor” is taken as the principle line, traditional villages along the corridor are included into the corridor and linked together, research on internal logic of traditional villages along the corridor is deepened, and a shared research platform covering different subjects such as architecture and ethology is built.
4 Research Method (1) Literature research method: this method is employed mainly to review, analyze and grasp overseas and Chinese theoretical researches and practical explorations relating to “The Ancient Miao Territory Corridor” and space system restructuring of traditional settlements, to provide theoretical reference for this paper; (2) Field study and surveying and mapping: There are few research results on traditional villages in the corridor, and such research results are scattered. Thus, it is objectively required to conduct field study on the realistic condition of traditional villages in the corridor and survey and map representative villages and buildings, to obtain first-hand information; (3) System approach: There is a trend of polarization in ethnic groups and boundaries as to researches on traditional villages in Guizhou. Thus, it is necessary to study space restructuring of traditional villages along the corridor with system approach as a whole.
5 Conclusion The proposal of “rural revitalization strategy” brings an opportunity for the protection and development of traditional villages. Although there are fruitful research results on space system restructuring which is an important content of rural revitalization, it is insufficient to put forward feasible guiding theory on this basis. This is because the space of traditional villages is concerned from limited dimensions rather than a systematic perspective. Thus, comprehensively grasping the contents of space system is the key to the success of space restructuring of traditional villages. According to the logic of space, material space, cultural space and “The Three Basic Spaces” are the basis, core and objective of protection and development of traditional villages
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respectively, which constitute the space system of traditional villages jointly. Based on the theoretical framework set forth above, this paper, on the basis of regional architecture theory, targets on traditional villages in “The Ancient Miao Territory Corridor” (Guizhou section), summarize the problems in space restructuring, rebuild the material space by integrating the space function structure and development orientation in combination with the realistic needs for development and construction of “The Ancient Miao Territory Corridor” and “rural revitalization”, and build a symbiotic model of production, ecology and life to rebuild “The Three Basic Spaces”. The strategy of space system restructuring of traditional villages in “The Ancient Miao Territory Corridor” is put forward on this basis, providing preliminary theoretical basis for figuring out appropriate reconstruction technology subsequently. Acknowledgements. Supported by General Research Project on Humanities and Social Sciences of the Ministry of Education: 18YJC760079, Science and Technology Plan Project of Guizhou Province: 20181070.
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Investigation, Development and Application of Wood Structure Dwellings in Qiannan Guiman Xu(&) and Haiya Han Qiannan Polytechnic for Nationalities, Duyun, China [email protected]
Abstract. In order to improve the residential environment of the traditional wooden structures for ethnic minorities in Qiannan, the local residential buildings and structures are investigated. The architectural features and traditional cultural connotation of the local residential buildings are explored. At the same time, the mechanics principles used for the traditional wooden structures are summarized. With the development of urbanization, the traditional wooden structures have gradually reduced. On the basis of preserving the features of traditional wooden structure dwellings, the deep-processed wood, steel connection and other reinforcement measures are proposed for the traditional wooden structures. These methods can improve the residential environment, and improve the safety, applicability and durability of wooden structures. As the notions of green development, recycling development, low-carbon development are widely adopted in the prefabricated construction, the combination of both traditional wood structure residential buildings and new building materials technology will develop the local traditional wood structure residential buildings in the near future. And the inheritances and developments of the local wooden structure dwellings are promoted. Keywords: Wood structure
Dwellings Laminated wood Buildings
1 Introduction The wood structure residential buildings have been developing for thousands of years in China, and they are the main structural forms of traditional residential buildings in China. So far, there are still many wooden structure residential buildings in China. For example, Forbidden City (Beijing), Main Hall in Nanzen-ji Temple (Mount Wutai, Shanxi) and East Hall in Foguang Temple (Mount Wutai, Shanxi), etc. The wooden structure residential buildings own unique aesthetic arts, stable structural performance and excellent durability. The traditional wooden structures not only inherit a long cultural history, but also conform to the development of ethnic tourism. China has many ethnic groups, large regional differences, many climate types and complex hydrological conditions. The national historical backgrounds and cultural traditions vary significantly in different places. There are many wooden structure residential buildings with their own characteristics in different periods and in different regions in China. According to the ethnic cultural characteristics, local climate and geographical
© Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1185–1193, 2021. https://doi.org/10.1007/978-981-15-3977-0_91
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environment, the ethnic groups in various regions have integrated these factors into their own cultures of residential buildings. Qiannan Buyei and Miao Autonomous Prefecture is located in the south-central part of Guizhou Province, with the Yunnan-Guizhou Plateau in the northwest and the Guangxi Hilly Region in the south. The Autonomous Prefecture has a high topography in the northwest and a low topography in the southeast. In the early stage of residential buildings, the main building materials are China fir, Chinese red pine, weeping cypress and pinus yunnanensis [1]. With the rapid development of urbanization in the Qiannan Prefecture, the cities are gradually being occupied by modern reinforced concrete buildings, and the wooden structures of ethnic groups have gradually decreased. When we walk into the countryside around the cities, most of the houses we see are imitation wood residential buildings. In more remote areas, such as the Gediu Miaozhai, the well-preserved residential houses with wooden structures are still luckily found. However, most of them have been abandoned or reinforced by reinforced concrete. With the gradual improvement of people’s living standard, the demands for environmental protection, energy saving, low carbon, renewable and comfort are increasing. The foreign new-style wooden building construction technologies have begun to be favored by Chinese people and have been introduced into the Chinese construction markets [2]. At present, some scholars have conducted some researches on the development of local wood structures [5, 6]. The wooden structures of ethnic minorities in Qiannan Buyei and Miao Autonomous Prefecture are studied in this article. The architectural structures of local dwellings are investigated and analyzed. Based on the development characteristics of modern wood structure, local ethnic cultures and characteristics of traditional residential buildings, the modern wood structure technologies are suggested to use. Therefore, the traditional cultures of the nation will be inherited. At the same time, the residential environment can be improved. The safety, applicability and durability of wooden structures can also be improved. Finally, some development directions are proposed for the inheritance of local ethnic characteristics and the development of wooden structure residential buildings.
2 Qiannan Traditional Wood Structure Dwellings Traditional residential buildings are shelters built to meet the needs of daily life and protect their own safety. The structures of traditional residential buildings not only meet the basic functions of the general building structures – applicability, durability and safety, but also have a set of functions that correspond to the local natural environment. In the culture, these structures can reflect local ethnic beliefs, symbols and folk cultures. The mountainous forms of the Qiannan Prefecture determine that the most of local dwellings are built at the foot of hills and beside streams. The houses are surrounded by bamboo forests. The rugged mountain roads surround and connect each family. And the villages live in groups.
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Fig. 1. Mouth-swallowing style house
The wooden structure residential buildings in Qiannan Prefecture are mainly in the forms of mouth-swallowing style houses and pile-dwelling houses. The swallow-style house is mainly composed of the three-opening rooms [7]. The middle room is the central room, which is about one meter deep and four meters wide comparing to the both sides (see Fig. 1). There are two kinds of pile-dwelling houses. The one is located on a relatively steep terrain. The front part is supported by pillars and the latter part is built on the mountain platform. The other one is in the flat terrain. The pillars are built firstly. Then a platform is established on the pillars. Lastly, the houses are constructed on the platform. The ground floor is used to trap livestock or poultry, and the people live in the upper floors [8]. In order to respect the ancestors and obtain the ancestral refuge, in the whole houses, the central room is used to worship the ancestors. The central room is the largest one in the whole houses, and it is an important place for family affairs and hospitality. The local residential buildings pay great attentions to the structural design of the central room. The designs not only show the wisdom of the structure design, but also contain the national architectural culture. According to the structural layouts of both beam and column, the basic structure forms of traditional wooden structure residential buildings can be roughly divided into post and lintel construction, column and tie construction, log cabin construction and pole-railing style construction (see Fig. 2). Various forms of structures have their own characteristics, and adapt to different environmental and climatic conditions. At the same time, they are the crystallization of people’s daily life refined from the structures of residential buildings. The four basic structural forms of wooden houses do not exist independently. As people understand the basic structures, the various basic structural forms are used interchangeably to form a variety of residential buildings. In these wooden structure residential buildings, it can be seen that people have used various methods to improve their living environment. These residential buildings represent the buildings developed by different ethnic groups under different natural environments, different social cultures and different historical conditions. It is not “planned” and “standardized”, but also has some commonalities of national architectural culture.
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Fig. 2. Basic styles of wood structure dwellings
3 Defects of Traditional Wood Structure Dwellings After investigating and consulting the information of traditional wood structure residential buildings, we find that the traditional wooden structure residential buildings have fully integrated human wisdom. However, various problems still occur during uses due to the lack of planning, technology and other reasons in ethnic minority areas, which are also the reasons why the wooden structures are gradually replaced by reinforced concrete buildings. These development trends will lead to the gradual disappearance of traditional architectural cultures in ethnic minority areas. Therefore, it is very necessary to analyze the defects of traditional wooden structure dwellings. And the reasons for the gradual decreases of traditional wood structure residential buildings can be found. Through the analysis, the main reasons can be summarized as follows. 3.1
Randomness of Wood
The traditional wooden structure residential buildings are basically built by the wood cut locally. Wood selection is based on the experience and appearance, not standards. Wood is not processed or simply processed before uses. The scars, hollows and other defects on wood are not easily detected. The wood is damaged due to wind and rain erosion, which causes structural safety problems. The crude wood has a circular crosssection and its longitudinal direction is not perfectly straight in the case of natural growth. If such wood is used as a pillar member, its carrying capacity is greatly reduced due to the existence of initial eccentric moment. If the wood is used as a beam member, the bending resistance is poor because the circular section wood has more material near the neutral axis. And the natural bending of crude wood will lead to inhomogeneous force and loosening. 3.2
Poor Corrosion Resistance of Wood
The previous level of daily life in Qiannan was low. Farmers mainly depended on animal husbandry to work. And people always lives in the upper floors and the livestock lives in the lower floor. The animals in captivity will produce a large amount of excrement, and the captive environment is humid. The wood used to built the traditional wooden structure residential buildings is directly driven into the soil and is susceptible to corrosion by excrement, rainwater and other harmful substances. The local decay occurs early in the bottom of the wood. Therefore, the entire building
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structure will be tilted, or even will collapse. It shortens the service life of the structure, and does not meet the requirements of modern people for residential buildings. 3.3
Poor Connectivity of Components
The connections between the components of traditional wooden houses are mostly fixed by tenon joint, socket connection or nail fixing. The wooden wall only plays the role of enclosing and does not bear the load. The connection components bear the load coming from different components, and transmit smoothly. The connection components are important parts of the entire structure. The connecting parts of traditional wood structure residential buildings are usually made by opening holes and slotting, so these connecting parts are weaken by themselves. In addition, the stability of the entire wood structure is affected due to the backward processing technology. In the long-term effects of the unfavorable natural environment, the connection performances of components gradually weaken, or even rot. Therefore, the house structure tends to tilt easily. When people face wooden structure residential buildings which own the large deformation, they often feel unsafe. 3.4
Poor Fire Resistance of Wood
Traditional wooden structure residential buildings are prone to fire. In the minority areas of Qiannan, the fire pit is often placed in the house according to the national culture. In daily life, it is all about the indoor heating. In the daily life, the cooking and heating depend on the fire in the house. In the traditional wooden structure residential buildings, most of the wood is not fireproofed and the wood is easy to burn. Especially in the hot and dry season, it is extremely easy to cause fires. As the local terrain is uneven, most of the residential buildings are built along the hillside. The distances between the houses are relatively small and there are no corresponding firefighting facilities. Once a fire occurs at a home, the rescue facilities cannot arrive in time, which will bring huge losses to the entire village. 3.5
High Costs of Wood Construction
There are no large-scale productions in the local timber industries in Qiannan, and the furniture supply is the main form. The wood used in engineering buildings is less and the price is high. Most of the wooden structures are processed at the construction sites. The utilization rate of wood is low and the waste is high. In the process of construction, the installation accuracy is insufficient because of the backward technology, random installation and lack of professional technicians and managers. Therefore, the sheets are not flat, the gap is large, the components are loose, the sound insulation effect is poor, and there is almost no warmth function. On the other hand, the installations of water and electricity are more disorderly due to the irregularity of the wall, which increase the costs of later maintenance and do not meet people’s requirements for residential buildings.
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4 Renovation of Modern Wood Structure As China advocates to develop the modern wooden structures, the urban and rural constructions are facing new challenges and opportunities in Qiannan Prefecture. At present, many distinctive traditional wooden houses have gradually been replaced by modern reinforced concrete houses. The reinforced concrete buildings have made a series of achievements, and has also eroded the characteristics of traditional dwellings. Wood has the advantages of renewable, light weight, high strength, aesthetics and excellent processability. It is the most suitable material for human living in all building materials. By means of modern technologies, the shortcomings of traditional wood structure residences can be improved. The developments of modern wooden structure buildings have great potential and room. 4.1
Deep Processing Technology of Raw Material
Modern wood structure buildings require deep processing to form the laminated wood which can be applied to building structure [9]. The main steps of deep processing include sawing of crude wood, kiln drying, stress grading, finger jointing, polishing, gluing, pressing, thicknesser and packing [10]. These deep processing processes are conducted in the factory. The standardized productions are adopted to produce the wood components. Therefore, the material quality and accuracy can be guaranteed. In addition, the fireproof coating is used in the processing of laminated wood, which can achieve the fireproof performance as masonry structures. The laminated wood is consistent with the requirements of fire protection code in China. 4.2
Transformation of Traditional Structure
The designing and processing of laminated wood are flexible. The factory prefabrication and field installation are more convenient. The laminated wood can be processed into various shapes according to designs to meet the requirements for both crosssectional shape and axis of beams and columns in residential building structures. For example, the large space is required during designing the central room in Qiannan Prefecture. The strength of laminated wood processed is high, which can meet the requirements. The cross-sectional shapes of beam can be designed and processed according to the requirement. The traditional circular section design of column can be retained. Due to the improvement of processing precision, the wall plates are tightly connected. In addition, the wood structures have good sound insulation and warmth effects. The uniformity of wood material can guarantee that the assembled wood structure residential buildings are more consistent with the designs. The structures have good strength, rigidity and stability, and the damages of structures also shows favorable ductility. 4.3
Improvement of Connection Style
The steel is adopted to connect both beams and columns of modern wood structures. Bolt connection, screw connection and pin connection are widely used [11]. The steel
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support is adopted to connect the wood components and foundation. The contact between the foundation and the wood is separated. Therefore, the wood structures are protected from the damages coming from humid foundation. In order to retain the traditional national cultures, wood connection materials can be used to cover the steel connections, such as penetrating ties and bracket sets. These methods will not only stabilize the structures but also preserve the characteristics of traditional residential buildings. 4.4
Simple and Unpolluted Construction
The assembly structure is adopted to modern wooden structure residential buildings. Each structure member is processed into standard component according to the size of the house type in the factory. The pipelines and insulation materials are installed according to the user’s diversified and personalized designs [12]. Then the components transported to the construction sites are installed. The period of construction is greatly reduced and the site is relatively clean. There are no steel, cement and dust at installation site. At the same time, the same maintenance as concrete works does not need. After the installations, people can move in to live. Moreover, an energy saving and clean environment for the dwellings are created, and the construction speed of the ethnic village tourism can be accelerated. The whole construction process will not cause environmental pollution and energy consumption. The green development, circular development and low carbon development are really achieved.
5 Construction Proposal of Wood Structure Residential Building In urbanization, improving the living environment of local residents is very necessary. At the same time, it is also necessary to use modern wooden construction methods to develop wooden structure residential buildings with traditional ethnic cultural characteristics. Therefore, the residential buildings can meet the cultures of minority nationality in Qiannan Prefecture. 5.1
Realizing the Industrialization of Wood and Reducing Cost
Construction cost is an important factor in improving the residential environment. The uses of inferior materials are eliminated, and the unqualified components cannot be used. The cost-effective materials are used to reduce construction costs so that the local villagers can accept the costs. The three aspects of work from the government level should conducted. At first, the local timber industry should be vigorously developed, the man-made forest should be planted, the timber yield should be increased. Therefore, the sustainable development and virtuous circle of timber industry can be realized. Secondly, the new processing technologies should be introduced in time and the hightech wood processing enterprises should be built. Therefore, the construction costs of wood structure residential building will be reduced, and the local employment will be promoted. At last, the government should encourage the local villagers to learn new
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technologies, and eliminate the backward technologies. The standardized operating standards should be established. And the blind deforestation and waste must be stopped. 5.2
Building Green Residential Architecture and Cultural Tradition Village
In the construction of urbanization, the local traditional wooden buildings should be protected enough. The understanding of local ethnic minorities on the traditional architectural cultures should be correctly guided. As the traditional wooden buildings are the crystallization of local ethnic minorities in architectural engineering technology, they carry the religious beliefs, ideological concepts and living habits of local ethnic minority cultures. The local traditional buildings should be avoided reconstructing as urban renewal based on respecting the traditional cultures and local residents. The new construction techniques should be provided. The construction costs should be reduced. The government should encourage ethnic minorities to improve the residential environment in accordance with planning. Dwelling built privately should be eliminated. The green residential architecture and cultural tradition village should be built. At the same time, the farmers’ income should be increased. 5.3
Cultivating Local Ethnic Construction Engineer
There are few local architectural technicians. Non-local talents who do not understand local ethnic cultures have been introduced. However, local youth are the inheritors of ethnic architectural cultures and also are the future of the nation. Training local professionals is a very important work. Government should encourage the local colleges and universities to set up the architectural engineering with national architectural features. Architectural talents should be reserved in time for the development of construction industry in Qiannan Prefecture.
References 1. Comprehensive utilization of wood property group in Forestry Institute of Guizhou. Experimental report on physical and mechanical properties of six kinds of wood in Guizhou. Guizhou For. Sci. Technol. (4), 26–35 (1975) 2. Zhao, Y., Yang, C., Qi, Y., Yang, C.: Development of wood architecture since the founding of new China. For. Mach. Woodwork. Equip. 40(5), 10–12 (2012) 3. Chen, L.: Analysis of present situation and prospects of wood structure industry in southeast Guizhou. For. Mach. Woodwork. Equip. 44(8), 4–6 (2016) 4. Lu, B., Li, F., Zhou, G.: Research and practice of traditional wooden houses protection and construction project in southeast of Guizhou province. China Forest Products Industry 43 (11), 10–13 (2016) 5. Tong, H.: Study on the counter measures of Diaojiaolou fire protection in Guizhou. J. Guiyang Univ. (Nat. Sci.) 6(3), 39–41 (2011)
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6. Li, L., Cen, X., Zhi, F.: Research on the application prospect of the assembled wood structure in the residential buildings in Qiandongnan. J. Kaili Univ. 33(6), 125–126 (2015) 7. Li, X., Zhou, L.: Investigation on the status and characteristics of the subject national traditional residence in Duyun. J. Tongren Univ. 13(3), 1–3 (2011) 8. Wei, C.: Sandu county’s railing-enclosed houses and their architectural culture. J. Guizhou Minzu Univ. (Philos. Soc. Sci.) (4), 73–75 (2009) 9. Lam, F.: Modern structural wood products. Prog. Struct. En. Mater. 3, 238–245 (2001) 10. Zhou, X., Cao, L., Zhou, J., Zeng, D.: Design and fabrication of glulam timber and products quality control. J. Central South Univ. Forestry Technol. 34(12), 136–139 (2014) 11. Deliang, X., Liu, W., Zhou, D., Xi, A.: Experimental study of bolted glued timber-to-timber joint. J. Build. Struct. 32(7), 93–99 (2011) 12. Sang, L.: Installation construction technologies of modern glued-laminated timber structure frame. Shanxi Architect. 40(17), 126–128 (2014)
Research on Renewable Energy Utilization in the New Countryside in Qinba Mountain: A Case Study in Bazhong, Sichuan Province Zhuoling Zhong, Jiayuan Wang(&), and Cheng Fan School of Civil Engineering, Shenzhen University, Shenzhen, China [email protected]
Abstract. As emphasized in the 19th National People Congress of Communist Party, the construction and upgrades of new countryside have become a key task with the aim of reducing the gap between urban and rural areas in sustainable development. It is therefore urgently needed to study the energy consumption characteristics in new countryside. This study aims to investigate the current energy consumption characteristics of Qinba Mountain Area in Bazhong, Sichuan province. The status quo of energy consumptions is analyzed considering the geographical layouts and energy consumption structures. The solar energy centralized biogas system is proposed to address the present problems on energy waste, irrational energy consumption structure, defects of traditional household biogas digesters. The core idea is to develop a low-carbon, energyefficient and comfortable living environment for rural areas. The research results indicate that solar energy centralized biogas system is of the greatest significance to the utilization of renewable energy in this region. It can help to reform the irrational energy consumption structures while minimizing the environmental burdens. Keywords: Sustainable development New countryside Energy consumption structures Solar energy Centralized biogas
1 Introduction Energy consumption has been increasing significantly in recent years. With the continuous economic developed, large amounts of energy consumption has been a prominent issue in the sustainable development of society, which has also had adverse effects on the environment, such as global warming and air pollution. Among them, building energy consumption accounts for about 32% of the total energy consumption [1]. Therefore, decreasing the energy consumption of buildings has been the main object. The planning and energy utilization of urban in China have always been highly concerned by the governments and scholars, and have also achieved a series of achievements. However, few people are concerned about the rural construction and rural energy utilization. China is a large agricultural country which has 589.73 million rural people accounting for 42.65% of the total numbers by 2016 [2]. The development of rural areas plays an essential role in achieving global sustainability. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1194–1211, 2021. https://doi.org/10.1007/978-981-15-3977-0_92
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The concept of new socialist countryside was proposed by president Jintao Hu as early as the Fifth Plenary Session of the 16th CPC Central Committee, which means a comprehensive construction of the rural economy, politics, culture, and society, and a new starting point for a comprehensive reform of the countryside under the socialist system and the requirements of the new era. It aims to break the urban-rural dual economic and social structure to meet the urban-rural economic balanced and harmonious development. At the 19th National People Congress of Communist Party, Speeding up the construction of the new countryside and implementing strategies for the rejuvenation of villages have also been pointed out. Therefore, constructing new countryside has been the main object to achieve two hundred-year goals. Meanwhile, a series of legal policy published for poverty alleviation working in the poor areas aims to realize the well-off level, Qinba Mountain, as one of the 11 concentrated destitute areas, constructing energy problems of this this region is recognized a great significance to the national strategic development. The construction of new countryside is mainly led by the government, and actively encourages the farmers to participate. At the same time, the old house base will be retired as arable land. Changing the distribution of traditional villages and carrying out collective construction aim to meet water and electricity supplied with centralized stations, and subsidizing will be done according to the type of new houses and the demolition of old houses. There are also a strong desire for the construction of a new countryside, only 7.14% of the people are reluctant to move into the new countryside constrained by economic conditions [3]. The rural population has shown a decreasing trend in recent years. However, with the improvement of the living standards of farmers, according to relevant statistics, the energy consumption has gradually increased. Taking Qinba Mountain areas as the research object and summarizing the characteristics of the rural environment and energy consumption, for the energy issues, a solar energy centralized biogas system is proposed to adjust the energy consumption structure in the areas and improve the living environment, which can address the issues of new countryside energy utilization in a targeted manner and provide suggestions for rural energy development under the guidance of the national strategy for the development of new countryside areas. The overall research framework is as follows. In first step, the current situation of rural natural environment and energy development in Qinba Mountain areas are summarized to find out the problems during the process of energy use in this region. Then, for the existing energy problems and the defects of the traditional household biogas digesters, the solar energy centralized biogas digester is proposed. Finally, feasibility analysis of this system is carried out from four aspects, i.e., technology, economy, environment and society. The results show that using the solar energy centralized biogas system has a great impact on the construction of renewable energy in the new countryside areas of this region, and can improve the irrational rural energy consumption structure and environmental issues effectively.
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2 Current Situation of Rural Energy Development in Qinba Mountain 2.1
Rural Natural Conditions
Qinba Mountain Areas refer to Daba Mountain, Qinling Mountain and the adjacent areas of the upstream of Han river, including 6 provinces, 18 cities and 75 towns in Gansu, Sichuan, Shanxi, Chongqing, Henan and Hubei provinces (Table 1). Table 1. Administrative region of Qinba mountain areas Province Henan Hubei Chongqing Sichuan Shanxi Gansu
City Luoyang, Pingdingshan, Sanmenxia, Nanyang Shiyan, Xiangyang Chongqing Mianyang, Guangyuan, Nanchong, Dazhou, Bazhong Xi’an, Baoji, Hanzhong, Ankang, Shangluo Longnan
The geographical distribution map of Qinba Mountain is shown in Fig. 1.
Bazhong
Fig. 1. Geographical distribution map of Qinba Mountain
Bazhong, in Sichuan Province, occupies the southwest corner of the Qinba Mountain areas, whose entire administrative area is located in the Qinba Mountain, and it’s one of the three central cities in Qinba Mountain areas. Qinba Mountain areas are dominated by hills, with complex geographical conditions and weak development of foundations, where the poor villages are often remote and inaccessible so that they are key areas for poverty alleviation.
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Monthly average maximum temperature Monthly average minimum temperature
Temperature( )
China’s rural areas are generally scattered, which result in great difficulties for infrastructure constructions, such as public transportation, telecommunication services and emergency medical services [4], as is the same in the Qinba mountain. Though the traffic is inconvenient and the infrastructure is poor [5], the climate is mild. There are 188 sunny days in Bazhong 2017 according to the statistics, and the monthly average temperature is as shown in Fig. 2, the monthly average insolation duration is as shown in Fig. 3.
35 30 25 20 15 10 5 0 Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 Month
Fig. 2. Monthly average temperatures in Bazhong
Insolation duration(h)
300 250 200 150 100 50 0
Month
Fig. 3. Monthly insolation duration in Bazhong
With the long insolation duration and high temperatures, the solar energy resource is abundant so that it can be fully utilized. In addition, there are large numbers of farmed animals, such as pig, cattle, poultry, and ect., Consequently, there are large amounts of animal excrement which can be used for biogas production. The details of farmed animals from 2000 to 2016 are shown in Fig. 4.
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3500.00 3000.00 2500.00 2000.00 1500.00 1000.00 500.00 0.00 2000 2005 2010 2011 2012 2013 2014 2015 2016 Year
Fig. 4. Annual output of farmed animals in Bazhong
The permanent populations of Bazhong rural areas are 2.02 million according to the statistical yearbook data, accounting for 61% of the total of Bazhong, and urbanization is only 39.1%, which is lower than the average level of Sichuan Province. Therefore, the urbanization of this region was highly valued by local government. Comparing to the scattered villages, new rural villages are constructed through a centralized fashion, e.g., the water and electricity are supplied based on centralized stations. It can improve the living standards and promote the sustainable development effectively. Meanwhile, it can also provide the foundation for sustainable development after natural disasters [4]. 2.2
Current of Rural Energy Consumption
In 2016, the energy consumption for China is 365.4 kg of standard coal per capita, which has a 33% increase compared to 2010 level. The raw coal production accounts for 69.6%, original production accounts for 8.2%, gas production accounts for 5.3% and renewable energy production accounts for 16.9% [2]. As shown in Fig. 5, the coal is still the dominant energy resource, resulting in great pressure for the environment.
Coal 8.2%
Oil Natural Gas Renewable Energy
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Fig. 5. Composition of energy production
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In addition, the construction of grid needs to go over the mountains, which will increase the energy loss in the transmission process and the cost of electricity. The price of electricity for rural Bazhong reaches ¥1.33 per KW ⋅ H according to the survey, which is 25.5% higher than urban areas. And the total electricity consumption in rural areas of Bazhong is amount of 70.33 million KW ⋅ H in 2016. In addition, there are 155,000 ha of arable land at the end of 2016, the amount of fertilizer used is 139,900 tons, and pesticides used is 0.2 million tons, equal to 905.2 kg of fertilizer and 13.1 kg of pesticide used per hectare of land, which are higher than the national average. Meanwhile, the total annual output of wheat, rice, corn and rapeseed in rural areas amounts to 1.53 million tons, which is estimated that 1.76 million tons of straw will be produced. 528 million m3 of biogas can be produced if all the straw is used for the production of biogas. The per capita disposable income in rural areas is ¥9969 [6], which is lower than the average level in Sichuan. Therefore, the ecological destruction in the Qinba Mountain is rather serious due to the pressure of economic development [7]. Energy consumptions in rural households rely mainly on straw (51.46%), firewood (28.02%), coal (12.83%), electricity (4.68%), biogas (1.47%), liquefied petroleum gas (1.43%) [8, 9], as shown in Fig. 6.
Straw Firewood Coal Electricity Biogas LPG
Fig. 6. Energy consumptions in rural households
In addition, the average household water heater is 31 per 100 units, and exhaust fume machine is an average of 4 per 100 units. The less use of water heaters and exhaust fume machines show that traditional stoves are used to produce and live in rural areas, and the renewable energy has not been popularized because the rural areas of Bazhong are remote and poor. 2.3
Research on Rural Energy Problems
The main energy resources for rural areas are straw and firewood. On the one hand, this pattern of energy consumption has been imposing destruction on the environment, and natural disasters such as mudslides and landslides. On the other hand, the heat utilization rate is only 10% by burning straw directly. However, the effective utilization rate is as high as 60% through the microbial fermentation into biogas, which is 5 to 6
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times higher than the direct combustion. Meanwhile, about 20% of the crop straws were simply discarded or burned without being utilized at all, which become the important cause of rural ecological environment [10, 11]. Coupled with the low burning technology in rural households, the public health and the environment are impacted significantly by the particles produced [12]. Living garbage in rural Bazhong has not been classified and concentrated, generally burned by the farmers themselves while piled to a certain height, which produces large amounts of poisonous gas and pollutes the environment seriously during the process [13]. In addition, using chemical fertilizers heavily makes the land barren, and the lack of effective use and reasonable planning of animal’s excrement make the rural living environment presented a dirty, messy and poor state. And Fu T M, et al., found that it was underestimated of energy use in all rural areas [14]. Table 2 shows the energy problems in rural areas detailed.
Table 2. Rural energy problems Energy problem Resources waste Low efficiency Ecological damaged Poor environment
Cause of the problem Most agricultural waste is not used efficiently Thermal efficiency of traditionally used stoves is low Straw direct combustion has low heat efficiency Trees are felled and the air is polluted heavily Farmers burn straw without any environment protection
Underestimated usage The energy use in rural areas is underestimated High cost The costs household fuels are high and rising rapidly
Articles [15, 16] [12] [17] [9, 18] [10, 15] [11, 17] [14] [9]
3 Research on Traditional Household Biogas The biogas technology is being promoted as an important choice to meet the increasing energy demand in developing countries’ rural areas [19]. As a clean energy source, it can not only improve the rural environment, but also reduce air pollution and trees felling, biogas benefits are shown in Table 3. Biogas is a mixture gas which is produced by the fermentation of microorganisms under anaerobic conditions, mainly consists of 50% to 70% of methane (CH4) and 30% to 50% of carbon dioxide (CO2) [20], and can be used for burning directly or for power generation [21]. And the total annual utilization of biogas will reach 44 billion m3 by 2020, of which the rural biogas utilization will reach 30 billion m3 according to the “Long-Term Development Plan for Renewable Energy”.
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Table 3. Benefits of biogas Overall benefits Contents Articles Ecological Decreasing the annual consumption of coal [22] Reducing the trees cutting [18, 23], Reducing fertilizer use and protecting the land [18, 24] Environmental Reducing carbon emission and global warming [25] Beautifying the environment [18] Economic Reducing the payment of fossil fuel [16] Gaining additional benefits by biogas residue and slurry [18] Social Improving standard living of new rural areas [16] Improving the employment rate of rural labor [18, 23, 26]
Biogas, as an important pillar of rural sustainable development programs [19], has been developed drastically during the last two decades under the government subsidies and preferential policies [16]. Clean Development Mechanism (CDM) refers to the task of emission reduction of developed countries, which is completed by developing countries with technical support or financial subsidies supported by developed countries. China has become the most important country in the development and implementation of CDM projects. The CDM brings an opportunity for the development of household biogas in rural China [23]. Small household biogas digesters [19] are used mostly in rural areas. However, the biogas digesters haven’t played their original role and have low effective production due to the knowledge gap between biogas technologies and rural farmers [23], and many biogas digesters are discontinued in winter [27]. For example, there are about 890 million tons of straw collected and 1.629 billion tons of animal’s manure in rural areas per year, which can produce 33.5 1010 m3 of potential biogas [28]. However, the total amount of biogas generated by households, large and medium-sized biogas projects (MLBPs) in 2012 was only 1.67 1010 m3 according to data from the National Bureau of Statistics of China [29], which means that only 5% of agricultural waste in rural areas is used for biogas production [16]. The main defects of household biogas digesters are shown in Table 4. Table 4. Disadvantages of traditional household biogas digesters Disadvantages A shortage of raw material of rural biogas Low efficiency of fermentation limited by temperature Inefficient management of farmers Unbalanced resource production
Articles [19] [19, 27] [18, 19] [20]
In addition, although biogas technology has been popularized, the actual performance is usually unsatisfactory due to the poor energy awareness of farmers and low management level of decentralized biogas systems [18]. In addition, traditional straws and firewood are still used for mainly life energy, resulting in an unreasonable energy consumption structure [9], the rural energy issue has not been resolved.
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4 Solar Energy Centralized Biogas System With the problems existing in the new countryside in Qinba Mountain and the defects of traditional household biogas digesters, the solar energy centralized biogas system is proposed. Considering the issues such as insufficient energy use of farms, the low management level of decentralized biogas systems [18], and the low effective production of biogas digesters, a centralized biogas system is adopted to solve the problems by unified management of professional and technical personnel. In addition, the continuity of biogas production is significantly impacted by the temperature, because the Qinba Mountain is a hot-summer and cold-winter region. Therefore, keeping the temperature of biogas is important. The insolation duration is long and the temperature is high of this region, so that the solar energy resource is rich. Considering using solar energy for biogas digesters to keep the temperature within a suitable range can not only strength the use of renewable energy, adjust the energy consumption structure in new countryside, but also increase the production efficiency. 4.1
Application of Solar Energy in Biogas Digesters
Rural biogas is generally suitable for medium-temperature fermentation (28 to 38 °C) and room-temperature fermentation ((less than 28 °C)). In this temperature range, biogas production will also increase as the fermentation temperature increases [30]. Although the application of biogas in rural areas is promoted and the technology is relatively mature, the temperature fluctuations have a great impact on the production of biogas digesters due to the typical hot-summer and cold-winter climate in Qinba Mountain areas [30]. In addition, the heat generated by solar energy is not enough for the residents during the winter, so it can be considered to be integrated into the biogas system [31, 32]. The principle of solar energy centralized biogas system is shown in Fig. 7.
Hot water circulation pipeline Cold water Solar Energy Biogas discharging port Feeding port
Biogas residue discharging port
Biogas digester
Hot water
Fig. 7. Schematic of solar biogas digester
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As shown in the picture, biogas digester is constructed with insulation materials. The yellow one is feed pipe, which transfers the raw material for biogas fermentation. The red one is hot water circulation pipeline, which transfers the hot water heated by solar energy to the biogas digester. The water’s temperature in the pipe gets down after the digester absorbs the heat, and it can be sent to the water heater for recycling. Thus the fermentation temperature of the biogas digester and the biogas production efficiency are increased to ensure the daily cooking needs in the winter. 4.2
Fermentation Materials
In addition to regard the animal’s excrement and straw used in the biogas digester as the raw material for biogas fermentation, the other resources such as excreta generated by residents and the living garbage classified are also regarded one of the fermentation materials in order to make reasonable use of resources and ensure that the biogas’ production meets the daily needs of residents. The details are as shown in Table 5.
Table 5. Fermentation materials of solar centralized biogas digester Fermentation materials Straw Animal’s excrement Living garbage
Annual output 0.176 million tons 0.753 million tons 18.05 million tons
Animal’s excrement was generally used in the conventional biogas digesters as a raw material for fermentation [19]. However, farmers need to purchase excrement at the farm to meet the daily needs of biogas due to insufficient animal’s excrement in household biogas digesters, which undoubtedly makes it more difficult for biogas used in rural areas. Straw is generally used for direct combustion in the local areas, as for the extra straw, the general treatment method is to burn in situ [17], because the ash, as a manure for the land, is beneficial to the growth of crops. However, large amounts of greenhouse gases are generated during the incineration process, which pollutes the environment seriously [10]. And open burning has a certain degree of danger because it will spread out to cause a fire if it is not noticed. Therefore, making full use of straw by using as a raw material for the fermentation of biogas digesters can not only providing people with daily needs but also have a positive impact on the environment. In addition, the local garbage in rural Bazhong has not been classified and concentrated due to the low awareness of environmental issues farmers have. Instead, all garbage is placed in the same place and generally burned by the farmers themselves while piled to a certain height. A large amount of poisonous gases are produced during the process, which not only pollute the environment, but also pose a threat to the human’s health. Therefore, as a raw material for fermentation, garbage can be properly handled and produce benefits for residents.
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Structure of Solar Centralized Biogas Digester
The investigation shows that the new rural houses in Bazhong are two-story and singlefamily buildings, one house with two households. Trees are planted on both sides of the house, and four households build a unit for standardization with a rural road in front of the house. The poultry and livestock are intensively farmed in order to make the living environment of farmers more comfortable, as shown in Fig. 8.
Fig. 8. Layout plan of new countryside
According to the layout features of the new countryside, the planned design of the solar energy centralized biogas digesters’ structure is shown in Fig. 9.
Discharging port1 Biogas lamp
Discharging port2 Cooking
Feeding port3 Feeding port4
Feeding port2
Feeding port1
Discharging port3
Biogas digester
Fig. 9. Structure of biogas digester
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Taking straw, animal’s excrement, classified living garbage as the raw materials of biogas digester, there are four feeding ports and three discharge ports in order to make full use of resources to ensure that the biogas’ production meets the daily needs of residents. The feeding port 1 is the excrement generated by the humans which is sent to the biogas digester through the landfill pipeline. The feeding port 2 is the excrement of the poultry and livestock. The feeding port 3 is straw. And the feeding port 4 is the garbage which is available to produce biogas after classified by farmers. The discharging port 1 is used for illumination of concentrated breeding spots like biogas lamps. The discharging port 2 reaching the residential houses through the landfill pipes is mainly used for cooking and heating. And the discharging port 3 is used for discharging the residue and slurry of the biogas digesters.
People
Living garbage
Biogas
Biogas Digesters
Pig, Sheep, and etc
Fodder Land
Manure
Fig. 10. Resource recycling system
The resource recycling model in Fig. 10 shows that the continuous circulation of resources can achieve maximum utilization of efficiency. 4.4
Advantages of Solar Energy Centralized Biogas Digester
Utilizing the characteristics of solar energy centralized biogas system can solve the problems of energy use in rural areas well. Compared with the previous traditional household biogas systems, solar heating is used to ensure the temperature of biogas digesters, and professionals are set up to manage them uniformly. The advantages are shown in Table 6.
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Solar energy centralized biogas system
Advantages Wide source of fermentation materials Using biogas residue and slurry as fertilizer directly Ensuring fermentation temperature and improving production efficiency Providing hot water for living in other seasons To solve the problem like lack of raw materials, labor shortage and lack of construction conditions Organized and Managed by professional personnel Saving land, reducing cost, improving efficiency and prolonging the life of biogas digesters Improving renewable energy efficiency
5 Feasibility Analysis 5.1
Technical Feasibility Analysis
As raw materials, the annual output of animal’s excrement in Bazhong is about 0.753 million tons, the annual output of straw is about 1.76 million tons, and the annual output of living garbage is about 18.05 million tons. The fermentation materials of biogas digester are abundant and easy to obtain. As natural conditions, there are 188 sunny days throughout the year, 53 sunny days in winter, and the temperature is above 0°, therefore, it can play a good role to ensure the fermentation temperature of biogas digesters in winter. As technology, the development of solar energy and traditional household biogas digesters technology is relatively mature although solar energy centralized biogas systems are not widely used, and the application of small, medium, and large centralized biogas digesters is constantly being encouraged and promoted by the government. In summary, the fermentation materials of the solar energy centralized biogas system are wide and ease to access. The basic technology is mature and meets the characteristics of the local new rural construction. So that it is feasible on technology. 5.2
Economic Feasibility Analysis
According to a large number of surveys, the cost of building 10 m3 of biogas digester is about ¥2,500, the solar heater is about ¥1,500, and the annual maintenance cost of biogas digester is about ¥100. About 600 m3 of biogas and lots of biogas residue and slurry will be produced annually assuming that it can be produced all year round. The price of electricity in rural Bazhong is ¥1.33 per KW ⋅ H, it will save electrical costs about ¥200 as breeding point lighting and save about ¥1,000 of coal and other fuel as kitchen cooking. In addition, the biogas residue and slurry used as fertilizer can save
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about ¥500, from what has been discussed above, the 10 m3 biogas digesters can save ¥1,700 per year. Considering the time value of funds, a dynamic investment payback period calculation method is adopted. Assuming that the benchmark return rate is 10%, and each symbol description is shown in Table 7. Table 7. Nomenclature i t C R NCFPV TNCFPV P NPV
Benchmark return rate Calculation period Construction or maintenance costs (RMB) Revenue from the biogas digester (RMB) Net cash flow present value (RMB) Total net cash flow present value (RMB) Payback period (Year) Net present value (RMB)
The cost and revenue of the biogas digester system is shown in Table 8.
Table 8. Cost and revenue of biogas digester t 1 2 3 4 5 C 4000 100 100 100 100 R 0 1700 1700 1700 1700 NCFPV −3636 1322 1202 1093 993 TNCFPV −3636 −2314 −1112 −19 974
The net cash flow present value equation for each year is described by: NCFPVt ¼
ðR CÞ ð1 þ iÞt
ð1Þ
Where R is the money that the human gained from the biogas digester (RMB), C is the money that the human need to pay for the biogas digester (RMB), i is the benchmark return rate, and t is the years. The total net cash flow present value equation for each year is described by: TNCFPV ¼ TNCFPVt1 þ NCFPVt
ð2Þ
The total net cash flow present value equation for year t equals to the total net cash flow present value equation for year t − 1 plus net cash flow present value equation for year t.
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The payback period of the biogas digesters system is equal to: P ¼ ðt 1Þ
jTNCFPVt1 j , While TNCFVP [ 0 NCFPVt
ð3Þ
According to the model of investment payback period and the data in the table, P is calculate as 4.02 years, which means that the biogas digester can recover its cost in the fourth year and profit from the fifth year. Using the net present value method determine whether the project is feasible. Assuming that the biogas system is operating for 10 years, the net present value is defined as: NPV ¼
10 X
ðR CÞt ð1 þ iÞt
ð4Þ
t¼1
The NPV of this system is ¥6194.3, which proves that the project is feasible on economy. In addition, a series of fertilizer products can also be produced if processing the biogas residue and slurry further, which can bring additional benefits to farmers. And the research object of this article is in remote and impoverished mountainous area, a series of subsidy advantages has been increased for this region under the great goal of realizing a well-off society in an all-round way. At the same time, the construction of rural biogas digesters is launched by the state to build the septic tanks into biogas digesters to recycle the toilet discharge which can provide life energy for farmers, the subsidy of the biogas is as highly as ¥200,000 according to the size of the biogas digesters. The utilization of solar energy centralized biogas system in rural can not only improve the living standards but also solve rural energy problems to protect the environment. 5.3
Environmental Feasibility Analysis
The use of solar energy centralized biogas digester has a positive impact on the rural environment mainly as follows: Firstly, the living environment in the new countryside is improved. The rational use of living garbage after classified, straw and animal’s excrement changes the previous treatment methods, reduces the emissions of the poisonous gas and greenhouse gas, and improves the overall cleanliness of new countryside. Secondly, the forestry resources are protected. Rural energy sources are partly derived from firewood in the past. It’s inevitable to cut trees during the use process, especially in winter. The use of biogas digesters can reduce the farmers’ dependence on wood and protect the ecological environment. Meanwhile, it can reduce the occurrence of natural disasters such as mudslides and landslide. Thirdly, the soil is protected and improved. Large amounts of fertilizers and pesticides were used to ensure the crop yield during the process of planting crops in the past years. The land generally becomes barren due to the long-term use of chemical
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fertilizers. However, the use of manure generated by residue and slurry of biogas can reduce the use of fertilizers and increase the fertility of the land and the crop yields. Finally, the waste of resources is reduced. There is a large amount of waste of resources in rural areas. At the same time, it has a great impact on the environment. Processing and transforming the waste into human’s living energy can increase the efficiency of resource use and reduce waste. 5.4
Social Feasibility Analysis
The application of solar energy centralized biogas digester, on the one hand, changes the traditional rural lifestyle and improves the living environment in rural areas. On the other hand, it increases the employment opportunities in rural areas which can improve the problem of labor shortage and human’s living standards. At the same time, the recycling of resources can ensure that the ecosystem is in a balanced and stable range. Therefore, it has a great significance to the sustainable development of countryside and society.
6 Conclusion Utilizing solar energy centralized biogas systems in the new countryside in Qinba Mountain is shown to be an effective strategy to achieve sustainable development. Making full use of renewable energy through the use of solar energy centralized biogas system can not only adjust the energy consumption structure in this region, solve the problems such as rural energy waste and inefficient utilization, but also improve people’s living standards and promote the development of the local economy. Compared with traditional biogas digesters, solar energy can ensure the fermentation temperature of biogas digesters and increase the production. The centralized system is maintained by professional personnel during the operation process so that its useful life is increased. In addition, the development of solar energy and biogas technology is relatively mature. Despite the promising aspects, a comprehensive management system of rural energy utilization is urgently needed to solve the problem of poor energy protection awareness and energy wasting behaviors.
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5. Yang, Y., Yang, J., Tang, Y., et al.: Poverty Attributions and Alleviation Frameworks of Qinling-Daba Mountain Region in Sichuan Province. Land Resour. Sci. Technol. Manag. 33 (2), 63–68 (2016). (in Chinese) 6. National Bureau of Statistics of China, 2000–2016a. China City Statistic Yearbook 7. Xi, H., Zheng, Z.: Problems and countermeasures of sustainable social development in Qinba mountainous area. J. Northwest Univ. (Philos. Soc. Sci.) 30(1), 136–141 (2000). (in Chinese) 8. Tian, Y.: Current status and future trends of rural energy development in China in 2012. China Energy 35(3), 11–15 (2013). (in Chinese) 9. Li, Z., Tang, R., Xia, C., et al.: Towards green rural energy in Yunnan. China. Renew. Energy. 30(2), 99–108 (2005) 10. Tian, Y.: Status and prospects of China’s rural energy development in 2015. China Energy 38(7), 25–29 (2016). (in Chinese) 11. Zhang, L.X., Yang, Z.F., Chen, B., et al.: Rural energy in China: pattern and policy. Trans. Chinese Soc. Agric. Eng. 34(12), 2813–2823 (2009) 12. Chen, Y., Tian, C., Feng, Y., et al.: Measurements of emission factors of PM 2.5, OC, EC, and BC for household stoves of coal combustion in China. Atmos. Environ. 109, 190–196 (2015) 13. Bigum, M., Damgaard, A., Scheutz, C., et al.: Environmental impacts and resource losses of incinerating misplaced household special wastes (WEEE, batteries, ink cartridges and cables). Resour. Conserv. Recycl. 122, 251–260 (2017) 14. Fu, T.M., Lee, S., Ho, K.F.: Carbonaceous aerosols in China: top-down constraints on primary sources and estimation of secondary contribution. Atmos. Chem. Phys. Discuss. 11 (10), 2725–2746 (2011) 15. Han, L., Teng, G., Liu, X., et al.: Straw resources and their utilization in China. Trans. Chinese Soc. Agric. Eng. 18(3), 87–91 (2002) 16. Wang, X., Lu, X., Yang, G., et al.: Development process and probable future transformations of rural biogas in China. Renew. Sustain. Energy Rev. 55, 703–712 (2016) 17. Jiang, X.Y., Sommer, S.G., Christensen, K.V.: A review of the biogas industry in China. Energy Policy. 39(10), 6073–6081 (2011) 18. Chen, Q., Liu, T.: Biogas system in rural China: upgrading from decentralized to centralized? Renew. Sustain. Energy Rev. 78, 933–944 (2017) 19. Chen, Y., Hu, W., Feng, Y., et al.: Status and prospects of rural biogas development in China. Renew. Sustain. Energy Rev. 39(6), 679–685 (2014) 20. Angelidaki, I., Treu, L., Tsapekos, P., et al.: Biogas upgrading and utilization: current status and perspectives. Biotechnol. Adv. 36(2), 452–466 (2018) 21. Benato, A., Macor, A., Rossetti, A.: Biogas engine emissions: standards and on-site measurements. Energy Procedia 126, 398–405 (2017) 22. Tu, W., Zhang, L.X., Zhou, Z., et al.: The development of renewable energy in resource-rich region: a case in China. Renew. Sustain. Energy Rev. 15(1), 856–860 (2011) 23. Chen, Y., Hu, W., Chen, P., et al.: Household biogas CDM project development in rural China. Renew. Sustain. Energy Rev. 67, 184–191 (2017) 24. Ashworth, A.J., Taylor, A.M., Reed, D.L., et al.: Environmental impact assessment of regional switchgrass feedstock production comparing nitrogen input scenarios and legumeintercropping systems. J. Clean. Prod. 87, 227–234 (2015) 25. Ding, W., Niu, H., Chen, J., et al.: Influence of household biogas digester use on household energy consumption in a semi-arid rural region of northwest China. Appl. Energy 97(3), 16– 23 (2012) 26. Zhang, P., Yang, Y., Tian, Y., et al.: Bioenergy industries development in China: dilemma and solution. Renew. Sustain. Energy Rev. 13(9), 2571–2579 (2009)
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Research on the Welfare of Homestead Transfer Under the Background of Targeted Poverty Alleviation—Based on Sen’s Feasibility Analysis Ping Lv1(&) and Yuewen Gu2 1
School of Public Administration, Renmin University of China, Beijing, China [email protected] 2 Real Estate Economy and Management, Beijing, China
Abstract. Objective: to explore the welfare changes of peasant households in poor areas before and after the transfer of homestead. Methods: to draw on the utility analysis and feasibility analysis framework of traditional welfare economics, and adopt case analysis and comprehensive deductive analysis method. Results: the increase and decrease of the link and the implementation of the relocation project are carried out in the land transfer pattern dominated by the government, in the short term increased the wealth of the poor peasant households individual utility and living conditions, but from the point of long-term development, poor farmers’ practical ability is still in a state of loss, hindered the advance of the land circulation process. Conclusion: from the three levels of basic goods, intention consciousness and potential ability, a systematic model of homestead transfer in poor areas is constructed. In the process of policy implementation, it not only needs financial support, but also needs to improve education and vocational skills of poor farmers, so as to effectively protect the rights and interests of poor individuals. Keywords: Poor areas analysis
Homestead circulation Welfare level Feasibility
1 Introduction With the deepening of reform, the central government has issued a series of policies to promote rural development. After the 19th congress, the revitalization of the countryside was an important aspect to guide the integration of urban and rural areas from a strategic perspective [1]. In this context, how to solve the problem of “one resident, more houses”, “no plan” and “no owner” in the land, is one of the most important problems which can improve the utilization efficiency of rural homestead and promote the process of homestead circulation, with the aim of the revitalization of the countryside. Many scholars have conducted in-depth research on the aspects of homestead transfer, at present. On the one hand, some scholars started from the perspective of peasant households, and studied the changes of farmers’ welfare income and willingness before and after the transfer of homestead. From the micro perspective, Guan etc. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1212–1224, 2021. https://doi.org/10.1007/978-981-15-3977-0_93
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think that farmers were influenced by education degree and income, and the willingness of homeownership was low by using questionnaires and Logistic Modeling [2]. On the other hand, there are also a lot of literatures from the local government and village collective level, analyze the patterns of homestead transfer and summary the experiences [3, 4]. Through the field investigations and analysis, Liu etc. put forward relevant suggestions on the basis of existing internal circulation [5, 6]. Chen etc. put forward the perfect path of rural housing system by using case study and comprehensive analysis, according to the relative deprivation theory [7]. Due to the different degrees of economic development in different regions, the circulation intention and patterns must be different [8, 9]. Under the background of the today’s targeted poverty alleviation, it is better to explore the transfer mode of homestead in poor areas [10], from the perspective of free development [11]. The directions and measures of homestead reform must be different, at different levels of development. Based on Sen’s theory, there are less researches on the change of individual welfare levels before and after the transfer of homestead. Focusing on the poverty-stricken areas as the breakthrough point, this paper tries to analyze the problem of the slow process of the reform of land circulation in poor areas, according to the practical ability of analysis framework, and combined with precise poverty alleviation that closely related to land reform in the increase or decrease hook relocation and plant relocation.
2 Problems and Countermeasures in the Circulation of Homestead 2.1
Current Situation and Problems of Homestead Circulation
The research group carried out a lot of researches on land reform pilots, and the transfer patterns of homestead can be divided into three kinds, the leadership of peasant households, village collective and government. The peasant households leadership usually happens in economically developed areas, where is a certain industrial base. For example, in Liu yang, Hunan, driven by the development of local industries, it will use its mortgage financing to finance the factory production of fireworks. The village collective leadership happens in the more developed areas, where is a certain collective economic foundation. Under the coordination of village committees and other grassroots organizations, the transfer of homestead is carried out by means of paid use and compensated withdrawal mechanism. For example, Yu Jiang in Jiangxi province, in order to promote homestead reform, the villagers’ affairs council was established, and the creative use of the ledger management system solves the contradiction between the new population and the supply of land. The government leadership usually happens in poorer areas where the benefits of homestead are relatively low. Therefore, it is often necessary to take indicators to transfer. Through the movement of homestead index in developed regions and poor areas, it provides fund development for the development of poor areas while increasing the land use for the developed areas. This pattern is the focus of the next discussion, as the Fig. 1 shows. In combination with the targeted poverty alleviation policy, the project is discussed in this paper.
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The increase or decrease link is closely related to the relocation project. First of all, from its root cause, the increase or decrease is aimed at the transfer of homestead, and the relocation is the construction of the farmhouse, which has a strong correlation. Secondly, the increase or decrease of the link project provides a real guarantee for the implementation of the relocation. In the process of relocation, the original residents’ homestead will land reclamation. In the process of land reclamation, the trade index is achieved through the balance of the increase and decrease of the linked projects. In addition, the most important point is that the overall implementation of the increase or decrease of the link and the relocation project is an effective mechanism to promote the integration of urban and rural areas and the construction of beautiful countryside.
Town planning
Industry for poverty alleviation
Housing Education poverty alleviation
Reside poverty alleviation
Social security
Targeted poverty reduction
Change of relocation
Land
Urban and rural integration
Rural development
Increase or decrease hook
Farmers' status
Fig. 1. Homestead transfer and poverty alleviation policy in poor areas
Specifically, the circulation of homestead in poor areas is mainly faced with the following two problems. First, homestead circulation is slow. It was found that in the case of farmers’ spontaneous transfer of homestead, they seldom deal with members other than village collective organizations. Second, the homestead idle phenomenon is serious. The development of poverty-stricken areas is mainly based on primary industry, so in order to get more income, farmers are going out to work. Besides, individual farmers are also unable to build houses because of low income, often in the situation of multi-family homes. Under the combined action of these factors, the vacancy rate of homestead in poor areas is high, and the utilization rate is low. To achieve coordinated urban and rural development, the government must increase input in rural areas and provide more public goods. Practice has proved that the implementation of the increase or decrease linkage, collating collective construction land, according to the principle of differential rent principle, and the requirements of the city to take the township, to supplement the farmers, it will be used for the development of rural collective economy, rural infrastructure and public service facilities. This will not only increase the income of farmers, improve the living standards of local farmers, but also change the rural backwardness and promote the development of new rural construction and urban and rural integration.
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Sen’s Theory and Analytical Framework
The evaluation of the personal standard of living in the framework of the feasibility analysis of Sen mainly includes both functional activity level and feasible ability collection, as shown in Fig. 1. Unlike traditional welfare economics, Sen’s analytical framework is a new measure of well-being [12]. It is neither the level of utility nor the basic object, but more the real freedom of life which the individual chooses to cherish. According to Sen’s theory, an individual’s “viable capability” is a combination of possible functional activities that are possible [13]: Vk ¼ fk hk ðxk k z1 ; z2 ; z3 Þ8fk 2 FK ; xk 2 Xk Where Vk represents the functional activity vector that the k person has, xk represents their goods, while hk changed commodities into eigenvector function, FK changed all into function set, z1 ; z2 ; z3 represents the characteristic factor, such as individual conditions, the specific social environment and other factors. Xk represents all possible collections of goods, namely that individuals must be constrained by resource constraints while implementing functional activities. Under certain conditions, f k ðhk ðxk k z1 ; z2 ; z3 ÞÞ can turn goods xk successful activity vector conversion function. The welfare research of before and after the loss of Chinese peasants showed that, except the changes in the living environment, the economic situation, social security and other functional indicators of farmers had deteriorated [14]. And the two characteristics of income and education have the greatest impact on the realization of functional activities [15]. In the process of level evaluation of individual life, first of all, it not just confined to the income and other basic goods and services, and more emphasis on individual heterogeneity and environmental diversity characteristics of multi-dimensional factors to transformation of functional vectors under the condition of the same income [16]. Secondly, the individual choice preference and the overall decision-making level are restricted by the key factors such as the multidimensional characteristic factor. And it further affects the transformation process of functional activities that have been realized by many functional vectors. Finally, Sen’s feasibility analysis framework studies the dialectical relationship between capability and function. Functional activities represent the level of living that has been achieved, while the set of viable capabilities reflects the potential of living standards that are potentially achievable. Sen pointed out that the welfare level of individuals is directly related to their actual living standards, so it is reasonable to focus on functional activities. But the welfare level is closely related to the individual ability, although the actual life is very important, the ability to make free choice also has important value [17]. Using the welfare set fa; wðAÞg to express, A represents the person ability, wðAÞ represents the welfare level, a represents the actual living standard, When the ability set fa; bg chooses the standard of living for a, and when the ability set is fag, the living standard is different from the welfare level wðAÞ corresponding to a. In addition, Sen pointed out that, in terms of the maximization of welfare level and given the uncertain conditions, the functional activities focused on realization and focusing on potential feasible capability sets are equivalent [18] (Fig. 2).
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Feasible capacity set
Goods and services
Acquired functional activities
Feature vector
Conversion
Personal heterogeneity Social and cultural Characteristic factor
Choose
Fig. 2. Feasibility analysis method
Under the framework of feasible capability analysis, the poverty phenomenon is not only limited to low income, but also the deficiency of individual feasible ability. As shown in Fig. 3, the income is an important factor of poverty measurement, but the cause of the individual poverty also include other factors such as health, level of education, while these factors constitute the ability of the feasible set. On the one hand, the lack of some abilities in the collection and low income is affected by some external factors, such as social role and geographical factors. On the other hand, the relationship between the income level and the set of feasible ability is the cause and effect of each other [19]. For example, factors such as individual age and gender will reduce their income, and a decline in relative income means a lack of absolute practicability. For example, people with relatively low incomes in developed regions, although their income level is higher than the overall average, will spend more income to achieve the same social functional activities.
External factors
Final result Methods Low income
Essence Poverty
One of the dimensions
External factors
Fig. 3. The feasibility of the deprivation theory
Feasible deprivation
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Utility Analysis of Welfare Based on Feasible Capability Framework
The analysis of the welfare utility of peasant households on the transfer of homestead will be compared from the perspectives of welfare economics and feasible capacity analysis, and further measure the welfare changes of farmers in poor areas. First of all, from the perspective of welfare economics, it is possible to use social welfare function to analyze whether Pareto optimality is realized by constructing utility model. A set of continuous utility functions ui that satisfy the consumer’s preference 1 2000 Café 6.96 2016 Croquet Area 4.79 1996 Library 2.79 2001 BBQs 0.76 Low 2001 Bus 0.17 value < 1 2008 Club room 0.13 2007 Community 0.12 1997 hall Computer 0.00 Zero 2015 room/senior’s value internet kiosk Gym 0.00 2017 Indoor 0.00 1997 bowling green Table tennis 0.00 2016
4000 10000 5000 2000 10000 550 85000 200000 300000
Maintenance cost/month ($)
Average charge residents WTP ($)
Total number of residents visits/month
3.33 8.33 4.2 80 8.33 10 250 600 250
10 18 10 2 2 1 5 3 10
7 6 4 30 8 3 10 77 83
0
0
0 0
0 0
0
0
40000 40
100000 83.33 1000 1 Donated 0
Based on the VEM, the values of these facilities to the residents are either greater or less than 1, or equals to zero (Table 1). In VE analysis, the value of an item or facility is highest (at maximum) when it is equal to 1 (Loveless 1986). A value greater than 1 means that the cost invested in an item or a facility is lower compared to the function.
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Thus, more value can be added to the beneficiaries, but at the same time creates an opportunity to increase the cost charged to the beneficiaries for accessing the item or facility (Wao et al. 2016). A value less than 1 suggests that more cost is invested in an item or a facility compared to the function. As a result, there is need to either reduce the cost or increase the function of the facility in order to maximise value (Wao et al. 2016). In sum, the opportunity to carry out VE analysis is for the item or facility whose value is greater or less than 1. A zero value then suggests that an item or a facility has neither significant function to the beneficiaries nor cost to the providers. High value facilities As shown in Table 1, there are five facilities with values greater than 1. Of this category, the chapel has the highest value to the residents (V = 34.82). The chapel is a place of Christian worship. The exceedingly high value of the chapel can thus be attributed to the religiosity of the case study whose residents are more likely to be Christians that engage in regular Christian worship. However, with such a high value, and a paltry initial and maintenance cost of this facility, there is enormous room to increase the cost of this facility without undermining the function to the residents. The analysis reveals that the respondents are willing to pay an average of $10 for the use of this facility. Following the chapel is the hair salon with a high value of 12.18 to the residents. The function of the hair salon to the residents is for regular hair care and treatments. Hence, the value of this facility to the residents suggests that they can pay more for its function on one hand. Based on the analysis, the cost to respondents in the case study should be at least $18. On the other hand, paying this amount or more will mean that the function of the facility is commensurate with its cost. In reality, hair salon in RV requires an expert hair dresser who is usually outsourced for a required payment or salary (Lederbauer and Matthews 2016), and as a result, residents pay more for it (Xia, Zuo et al. 2015a). The next facility is the café with a value of 6.96 to the residents. Bernard et al. (2012) state that where this facility is offered, it has the potential to be the focal point for residents where they meet with friends to dine and drink. In corroboration, the analysis reveals that the respondents are willing to pay an average of $10 for the use of this facility (Table 1). Therefore, the value of the café to the residents can be attributed to its potential to provide an avenue for socialisation (van der Vliet 2016). The next facility of value greater than 1 to the respondents is the croquet area (V = 4.79) which is an indoor game where two or more people can use mallets to hit wooden balls through small metal hoops fixed into the grass. More than any other facility in this category, the analysis reveals that the respondents visit this facility 30 times in a month, and are willing to pay $2 per visit. According Xia, Skitmore et al. (2015a), the provision of this facility is characterised of a RV with large outdoor area. More importantly, previous studies reveal that the value of the croquet area to the residents is that it facilitates interaction among them (Evans 2009; Means and Evans 2012). The last facility in this category is the library with a value of 2.79 to the respondents in the case study. Library is commonly provided in both not-for-profit and for-profit RV for residents to engage their minds by reading different publications (Towart 2017), and similar to the croquet area, this facility is of value to residents because it enables
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them to interact and relate among themselves (van der Vliet 2016; Xia, Zuo et al. 2015b). The respondents in the case study visit this facility 8 times in a month and willing to pay an average of $2 per visit. In sum, as the facilities in this category are of low initial and maintenance costs to the providers, but of high function to the residents, then there is huge opportunity to maximise their value. Low value facilities The second category comprises those facilities whose value to the residents is less than 1. As revealed in Table 1, these facilities include BBQ, bus, and club room and community hall in descending order of value to the respondents. The barbecue appliance is for an outdoor meal, meat and fish for residents. Often in Australia, the use of this facility is symbolic of an occasional and mild social gathering by friends or families. Hence, the value (V = 0.76) lies in fostering social connection among RV residents (Stimson and McCrea 2004). However, being an occasionally used facility, respondents in the analysis only visit this facility 3 times in a month and willing to pay a paltry of $1 per visit. The function of the bus is for regular trips to nearby commercial/retail facilities (Towart 2017; Xia, Skitmore et al. 2015a), and thereby helping the residents to connect with their neighbourhood (Hu, Xia, Buys et al. 2017). To the RV residents, a bus transport is regarded as care support service to address their limited mobility to locations of choice as a result of old age (Stimson and McCrea 2004; Xia et al. 2014). Therefore, the value of a bus to the residents is of transportation, connection and care. However, the analysis shows that the respondents in the case study are not deriving this value (V = 0.17) at the maximum level. Therefore, optimising the value of this facility for the residents is necessary, by limiting the maintenance cost and charging less than $5 for its use. This suggestion has the tendency to increase the number of times residents use the facility. The values of both the club room and community hall to the residents are lesser than expected at V = 0.13 and 0.12 respectively. This is unexpected because the community hall is normally regarded as the heart of the RV (Hu, Xia, Skitmore et al. 2017), and can be found in most RV (Xia, Skitmore et al. 2015a; McDougall, Barrie and Lange 2017). Where the club house is separate from the community hall, both uses are almost similar. From the interview, the facility manager mentioned that the club house is additionally used by the residents for morning tea, birthday celebrations, board games, bible study and singing practice, all of which help to limit loneliness and increase social connectivity (Gray and Worlledge 2016). Therefore, the opportunity to increase the value of these facilities is not to increase their functions. For these facilities, the alternative option to lessen their initial and maintenance costs may not be plausible. This study is suggesting that either of community hall or club house should be provided in RV due to similarities in their functions. Zero value facilities The third category covers those facilities with zero value. They include the gym, computer room/internet kiosk, indoor bowling and the table tennis. With the exception of the table tennis that was donated, the analysis reveals both the initial and maintenance costs are incurred on these facilities, but without commensurate function. The respondents would neither visit these facilities nor be willing to pay to access them. From the interview, the facility manager mentioned that the gym was recently procured
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in the middle of 2017, and as a result, the respondents may not yet be accustomed to its functionality. In addition, these respondents may have found gym to be luxury to them (Crisp et al. 2013). The respondents are above 70 years of age, and according to Gray and Worlledge (2016), old people of this age bracket would not use computer/internet related facilities, due to lack of know-how and appropriate support (Means and Evans 2012). Hence, this is the likely reason why the respondents would not visit nor willing to pay to access the computer/internet facilities, which by extension, means it is of no function to them. For the RV residents of lower age bracket who do not have their own personal/mobile computer appliances, it is still important to provide computer/internet facilities for this category to prevent loneliness (Gray and Worlledge 2016) and promote social interaction and community belonging (Means and Evans 2012). Finally, both the indoor bowling and table tennis are sport-based facilities that require agility and strength to use them. At age 70 and above, the respondents are not in strong and agile physical state to use such facilities. Instead, and at such age, the analysis reveals that the respondents are satisfied with the less physically demanding croquet area sport activity which is at high value to them (V = 4.79).
5 Discussion and Conclusions This study has explored optimal strategies on facilities provision in the not-for-profit RV for the developers to meet the residents’ facility requirements within budget constraints. This study is based on the theoretical framework of VE, which defines the concept of value as the ratio of the function to cost of facilities to RV residents. Function is expressed as the product of the frequency of use and willingness of residents to pay for a facility, while the cost is expressed as the estimated cost for providing the facilities over a lifetime period by the developers. A VEM is developed to operationalise these parameters. The VEM is therefore demonstrated in a case study that utilises both interview and survey methods of data collection in a not-for-profit RV in Queensland, Australia. The demonstration is expected to help developers to optimise to determine and provide facilities that are of value to residents under budget constraints. In descending order, the analysis reveals that the values of chapel, hair salon, café, croquet area and library to the residents are greater than 1. Therefore, from VE perspective, more value can be added to the residents through the provision of these facilities. For the developers, these facilities should be accorded top priority in the face of budget constraints. The analysis further reveals that the values of barbeque appliance, bus, and club room and community hall to the residents are less than 1. Therefore, while these facilities can be provided if there is enough budget, the providers need to ensure that they are provided at low costs. This can be ensured by both procuring them at low costs and also keeping their maintenance costs very low. Alternatively, the providers need to increase the functions of these facilities to the residents. For both categories, the value of the facilities are experienced by the residents in terms of religious participation, care, social interaction, physical engagements and mobility. Therefore, this study reinforces the RV as the viable housing option that satisfies the living requirements of old people in terms of independence, socialisation, and health
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care and improved quality of life. Through this, this study links the body of knowledge of value engineering to that of housing for old people. To explore and develop this link further, the VEM can be employed to identify the facility requirements for old people in different types of housing options. The third category are facilities such as computer room/internet kiosk, gym, indoor bowling and table tennis that are of zero value to the residents. Theoretically, the providers should not provide these facilities whether there is adequate budget or not. This study is of primary benefits to the not-for-profit RV developers. They can prioritise the facilities provision for the residents in their villages. In addition, this study provides practical implications to enabling them to add value of facilities to residents in their villages either by increasing functions or reducing costs. Furthermore, by following the VEM model proposed in this study, they can optimise facility provision when undertaking new village development. As a result, more RV can be developed at cheaper cost but more value to residents. This study can be used by the retirement village industry to inform relevant stakeholders including developers and policy makers to inculcate the concept of value in the programs targeted at developing the industry. Researchers in the fields of VE and ageing can also use this model (or modify it) to explore the concept of value in the context of housing for old people. Nevertheless, this study also suffers a number of limitations with the primary one as the limited data used. It includes an interview of a facility manager and survey of 13 respondents. While this can affect the generalisation of findings, this study is still applicable to other residents in the case study due to the random method of sampling. In addition, this study is a demonstration of how to optimise facilities provision in the not-for-profit RV under budget constraints. Thus, other not-for-profit RVs can follow the process demonstrated in this study. For instance, these villages can select different facilities that have different initial and maintenance costs, and different discounting rate. Further research should seek to build on this limitation, mainly to use more data and cover more villages.
References Baldwin, R.J., Kelly, J., Dixon, T., Witham, H.: The Future of Housing for Older Australians Position Paper (2015) Barrie, H.: Retirement villages capitalise on aged care changes. Aust. Ageing Agenda (Jul/Aug 2017), 18 (2017) Bernard, M., Liddle, J., Bartlam, B., Scharf, T., Sim, J.: Then and now: evolving community in the context of a retirement village. Ageing Soc. 32(1), 103–129 (2012) Bhattacherjee, A.: Social Science Research: Principles, Methods, and Practices (2012) Bohle, P., Rawlings-Way, O., Finn, J., Ang, J., Kennedy, D.J.: Housing choice in retirement: community versus separation. Hous. Stud. 29(1), 108–127 (2014) Crisp, D.A., Windsor, T.D., Butterworth, P., Anstey, K.J.: What are older adults seeking? Factors encouraging or discouraging retirement village living. Australas. J. Ageing 32(3), 163–170 (2013) Cummins, C., Johanson, S.: Retirement ownership in for a shake-up. Accessed 20 Nov 2017. http://www.smh.com.au/business/property/retirement-ownership-in-for-a-shakeup-20170831gy89mg.html
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Davy, L., Bridge, C., Flatau, P., Judd, B., Morris, A., Phibbs, P.: Age-specific housing and care for low to moderate income older people. Positioning Paper. Australian Housing and Urban Research Institute, Melbourne (2010) Elias, S.E.G.: Value engineering, a powerful productivity tool. Comput. Ind. Eng. 35(3–4), 381– 393 (1998) Evans, S.: ‘That lot up there and us down here’: social interaction and a sense of community in a mixed tenure UK retirement village. Ageing Soc. 29(2), 199–216 (2009) Evans, S., et al.: A community hub approach to older people’s housing. Qual. Ageing Older Adults 18(1), 20–32 (2017) Gray, A., Worlledge, G.: Addressing loneliness and isolation in retirement housing. Ageing Soc. 1–30 (2016) Gustafsson, J.: Single case studies vs. multiple case studies: a comparative study (2017) Hu, X., Xia, B., Buys, L., Skitmore, M.: Availability of services in registered retirement villages in Queensland, Australia: a content analysis. Australas. J. Ageing (2017) Hu, X., Xia, B., Buys, L., Skitmore, M., Kennedy, R., Drogemuller, R.: Stakeholder analysis of a retirement village development in Australia: insights from an interdisciplinary workshop. Int. J. Constr. Manage. 15(4), 299–309 (2015) Hu, X., Xia, B., Skitmore, M., Buys, L.: Providing a sustainable living environment in not-forprofit retirement villages: a case study in Australia. Facilities (2017) Jayawardena, C., et al.: Deployment of a service robot to help older people. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5990–5995. IEEE (2010) Judd, B., Liu, E., Easthope, H., Bridge, C.: Retirement village or the general community? Downsizing choices of older Australians. In: State of Australian Cities Conference (2015) Lederbauer, G., Matthews, J.: Retirement village lifestyle. Soc. Altern. 35(3), 61 (2016) Lotvonen, S., Kyngäs, H., Koistinen, P., Bloigu, R., Elo, S.: Social environment of older people during the first year in senior housing and its association with physical performance. Int. J. Environ. Res. Public Health 14(9), 960 (2017) Loveless, B.K.: Value engineering in the construction process (1986) McAuliffe, B.: Resident-funded retirement village valuations: complications with the application of the DCF. Aust. N.Z. Property J. 2(8), 485–493 (2010) McAuliffe, B.: Valuation methods for resident funded retirement villages in Australia: a practitioner’s perspective. In: Proceedings of the 16th Annual Conference on Pacific Rim Real Estate Society (PRRES), pp. 1–10. Pacific Rim Real Estate Society (PRRES) (2010b) McDougall, K., Barrie, H., Lange, J.: South Australia Retirement Village Survey 2016 (2017) Means, R., Evans, S.: Communities of place and communities of interest? An exploration of their changing role in later life. Ageing Soc. 32(8), 1300–1318 (2012) Nathan, A., Wood, L., Giles-Corti, B.: Perceptions of the built environment and associations with walking among retirement village residents. Environ. Behav. 46(1), 46–69 (2014) Pant, P.: How Much Should You Budget for Home Maintenance? Accessed Nov 20. https:// www.thebalance.com/home-maintenance-budget-453820. 2017 Stafford, R.Q., et al.: Improved robot attitudes and emotions at a retirement home after meeting a robot. In: RO-MAN, IEEE, pp. 82–87. IEEE (2010) Stara, V., Felici, E., Di Rosa, M., Olivetti, P., Rossi, L.: Multifaceted factors that influence the housing decision-making process: a pilot study with older adults. J. Gerontol. Geriatr. Res. 6 (441), 2 (2017) Stimson, R.J., McCrea, R.: A push–pull framework for modelling the relocation of retirees to a retirement village: the Australian experience. Environ. Plann. A 36(8), 1451–1470 (2004)
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Design of “Point Spirit” Cultural Heritage Protection Mobile Platform Based on LIDAR Jie Zhao, Mengtian Cao(&), Shufang Wu, and Zhigang Wu School of Tourism Management, South China Normal University, Guangzhou, China [email protected]
Abstract. As the valuable wealth of a country, cultural heritage is the symbol of strengthening the cultural confidence and promoting the social and cultural prosperity, so it is particularly important to enhance the protection and inheritance of cultural heritage. With the continuous development of digital technology, it plays a significant role in the protection, restoration and utilization of cultural heritage. Therefore, through the analysis on the current status of the application of LIDAR technology in the protection of cultural heritage at home and abroad, this paper adopts Internet technology to independently develop the “point spirit” mobile platform of cultural heritage protection. With the functions of point cloud angle measurement, distance measurement and area measurement, the platform can also conduct color rendering in accordance with the attributes of point clouds to present different display effects. Enriching the digital protection of cultural heritage in theory and practice. This provides new technical methods for the establishment of the original database of cultural relics and historic sites and the protection practice of cultural heritage. Keywords: LIDAR Cultural heritage GIS platform “Point spirit”
Protection and inheritance Mobile
1 Introduction Cultural heritage is the valuable wealth of a country. As an important part of the national cultural development strategies, protecting cultural heritage is the protection of the nation’s cultural gene and spiritual home as well as a crucial method of implementing the national cultural strategies [1, 2]. UNESCO adopted “Convention Concerning the Protection of the World Cultural and Natural Heritage” and “Convention for the Safeguarding of the Intangible Cultural Heritage” in 1972 and 2003, respectively, and the protection and inheritance of cultural heritage has become a hot topic in the world. With the development of various high and new technologies, digital technology has pointed out new directions for the protection, preservation and interpretation of cultural heritage [3]. Foreign scholars mainly conduct the research on cultural heritage protection from digital storage, restoration, dissemination, virtual technology and many other technical levels [4–6]. However, domestic scholars primarily use texts, audio recordings, video recordings, digital multimedia and other methods to truly, © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1237–1245, 2021. https://doi.org/10.1007/978-981-15-3977-0_95
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systematically and comprehensively record cultural heritage and establish the archives and databases, to achieve the data inheritance of cultural heritage [7]. At the same time, the Chinese government has issued the relevant plans to identify the importance of the realization of the protection, restoration and utilization of cultural heritage by means of high-tech means. For example, in December 2016, the “13th Five-Year Plan” clearly put forward that it is necessary to focus on the four key directions of value recognition, protection restoration, inheritance utilization and public cultural service of cultural heritage, and it is planned that the scientific and technological innovation system of cultural heritage and public cultural service in China will be basically established by 2020 [8]. In recent years, domestic and foreign scholars believe that LIDAR technology is one of the finer and quicker methods of cultural heritage protection. It can provide extremely dense 3D points on the surface of high-precision objects, and threedimensional models and digital orthophoto images can be quickly generated by using these 3D point clouds and digital images [9, 10]. Therefore, LIDAR technology can play a crucial role in the display of cultural relics, accurately record the 3D data and be conductive to the restoration and protection of cultural relics. Hence, firstly, through reviewing the domestic and foreign scholars’ research on the application of LIDAR technology in the protection of cultural heritage, combined with Internet technology, this study independently develops the “point spirit” mobile platform of cultural heritage protection. Meanwhile, it establishes the fine original database of cultural relics and historic sites, which plays an important role in repairing the damaged cultural relics and buildings. Furthermore, it uses a more convenient way to realize the overall 3D modeling of cultural relics and historic sites as well as the measurement of color, angle, height and area of local areas, so that relevant scholars specializing in urban planning and cultural relic protection can more conveniently use data and more rapidly obtain relevant geographic data, and users can have new experiences. This provides new technical methods for the practical application of the protection and inheritance of cultural heritage as well. It not only deepens the application of digital technology in protection of cultural heritage, but also strengthens the in-depth study of LIDAR.
2 Research on the Application of Lidar in Cultural Heritage Protection 2.1
Application of Ground Lidar in Cultural Heritage Protection
At present, in terms of the digital protection and renovation design of ancient buildings, some scholars have put forward the use of LIDAR to make the digital orthophoto maps of ancient buildings, so as to truly reflect the original appearance of ancient buildings [11]. Some scholars have also proposed a scheme for the rapid 3D reconstruction of ancient buildings with the help of laser scanners and digital cameras [12]. He Bin, et al. have argued that the traditional repair methods cannot meet the needs of the renovation of ancient buildings at the present stage, discussing the basic principles, operation
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processes, main errors and important issues of Ground LIDAR technology [10]. Some researchers have used the ground laser scanner to conduct the comprehensive scanning measurement of Zhenbeitai Fortress, “the first fortress of the Great Wall”, completely recording the 3D spatial characteristics of Zhenbeitai Fortress. At the same time, they have carried out the detailed scanning of the local cultural relics in Zhenbeitai Fortress and obtained the 3D model and various line drawings [13]. It can be seen that the 3D model constructed by Ground LIDAR can accurately record the 3D data without contact with cultural relics, so as to play a significant role in the restoration of cultural relics in the future. 2.2
Application of Airborne LIDAR in Cultural Heritage Protection
When the protection and study of heritage was conducted through optical remote sensing, the impact of the covering, etc. on the extraction of spatial information of cultural heritage needed to be solved urgently, so Airborne LIDAR technology has emerged. LIDAR has a penetration effect on vegetation and other coverings and can quickly acquire the abundant information of the ground objects under the covering. At the same time, it can accurately monitor the vegetation coverage of heritage sites, so that researchers can understand the degree of environmental destruction of heritage sites [14]. The accurate segmentation of the top area of the building is the key to the 3D reconstruction of the building in Airborne LIDAR point cloud data. Yu Haiyang et al. have used LIDAR point cloud data vector analysis, curvature calculation and other methods to carry out the LIDAR point cloud data segmentation of the top area growth of the building and further deal with the 3D model of the reconstructed building. Aiming at the shortcomings of traditional measurement, such as substantial time consumption, considerable labor consumption and poor access to the precise side information of the ancient city wall [15], Wang Yajun et al. have proposed the point cloud extraction algorithm of the top and side of the city wall of “horizontal detection longitudinal detection” based on the wall section as well as the technical scheme of “the extraction of the candidate area of the city wall - the construction of the grid of the section - the extraction of the point clouds of the top and side”, so as to effectively overcome the difficulty in point cloud segmentation caused by the special spatial form and complex point cloud structure of the city wall and realize the automatic extraction of Airborne LIDAR point cloud data of large areas [16]. It can be seen that Airborne LIDAR technology has a vital significance for the management and protection of cultural heritage, and through continuous improvement and breakthroughs, it has been successfully applied with the unique advantages of high efficiency and high precision. 2.3
Application of Other LIDAR in Cultural Heritage Protection
The protection of cultural heritage usually requires the application of highly interdisciplinary and comprehensive technology. Fluorescent LIDAR has been successfully applied in the detection and identification of phytoplankton in seawater, especially the assessment of forest degradation. At the same time, it can also be used to identify the
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specific areas that require further analysis measurement or laboratory analysis sampling [17]. In addition, the scanning LIDAR device plays a crucial role in the laboratory’s involvement in the restoration of antiques in Europe and the restoration of related wall paintings of certain cultural heritage in southern Italy. This technology can show the biodegradation of different microorganisms through scanning images of different spectral channels, so as to use different repair technologies to carry out the restoration of cultural relics [18]. Through the application of the integrated 3S technology in LIDAR data, some scholars have sampled the Roman gold field in northwestern Spain with the help of UAV-assisted photography, exploring and comparing the influences of digital elevation model (DEM) and different collection methods, resolutions and precisions on archaeological remain analysis. Eventually, through reconstructing the 3D virtual model of the selected feature area, the archaeological records are presented to the public in different ways [19]. Thus, in addition to Ground LIDAR and Airborne LIDAR, LIDAR technology can be organically integrated with other technologies to provide important assistance for the protection of cultural heritage and the restoration of cultural relics. This study combines ground LIDAR data and airborne LIDAR data, and innovatively develops “point spirit” software to achieve in-depth application of LIDAR.
3 Methods The “point spirit” mobile platform of cultural heritage protection is based on B/S mode, using LIDAR, WebGL, GPU and other technologies to achieve smooth browsing on PC terminals or mobile terminals. The system principle is shown in Fig. 1. The first stage is the stage of data preprocessing. Firstly, LIDAR equipment is used to collect the point cloud data; secondly, the point cloud data are sliced and layered by the quadtree network cutting, to make the browsing and loading of data smoother and more lay the foundation for the later layered rendering; finally, the server terminal is set with the help of Internet Information Services (IIS), to prepare for the later browsing. The second stage is the stage of data browsing and application. This stage mainly uses WebGL technology to call the graphics card GPU on the browser terminal for 3D display. Meanwhile, on the one hand, the efficient data structures and algorithms are developed, and huge point-based model is presented in a way that allows high speed or saves flows; on the other hand, lighting and rendering algorithms are used to improve the look and feel of the model and optimize the user experience. Through the above design, “point spirit” can be widely used in cultural relic protection, building restoration, 3D measurement, digital ground model production, urban planning and other fields.
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Fig. 1. Schematic diagram of “Point Spirit” systematic principle
4 “Point Spirit” Cultural Heritage Protection Mobile Software Design 4.1
“Point Spirit” Software Principles
This study designs and develops Flisionpointspirit, which is the point spirit software, using the 3D display technology based on WebGL to carry out the 3D rendering of the massive laser point clouds. Through the software, the massive laser point cloud data are sliced and layered, so that the users can roam the point cloud echo data acquired by various types of ground laser scanners and airborne laser scanners in the 3D visualization environment. The browsing terminal can be a PC browser or a mobile terminal. Browsing speed is not affected by the number of point clouds, and within the limits of the uplink and downlink speeds of the normal 4G network, the loading, uploading, roaming, measurement and other functions of point clouds are smooth and without time delay. With the functions of point cloud angle measurement, distance measurement and area measurement, the software can also conduct color rendering in accordance with the attributes of point clouds to present different display effects. 4.2
“Point Spirit” Software Function
The first major system function of the point spirit software is the browsing of the massive laser point clouds. From Fig. 2, it can be seen that it can provide users with the 3D large scene browsing of laser point clouds, allow users to experience different browsing feelings and obtain diversified geographic information from a variety of browsing methods. The second major function is the measurement of laser point clouds
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Fig. 2. Massive laser point cloud browsing system interface
Fig. 3. Laser point cloud distance measurement system interface
including distance measurement, angle measurement and area measurement (Fig. 3). The third major function is the layered color rendering of attributes. It can be seen from Fig. 4 that point spirit can carry out different rendering display according to the threshold range of the classification, elevation and other information of point cloud data, which is conducive to distinguishing different types of ground objects. Besides, the point spirit software also has the basic functions, such as uploading and downloading of massive point cloud data files.
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Fig. 4. Attribute hierarchical color rendering system interface
4.3
“Point Spirit” Software Advantages
The “point spirit” mobile platform of cultural heritage protection is a mobile platform that can realize browser publishing, measurement and point cloud data application in B/S mode, and it achieves the smooth visualization effect of the massive point clouds through multi-threading technology, parallel computing, GPU and other strategies, so that computers and mobile phones can realize the scheduling management and realtime visualization of the massive laser point cloud data. The purpose is to build a 3D visualization processing platform of point cloud data, which can be extended to mobile websites, APPs and other platforms for professionals, scientific researchers, tourists and other groups, so as to provide a complete solution for massive point cloud data sharing, realize the real-time monitoring and protection of cultural heritage and provide the carrier for the propaganda, education, inheritance and development of cultural heritage.
5 Conclusions and Discussions The research conclusions are as follows: firstly, through the analysis on the relevant research dynamics of the application of LIDAR technology in cultural heritage protection at home and abroad, it can be seen that Ground LIDAR technology will become one of the finest and quickest methods of cultural heritage protection, whereas Airborne LIDAR technology and other LIDAR technologies play an increasingly important role in the protection of cultural heritage as well; secondly, through the independently-developed “point spirit” software, WebGL technology is adopted to achieve the comprehensive scanning of the façades of cultural heritage, and the point cloud data of ground laser scanners and airborne laser scanners are effectively obtained by slicing and layering the laser point clouds, while the convenient browsing of PC terminals and mobile terminals as well as the smooth operation of system functions are realized by software design. The software organically combines Ground LIDAR data
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with Airborne LIDAR data, providing the possibility for the realization of the comprehensive digital protection of cultural heritage through the convenient function design. Although, the present research has several limitations. Because of time and funding constraints, on the one hand, the accuracy of massive laser point cloud data needs further research; on the other hand, the system functions are relatively simple at this stage, and the more complete functions require further development. Nowadays, the digital protection of cultural heritage has gradually become one of the most important methods of cultural heritage protection. How to organically combine various LIDAR technologies with other digital technologies, continuously enrich the system functions of the cultural heritage protection platform and realize the entire spatiotemporal and comprehensive protection of cultural heritage will become the key direction of the future research. Acknowledgments. We thank all funding support from the science and technology program in Guangdong province of China (Grant NO. 2017A020220009), the 61st batch of Chinese postdoctoral program (Grant NO. 2017M612683), the south China normal university youth teacher scientific research cultivating fund program (Grant NO. 2016JK102).
References 1. Wang, W.Z., Chen, F.L.: Non-material cultural heritage protection and national cultural development strategy. J. Huazhong Normal Univ. (Humanit. Soc. Sci.) (2), 81–89 (2008) 2. Ma, C.: Protection of cultural heritage and inheritance of tradition: reflections on Korean experience of cultural heritage protection. J. Guangxi Normal Univ. Philos. Soc. Sci. Edn. 45 (1), 13–17 (2009) 3. Refsland, S.T., Ojika, T., Stone, R.: Virtual Heritage: breathing new life into our ancient past Multimedia. IEEE, 7(2), 20–21 (2000) 4. Rusinkiewicz, S., Ttler-Frankln, C.: Matching, Archiving and Visualizing Cultural Heritage Artifacts using Multi-Channel Images. Princetion University, Princetion (2011) 5. Yang, C., Sun, S., Xu, C.: Recovery of cultural activity for digital safeguarding of intangible cultural heritage. In: Proceeding of the 6th World Congress on Intelligent Control and Automation, Dalian, pp. 10337–10341. IEEE (2006) 6. Shi, Y., Hao, J., Sun, S.Q.: The digital protection of intangible cultural heritage-the construction of digital museum. In: Proceedings of 2008 IEEE 9th International Conference on Computer-Aided Industrial Design and Conceptual Design, Kunming, pp. 1196–1199 (2008) 7. Wang, X.G., Jia, B.Q.: The Protection Mechanism of Historical and Cultural Heritage in Other Countries and Revelation for Our Country. Study Ethnics Guangxi 1, 178–185 (2008) 8. Science and Technology, Culture Ministry, State Administration of Cultural Heritage. The National “13th five year” Cultural Heritage Protection and Public Cultural Services Science and Technology Innovation Plan, 2016–12–19 9. Yastikli, N.: Documentation of cultural heritage using digital photogrammetry and laser scanning. J. Cult. Herit. 8(4), 423–427 (2007) 10. He, B., Liu, Y., Zhang, D.W.: Application of three-dimensional laser scanning in repair of ancient buildings. Jinlin Geol. 28(04), 178–181 (2009)
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11. Wang, Y.M., Guo, M., Wang, G.L., Zhao, Y.S., Li, Y.M., Hu, C.M.: Making orthographic images of ancient architecture with LIDAR technique. J. Beijing Inst. Civ. Eng. Architect. 4, 19–22 (2006) 12. Deng, F., Zhang, Z.X., Zhang, J.Q.: Study on three-dimensional reconstruction of ancient buildings by laser scanning and digital camera. Sci. Surv. Map. (2), 29–30+176–177 (2007) 13. Yang, X.F., Xue, Z.Y., Li, H.Q.: Application of ground lidar in antiquity surveying and 3D modeling. Geomat. Spat. Inf. Technol. 34(2), 73–74 (2011) 14. Chase, A.F., Chase, D.Z., Fisher, C.T.: Geospatial revolution and remote sensing LiDAR in mesoamerican archaeology. PNAS 109(32), 12916–12921 (2012) 15. Yu, H.Y., Yu, P.L., Xie, Q.P., Li, N., Lu, X.P.: Building top segmentation with airborne LIDAR point cloud data. Bull. Surv. Map. 6, 20–23 (2014) 16. Wang, Y.J., Cheng, L., Xu, H., Yuan, Y., Li, M.C.: Automatic extraction of city wall in large area of airborne LiDAR data. Sci. Surv. Map. 42(4), 137–140+191 (2017) 17. Cecchi, G., Pantani, L., Raimondi, V., Tirelli, D., Tomaselli, L., Lamenti, G., Bosco, M., Tiano, P.: Fluorescence lidar technique for the monitoring of biodeteriogens in cultural heritage studies. Remote Sensing (2016) 18. Aristipini, P., Colao, F., Fantoni, R., Fiorani, L., Palucci, A.: Scanning lidar fluorosensor for cultural heritage diagnostics. In: International Conference on Lasers Applications and Technologies (2006) 19. Fernández-Lozano, J., Gutiérrez-Alonso, G.: Improving archaeological prospection using localized UAVs assisted photogrammetry: an example from the Roman Gold District of the Eria River Valley (NW Spain). J. Archaeol. Sci. Rep. (2016)
Discovering Spatial Interdependencies from Mobile Phone Data and Transportation Data: Evidence from Guizhou Province F. J. Long1,2, L. F. Zheng2(&), and L. Shi2 1
2
Guizhou Institute of Technology, Guiyang, China [email protected] Department of Construction Management, Tsinghua University, Beijing, China [email protected]
Abstract. With the continuous urbanization of China, more and more attention has been paid to the balanced development of different regions at all levels, which demands that the government clarify spatial interdependencies before making plan. Previous studies focused more on information or physical space, and few studied the interaction between them. From a new perspective, this paper involves mobile phone data and transportation data in discovering interdependencies between different regions in the context of information space and physical space. First, we establish two networks composed of 81 counties in Guizhou province. Next, both the physical connection and the information connection between these counties are clarified by measuring the call flow and traffic flow in each network. The 81 counties are then divided into several communities according to the complex network theory. The results break through the administrative division and truly reflect the hierarchy and spatial structure of the urban network system of Guizhou province. The correlation between traffic and information connection is also presented, and we confirm that the attenuation with distance of information flow is significantly smaller than the traffic flow. As an attempt to analyze the interdependencies between different regions with big data, the general framework of our research can be extended to a larger scope if the data are available. Keywords: Spatial interdependencies Mobile phone data data Urban network system Complex network theory
Transportation
1 Introduction With the proposal of “National new urbanization plan (2014–2020)”, the process of urbanization in China has reached a new stage. This new urbanization emphasizes the coordinated development of different regions, which means that we should pay the same attention to the development of small cities and counties as we do to big cities. Small cities and counties could hardly develop without the driving role of big cities in the current China [1]. The segmented governance system based on administrative divisions in China sometimes hinders the coordinated development of different regions and is not conducive to the optimal allocation of resources. That is why we shall clarify © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1246–1255, 2021. https://doi.org/10.1007/978-981-15-3977-0_96
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the spatial interdependencies and structure of the urban network system before making development plans. As a classic research concept of urban geography, the urban network system mainly arrives from a hierarchy structure, spatial structure and function structure [2]. There are two popular methods of researching the spatial structure of the urban network system. The first is normally based on the gravity model and its derivative models, while the second one is normally based on the flow of people, goods and capital [3–7]. The second method, which originated from the theory of space of flow proposed by Castells [8], can reflect the connections in the system more intuitively when compared to the first method. With the construction of transport infrastructure in recent years, the speed and capacity of material flow such as the flow of goods and labor resources between different regions of China have been greatly promoted [9–11]. Meanwhile, the highly developed communication network has led to increasing socio-economic interdependencies between different regions [12, 13]. However, the research based on such types of method was often limited by the unavailability of data. Fortunately, in the age of big data, the applications of multivariate heterogeneous data make it possible to perceive the connections between regions directly through the senses. In this paper, we attempt to use the mobile phone data and transportation data to measure call flow and traffic flow in the urban network system of Guizhou province. By incorporating the complex network theory, 81 counties in Guizhou Province are divided into several communities. The correlation coefficient of two kinds of flow is also calculated based on the quadratic assignment procedure to reveal the relationship between the information connection and traffic connection. The paper is organized as follows. In Sect. 2, we introduce the data and study methods we adopted. Section 3 describes the results of our research and discusses what we find. The viewpoints and meanings of this paper are summarized and highlighted in Sect. 4.
2 Data and Methods 2.1
Data Description and Data Processing
2.1.1 Mobile Phone Data The mobile phone has become one of the main media for people to communicate with each other in recent years. Mobile phone data in this paper refer to the total call duration between the 81 counties in Guizhou Province. The activity of each mobile phone call will be recorded by the mobile operator, including the information of locations of the caller and the receiver and the duration of the call. For our research, all call activities occurring within the area of Guizhou province from April 1, 2017, to April 20, 2017, are gathered statistics by China Mobile Communication Corporation, who accounts for nearly 70% of the market share in Guizhou province. This makes the data we use close to covering the full sample. The format of the statistical data provided by China Mobile is shown in Table 1. All mobile activities within the urban area of Guiyang city from December 3, 2016, to December 11, 2016, are recorded in the data. In total, there are 2 billion pieces of mobile signaling data, 271.9 GB in the aggregate, which warrants the name big data.
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Each piece of data includes the following parameters (see Table 1): 1) the processed constant ID number (for privacy issues) of mobile subscribers; 2) the code of the city in which mobile activities occur (“851” refers to Guiyang city); 3) the unique ID number of the mobile base station and its longitude and latitude; 4) the start time and duration of a mobile activity; and 5) the types of mobile activities, including call, 4G and GPRS. Table 1. The format of the statistical result by China Mobile Location_caller Location_receiver Number Total duration of the call of the call (sec.) Anlong Anlong 3499607 264390545 Anlong Anshun 6875 891694 Anlong Bijie 1677 414049
2.1.2 Transportation Data Transportation data in this paper refers to the traffic volume of the expressway among 81 counties in Guizhou province. The total mileage of expressway in Guizhou province reached 5,100 km by the year of 2015, allowing the expressway to connect all the counties. The data also record the name of both entrance toll station and the exit toll station for each vehicle, which clarifies the two endpoints of each traffic flow and avoids errors caused by the middle points. The format of the raw transportation data provided by transport department of Guizhou Province is shown in Table 2. There are a total of 4 GB and 1 million pieces of data. Generally, the data we use deserve the name big data. Table 2. The format of raw transportation data Vehicle_id
Vehicle_type
xxxxxxx
Class 1
Entrance toll station Anlong
xxxxxxx
Class 1
Chishui
Entrance time 2017/4/13 17:02 2017/4/17 10:51
Exit toll station Bijie Guiyang
Exit time 2017/4/13 22:33 2017/4/17 15:17
2.1.3 Data Processing After obtaining the statistical results of the total call duration and traffic volume between each county, we transformed them to two 81 81 symmetric matrices. Then, the data were normalized based on the Min-Max normalization. Both the network analysis based on the complex network theory and the correlation analysis based on the quadratic assignment procedure are according to the two normalized symmetric matrices. Privacy issues have drawn increasing public concern in China in recent years. The original plate number was processed to protect the personal privacy of the owner of
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each vehicle. Each vehicle is randomly assigned a constant ID number so that there are no opportunities to extract individual information from the data. 2.2
Study Methods
2.2.1 The Complex Network Theory The world we live in composes of a variety of systems, either simple or complex. Each system normally constitutes a network with the nodes formed by the elements and the edges formed by the relationship between the elements [14]. The complex network theory was developed to study the structure of different types of networks. The key concepts of the theory include nodes, edges, centrality and community. In our research, we regard the county system of Guizhou province as a network. The nodes refer to the counties, while the edges refer to the call flow or traffic flow between each county. The county has more importance when it has more connections with other counties. Therefore, we adopt the concept of centrality of the theory to reflect the importance of each county. According to the theory, community refers to a subset of a network. The nodes of the network can be grouped into sets of nodes so that each community is densely connected internally [15]. Clustering is a process that divides a data set into clusters so that similarities between objects in the same cluster is stronger than that of other objects. The purpose of clustering is to maximize the homogeneity of intra-cluster objects and to maximize the heterogeneity of objects from different clusters [16]. Thus, in this paper, 81 counties in Guizhou province are divided into several communities to reflect the structure of urban network system with clustering method of the complex network theory. 2.2.2 Quadratic Assignment Procedure Quadratic assignment procedure (QAP) is a commonly used method to analyze the similarities of the elements in two square matrices. The method is primarily based on data resampling and randomized testing. QAP is implemented in this paper to discover the correlation between the information connection and transportation connection between different regions. Both the work of network analysis and the work of correlation analysis are done with the assistance of UCINET v 6.415. 2.2.3 Quantitative Analysis We attempt to compare the speed of the decay with the distance of information flow and traffic flow. In the past, many studies analyzed this based on the gravity model, with a single piece of data. As the name suggests, the gravity model is similar to the law of gravity in physics. The flow of information or traffic is proportional to the size of the two regions and is inversely proportional to the distance between the two regions, as shown in Eq. (1). Tij ¼ K
Pi Pj dijb
:
ð1Þ
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where T ij is the gravitational force between two regions. It is expressed in this paper by information and traffic flows. Pi and Pj are the scales of the two regions and we can use indicators such as population and GDP to describe them. d ij is the distance between two regions, and b is the coefficient of distance attenuation. The larger b represents the gravitational force decays with a faster distance faster, and vice versa. The value of b is a focus of attention in the gravity model. Different scholars have different values when conducting different studies. Therefore, we established a regression equation based on the gravity model as shown in function. (2) to compare and analyze the differences in b values between information and traffic flow space. ln volumeij ¼ a þ hlnGDPi þ lnGDPj þ blndij þ dZij þ eij :
ð2Þ
Among them, volumeij is the information flow or traffic flow between county i and county j. Z ij represents other influencing factors, such as ethnic groups and administrative regions.
3 Results and Discussion 3.1
Network Establishment
The first step of network analysis is to build the two networks in the context of either the information space or physical space. According to Sect. 2.2.1, there are a total of 81 nodes representing 81 counties, and (81 80 = ) 6480 edges representing either call flow or traffic flow. The weight of each edge is based on the total call duration or traffic volume. Figure 1 shows the network establishment results. The thicker the line, the stronger the connection between two counties. We only mapped the top 5 or 4 connections of each county to make the network diagram clearer.
Fig. 1. Network establishment: (a) based on the call flow; (b) based on the traffic flow
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Centrality Calculation
As mentioned in Sect. 2.2.1, we adopt the concept of centrality to reflect the importance of counties in the network. The formula to calculate the centrality in this paper is as follows: Ki ¼
n X
xij
ð3Þ
j
where Ki denotes the centrality of node i and xij denotes the weight of the edge that directly connects nodes i and j. In this research, n is 81. The centrality of each county in Guizhou province is calculated with the formula based on the call flow and traffic flow, respectively. The results are divided into 7 grades according to the cluster analysis. As seen in Table 3 and Table 4, Guiyang and Zunyi are the absolute cores in the urban network system with the highest centralities, indicating the dual centers’ structure of Guizhou province.
Table 3. Rank of centrality based on call flow 1 2 3 4
5 6 7
3.3
Guiyang (downtown), Zunyi (downtown) Xingyi, Kaili, Tongren, Zhongshan Zhenyuan, Duyun Shuicheng, Dafang, Anshun, Xingren, Bijie, Anlong, Fenggang, Cengong, Xishui, Dejiang, Dushan, Zhijin, Congjiang, Daozhen, Chishui, Taijiang, Liuzhi, Meitan, Weining, Liping, Qinglong, Rongjiang, Fuquan, Changshun, Jianhe, Pan, Jiangkou, Guiding, Huangping, Sandu, Qingzhen, Songtao, Jinping, Ceheng, Renhuai, Guanling, Weng’an, Zheng’an, Suiyang, Shiqian Sinan, Zhenfeng, Tongzi, Qianxi, Yuping, Pu’an, Jinsha, Majiang, Huaxi, Wangmo, Hezhang, Nayong, Shibing, Pingba Pingtang, Sansui, Libo, Wuchuan, Luodian, Zhenning, Puding, Longli, Xiuwen, Yanhe, Kaiyang, Yuqing, Yinjiang, Leishan, Tianzhu, Xifeng, Ziyun Danzhai, Wanshan
Community Detection
The communities of the two networks are detected based on the clustering method of the complex network theory and with the assistance of UCINET v 6.415 (see Fig. 2). The counties in the same color have closer connections with each other. The results from comparing the administrative division with two community detection results include the followings: 1) As the two centers in Guizhou province, Guiyang and Zunyi are always in the same community, indicating that the connection between the two centers is strong, which is beneficial to the overall development of the urban network system. 2) The difference between the two community detection results is reflected mainly in the middle part of Guizhou province, which shows that the interdependencies
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1 2 3 4
5 6 7
Guiyang (downtown), Zunyi (downtown) Kaili, Tongren, Zhenyuan, Bijie, Yuping, Xingyi, Qingzhen, Zhongshan, Duyun, Shuicheng, Dafang, Anshun, Xingren, Anlong, Fenggang, Cengong, Xishui, Dejiang, Dushan, Zhijin, Congjiang, Daozhen, Chishui, Sinan, Zhenfeng, Taijiang, Liuzhi, Meitan, Weining, Liping, Qinglong, Rongjiang, Fuquan, Changshun, Jianhe, Pan, Jinping, Ceheng, Renhuai, Guanling, Weng'an, Zheng'an, Suiyang, Shiqian Tongzi, Qianxi, Pu'an, Jinsha, Majiang, Huaxi, Wangmo, Hezhang, Nayong, Shibing, Pingba, Jiangkou, Guiding, Huangping, Sandu, Songtao, Pingtang, Danzhai, Sansui, Libo, Luodian, Longli, Xiuwen, Yanhe, Kaiyang, Yuqing, Yinjiang, Leishan, Tianzhu, Xifeng, Ziyun Wanshan, Wuchuan, Zhenning, Puding,
between counties in this part is more complex. 3) Three cities in the western part of Guizhou province are incorporated into one community both in the context of the information space and the physical space, reflecting that there is a close relationship in west Guizhou. 4) Two cities in the eastern part are divided into three or four communities in the context of the information space and the physical space, reflecting that the connections in east Guizhou are relatively loosened. We speculate that the latter two phenomena arise from the ethnic, cultural and linguistic varieties in different parts of Guizhou. The specific reasons warrant further studies.
Fig. 2. Administrative division and community detection based on the (b) call flow; (c) traffic flow
3.4
The Correlation Between the Two Kinds of Flow
We first calculate the correlation coefficient between two original matrices according to the QAP method. The result shows that the correlation between two kinds of flow is positive (0.230). We then construct the non-parametric tests with 5000 random permutations and obtain a distribution of the correlation coefficients. Comparing the correlation coefficient calculated in the first step with the distribution shows that the correlation between information flow and traffic flow is very significant, and the
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significance level of the non-parametric tests approaches 0. Therefore, good traffic commuting is usually accompanied by good information exchanges in most parts of Guizhou province (Table 5). Table 5. Correlation test between the information connection and transportation connection Obs value Significance Average Std dev. Min Max Pearson correlation 0.230 0.000 −0.000 0.019 −0.056 0.122
3.5
Attenuation Rule of the Two Kinds of Flow
We obtain the regression results shown in Table 6 according to the regression model of Eq. (2). Firstly, traffic flow and call flow decrease significantly as distance increases, which is in accordance with Tobler’s first law of geography. Second, we find that the attenuation coefficient b of traffic flow is significantly greater than the traffic flow. The absolute value of the former is approximately 0.6 greater than that of the latter. It shows that geographical distance to the information flow with the development of technology is much less than the flow of passengers and goods. This is in line with our theoretical expectations. Guizhou province invested a large amount of funds to build information infrastructure in recent years, which laid the foundation for the development of the big data industry. It quickly became the big data industry center in China and Asia. In this context, the information links between counties become closer, which
Table 6. Regression results of the gravitational force and distance
Dist_S
(1) Traffic flow −2.578*** (0.0602)
(2) Call flow −1.893*** (0.0277)
(3) Traffic flow
(4) Call flow
(5) Traffic flow −2.198*** (0.0707)
(6) Call flow −1.570*** (0.0303)
−2.552*** −1.638*** (0.0755) (0.0346) GDP_l 0.803*** 0.737*** 0.747*** 0.908*** 0.759*** 0.924*** (0.0434) (0.0196) (0.0561) (0.0211) (0.0576) (0.0214) GDP_f 0.924*** 0.830*** 0.846*** 0.976*** 0.907*** 1.015*** (0.0394) (0.0191) (0.0541) (0.0213) (0.0561) (0.0214) City 0.902*** 1.262*** 1.074*** 1.227*** (0.111) (0.0564) (0.121) (0.0551) Controls No No Yes Yes Yes Yes R2 0.492 0.758 0.560 0.829 0.511 0.821 Obs 3240 3240 3240 3240 3240 3240 Notes: Standard deviations are in parenthesis. *, **, *** indicate statistical significance at 10%, 5% and 1%, respectively. Variable Dist_S is the straight distance between two counties. Dist_R is the distance between two counties based on the road network. City is a dummy that takes value one when two counties belong to the same prefecture-level city. Control variables contain GDP per capita and permanent resident population Dist_R
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plays an increasingly important role in the reconstruction of the urban system. Third, we also found that the traffic and call flow between the counties that belong to a prefecture-level city are clearly greater. This can be seen from the coefficient of the City variable. The counties from the same prefecture-level city are close, with similar living habits and dialect, and communication costs are low.
4 Conclusion Clarifying the actual interdependencies between different regions is becoming more and more important with the rapid urbanization development in China. Traditional studies about the urban network system are often limited by weak data availability. Fortunately, the use of big data makes it possible to show the various types of flow between regions. The main work we have done in this research can be summarized in two parts. First, the hierarchy structure and spatial structure of the urban network system of Guizhou province are discovered both in the context of information space and in the context of physical space. Second, we find that traffic flow and call flow between different regions have a positive impact on each other. Geographical distance hinders the information flow much less than the impediments to the flow of passengers and goods. We would like to regard this paper as an initial discovery of spatial interdependencies based on big data. Further research is required to understand the causal relations of these community detection results. The research originating from this paper can be extended to a larger scope if more data become available. Acknowledgement. This work was supported by the National Social Science Foundation (14AJY012) for funding.
References 1. Zhang, N.N., Gu, C.L.: From geographical space to composite space—the urban space under the influence of information networks. Hum. Geogr. (2002) 2. Gu, C., Pang, H.: Study on spatial relations of Chinese urban system: gravity model approach. Geogr. Res. 27(1), 1–12 (2008) 3. Avgerou, C.: The informational city: information technology economic restructuring and the urban regional process. Eur. J. Inf. Syst. 1(1), 76–77 (1991) 4. Mitchell, W.J.: City of Bits: Space, Place, and the Infobahn. The MIT Press, Cambridge (1996) 5. Yan, X.: Information sector and world urban system. Econ. Geogr. (1995) 6. Kitchin, R.M.: Towards geographies of cyberspace. Prog. Hum. Geogr. 22(3), 385–406 (1998) 7. Rutherford, J., Gillespie, A., Richardson, R.: The territoriality of pan-european telecommunications backbone networks. J. Urban Technol. 11(3), 1–34 (2004) 8. Castells, M.: Grassrooting the space of flows. Urban Geogr. 20(4), 294–302 (1999) 9. Barnett, G.A., Chon, B.S., Rosen, D.: The structure of the internet flows in cyberspace. Proc. R. Entomol. Soc. London 39(7–9), 111–117 (2001)
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10. Sun, Z.W., Zi, L.U., Jun-Liang, H.E.: Research on spatial pattern and organization mechanism of international internet information flows. Hum. Geogr. (2009) 11. Cao, Z.W., Luo Z.D., Geng, L.: Information-flow based comparative research of urbanregion relations—a case study of Ma’anshan and Wuhu. Econ. Geogr. (2013) 12. Zhang, J., Chao Lin, G.U., Jin Kang, D.U., Zhou, Y.K., Gan, M.Y.: Geographical approach to cyberspace—review and prospect. Scientia Geographica Sinica (2000) 13. Graham, S., Marvin, S.: Telecommunications and the City: Electronic Spaces. Telecommunications and the City: Electronic Spaces, Urban Places (2001) 14. Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393 (6684), 440 (1998) 15. Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., Parisi, D.: Defining and identifying communities in networks. Proc. Natl. Acad. Sci. U.S.A. 101(9), 2658 (2004) 16. Newman, M.E.: Fast algorithm for detecting community structure in networks. Phys. Rev. E: Stat. Nonlin. Soft Matter Phys. 69(6 Pt 2), 066133 (2003)
Research Trends of Information Technology Application in Construction Workers’ Behavior Monitoring Gui Ye(&), Ran Lu, Jingjing Yang, and Xiaoyu Tang School of Construction Management and Real Estate, Chongqing University, Chongqing, China [email protected]
Abstract. In construction, about 80%–90% of accidents are associated with workers’ unsafe behavior. It is widely agreed that monitoring workers’ behavior can help reduce accidents, but it would be restrained by the limitation of traditional methods like observation. With the development of information technology, construction safety has been improved by monitoring construction workers’ behavior. A systematic overview of current research would provide consolidated information, including lack of current research and future research direction, for researchers and practitioners. However, there are few such systematic overviews of construction workers’ behavior safety monitoring by information technology. Therefore, this paper reviews previous research in monitoring workers’ behavior in order to understand the current status and tendency of techniques. To be specific, this paper classifies previous studies into three categories: vision-based technology, radio frequency based technology and fusion technology. Several issues on practical application are identified including the negative effect of using cameras to capture workers’ operations and limited types of workers’ unsafe behavior. These challenges indicate that further study in these areas is required. Accordingly, this paper proposes future research directions to enhance the automatic monitoring of workers’ behavior for construction safety. Keywords: Monitoring technology Review
Behavior Construction safety Information
1 Introduction The construction industry is one of the most hazardous industries due to the adverse and changeable work environment [1]. Considering that the accident rate caused by unsafe behavior of workers accounts for about 80–90% [2], enhancing workers’ behavior management is critical to reduce accidents on site. In addition, it is evidential that there is a close relationship between behavior monitoring and accident rates [3]. Obviously, construction safety can be improved through monitoring workers’ behavior, such as spotting helmet-nonuse of the worker, worker-on-foot close to the giant equipment.
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Traditional methods (e.g., feedback, observation) of monitoring workers’ unsafe behavior have some defects, for example, (1) too much time and labor consuming in collecting and analyzing the data [4]; (2) process of data collection leading to deviations in results [5]. These shortcomings contribute to the constraints on empirical application of behavior monitoring. With the development of information technology, the application of information technology–based data acquisition tools or equipment has been widely boosted for workers’ behavior safety monitoring in construction industry. These tools enable the ability to retrieve data, collect data, process data, transmit data and especially store data during the construction project implementation [6]. For instance, Kinect depth senor has been used to collect data about unsafe behavior which could be identified later by machine learning method [7]. Based on the Bluetooth technology, a real-time tracking system has been proposed to check the workers’ usage of helmet [8]. Although the information technology has been regarded as a more advanced approach to improving behavior safety monitoring than traditional methods, there are few such systematic overviews of construction workers’ behavior safety monitoring by information technology. This study, therefore, provides a general review of research related to the information technology implementation in worker behavior safety monitoring. In the following sections, overall research is firstly analyzed, then information technology-based behavior safety monitoring is reviewed, and the trend of related research is identified.
2 Overall Research Analysis Web of Science (WOS) is the largest comprehensive academic information resource in the world. WOS Core Collection is selected as the data source. Research keywords were selected as (construction or building) AND (“unsafe* behavio*” or “safe* behavio*” or “safe* act*” or “unsafe* act*” or “unsafe* motion” or “safe* motion”) AND (identif* or monitor* or recogni* or measure* or detect*), and document type was chosen as “article or review or proceedings paper”. A total of 219 literatures were filtered out, and eventually 39 articles are selected by reading the abstract of each one. Detailed analysis of these 39 articles is as follows. 2.1
Year Profile of Publications
From the Fig. 1, it is obvious to find that the trend of the number of papers on construction workers’ behavior monitoring has roughly gone through two stages in the period of 2008 to 2018. From 2008 to 2013, the rapid increase suggests that much attention has been paid to this field in this period; and from 2014 till now, the number of papers is relatively stable at about 5 for each year. 2.2
Research Author
On the basis of Price Law [9], 9 authors are considered as main researchers in construction workers’ behavior monitoring, and all of them have contributed to the
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Fig. 1. Year profile of publications (till March 2018)
development of this field. Among these 9 authors, LEE S ranks first, of whom the number of papers takes up one third of the total; the second is HAN S, with 12 related papers published; and the next one is TEIZER J who has contributed 9 papers. Therefore, they may be the focus of the theme of monitoring construction workers’ behavior (Table 1). Table 1. Authors of publications on construction workers’ behavior monitoring Author No. of articles Author LEE S 13 CHENG T HAN S 12 DING LY TEIZER J 9 LUO HB LI H 5 SKITMORE M Peña-Mora, Feniosky A. 4
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As shown in the Table 2, a total of 9 countries are covered in the selected papers. The United States contributes over 60% of the studies. Other notable countries with remarkable number of articles are China, Canada, Australia and South Korea. Considering the emphasis on the technology and safety in the United States, a large volume of papers on automatic monitoring technology have been conducted. 2.4
Journal
Journals with the frequency greater than or equal to 4 are shown in Fig. 2. There are 15 publications in Automation in Construction, 5 papers included in Advanced Engineering Informatics, and 4 in Journal of Computing in Civil Engineering. In addition, the main research domain of Automation in Construction is Construction & Building
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Table 2. The number of publications distributed by country Country No. of articles Country No. of articles United States 24 Germany 2 China 10 England 1 Canada 7 Italy 1 Australia 6 Spain 1 South Korea 5
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Technology, and Advanced Engineering Informatics and Journal of Computing in Civil Engineering share the same key focus area: Computer Science & Engineering. 20
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Journal Fig. 2. The number of publications distributed by journal
3 Classification of Research on Information Technology Based Workers’ Behavior Safety Monitoring A large number of technologies have been applied to research behavior safety monitoring. Based on the literature, they are divided into the following three categories: the vision-based technology, the radio frequency based technology, and the fusion of technology [10]. Specific description of these technologies are as follows. 3.1
Vision-Based Technology for Behavior Safety Monitoring
The vision-based technology fuses computer vision algorithms with video cameras to monitor construction workers’ behavior [10]. A vision-based approach is especially suitable for the construction industry because of its low cost, high efficiency, visualization [11], providing rich content for behavior-related analysis [12]. 3.1.1 Surveillance Cameras Several studies have focused on the use of surveillance cameras to promote construction workers’ safety behavior. Some attempts have been made to monitor whether workers properly use personal protective equipment (PPE). For instance, Park, M.W.
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et al. (2015) obtained live streaming or time-lapse videos of construction site by using surveillance cameras, then used the background subtraction and the histogram of oriented gradients features to identify the workers and the shape of the helmet. Next, the information was classified by support vector machine, and the workers would be automatically warned when they were not wearing the safety helmet [13]. Shrestha, K. et al. (2015) used closed-circuit television cameras to collect video information, then used face detection program and edge detection algorithm to detect workers and helmets respectively. If the helmet is not detected, the program will issue a warning to the manager [14]. Similar research has also been conducted by combining Faster R-CNN [15]. However, all these methods above would be invalid if the camera fails to recognize the face of the workers. Besides, other research used intelligent video surveillance to detect workers’ unsafe behavior. Guo, S.Y. et al. (2016) built a database of risk knowledge, collected workers’ behavior through the Intelligent Surveillance Video, and used Job Hazard analysis and Vector Space Model to convert unsafe behavior from the image format into the format that a mobile application can recognize, which was finally stored in Hadoop Distributed File System [16]. Moreover, in the further research, they constructed the temporal association rule model of unsafe behavior of workers, and used Apriori algorithm to determine the unsafe behavior in different construction phases [17]. However, on-site spatial influence on camera monitoring and the efficiency and accuracy of detection are still unresolved issues, because a camera is expected to identify an unsafe behavior only. Considering the existence of interacting workforce, a tracking algorithm based on machine learning method was used by Yang, J. et al. (2010) to analyze and track multiple interactive trajectories of workers who had similar appearances on site [18]. Furthermore, a trend in intelligent video surveillance on construction safety to obtain and analyze workers’ unsafe behavior in real-time was studied by Guo, H. et al. (2017) [19]. 3.1.2 Portable Cameras Portable cameras are used in the construction industry because of its portability and operational simplicity. A comparative study on the personnel tracking method in the construction site was conducted by Teizer, J. et al. (2009) by using monocular cameras, and the feasibility of tracking workers from dynamically moving and statically placed cameras was verified. This paper focused on the comparison of the four algorithms: the density mean-shift, the Bayesian contours, the active contours, and the graph-cuts. The Bayesian contours proved to have the best performance in this paper [20]. Furthermore, Gong, J. et al. (2011) used hand-held camcorders to obtain videos on-site, explored the framework of action learning and classification of construction workers and equipment, and then combined the Bayesian learning methods and the bag-of-video-feature-words model to evaluate the performance of the method. Compared with the research on the classification of the existing construction workers’ equipment, the model performed well on the recognition of multi-action classification when coping with issues of the view point, the partial occlusion, and scope changes. In this paper, the performance of the framework model was analyzed by using the five classical actions of template workers [21].
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However, these studies are limited to the observation of individual worker, and the tracking on multiple workers was not taken into consideration. On the basis of this, efforts were made by Liu, M. et al. (2016) to track multiple workers. In this research, a vision based human action recognition framework was presented, which could recognize multiple human actions by using Single-view Video. What is more, this article focused on how to remove unrelated people and objects, how to update learning process of action recognition and background subtraction in the frame, in order to track multiple individuals who wear similar clothes [22]. 3.1.3 RGB-D Sensors RGB-D sensors have gained great attention as a readily and cost-effectively available device for motion capture in recent years. There are two types of RGB-D sensors commonly used in previous studies: Kinect sensor and VICON. Several notable advantages of Kinect are as follows: cost-efficiency; simplicity of use; no interference in normal work due to no requirements for additional attachment. To evaluate the performance of Kinect on motion capture and action recognition for construction worker monitoring, an experiment was conducted by Han, S.U. et al. (2013) to collect 25 ladder climbing behavior data and then to analyze the accuracy of 3D position and rotation angles. The result showed a difference of 10.7 cm in 3D position and a discrepancy of 16.2° in rotation angles. These deviations may limit the application of Kinect when requiring high accuracy [23]. Another research was implemented by using Kinect motion capture system to collect behavioral data, and then four motion data types which were rotation angles, position vectors, joint angles, and movement direction were used to classify workers’ behavior [24]. In addition, in order to monitor workers’ gestures, Ray, S.J. et al. used a Kinect™ range camer, and classified the activities of human body engineering with a series of defined rules. The scope of this study was restricted to high-altitude operation, ground lifting, kneeling or crawling etc. This study contributed to automatically categorizing the work activities of ergonomics in favor of workers’ training, education, and safe and healthy settings [25]. Han, S. et al. (2013) used Kinect depth senor to collect data, and automatically detected workers’ unsafe behavior based on machine learning method, then evaluated the method by using the ladder climbing unsafe behavior inspection [7, 26]. However, these methods cannot provide real-time analysis for workers’ unsafe behavior, in face of this situation, Yu, Y. et al. (2017) used the Kinect to collect workers’ posture data, then a Microsoft-provided algorithm was used to extract the workers’ human joint information from the image, and then the information was compared with the parameters of the previously identified unsafe behavior to achieve real-time identification of workers’ unsafe behavior [27]. This research provides less redundant data and does not require training periods, but the data it provided are unstable and this research has not been used in the construction site. As for the application of VICON, Han, S. et al. (2013) collected motion data in lab using Vicon motion capture system. Reflective markers were attached to the joints of a human body, then 8 video cameras were used for image acquisition, the behavior of the workers in the form of the human body skeleton and joints was presented in virtual reality environment [11]. The other two researches have been done for behavior classification [28] and dimension reduction [29] respectively. They used Dynamic
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Time Warping to classify workers’ behavior, and Kernel Principal Component Analysis was applied to reduce dimension of workers’ motion recognition, which, however, may lead to long latency time because it took too much time to calculate the value of these features [27]. 3.1.4 Stereo Vision Camera Liu, M. et al. (2013) proposed a tracking method to extract 3D human skeleton from stereo video stream. Instead of detecting the body part from each image, the initialized body posture was used to track the position of the body joints in the proposed method. The stereo vision system proposed in this paper is to conduct 3D evaluation of 3D human skeletal model from the trajectories of body and multiple angle of view in 2D images [30]. The performance of method was evaluated by doing experiments in the laboratory, occlusion, illumination and the view of camera will have an influence on the tracking method on the actual construction site. A markerless motion capture approach was proposed in face of this limitation. Starbuck, R. et al. (2014) fused optical image and stereo vision cameras to obtain depth data. This method is not restricted by the construction site environment compared with RGB-D sensor [31]. 3.2
Radio Frequency Based Technology for Behavior Safety Monitoring
Current study on behavior safety monitoring utilizing radio frequency based technology are mainly focus on Radio Frequency Identification (RFID), Ultrawideband (UWB), and some other technologies like Chirp-spread-spectrum (CSS). 3.2.1 RFID RFID is a kind of technology that can automatically identify target objects and obtain data from a tag through using radio frequencies. The major application of RFID for monitoring workers’ behavior safety is the safety early warning system that could warn workers of potential hazards on the site. Teizer, J. et al. (2010) proposed Very-High Frequency active Radio Frequency technology as wireless communication means. The Equipment Protection Unit was put on equipment, and the Personal Protection Unit is installed on the workers’ clothing, warning or alerting equipment operators and workers-on-foot once a worker gets too close to the equipment [32]. However, signal transmission may be weakened by the blocking of building materials. Some other researchers tend to monitor the use of PPE by applying RFID. Kelm, A. et al. (2013) carried out a study by installing low-cost passive RFID tags on the PPE. It can automatically make statistical analysis of the use of PPE by workers, and increase the awareness of workers using PPE at the same time [33]. However, RFID is not suggested to be used for ubiquitous real-time monitoring because of its limited communication range and low-accuracy [34]. 3.2.2 UWB UWB technology is mainly applied to prevent potential accidents by tracking location of workers and equipment. Teizer, J. et al. (2008) used UWB to locate building resources in real time, and the observation data can be integrated into automatic alarming equipment of the staff or the equipment operator to achieve
the the the the
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early warning function [35]. A large number of fatal accidents are related to collisions caused by events, such as the proximity of workers to the construction equipment, and to other geo-referenced hazard or restricted areas. Based on this issue, in further studies, Teizer, J. et al. (2015) designed an innovative framework for real-time location tracking, and data of near miss was collected to test the framework. The purpose of this paper was to identify the static and dynamic hazardous areas of construction sites, obtain and analyze temporary space conflicts between workers-on-foot and the identified danger zones automatically, then convert these collected hazard data of workers’ operations, equipment and geo-referenced into meaningful security information [36]. Another similar study was made by Carbonari, A. et al. (2011). This article built an active security management system based on UWB technology to detect potential indirect danger in real time and to observe whether workers are close to dangerous areas [34]. 3.2.3 Other Radio Frequency Based Technology Expect for RFID and UWB, other radio frequency based researches have also been used for construction safety. Li, H. et al. (2015) proposed a real-time positioning system based on CSS to locate the workers, the experimental results showed that the experimental error of CSS was 0.8 m, and the corresponding rate was 200 ms, which showed that CSS may be the Real-Time Location System (RTLS) that provide the most accurate data in a wireless environment. Futhermore, it is cheaper than RFID and UWB, little influence on normal construction for its easy for installation. Both two advantages make CSS appropriate to be used in construction site [37]. In addition, mobile sensor was also being applied in behavioral recognition. Akhavian, R. et al. (2016) collected the accelerometer and gyroscope data from many construction workers to participate in different activities by setting smartphone with sports armband on the tsestee’ arm, and classified the behavior of workers using a variety of algorithms such as neural network, decision tree and Knearest neighbor [38]. Moreover, Li, H. et al. (2017) designed a real-time tracking system called the Eye on Project (EOP) to implement safety helmet usage by using bluetooth technology. This system overcomes the disadvantages of traditional records like self-report, and it can automatically check for errors and record safety helmet use. EOP is suitable for daily activities of workers. However, it can only identify the related factors such as age, gender, individual experience and time of not wearing the helmet, other potential influencing factors such as location may not be recorded accurately [8]. 3.3
Fusion Technology for Behavior Safety Monitoring
Due to the diverse types of information provided by various methods, it is not recommended that a single measure is used alone [39], some researchers combined different approaches to eliminate the disadvantages of a single technology. Teizer, J. et al. (2013) combined location tracking based on UWB with data visualization technology to improve construction safety. The training framework and algorithm proposed could process workers’ tracking data collected visually, and trainers could point out improper environment at any time during the period of training. Moreover, performance of unsafe activities may be displayed in 3D visualization, and virtual model was able to
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present the current training facilities accurately [40]. Based on Behavior-based safety (BBS), Li, H. et al. (2015) proposed Proactive behavior-based safety (PBBS) to monitor workers’ location-based behaviors automatically. PBBS developed the theory of BBS with the technology of Proactive Construction Management System, which includes two parts: the Real-Time Location System (RTLS) and the Virtual Construction Simulation System [41]. Besides, a deep hybrid learning model was built to detect construction workers’ unsafe behavior by combining Convolution Neural Networks and Long Short-Term Memory. The probability of successful recognition of safe and unsafe behaviors are 97% and 92% respectively, indicated that the model with high precision in identifying unsafe behavior [42]. Cheng, T. et al. (2013) applied RTLS based on UWB to collect data, combined with Physiological Status Monitoring to observe the real-time Status of workers, result showed that it could identify unsafe behaviors related to ergonomics automatically. However, because of the limitation of the technology, the distinguish of squats and normal gesture need to be further explored [43]. In addition, a common limitation of radio frequency based technology is the block of building material to signal. In face of that, Lee, H.S. et al. (2012) proposed RTLS based RFID by using the Time of Arrival to acquire a high-precision positioning data, the CSS for signal transmission, and Assistant Tag was used to weaken the block of transmission signals due to building obstacles [44]. Barro-Torres, S. et al. (2012) designed a Cyberphysical System to observe how workers use PPE. By fusing RFID and Zigbee technology, the presence of PPEs was detected and a report would be send to the central unit, then a warning or historical data was formed [45].
4 Discussion and Future Research 4.1
Discussion
This paper presented a wide array review of several approaches for monitoring workers’ behavior at construction sites. Based on current research for safety monitoring, these technologies are divided into (1) vision-based technology; (2) radio frequency based technology; and (3) fusion technology. Efforts made by researchers to detecting workers’ behavior with these technologies are vital in promoting workers’ safety at construction sites. However, there are still some gaps between current technology and application to construction site. Among vision-based technology, radio frequency based technology and fusion technology, limitations still exist for use of monitoring worker unsafe behavior on job site. Vision-based technology may meet with barriers as a result of limited applicable tasks on the process of collecting data, disturbance with workers’ ongoing work and private personality invasiveness. For instance, Vicon and Kinect are not suitable for outdoor environments due to sensitivity to illumination and occlusion [46], but operating work is usually in open air in construction site and therefore they are limited to use for monitoring site behavior safety. As for a variety of cameras, there are some disputes about whether cameras being allowed or not to be used for automatically monitoring workers’ behavior [47]. Some agree with automated inspection by reason to benefits of organizational safety, while others criticize it invades workers’ personal privacy, which increases their work
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pressure [47]. On this occasion, vision-based technology used for collecting data in the workplace causes negative effects on workers, and therefore has been restricted the additional application in practice. Compared to the vision-based technology, the other two technologies can be applied to support construction site monitoring. However, the type of unsafe behavior monitored is limited, mainly focusing on the use of personal protect equipment and location tracking of worker access to danger zone. For example, RFID tags are installed on the PPE to analyze the use of PPE by workers [33], and UWB technology is applied to automatically identify space conflicts between workers on foot and hazardous area [36]. Even then fusion technology is adopted to monitoring workers’ behavior, which can cover the shortage of single measure, the problem about the range of unsafe behavior still exists. 4.2
Future Research Direction
The use of information technology will bring more efficiency and lower cost in monitoring construction worker behavior safety. Based on the description earlier, there exists some future research points about technologies applied to monitoring behavior in construction industry. With regard to vision-based technology, future study should consider how a single camera with other technology, such as motion perception technology, can monitor, classify and identify kinds of unsafe behaviors. Besides, the solution to use multiple cameras to collect data may reduce occlusions on site, thereby increasing behavior estimation accuracy. Furthermore, to mediate the adverse effects of vision-based monitoring due to invasion of workers’ privacy, measures need to be taken by managers to make worker himself aware that he will be monitored, and this will contribute to reducing injuries and improving construction safety. As for radio frequency based technology, further study of reducing the weakening of signal because of building block to improve signal transmission efficiency is required.
5 Conclusion This paper presented an extensive review of information technology based approach for construction workers’ behavior monitoring from 2008 to 2018, involving 39 relevant papers contained in the Web of Science database. It was found that current research had employed information technology to assist in construction workers’ behavior monitoring, and these technologies were classified into: (1) vision based; (2) radio frequency based; (3) fusion technology. Vision-based technology included surveillance cameras, portable cameras, RGB-D sensors, and stereo video stream. Radio frequency based technology contained RFID, UWB, CSS, etc. In addition, multiple information technology adopted in those analyzed papers, such as the combination of UWB and Physiological Status Monitoring, was defined as fusion technology by the current research. The shortcomings of information technology mentioned above were discussed, for example, the lack of vision-based technology in disturbance with workers’ ongoing work and private personality invasiveness, the limitation of radio frequency based
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technology and fusion technology in the types of unsafe behavior monitored. Future research directions were suggested, involving increasing the types of unsafe behaviors monitored, reducing occlusions on site, mediating the effects of invasion of workers’ privacy. The main contribution of this paper is to help researchers to understand the status of this domain and identify future research directions in theory. In addition, the present research can lead practicer apply information technology in construction workers’ behavior monitoring, thus improving construction safety management. Acknowledgments. This paper was supported by the National Natural Science Foundation of China (grant number 71471023).
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The Visualization Analysis of Organizational Information Ecosystem Development Based on Social Networks Wenjia Guo1, Junwei Zheng2(&), and Hongtao Xie2 2
1 Guizhou Normal University, Guiyang, China Kunming University of Science and Technology, Kunming, China [email protected]
Abstract. In the information ecological chain, the social network has great impact on the propagation of organizational information. It is necessary to analyze and summarize the relevant research. Based on the journal papers published by Web of Science core collection from 1997 to 2018, the paper applies the visualization analysis to draw knowledge maps about the information ecosystem based the social network, and carrying on the detailed analysis from the knowledge structure and research hotspots of the impact mechanism. It promotes the development and construction of organizational information ecosystem in new social media…………………. Keywords: Social network Information visualization
Information ecosystem Knowledge map
1 Introduction Thomas H [1] proposed the concept of information ecology at the micro level in 1997 and used the overall system perspective to process and use information within the organization. Bonnie A & Vicki L [2] defines the information ecosystem as a system formed by people, information, technology and value in a specific environment. In this system, human activities constitute the core elements of the system. Value creation does not simply add up with each other, it depends on node optimization coordination. The person is an information person with a certain social network [3]. The social network relationship between the subjects forms a cross-dimensional dimension, which is interfered by the uncertainty of the subject’s psychological state, social and cultural context, organizational structure, and communication channels [4, 5]. In this process stable trust between subject, cultural and institutional content of mutual adaptation between enterprises and organizations can help enterprise to adjust information nodes [6], reduce information acquisition of risk challenge and process uncertainty [4]. At last these can optimize cooperation patterns to achieve a balanced state with subjects and realize the purpose of complementary resources and information flow. Scholars have researched the information flow and transformation between the reciprocal cooperation in the perspective of information ecology in order to achieve good coordination and improve the overall value of the information ecological chain. © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1269–1281, 2021. https://doi.org/10.1007/978-981-15-3977-0_98
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Although there have been some research in this direction, the breadth and depth of its theoretical and empirical researches need to be further explored. This paper uses knowledge mapping to review the cross-research direction of social networks and information ecosystems. It’s to explore mutual relationship. Clearly and correctly understand the establishment and optimization of information ecosystems on the basis of social networks, and make predictions on the research priorities and leading directions in this field.
2 Data Collection and Research Methods The Web of Science core collection is used as a foreign language database to collect information data in the field of information ecosystems and social networks. The search terms are input into “Information Ecology & Social Network”, “Information Ecosystem & Social Network” and “Green Information & Social Network”. The literature type select periodical literature. At last the database retrieve 665 retrieved record from 1997 to 2018. After data deduplication, 608 articles were retained. But the number of documents in the field from 1997 to 2003 is stable. The number of documents gradually increased since 2004 in Fig. 1. It indicates that it has received extensive attention from scholars. Therefore, we set the time slicing from 2004 to 2018 in the software package Citespace.
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In this paper, we use the software package Citespace (Version: 5.1.R8) [7] to conduct bibliometric analysis. It drawa the multivariate, time-division, and dynamic diversification maps to show the domain evolution law, research hotspots and subject knowledge bases, and to reflect the period of dynamic evolution in a certain period [7, 8].
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The 608 retrieved record (including cited references) import into the software package Citespace (Version: 5.1.R8) for knowledge mapping. By setting Time Slicing, Term Source, Term Type, and Node Type, we can get co-occurring subject category network, co-occurring keywords network, journal co-citation network, author cocitation network, document co-citation network and analysis of research hotspots, development structure and knowledge base.
3 Research Hotspots and Development Structure Analysis There are numerous research literatures on information ecosystems and social networks. It focus research issues in multiple levels and multiple perspectives. Thought the cluster analysis of categories, journals, and keywords sort out the research progress and context to understand its development trend and direction. 3.1
Co-occurring Subject Category Network
We select the node type as the category and use the Minimum Spanning Trees to pruning to generate a co-occurring subject category network map in the software package Citespace (Version: 5.1.R8) [7]. The category map consists of 73 nodes and 152 links. The top five themes are Environmental science & ecology (168 articles, centrality = 0.62), Computer science (123 articles, Centrality = 0.05), Environmental Science (85 articles, Centrality = 0.46), Ecology (74 articles, Centrality = 0.63), Engineering (68 articles, Centrality = 1.29), and Business & Economics (52 articles, Centrality = 0.86). As shown in Fig. 2, the node size is proportional to the number of documents contained in the category.
Fig. 2. Co-occurring subject category network
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According to the number of documents and the central value in each category, the research in this field focuses on the organization of engineering manufacturing. Through scientific and rigorous quantitative analysis method to explore the role of social networks establishment and maintenance on the flow of information, and adapt organizational ecology environment. 3.2
Journal Co-citation Network
The node type selects the cited journal to generate the corresponding journal co-citation network map in the software package Citespace, which reflects the interrelationship between the journals. We combine the journal co-citation network with the Cooccurring subject category network to complement each other and interpret interdisciplinary links. Figure 3 is roughly divided into two clusters. First, these journal explore the formation and development of relations in social organizations, and the role of internal and external environmental factors based on sociological theories, such as American Journal of Sociology, Social Networks, and Annual Review of Sociology. The second cluster explore the research direction of commercial economy based on management theory, such as Administrative Science Quarterly, Academy of Management Review, etc.
Fig. 3. Journal co-citation network
The highly cited literature journals focus on the perspective of sociology and management economics to discuss the role of the information ecosystem in establishing and maintaining the social networks.
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Co-occurring Keywords Network
The node type selects the keyword and use the Minimum Spanning Trees to pruning to generate keyword co-occurrence maps in the software package Citespace [9]. After merging similar keywords, Social network is merged with Social networking into social network node. Ecosystem and Ecology are merged into Ecosystem nodes, and a cooccurring keywords network map composed of 281 nodes and 524 links is finally generated. As shown in Fig. 4, the modularity Q = 0.8897, the mean silhouette = 0.5871, the modularity Q and mean silhouette are the criteria for defining the quality of the image. And the modularity Q is above 0.3 and the mean silhouette is above 0.5 can mean the significant of image [10]. So the figure is an ideal co-occurring keywords network map.
Fig. 4. Co-occurring keywords network
In the co-occurring keywords network map the two nodes of Social Network and Ecosystem overlap, indicating that the research content of the two nodes intertwine with each other, while the rest of nodes are known from the color of lines and node outline. We know that they form later and cite fewer times, but they are related to each other. The nodes are the ecosystem services, social media, management and so on. The strong and weak relationship between social networks affects the acquisition of resources such as partners and knowledge information [11, 12]. Effective network relationships play a role to generate information flow, at the same time motivation [12], cognition [13], trust [14] and density [15] affect the quality and quantity of information dissemination. The emergence of social media in a dynamic and rapidly changing environment has changed the traditional way of communication, collaboration and creativity [16]. It also breaks the boundaries of communication and innovation to causing changes in social
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structure and relationships. So Kbar [17], Tufekci [18], Ripperger [19] established a diversified analysis path model to exploring the impact of new information network media on the reconstruction of stable social networks [20]. And Isaac point out that it can help leader to identify individual and overall hidden behavioral goal though the conclusions of the new diversification analysis [21]. With the rapid development of the social media, the organization must changes internal forms to meet market competition needs through internal selection and retention. With a new form of organization based on online communication has emerged [22]. This new form of organization has the characteristics of minimizing cost expenditure and a low proportion of survival [23]. So it requires to quickly adjust internal organizational forms and structures to achieve selection, change, retention of resources and technologies [24] and face external changes new opportunities in short time [25]. Thereby the change of rules and social values happen [26]. The previous studies lack an overall research perspective of the intersection of information technology and society. Seol [27] introduced the communication ecology theory, which was first proposed and developed by Altheide [28]. Tacchi [29] defined communication ecology as “social networks connect through minimal media and it form the organization”, focusing on the mutual dynamic relationship between technology, content and social relations based on social media [30]. Because the actor, social relationship and the media are diverse and multifaceted. Foth [30] divides technology, content, and society into three layers. The technical layer aspect the construction of information technology services and media platforms. Content and society layers refer to the themes and processes of communication between the actors. Social relations are an important and significant factor in the framework, reflecting the degree to which they are needed. So high-quality social contacts can help to achieve goals and affect content effectiveness, communication pleasure, and satisfaction [31]. Lin [32] incorporate the analysis of information quality and relationship characteristics in the model, then measure information quality characteristics by assessing content validity, communication pleasure, and satisfaction factors to exploring the impact of their participation in behavior [33].
4 Knowledge Base Analysis Knowledge base analysis can lead to key literature nodes in domain development by analyzing citations and co-citation trajectories in scientific literature collections [34]. So researchers more clearly and accurately understand the development of the domain with time dimensions. By analyzing the basis of the literature, the structural relationship between the documents and information exchange are clarified [35]. 4.1
Author Co-citation Network
The analysis of author co-citation network in the literature is to establish the structural relationship between high-cited authors. The node type in the software package Citespace selects the cited author to obtain the author co-citation network map, resulting in
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Fig. 5. Author co-citation network
450 nodes, 629 links. As shown in Fig. 5, the view the modularity Q = 0.9096 and the mean silhouette = 0.5316 exceed the criterion of significant line [10]. In Fig. 5, the top three high cited authors Borgatti SP, Newman MEJ, and Wasserman S form a cluster to analyze the establishment, structure, and scale of social networks. Berkes F and Ostrom E study the effective dissemination of knowledge information in the team. Burt RS explores the mechanism of the impact on information sharing in social networks from the perspective of trust. In addition, a class of authors in the map has a relatively low number of citations, but has a higher citation burst. This phenomenon indicates that the author’s article has caused a shift in research directions in a certain period of time. In the field the authors of higher citation burst mainly take the new social media as the intervention point and explore the related research of the organization’s common management, knowledge dissemination and transfer mechanism. Among them, Borgatti SP scholars have high citation frequency, high centrality and high salience. His published articles summarize the basic assumptions, goals and interpretive mechanisms of social network analysis in 2008 [36], which lays an important foundational role in field development. 4.2
Document Co-citation Network
The document co-citation network map reflects key document nodes and mutual structural relationships in the development process of the domain. The node type in the software package Citespace selects cited reference. It generates a total of 304 nodes and 2171 links map. The document co-citation network map is divided into two clusters by highly cited literature in Fig. 6. The two clusters are about social network and organization information sharing transfer mechanism. Firstly the social network cluster has two reviews that describe the basic assumptions, interpretation mechanisms and dynamic structure
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of social network [36, 37]. Bodin [38] with high citation frequency and high center value is based on the characteristics of complex networks to explore the roles played by each other in the process of inter-organizational inequality in ecosystem cooperation and analyze the influence of the relationship density, integration and centrality on the output of information. Cooperative management of effective mechanisms across organizations is beneficial to building trust and avoiding unnecessary conflicts in the process of knowledge dissemination [39]. Through mutual learning and communication the organization establishes a common management mechanism to effectively improve collaborative behavior and stabilize organizational resource networks [40, 41]. The stakeholders play a core mediation role in the management mechanism [42].
Fig. 6. Document co-citation network
Regarding the cluster of organization information sharing transfer mechanism, scholars mentioned that establishing an information ecosystem based on large-scale data is conducive to identifying and constructing an idealized stable organizational cooperation platform [43], which facilitates the transfer of knowledge and experience across organizations and individual [44–46]. even the platform play as a central role [47]. In the process, the relationship of trust in turn promotes the improvement of the social network model and structure [46, 48, 49]. 4.3
Structural Variation Analysis
Chen [50] proposed to apply a structural variation analysis method to judge whether a paper was published to construct a bridge relationship between clusters and analyze whether it is possible to determine the value of cluster boundaries that are related to each other or separated. Structural Variation Analysis is selected in the software package Citespace, as shown in Fig. 7.
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Fig. 7. Structural variation analysis
In the era of the rapid development of social media and the rapid replacement of social groups, the use of new social media to effectively find, identify, use information [51] and create a new type of information ecosystem [52] is the key to companies’ priority market access. The formation of interrelated feature sets through the content and characteristics behind the social information dissemination media is the key for the company to obtain market trends [53]. Then Bailey [54] mentioned that it is necessary to use information technology to assist knowledge management and achieve the completion of goal and task. Big data processing techniques can effectively provide organizations with objective and accurate data analysis results. And the results can provide basic support for subsequent decision-making [55, 56]. When the mobile social platform changes the structure and composition of the information ecosystem [57], creating a knowledge governance mechanism adapted to the environment of the organization is also the key to the sound operation of the information ecosystem [58]. In the reverse social mode individuals choose and are selected easier to establish trust relationships [59], and also promotes the formation of a new behavioral model framework [60].
5 Conclusion In this paper, 608 articles retrieved from the Web of Science core collection related to organizational information ecosystems on the basis of social relations. These retrieved record are used to establish co-occurring subject category network, co-occurring keywords network, journal co-citation network.etc. and reflect the development foundation and hotspot direction in this field.
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Under the background of rapid changes in market demand, the field explores social network reconstruction and changes in information flow and processing methods under new social media from the perspectives of sociology and management. The author and document co-citation network are clustered by high-cited authors or highly cited papers. The Borgatti SP, Berkes F, Burt RS and other scholars form different perspectives to construct the channels of information dissemination and its influencing factors on social networks. At the same time Bodin explores the degree of influence information output on the role of play and integration in the process of non-equality cooperation between organizations based on complex network characteristics. This literature establishes the connection between social network and organizational information cluster and lays the foundation for each cluster. The author of higher citation burst use the new social media as the intervention point to explore the information transmission mode to change the original stable social network information management, sharing and transfer mechanism. The co-occurring keywords network divides the hotspot into two clusters of social network and ecosystem. On the basis of the research on the social networks that is the degree of strong and weak relationship, which is beneficial to information and knowledge transfer. This direction of research emphasizes rapid and continuous response of the organization to the external environment in the information ecosystem. And it focus on the communication of content effectiveness, satisfaction and communication pleasure between the two parties. Because of all factors affect the quality of information and the participation of subject behavior. In the structural variation analysis, the literature is more integrated into the communication mode to explore its individual psychological and behavioral changes. In the future, we can combine new social media features on the Internet to discuss the content, transfer methods and modes of information exchange and improve the reconstruction and management of the organizational information ecosystem structure.
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Research on the Mechanism of the Economic Compensation to Prefabricated Building Based on the Loss of Developers’ Revenue Yang Chen(&), Hao Wu, and Jiuxia Tan School of Economics and Management, Chongqing Jiaotong University, Chongqing, China [email protected]
Abstract. The development of prefabricated building in China is not smooth, the policy system is not perfect, and the incremental cost is too high. Therefore, the establishment of a scientific and effective incentive mechanism is an important factor to promote the healthy development of prefabricated building. Based on the definition of incremental cost, this paper puts forward the economic compensation mechanism based on the loss of developers’ revenue; By analyzing the source and characteristics of the revenue loss of the developers, the composition of the profit loss of the prefabricated building is summarized; The profit function is constructed by using the C-D production function, and the loss compensation line is discussed; The economic, environmental and social effects of the assembly building are analyzed, and the model of the developer and the government is set up to establish an incentive mechanism for the prefabricated building based on the loss of revenue. Keywords: Prefabricated building Loss of revenue Apportionment model Incentive
1 Introduction Compared with traditional buildings, the advantages of prefabricated buildings are obvious, and their advantages of resource conservation, green construction, and rapid construction are in line with the current development policies of the country. It can meet the construction requirements of energy conservation and environmental protection to a great extent and has become an important symbol of industrialization in the developed countries. Under the background of the transformation and upgrading of the manufacturing industry, the central government continued to introduce relevant policies to promote prefabricated building. In September 2016, at the State Council’s executive meeting, it decided to vigorously develop fabricated structures such as steel structures and promote industrial restructuring and upgrading. In many programs, it is clearly stated that by 2020, the percentage of newly-built buildings in China will exceed 15%, of which the key areas will be over 20%, the areas actively promoted will be over 15%, and the areas to be promoted will be over 10% [1]. As of January 2018, more than 30 provinces, © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1282–1294, 2021. https://doi.org/10.1007/978-981-15-3977-0_99
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cities, and regions in China have provided relevant guidance and supporting measures for the development of fabricated buildings. Among them, 22 provinces have formulated phased targets for the scale of assembly building and have successively introduced them. Specific refinement of local assembly-type building policies to support the development of the industry. During the period of 14th Five-Year Plan (2021 2025), the proportion of prefabricated buildings in newly-built buildings is to exceed 50% [2]. However, the situation at this stage is far from the policy goal set by the state, and the development of fabricated buildings still faces enormous challenges. The inadequacy of its technical system and insufficient support for standards and standards are limiting the development of prefabricated buildings in China. From the policy point of view, the formulation and implementation of China’s prefabricated building policy is still at an initial stage. The incentive and restraint mechanisms in the industry are still not perfect, the compensation system is not perfect, and the compensation factors are not comprehensive, resulting in the ineffectiveness of the existing compensation system. If the construction unit chooses to implement assembly-type construction or increase the prefabrication rate of its building, it will face the problem of initial investment increase. This undoubtedly adds a lot of uncertainty to the construction input cost risk and causes the construction unit to choose conservative construction to reduce the cost risk. To protect their own interests. Therefore, the establishment of a scientific and effective compensation mechanism is an important means to promote the development of prefabricated buildings in China. In recent years, many experts and scholars at home and abroad have discussed the compensation of different types of buildings. For example, by sorting out the literature of nearly three years, Li Lihong [3] found that the reason why the development of fabricated building was blocked was that its price was high, but the price compensation mechanism was still not perfect. It also puts forward compensation mechanisms, such as policy compensation, monetary compensation, physical compensation and price compensation. Qi Baoku [4] uses the game theory model to analyze the main stakeholders, the relationship between the government, the owner of the project and the prefabricated component manufacturers and design the government compensation mechanism for the assembly building. In order to maximize the efficiency of the system and avoid the unfair distribution of income distribution under the compensation mechanism, Qing Qiankai [5] put forward the revenue sharing mechanism under the decentralized decision-making model and the cooperative decision model. Wu Yilin [6] believes that the environmental and social benefits of incremental cost of green buildings are far greater than their economic benefits, and a model of incremental cost sharing is proposed by reference to advanced quantitative methods. Li Ming [7] analyzed the effect of green building, constructed the ecological environment effect compensation model of green building, and used the opportunity cost method, market value method, ecological recovery cost method to measure green building environment effect, in order to establish the green building incentive mechanism of ecological environment benefit compensation. Li [8] believes that the compensation mechanism of the government as a single subject is unstable and low standard, and many forms of compensation mechanism should be realized, including government leading mechanism, market supervision mechanism, legal constraint mechanism and public participation mechanism, so as to improve and improve the compensation mechanism of the single subject.
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From the perspective of related literature, most of the studies have focused on using the incremental cost of fabricated buildings to consider the compensation mechanism but have not considered the compensation standards for the economic losses assumed by the main body of prefabricated buildings. Prefabricated buildings are also a kind of green ecological buildings, but most of the compensation mechanisms do not take into account the environmental effects produced by prefabricated buildings, and thus have limited incentive for developers of prefabricated buildings. This paper proposes a revenue loss based on the main body of a prefabricated building development and establishes a price compensation mechanism that allocates this part of the loss between the government and the developer.
2 Theoretical Analysis of Loss of Revenue Loss-based compensation refers to the basic basis of compensation for the loss of economic benefits of real-time entities in the process of eco-environmental restoration and eco-environmental protection, so as to ensure that the ecological interests of the eco-protectors are not impaired, while ensuring the sustainable development of the local economy. As developers of prefabricated buildings as environmentalists and sustainable developers, they may face various economic losses during the development of prefabricated buildings, and social beneficiaries should give them certain compensation. Most of the existing compensation annotations only compensate for the incremental costs of developing prefabricated buildings, ignoring that prefabricated building developers may face greater losses than incremental costs in their market competition [9]. 2.1
Analysis of Source of Loss of Revenue
The fundamental reason of the compensation mechanism based on the loss of revenue is the insufficiency of the internal power of the assembly-type building development. In the market, power can be divided into two kinds: profit and competition, which is the motive force of market operation. Market operation is the process of interest chasing, in the process of interest chasing along with competition, compared with traditional buildings, the assembly-type building in cost is not competitive. According to the competition law of survival of the fittest, the assembly-type building must adjust the development mode, enhance its competitiveness and optimize itself continuously. Otherwise, in the long-term market competition mode, will inevitably be eliminated. In this paper, a simple two-party game model is used to verify the revenue loss of the assembly building developers. In order to facilitate the analysis of the source of loss for green building developers, this article assumes that prefabricated buildings and traditional buildings are two developers in an oligopolistic market and analyze their respective development strategy games. In a certain area, China’s building development market is very fitting oligopoly market situation, so, this article selected oligopoly market, there are two types of building developers, namely, traditional building developers and assembly-type building developers [10]. For ease of analysis, this model selects only two developers, before
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building development, two developers have two development strategies to choose from, namely, the development of traditional architecture and the development of assemblystyle architecture. Table 1. Two game matrix between developers
A developer
Traditional building Fabricated building
B developer Traditional building ½ðP0 C0 ÞQ0 ; ðP0 C0 ÞQ0
Fabricated building ½ðP0 C0 ÞQ0 ; ðPZ CZ ÞQZ
½ðPZ CZ ÞQZ ; ðP0 C0 ÞQ0
½ðPZ CZ ÞQZ ; ðPZ CZ ÞQZ
In Table 1, In this model, P0 is the unit market price of traditional buildings, C0 is the unit cost of developing traditional buildings, Q0 is the sales volume of developing traditional buildings, PZ is the unit market price of prefabricated buildings, CZ is the unit cost of developing prefabricated buildings, QZ is the development prefabricated building sales. P0 C0 represents the unit profit of the development of traditional buildings, and PZ CZ represents the unit profit of the development of prefabricated buildings. Therefore, the income from the development of traditional buildings is ðP0 C0 ÞQ0 , and the gain from the development of fabricated buildings is ðPZ CZ ÞQZ . Among them, prefabricated buildings use more energy-saving and environmental-friendly materials and more demanding construction techniques, and they have more manpower to invest in. The amount of investment required for the same amount of development is greater, that is, CZ C0 . To ensure a certain unit profit, the market sales price is PZ P0 . Usually, the building product developed in the same area is a flexible product (e > 1), and the sales unit price for each unit will receive more than one unit of income. In this model, PZ P0 , then QZ Q0 , resulting in ðPZ CZ ÞQZ ðP0 C0 ÞQ0 . That is, the total income of the developers of fabricated building is less than the total income of the developers of traditional buildings. Because lots and prices are a major concern for consumers to buy real estate, consumers pay little attention to the technological content of the building itself. such as two developers in the same area to develop products, that is, the same location advantages, consumers tend to buy low prices of products, investment in the construction of environmental science and technology sensitivity is not high, consumers easily choose a relatively low price of traditional buildings, making traditional building sales more than the assemblytype construction sales. Traditional building developers occupy more market share because of low sales price, and the fabricated building developers are at a disadvantage in the market price competition because of the higher development cost, which leads to the loss of profits. From this, we can through the game results and the development of the assemblytype building of the reasons for the lack of motivation can be measured, the construction cost of the fabricated building is higher than the traditional construction, and the high cost means higher price, but the consumers will buy the house more favor the
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lower price of the traditional building, and lower the price, the profit of the developer will be reduced. In accordance with the principle of interest-driven, developers to develop assembly-style building is not enough power, will choose to develop a nonassembled building, so that the assembly-style building into a gimmick, symptomatic solution is the government to support the development of assembly-type building, to provide sufficient incentive policy, so that developers to develop the benefits of assembly-style building more than the benefits of the development of traditional buildings. 2.2
Determination of Compensation for Loss of Revenue
From the above game analysis, it can be seen that the amount of compensation for the developers of prefabricated buildings is the loss of their revenue, that is, the loss of profits in comparison with traditional building developers. To determine this part of the loss of profits, a Cobb-Douglas production function for building development can be established: Y ¼ AK T LU
ð1Þ
Among them, for the amount of development, the level of technological progress (constant during the investigation period), capital investment, labor input, respectively, the output elasticity index of capital, labor, and formula (1) can not dynamically reflect technological progress and technology Structure, so the building development function used is as follows: Yt ¼ A0 ‘kt K1a K2b Lu
ð2Þ
Among them, K is the capital investment for building development, that is, the total material consumption of buildings (including the depreciation of fixed assets). A0 represents a common coefficient of technological progress, k is technical efficiency, ‘kt is the t-th level of technological progress, K is divided into K1a and K2b , The building profit function that includes the C–D production function is: Y t
¼ ð1 þ gÞPA0 ‘kt K1a K2b LU t K1t PK1 K2t PK2 Lt PL
ð3Þ
Therefore, the value of the profit function of the traditional building and the prefabricated construction can be determined by the difference between the cost of the Assembly Building developer. b b U a kn t a Ct ¼ P½A0 ‘km t K1tm K2tm LU tm ð1 þ gÞA0 ‘ K1tn K2tn Ltn ðK1tm K1tn ÞPK1 ðK2tm K2tn ÞPK2 ðLtm Ltn ÞPL
ð4Þ
For (3) andQ(4) two formulas. Among them, indicates the Yt phase of construction development, t is t-phase profit, Ct indicates that phase t should compensate for loss of developer revenue. P, PK1 , PK2 , and PL represent traditional buildings, high-consumption
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production factors, low-consumption production factors, and labor unit prices, respectively, and are exogenous variables.; ð1 þ gÞ is the sales unit price for fabricated buildings, g [ 0, and related to the quality of fabricated buildings. For traditional buildings, g ¼ 0; km 6¼ kn , Both have different technical efficiency. K1tm and K1tn respectively express the high consumption factor input of traditional building and assembly building, K2tm and K2tm respectively indicate the input of traditional and assembly building type production factors, and Ltm and Ltn are the labor input of traditional and assembly construction.
3 Apportionment Model Based on Revenue Loss Assembled construction increases construction cost investment, causing economic losses to the assembly building developers, but it also has a great overall benefit. As the construction unit is a collective for the pursuit of profits, it cannot be enjoyed alone, but it has to bear it alone. When economic losses occur, it is rational to decisively give up. The “Government-Building Unit’s prefabricated construction Economic Loss Allocation Model” was proposed. 3.1
Apportionment Ideas
The implementation of prefabricated construction will result in a reduction of economic benefits, i.e. loss of revenue, but at the same time, prefabricated buildings will also bring a large number of comprehensive benefits, but these comprehensive benefits do not belong to the construction unit alone. In the event that all of them cannot be obtained, it is difficult for construction units to independently choose to implement assembly-type construction. In the early stage of assembly-type construction, the government should introduce an effective incentive mechanism to effectively reduce the economic cost of assembly-type construction technology and fully mobilize the enthusiasm of the construction unit. Therefore, this paper calculates the economic benefits loss of the prefabricated construction developers, quantifies the comprehensive benefits brought by the developers and the public’s respective prefabricated buildings, and establishes a model for the loss-assessment of economic benefits from prefabricated construction. Calculate the apportionment coefficient and the cost-sharing of the loss of income between the government and the construction unit. This paper establishes an amortization model and expects the government to issue corresponding compensation measures to compensate the construction unit for the cost of implementing assembly construction and reduce the risk of cost investment to encourage construction units to implement assembly construction. 3.2
The Rationality of Compensation
Compared with the traditional architecture, the cost of assembly-type construction is higher than that of traditional buildings, and the economic benefit has no advantage, which leads to insufficient power in the development of assembly-type building, which restricts its environmental benefit and social benefit. In the process of assembling
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building development, the internal development power is insufficient, and the lack of external impetus, the development of assembly-type building will stagnate. Externality theory is one of the basic theories of environmental economics and ecological economics, and it is also an important theoretical basis for the compensation of prefabricated building development. Henry Sidgwick put forward the importance of externality theory. He believes that externality stems from the fact that private and social costs, private benefits, and social benefits are not always consistent between economic activities. Individual economic behavior is based on self-interest, but it is also possible. Serve as a service to others, and these people do not pay for this service. In addition to the features of green buildings, prefabricated buildings save resources (energy-saving, land-saving, water-saving, material-saving), protect the environment, reduce pollution, and provide people with healthy, applicable and efficient use. Space, building in harmony with nature. At the same time, the efficiency of construction of prefabricated buildings is high, the speed of construction is increased, noise is low, and dust is small. The impact on the surrounding residents is minimized. The special construction method of prefabricated buildings also reduces the number of construction workers on site, and greatly improves construction safety and construction quality. Therefore, developers developing prefabricated buildings can save energy and reduce emissions, optimize environmental quality, and promote the sustainable development of related industries. At the same time, they can improve construction efficiency and ensure construction quality and safe production. While creating revenue for itself, it also creates certain social and ecological benefits for the society and others. However, they do not pay developers any costs. Therefore, developers have some positive externalities in the development of fabricated buildings.
Fig. 1. Analysis of the externality of prefabricated construction
The prefabricated construction is a public product with strong commonweal and has external effect [11]. The developer’s development behavior will bring the rich public interest to the society, the Assembly type construction additional function’s beneficiary is the society overall, it provides the consumer the more comfortable living environment,
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however the operation stage usage expense reduction amplitude is insufficient to urge the consumer to buy the construction cost and the price higher assembly type construction. Developers are seeking economic benefits, in the current market economy, developers can’t obtain that part of the external benefits. The relationship between the amount of fabricated building development and the price, as shown in Fig. 1. The marginal cost is MC, the private marginal income is MR, the social marginal income is MSR, the developer in order to pursue private benefit maximization, the actual development quantity is Q1 , and the development quantity that achieves social income maximization should be Q2 . As a result, the external economy of the fabricated construction economy is produced, which is represented as the vertical distance between MR and MSR, that is, ME. Through the above analysis, it can be seen that developers have some benefits from the development of fabricated buildings as social benefits. Among them, ecoenvironmental benefits indirectly generate huge positive benefits for the beneficiary groups and even the whole society. However, for the implementation of ecological environmental protection, the implementation of the main cause of some losses, only the main body of the prefabricated construction of reasonable compensation, in order to motivate it to better use prefabricated construction methods for construction, improve the industrialization rate of the building. Therefore, the society should take the initiative to develop the assembly-type construction enterprises must compensate, encourage them to continue to develop and form a virtuous circle. So that the assembly-style building can bring more benefits to society.
4 The Establishment of Apportionment Model 4.1
The Establishment of the Model
In the previous article, it has been mentioned that the development of the assemblytype building is not enough to hinder the development of the assembly-type building is a big reason, the need to exert external forces to strengthen the market power, and the government is to improve the market dynamic mechanism of the strong external thrust, the government needs according to the establishment of a complete set of construction price compensation mechanism, to determine the reasonable compensation standards, is conducive to fully mobilize developers to develop assembly-style building enthusiasm and enthusiasm, assembly-style building to obtain rapid development, and then drive the modern construction industry structure adjustment, economic benefits and environmental benefits significantly improved. Through the market competition, Lowcost, powerful, good quality of the assembly-type building is selected, the government’s compensation for the assembly type of building with the market competition is shrinking. Thus forming a virtuous circle Although the assembly-type building has the advantages of environmental protection and energy saving, but the high price has been puzzling the development of the assembly-style building, how to achieve the assemblystyle building and traditional construction costs flat or even lower than the traditional construction cost of the goal, need to work together. As the guide of the development
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of the assembly-type building, the government should make a reasonable incentive mechanism. Therefore, this paper puts forward the research of price compensation mechanism based on the loss of revenue. In this part, the paper introduces the model of the government and the developer to share the loss of revenue. Through the calculation of the loss of income from prefabricated construction. According to the principles of risk sharing in risk allocation and income distribution, the principle of apportioning loss of assembly construction is designed, that is, how much of the economic loss is determined by the amount of income obtained. The model is established as follows: First, based on the quantitative calculation of incremental benefits Calculated values of economic, environmental, and social benefits, and then calculate the percentage of benefits that the government and construction units have in incremental overall benefits. C1 þ P1 C2 þ P2 C3 C4
ð5Þ
ð1 P1 ÞC2 þ ð1 P2 ÞC3 C4
ð6Þ
PE ¼ GE ¼
Secondly, according to the calculated percentage factor to allocate green construction The amount of the incremental cost allocation. PC ¼ Ct PE
ð7Þ
GC ¼ Ct GE
ð8Þ
Among them, C1 represents the overall economic benefits brought about by prefabricated buildings, C2 represents environmental benefits, C3 represents social benefits, and C4 represents the sum of incremental benefits brought about by prefabricated buildings. PE represents the allocation factor of the developer, and GE represents the share factor of the government. PC for the enterprise share of the assembly-type construction income loss; The cost of the assembly-type construction of the GC for the Government; P1 and P2 are the percentage of the construction unit’s own benefit in environmental and social benefits. 4.2
Comprehensive Benefit Calculation
4.2.1 Economic Benefits The economic benefits of prefabricated construction include the direct economic benefits of land, energy saving, water saving, material and so on. The economic benefits of the land section. The benefits of a built-up building economy include the benefits of surplus land and the benefits of taking full advantage of underground space, in other words, improving land use efficiency, reducing footprint and taking advantage of the benefits of existing buildings and roads.:
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Et;1 ¼ B1 þ Ut;1
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ð9Þ
Among them, Et;1 is the benefit of the Project section (yuan), B1 for the surplus land transfer income (yuan), and Ut;1 for the T-year use of underground space gains. Economic benefits of energy conservation. prefabricated constructions adopt environmental protection facilities and equipment, which can save electricity, while reducing coal combustion can save energy. Et;2 ¼ Pt ðQt;2 þ
1 Mt;2 Þ 3600
ð10Þ
Among them, Et;2 is the project Energy Saving benefit (yuan); Pt the unit price (Yuan/kwh) for the T-year, Qt;2 for the year t (kwh), Mt;2 is the energy value (KJ) saved by the reduction of coal combustion in the year t. The economic benefits of water conservation. The project saves water and can reduce expenses, mainly reflected in the prefabrication of prefabricated components in prefabricated building components, and less of the work on the site, so the use of water resources is more reasonable and efficient, resulting in economic benefits. Et;3 ¼ Wt Qt;3
ð11Þ
Among them, Et;3 is the water saving benefit (yuan) in the t year of the project; Wt is the water unit price (yuan/m3) in the t-th year; Qt;3 is the water saving volume of the project (m3). The economic benefits of materials. Similarly, the production of prefabricated components in prefabricated buildings can reduce the waste of materials and control the amount of materials used more accurately than the cast-in-place construction methods of traditional buildings, thus achieving the purpose of material conservation. Et;4 ¼ Xt;4 Yt;4
ð12Þ
Among them, Et;4 is the annual savings of the project in year t (yuan); Xt;4 is the price of the material in the t year of the project (yuan); Yt;4 is the nth project The amount of material saved in year t. As a result, the economic benefits of the entire project can be calculated: C1 ¼ Et;1 þ Et;2 þ Et;3 þ Et;4
ð13Þ
4.2.2 Environmental Benefits The method of construction of prefabricated buildings is very environmentally friendly and green, so it has high environmental benefits, mainly reflected in reduced carbon dioxide emissions. Therefore, the environmental benefits brought about by prefabricated buildings can be measured by the treatment cost of carbon dioxide and other exhaust gases.
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Environmental benefits from reduced CO2 emissions. Reducing CO2 emissions can save CO2 treatment costs. According to calculations, approximately 2.66 to 2.72 t CO2 per ton of standard coal is emitted, while the current cost per ton of CO2 is approximately 205 to 486 yuan. Et;5 ¼ At;5 Dt;5
ð14Þ
Among them, Et;5 is the environmental benefit of reduction of CO2 emission in the first year of the project (yuan); At;5 is the reduction of CO2 emission (t) in the year; Dt;5 is the year CO2 unit processing cost (yuan/t). The environmental benefits of fabricated buildings are: C2 ¼ Et;5
ð15Þ
4.2.3 Social Benefits The construction methods of traditional buildings make them have a lot of noise, dust, abandoned construction waste and sewage discharge are negative external impact on the surrounding communities, and dry construction methods of fabricated buildings can be a good way to avoid this shortcoming. Therefore, the social benefits of prefabricated buildings can be reduced by the treatment costs of sewage discharge. Reduce the disposal costs of construction waste emissions to measure. Et;6 ¼ Ft;6 Qt;6
ð16Þ
Among them, Et;6 is the reduction of pollutant emission and construction waste efficiency (yuan) in the tth year of the project; Ft;6 is the sewage treatment fee or construction waste disposal fee per unit volume of the region (yuan/m3); Qt;6 is the amount of waste water or construction waste that the project reduced during the year. So the social benefits brought about by prefabricated buildings are: C3 ¼ Et;6
ð17Þ
The combined benefits of prefabricated construction can also be expressed as: C4 ¼
n X
Et;t t ¼ 1; 2; 3. . .n
ð18Þ
1
From this, we can calculate their respective allocation coefficient by the benefit of the government and the developer, multiply the profit loss of the developer to calculate their respective amount. Through the above analysis, developers to develop assemblystyle building has some income to become social income. Among them, the ecological environment benefit indirectly to the benefit group and even the whole society produces the huge positive benefit. But for the implementation of ecological protection of the main body has caused a certain loss, only the implementation of the assembly-type construction of the main body to make reasonable compensation, can be encouraged to
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better use the construction of prefabricated assembly method for construction, improve the rate of building industrialization. The standard for loss-based compensation is to make it less profitable for developers to choose to develop assembly-style buildings than to choose to develop traditional buildings. Considering compensation on the basis of the main loss, the general use of the form of a level difference subsidy, that is, in the initial stage, the subsidy is higher, and then decreases year by day until the subsidy is eliminated. This is mainly because when the green building production technology matures gradually, the market recognition degree increases gradually, the development enterprise gradually increases, the development quantity increases gradually, each enterprise competition environment tends to be fair, the assembly type construction developer’s profit loss is smaller and lesser.
5 Conclusion The implementation of prefabricated building will result in an increase in initial investment, that is, incremental cost. At the same time, the incremental comprehensive benefits will not only belong to the construction unit. In the case where such benefits are not fully available, the construction unit is very It is difficult to independently choose to implement prefabricated building [12]. In the early stage of assembly-type construction, the government should introduce an effective incentive mechanism to effectively reduce the economic cost of assembly-type construction technology and fully mobilize the enthusiasm of the construction unit. To compensate the construction unit’s expenses and reduce the risk of cost investment, to encourage construction units to implement assembly-type construction. In addition, the construction technology of prefabricated assembly covers a wide range and has many impacts, and the geography, climate and construction level of our country are unbalanced, so the problems appearing in the construction process cannot be identical. Therefore, considering the influence of policy, economy and technology, and with the progress of technology and the development of economy, as well as the research, the research content will be continuously increased and the research methods will be improved. This paper makes some suggestions based on the present situation. First of all, the development and promotion of prefabricated assembly construction is both realistic and urgent. In order to solve the practical problems in engineering practice, prefabricated constructions should overcome the traditional technical concepts, grasp the key technology of “four environmental protection”, and pay attention to the differences of different regions and different climates in China [13]. Secondly, to increase the cost-benefit of the assembly-type building life cycle, combining prefabricated assembly construction technology with economic research, through new research ideas and methods, according to the development stage and requirements of prefabricated construction, timely promulgate the economic incentive measures of diversification, multi-level and multi-angle, and further standardize green construction and promote green construction. Finally, the assembly-type building in China has just arisen, the Precast Assembly technology system has not been fully validated, it is suggested that in the future
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promotion practice, strengthen the application of prefabricated assembly technology test and feedback, and constantly improve the assembly-type construction technology system.
References 1. Zhu, Q.: National Assembly-type building policy summary. Prospective Industry Research Institute (2018) 2. Lee, Y.: Housing Construction Department: 2025 years of assembly-type building accounted for more than 50% new building. Tiles, (7) (2016) 3. Lee L.H.: Research on price compensation mechanism of assembled building. Constr. Econ. (2016) 4. Qi, B.K.: Research on the design of government compensation mechanism of assembly-type building based on game theory. Build. Technol. (8) (2017) 5. Qing, Q.K.: Research on revenue sharing in the different decision modes of assembled VMI system. Control Dec. Making (2014) 6. Wu, Y.L., Shen, L., Sun, Q.H.: Study on economic incentive measures for green construction of construction project. Enterp. Econ. (2015) 7. Lee, M., Liu, Y.Z.: Study on incentive mechanism of green building based on ecoenvironmental benefit compensation. Sci. Technol. Progress Countermeasures (2017) 8. Li, M.: Consideration about construction of compensation mechanism of green building healthy development. Adv. Mater. Res. 598, 71–74 (2012) 9. Zhang, X.L., Platten, A., Shen, L.: Green property development practice in China: Costs and barriers. Build. Eviron. (46) (2011) 10. Qiao, Y.N.: Study on the incentive mechanism of green construction in Construction Engineering. Xi’an Architecture University (2009) 11. Bo, Y., Zhao, L.M.: Research on Externality and incentive mechanism of green building development. Sci. Manage. 1, 137–138 (2014) 12. Wang, W.R., Sai, Y.X., Li, H.M.: Study on energy-saving renovation of existing buildings and optimal combination model of environmental compensation model. J. Shaanxi Normal Univ. (2013) 13. Qian, Z.F., Lu, H.M.: Reflections on the development of China’s architectural industrialization. Jiangsu Constr. (2008)
The Correlation Between Intangible Assets and Business Performance of Listed Construction Enterprises in China Yousong Wang1, Jing Huang1, and Hongyang Li1,2(&) 1 School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China [email protected] 2 Department of Construction Management, South China University of Technology, Guangzhou, China
Abstract. This research starts with a comprehensive review of previous studies of intangible assets and their value relevance. 30 listed construction enterprises in China were then chosen and their statistical data between 2010–2015 were used to set up panel data regression models. The empirical analysis of the correlation between intangible assets and enterprise business performance were carried out in the end. It is concluded that the overall intangible assets have a significant positive effect on enterprise business performance. Every 1% increase in the number of intangible assets will increase the enterprise’s basic earnings per share by 0.05 yuan when the other conditions remain unchanged. Intangible assets of rights have the least influence coefficient while the technical intangible assets possess the greatest one. The contribution of technical intangible assets on enterprise business performance occupy the top of the list, although it only accounts for 0.74% of the total intangible assets. By taking into account of the status quo of intangible assets of the listed construction enterprises in China, this paper also provides some suggestions for strengthening the cultivation and management of intangible assets for enterprises. Keywords: Listed construction enterprises performance Correlation China
Intangible assets Business
1 Introduction Since the 1980s, the importance of intangible assets has increased gradually and become a driving factor for enterprises to make profits. Enterprises are paying more and more attention to the community of tangible assets and intangible assets [1]. Intangible assets are also the powerful bargaining chip for modern enterprises to win market competition in the context of economic transformation. At present, China’s construction industry is still developing in a labor-intensive and extensive mode. The increasing output value is achieved mainly through increasing investment in tangible assets, rather than relying on advanced technical means, highquality management level, good corporate reputation and other intangible assets. Compared with other industries in China, the profits of construction industry are © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1295–1308, 2021. https://doi.org/10.1007/978-981-15-3977-0_100
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relatively low, which is related to the insufficient investment of intangible assets as a whole. It is proposed that with the arrival of the knowledge age, the definition of intangible assets of construction enterprises is a challenge, and its scientific management is also a progress [2]. This paper chooses 30 listed construction enterprises in China and summarizes the current situation of intangible assets according to the accounting standards. Panel data models are then established to conduct regression analysis regarding intangible assets and business performance of the enterprises. The conclusions are expected to provide suggestions for construction enterprises to optimize assets structure. The results are also helpful to strengthen the cultivation and management of intangible assets, so as to enhance the market competitiveness for the construction enterprises in China.
2 Literature Review 2.1
Definition and Classification of Intangible Assets
From the perspective of accounting, intangible assets refer to identifiable non-monetary assets owned or controlled by enterprises without physical form [3]. Based on the accounting definition method, Zhao Min (2012) divided intangible assets into three categories, namely, intangible assets of rights, technical intangible assets and other intangible assets according to the specific content reflected by intangible assets themselves [4]. Wang Weiping (2007) divided intangible assets into knowledge-based intangible assets and power-based intangible assets. The former refers to a kind of intangible assets that are highly accumulated through knowledge, wisdom and technology, most of which are protected by law. And power-based intangible assets are a kind of intangible assets that generate excess returns mainly through franchisor, which are protected by administrative power [5]. The definition of intangible assets in economics is more extensive. In terms of macro level and long-term investment, intangible assets include not only material assets, intellectual assets, but also human resources and organizational assets. Hansen and Serin (1997) put forward that human resources, organizational assets, advertising and marketing were also important factors which greatly influenced the innovation and economic growth of the enterprise. These intangible assets may have a greater impact on economic growth [6]. Corrado et al. (2009) divided intangible assets into three categories: computer information assets (software, database, etc.), innovation assets (R&D, copyrights, patents, etc.) and economic competitiveness assets (brands, human and organizational resources, etc.) [7]. This method is applicable to macro-economic research. However, different industries have different characteristics, and this method is not suitable for the study of intangible assets of specific industries. In the field of construction, Zhang Maolin (2000) analyzed the positive effect of intangible assets on project contracting, as well as the effect on project quality and construction production efficiency. Zhang put forward that human resources
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management, information construction, corporate culture, corporate risks management and leadership innovation constitute the “five core” of intangible assets [8]. Zhang Dingzu and Tan Lixin (2006) thought that intangible assets of construction enterprises include qualification level, business performance, all kinds of high quality and enterprise quota, construction techniques for new structures, as well as managerial experiences mastered by the enterprises [9]. Shao Jianying (2012) believed that the profits of intangible assets in construction industry were indirect and intangible assets had the property of secondary development [2]. In addition, there were also some scholars using financial data disclosed by listed enterprises to analyze the correlation between intangible assets and business performance. Different definition and classification methods have enriched the connotation of intangible assets. Among them, accounting method focuses on whether intangible assets can bring economic benefits to enterprises from the perspective of assets judgment. It measures the value of various intangible assets through measuring their acquisition costs. This is also a measurement method commonly used in various industries. Accordingly, in this paper, the intangible assets are defined by adopting relevant definitions in enterprise accounting standards, namely, they are identifiable non-monetary assets owned or controlled by enterprises without physical form. 2.2
Value Relevance of Intangible Assets
Baruch Lev is perhaps the leading accounting academic who is writing and researching on intangibles. Through his study of enterprises investment on R&D (1979–1999), Lev found that intangible assets gradually replace the role of tangible assets in corporate functions. There’s a significant positive correlation between intangible asset investment and productivity growth and corporate profits [10]. Crass et al. (2014) studied the different contributions of intangible assets to labor productivity in Germany from 1995 to 2006 [11]. Gennady and Elena (2015) analyzed the commercial value of intangible assets and it’s proved that effective management of intangible assets can help Russian food retailers gain additional competitive advantages [12]. In China, Xue Yunkui and Wang Zhitai (2001) found that intangible assets play a more important role in business activities than fixed assets by examining the data of Shanghai stock market from 1995 to 1999 [13]. Guan Honghui (2011) researched the development situation of China’s service industry from 2003 to 2008. It’s found that the average annual growth rate of intangible assets of China’s service industry is 40%, but the correlation between intangible assets and operating profit is not significant, which may be related to the fact that the industry itself is labor-intensive and the entry threshold is relatively low [14]. Through the analysis of different industries from 2007 to 2011, Zhao Min (2012) found that technical intangible assets played a positive role in the performance of manufacturing, mining and real estate companies and those kinds of resources had a significant impact on business performance of enterprises [4]. The above studies show that intangible assets are an important factor for enterprises to obtain benefits. They also play a guiding role for enterprises to make better use of
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intangible assets and promote their operation. However, in the existing literatures, there are few studies focusing on the intangible assets of construction industry through quantitative approaches, and the applicability of the existing measurement models in construction field still needs further study.
3 Research Hypothesis and Model Establishment 3.1
Research Hypothesis
In this paper, the correlation between intangible assets and business performance will be investigated from two aspects. Firstly, the intangible assets of listed companies are taken as a whole for regression analysis, so as to grasp the impact of overall intangible assets on the enterprise’s business performance. Then, examine the contribution of different types of intangible assets to business performance from the internal structure of intangible assets. Accordingly, the following hypothesis are proposed: Hypothesis 1: intangible assets have a significant positive impact on business performance as a whole Hypothesis 2: different types of intangible assets have different effects on business performance 3.2
Model Establishment
Panel data model has obvious advantages in explaining dynamic information about economic phenomena. The general form of a panel data model is: Yi;t ¼a þ cZi þ b1 X1it þ b2 X2it þ þ bk Xkit þ li;t
ð1Þ
In Eq. (1), i = 1, 2…, N represents the number of samples on the cross section; t = 1,2,… ,T represents the study period. K means the number of independent variables. Yi;t represents the value of the dependent variable at cross-section i and period t, and Xkit represents the independent variable.li;t stands for random error term. Zi is for unobservable individual influencing factors on the cross section. a , c , b1 ,… , bk represent the parameters to be estimated. Based on Lev’s research method (1999) [10] and referring to Zhao Min’s empirical research model (2012) [4], in this paper, the following panel data models will be used to examine the impact of the overall intangible assets and different types of intangible assets on business performance. PEPSi;t ¼ a0 þ a1 INTANG0i;t þ a2 PBi;t þ a3 CSi;t þ a4 ASSETi;t þ li;t PROFITi;t ¼ b0 þ b1 INTANG1i;t þ b2 INTANG2i;t þ b3 INTANG3i;t þ b4 PBi;t þ b5 CSi;t þ b6 ASSETi;t þ l0i;t
ð2Þ ð3Þ
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Variable Definition
3.3.1 Dependent Variable PEPS represents the basic earnings per share, which is calculated by dividing the current net profit of common shareholders by the weighted average of the issued common shares. It’s an important basis reflecting the profitability of the enterprise. When examining the impact of the overall intangible assets, PEPS is taken as the index to measure business performance. PROFIT represents the operating profit. When examining the influence of different types of intangible assets, PROFIT is taken as the index of the dependent variable. 3.3.2 Independent Variable INTANG0 means the natural logarithm of the total intangible assets at the end of year t, and the intangible assets are defined by adopting relevant definitions in enterprise accounting standards. According to the content and nature reflected by intangible assets themselves, the specific composition of intangible assets can be further divided into rights, technology and other intangible assets. Among them, INTANG1 is used for intangible assets of rights, INTANG2 for technical intangible assets and INTANG3 for other intangible assets. 3.3.3 Control Variable PB means the P/B ratio. It represents the ratio of share price to the net asset value, which is used to control the potential impact of corporate risk and growth. P/B = the closing price/ net asset value per share x100%. CS is the asset-liability ratio, which refers to the percentage of total liabilities in total assets. It is used to control the impact of a enterprise’s capital structure and solvency. CS = total liabilities/ total assets x100%. ASSET is the natural logarithm of a enterprise’s total assets, which is used to control the impact of the enterprise scale. And total assets refer to all assets owned or controlled by an enterprise that can bring economic benefits, including current assets, longterm investments, fixed assets, intangible assets and deferred assets. a0 and b0 represent the constant terms, a1, …, a4 and b1, …, b6 are for regression coefficients. l and l’ represent the random errors, and i refers to the sample companies. The definitions of each variable are shown in Table 1.
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Type Dependent Variable Independent Variable
Control Variable
Code PEPS PROFIT INTANG0 INTANG1 INTANG2 INTANG3 PB CS ASSET
Explanation The basic earnings per share of the sample enterprise = net profit/total stock The operating profit of the sample enterprise The natural logarithm of the total intangible assets of the sample enterprise Intangible assets of rights of the sample enterprise Technical intangible assets of the sample enterprise Other intangible assets of the sample enterprise P/B = the closing price/net asset value per share x100% CS = total liabilities/total assets x100% The natural logarithm of a enterprise’s total assets
4 Sample Selection and Data Statistics 4.1
Sample Selection
On May 1, 2016, Ministry of Finance of China incorporated the construction industry and real estate industry into the pilot scope of replacing business tax with value-added tax, and the accounting of the industry changed accordingly. In order to avoid the possible interference brought by the tax reform to the research object, the research scope of this paper is set as 2010–2015. Information of the listed construction enterprises in Shanghai and Shenzhen was collected through CCERDATA database, and the criteria for sample selection are as follows: (1) The enterprises with ST and *ST losses were excluded. (2) The enterprises that had been suspended or suspended from listing as of December 31, 2015 were excluded. (3) The enterprises with missing financial data were excluded. (4) The enterprises whose main business has changed were excluded. According to the above standards, 30 listed sample enterprises in construction industry were finally obtained. 4.2
Data Statistics
4.2.1 Overall Situation of Intangible Assets The size of the sample enterprise’s intangible assets and their proportion in total assets are shown in Table 2. It can be seen that the total assets and intangible assets of listed companies in China’s construction industry are both increasing year by year.
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Table 2. Quantity of intangible assets of listed construction enterprises Year
N
2010 2011 2012 2013 2014 2015
30 30 30 30 30 30
Mean intangible assets (thousand RMB) 2,068,996 2,532,707 3,243,530 3,435,582 4,064,940 4,895,835
Mean total assets (thousand RMB) 48,113,126 59,912,769 74,161,334 87,028,223 99,597,641 111,832,835
The proportion of intangible assets (%) 4.30 4.23 4.37 3.95 4.08 4.38
In 2010, the average intangible assets of the sample construction enterprises were about 2.069 billion yuan, which reached 4.896 billion yuan in 2015, and it’s 2.4 times that of 2010. The proportion of intangible assets in total assets was about 4.2%. In 2015, it reached the maximum value of 4.38% in the research period, reflecting that listed construction enterprises have increased their attention and investment on intangible assets during the development process in recent years. According to relevant statistics, intangible assets of many enterprises in western developed countries account for 50–60% of total assets. By investigating the assets of thousands of American enterprises from 1978 to 1998, some scholars found that the ratio of tangible assets to intangible assets changed from 8:2 to 2:8 [15]. Compared with the situation of developed countries, the proportion of intangible assets in China’s listed construction enterprises is relatively low, and the overall scale of intangible assets still needs to be improved. The reason for such a difference, on the one hand, it comes from different definitions of intangible assets at home and abroad. Foreign accounting of intangible assets is more extensive, including organizational assets and brand value. On the other hand, it is related to the development characteristics of the industry itself. The expansion model of the construction industry relies more on increasing investment in tangible assets such as fixed assets and labor than on increasing intangible assets 4.2.2 Composition of Intangible Assets The specific compositions of intangible assets are shown in Table 3, which can be obtained by referring to the annotated information of annual report of the listed enterprise. According to the statistical results, various types of use rights account for the largest proportion, among which land use rights account for 20.95%, and franchising rights account for 59.90%. However, the size of trademarks, management system, professional qualification and copyrights is very small, each accounting for less than 0.01%.
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Item
N
Intangible assets Land use rights Venue use rights Highway operation rights Mining rights Maritime use rights Franchise rights Other special permissions Software Professional qualifications Patents Proprietary technology Copyrights Management systems Trademarks Other
180 180 180 180 180 180 180 180 180 180 180 180 180 180 180 180
Total (thousand RMB) 607,247,700 127,183,148 518,169 58,425,096 30,621,078 791,965 363,741,098 17,148,903 2,060,364 15,063 736,000 1,676,395 17,234 9,825 1,393 4,301,964
Average (thousand RMB) 3,373,598 706,573 2,879 324,584 170,117 4,400 2,020,784 95,272 11,446 84 4,089 9,313 96 55 8 23,900
Standard deviation
Occupying overall intangible assets (%)
9,053,936 1,714,415 31,326 1,670,425 821,807 41,634 6,693,081 1,186,909 28,270 639 14,476 47,706 490 427 37 97,394
100 20.95 0.09 9.62 5.04 0.13 59.90 2.82 0.34 0.002 0.12 0.28 0.0028 0.0016 0.0002 0.71
Furtherly, according to the nature and content of intangible assets themselves, the above specific compositions can be divided into three types: intangible assets of rights, technical intangible assets and other intangible assets. The quantity and growth are shown in Table 4.
Table 4. The number and growth situation of different types of intangible assets Type of intangible assets Rights Technology Other
Average (thousand yuan) 99,738,243 750,843 718,864
Occupying overall intangible assets (%) 98.55 0.74 0.71
Average annual growth (%) 18.96 27.06 68.37
1. Intangible assets of rights include site use rights, highway operation rights, mining rights, maritime use rights, franchise rights and other special permissions. This kind of intangible assets mostly come from special policies or administrative licenses of the state, and the enterprises can obtain exclusive rights of resources in a certain way. The value of these rights accounts for 98.55% of the total intangible assets. 2. Technical intangible assets consist of software, professional qualifications, patents, proprietary technology, copyrights, etc. Such intangible assets can enable enterprises to continuously improve their production processes, reduce production costs, and achieve higher production efficiency so as to obtain excess profits. The
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statistical results in Table 4 show that the proportion of software (0.34%), patents (0.12%), proprietary technology (0.28%) is very low. Those technical intangible assets in total only account for 0.74% of the overall intangible assets. It reflects the poor quality of intangible assets of listed construction enterprises in China, and the overall structure of assets is still low-tech. 3. Other intangible assets refer to management systems, trademarks and other intangible assets that have not been disclosed. Such intangible assets can create a good development environment for enterprises, create favorable production conditions, and combine with other assets to enhance the competitiveness of enterprises. This kind of intangible assets accounts for 0.71% of the total intangible assets. In terms of quantity, the number of intangible assets of rights is the largest (98.55%), followed by technical intangible assets and other intangible assets. Obviously, the number of three types of intangible assets varies greatly, which is partly attributed to the defects of the disclosure rules of the enterprise accounting standards system. China currently has certain limitations to the definition of intangible assets. When measuring intangible assets, more attention is paid to the transaction itself. Meanwhile, the quantitative standard guidance on resources related to enterprise competitiveness is insufficient, and it is difficult for construction enterprises to reflect the advantages formed in the operation process through financial statements [16]. In terms of the growth rate, other intangible assets grow the fastest, with an average annual growth rate of 68.37%. Secondly, technical intangible assets increased by 27.06% annually, and the average annual growth of intangible assets of rights is 18.96%. Above all, technical intangible assets and other intangible assets account for a small proportion – less than 1% of the total number of intangible assets, but both have grown rapidly in recent years, reflecting that China’s listed construction enterprises pay more and more attention to the investment in computer products and commercial copyrights.
5 Empirical Test and Regression Analysis 5.1
Unit Root Testing
Some non-stationary economic sequences may show a trend of common change. However, these sequences themselves do not necessarily have direct correlation, and their regression results are of no practical significance. Therefore, the unit root test is needed before using panel data model to avoid false regression [17]. In this paper, the unit root test methods of LLC, IPS, Fisher-ADF and Fisher-PP are used to comprehensively determine whether the panel data are stationary sequences. Among them, LLC is for common unit root test, and others are for individual unit root test. Through Eviews9 software testing, the results are summarized in Table 5. The significance levels of the variables INTANG2, PB and ASSET are all less than 0.05, which rejects the original assumption that the sequence had a unit root. It’s concluded that these variables are all stationary sequences.
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Other variables also pass the common-rooted LLC test, and pass at least one test in IPS, Fisher-ADF and Fisher-PP method. Therefore, all the above variables pass the unit root test and they can be used for further regression analysis. Table 5. The statistical results of unit root test Variable PEPS PROFIT INTANG0 INTANG1 INTANG2 INTANG3 PB CS ASSET
5.2
Commend-rooted test Individual-rooted test LLC IPS Fisher-ADF Fisher-PP 0.0000 0.1089 0.0004 0.0000 0.0000 0.7679 0.4829 0.0000 0.0000 0.0086 0.1514 0.0000 0.0000 0.2547 0.3335 0.0129 0.0000 0.0031 0.0020 0.0000 0.0000 0.6816 0.0026 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0595 0.0113 0.0000 0.0000 0.0028 0.0000 0.0000
Model Testing
Panel data model can be divided into pool model, fixed effects model (FE) and random effects model (RE). FE and RE can be further divided into individual effects model and time effects model. In order to distinguish the regression types of model (2) and model (3), further analysis can be carried out through LR test and Hausman test. Table 6 is the test result of model (2) in Eviews9, where (1)–(3) are three situations of LR test, and (4) represents Hausman test. Table 6. Statistics of LR test and Hausman test of model (2) Model assumption Statistic (1) Cross-section F 10.521404 (1) Cross-section Chi-square 207.329347 (2) Period F 0.700916 (1) Period Chi-square 4.419233 (3) Cross-Section/Period F 9.575969 (1) Cross-Section/Period Chi-square 215.401665 (4) Cross-section random 94.638153
Prob. 0.0000 0.0000 0.6236 0.4908 0.0000 0.0000 0.0000
The results show that null hypothesis of the pool model is rejected by situation (1) and situation (3) in the LR test, indicating that the mixed regression model is not applicable. The probability of situation (4) is 0.0000 and the individual-time point RE model is also rejected. Therefore, model (2) which refers to the regression model of overall intangible assets and business performance is determined as an individual-fixed panel data model.
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Similarly, according to the results in Table 7, model (3) which represents the regression model of different types of intangible assets and operating performance is also an individual-fixed panel data model. 5.3
Results Analysis
The least square method is used to make regression analysis for model (2) and model (3), and the calculation results are shown in Table 8 and Table 9. Table 7. Statistics of LR test and Hausman test of model (3) Model assumption Statistic (1) Cross-section F 28.635183 (1) Cross-section Chi-square 349.600381 (2) Period F 0.727852 (1) Period Chi-square 4.652073 (3) Cross-Section/Period F 24.95991 (1) Cross-Section/Period Chi-square 352.951421 (4) Cross-section random 25.390784
Prob. 0.0000 0.0000 0.6037 0.4598 0.0000 0.0000 0.0003
5.3.1 Overall Intangible Assets and Business Performance In Table 8, the adjusted R2 is 0.72 which indicates that the explanatory effect of independent variables on dependent variables is relatively satisfactory. The F-statistic value is 14.63968 and the probability is zero, indicating that the fitting effect of the model is acceptable. Table 8. Regression results of model (2) Variable C INTANG0 PB CS ASSET Effects Specification Adjusted R2 F-statistic Prob(F-statistic)
Coefficient 6.987503 0.051273 −0.063484 −0.001012 −0.302455
t-Statistic
Prob.
6.758116 2.849132 −5.226549 −0.299806 −5.572435
0.0000 0.0050 0.0000 0.7648 0.0000
0.715471 14.63968 0.000000
Consequently, the overall intangible assets, P/B ratio and total assets are the factors that affect the enterprise’s business performance. The influence coefficient of overall intangible assets is 0.05 with a probability of 0.005 and it passes the test of significance, showing that the contribution of the overall intangible assets to the enterprise’s
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basic earnings per share is positive and significant. On the condition that other variables remain unchanged, every 1% increase in the number of intangible assets will increase the enterprise’s basic earnings per share by 0.05 yuan. This result validates hypothesis 1, that’s to say, intangible assets as a whole have a significant positive impact on the enterprise’s business performance. 5.3.2 Different Types of Intangible Assets and Business Performance In Table 9, the adjusted R2 of the model is 0.72, the F-statistic value is 14.63968 and the probability is zero. This significance test also shows a satisfying result about the model fitting effect. The specific analysis of the three types of intangible assets is as follows: (1) Intangible assets of rights Regression results show that the influence coefficient of the variable INTANG1 is positive, and the t-statistic value of 0.0014 passes the significance test, indicating that intangible assets of rights are significantly and positively correlated with the operating profit of the sample enterprise. The influence coefficient is 0.19, that is, if other variables remain unchanged, the operating profit will increase by 0.19 million yuan for every 10,000 yuan increase in rights value. Although rights do not have the physical form, they can make the construction enterprise in a certain monopoly position and obtain exclusive rights of resources through special national policies or administrative licenses. Take the land use rights as an example, due to the certain scarcity of this rights, such intangible assets can sometimes bring more value to the construction enterprise than fixed assets. However, the influence coefficient reflects that intangible assets of rights just have a little influence on business performance.
Table 9. Regression results of model (3) Variable C INTANG1 INTANG2 INTANG3 PB CS ASSET Effects Specification Adjusted R2 F-statistic Prob(F-statistic)
Coefficient −567811.2 0.189329 10.97935 6.762273 −4576.156 −495.4796 32455.39
t-Statistic
Prob.
−0.628088 3.248181 3.412892 3.55371 −0.43748 −0.166363 0.761886
0.5309 0.0014 0.0008 0.0005 0.6624 0.8681 0.4474
0.920954 60.58605 0.000000
(2) Technical intangible assets The influence coefficient of the variable INTANG2 is 10.98, and the t-statistic value of 0.0008 passes the significance test, showing that there is also a significant positive
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correlation between technical intangible assets and operating profits. Under the condition that other variables remain unchanged, the increase of technical intangible assets will bring the increase of operating profit of 109,800 yuan for every 10,000 yuan. Technical intangible assets are a kind of technical products presented by direct or indirect carriers, which are technological achievements in an intelligent form. Although it only accounts for 0.74% of overall intangible assets, its contribution to the enterprise’s business performance is the most outstanding, and its impact is far greater than that of the intangible assets of rights. Technical intangible assets play a significant role in promoting the company’s operation and development, and construction enterprises need to strengthen the investment, cultivation and disclosure of technical intangible assets. (3) Other intangible assets The test result of variable INTANG3 is similar to that of variable INTANG2. The influence coefficient is 6.76, indicating that when other variables remain unchanged, the operating profit will increase by 6.76 million yuan for every 10,000 yuan increase in other intangible assets value. As controllable economic resource, such intangible assets also bring excess benefits to the enterprise. Its contribution to the enterprise’s business performance is less than that of technical intangible assets, but it has a greater impact than intangible assets of rights. The above regression results also verify hypothesis 2, that is, the correlation between three types of intangible assets and corporate business performance is different.
6 Conclusions Based on the data (from 2010 to 2015) of 30 listed construction enterprises in China, panel data regression models are established in this study to analyze the correlation between intangible assets and business performance. Conclusions are as follows: (1) The intangible assets account for 4.2% of total assets of the listed construction enterprises and of the intangible assets, 98.55% are rights intangible assets; (2) Intangible assets as a whole have a significant positive impact on the enterprise’s business performance. Every 1% increase in the number of intangible assets will increase the enterprise’s basic earnings per share by 0.05 yuan when other variables remain unchanged; (3) There is a significant positive correlation between the three types of intangible assets and the enterprise’s business performance. Technical intangible assets only account for 0.74% of the total intangible assets, they contribute the most however. The number of intangible assets of rights is the largest while their impact is relatively weak. At present, the overall scale of intangible assets of China’s construction enterprises is expanding. There is still a long way to go in developing an accounting model for the world of intangibles. Strengthening the awareness of cultivating and maintaining intangible assets and conducting scientific measurement of intangible assets, is an important way to deal with the downward risks of the overall industry. Advanced technology and commercial copyrights are important asset elements. Intensive use of
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IT and other technical assets allows the enterprises to manage operations and new relationships efficiently. In conclusion, construction enterprises should strengthen the investment, management and confirmation of technical intangible assets, and should also pay attention to the accumulation of independent development of intangible assets.
References 1. Higson, C.: Intangibles: Management, Measurement, and Reporting: by Baruch Lev. Int. J. Account. 36(4), 501–503 (2001) 2. Shao, J.Y.: The extension of intangible assets connotation based on the particularity of construction enterprises. J. Value Eng. 31(11), 121–122 (2012) 3. IASC. International Accounting Standards 2000, Standards of Accounting Standards Committee of The Ministry of Finance. pp. 543–647 (2000) 4. Zhao, M.: Study on industrial characteristic and internal structure of intangible assets and the relationship with corporate performance. J. Rev. Finance Econ. 06, 57–63 (2012) 5. Wang, W.P., Shi, Y.: Four categories of intangible assets of modern enterprises. J. Account. Res. 12, 58–60 (2007) 6. Hansen, P.A., Serin, G.: Will low technology products disappear? The hidden innovation processes in low technology industries. J. Technol. Forecast. Social Change 55(2), 179–191 (1997) 7. Corrado, C., Hulten, C., Sichel, D.: Intangible capital and U.S. economic growth. J. Rev. Income Wealth. 55(3), 661–685 (2009) 8. Zhang, M.L.: The role of intangible assets in modern construction enterprises. J. Manage. Admin. 9, 10–12 (2000) 9. Zhang, D.Z., Tan, L.X.: BOT financing model: a new idea of capital operation of construction enterprises. J. Const. Econ. 4, 34–37 (2006) 10. Baruch, L.: R&D and capital markets. J. Appl. Corp. Finance 11(4), 21–35 (1999) 11. Crass, D., Licht, G., Peters, B.: Intangible assets and investments at the sector level: empirical evidence for germany. In: Bounfour A., Miyagawa T. (eds) Intangibles, Market Failure and Innovation Performance. Springer, Cham (2014) 12. Ivanov, G., Mayorova, E.: Intangible assets and competitive advantage in retail: case study from Russia. J. Asian Soc. Sci. 11(12), p. 38 (2015) 13. Xue, Y.K., Wang, Z.T.: Research on intangible asset disclosure and its value relevance. J. Account. Res. 11, 40–47 (2001) 14. Guan, H.H.: Study of intangible assets impact on performance of listed companies. Dissertation of University of Science and Technology of China (2011) 15. Chen, Q.X.: Study on the contribution of intangible assets to enterprise value in China. J. Friends Account. 27, 55–58 (2013) 16. Shui, X., He, Y.Q., Xue, L.: A detailed discussion on the definition and scope of intangible assets in China. J. Friends Account. 34, 38–39 (2012) 17. Bornhorst, F., Baum, C.F.L.: Stata module to perform Levin-Lin-Chu panel unit root test. J. Stat. Software Comp. (2006)
Structure Analysis of Information Flow in Project Design Stage Based on Information Theory Yunshan Jiang, Pengpeng Xu(&), Chao Mao, and Yan Fu Faculty of Construction Management and Real Estate, Chongqing University, Chongqing 400045, China [email protected] Abstract. To explore the importance of information in the project design stage, the uncertainty of information state of each link in the project design stage is analyzed through the information entropy analysis. And the difficulty of the obstacle encountered in each link is analyzed through the information distance theory. Then, the TBS method in product design is adopted to analyze the information state of the project architectural design stage. The result shows that when the demand information of the construction unit or the owner is fuzzy, more information needs to be processed in the design process. This leads to lower design efficiency and lower customer satisfaction with the result. This paper proves the importance of information in the project design stage from the perspective of information and provides the basis for the improvement of efficiency and customer satisfaction in the project design stage. Keyword: PLC distance
Project design TBS Information entropy Information
1 Introduction The rapid development of information technology has promoted the progress of society and various industries, including the construction industry [1]. But in the construction industry, the application of information and information technology is not obvious enough [2]. Partly because we don’t know enough about how information affects the project. While the information and information technology are increasingly used by project personnel in all types of industry, not much is known on the characteristics of these information and information technology that contribute to project success. In the project life cycle, the construction unit or the owner’s demand information affects the total project life cycle stages, especially the construction design phase, and these demand information is directly translated into the design parameters of the architectural design stage during the project whole life cycle. In addition, there is a certain similarity between the product design in the manufacturing industry and the project design stage in the whole life cycle phase of the project. The enterprise takes customer demand as the foundation of development in the product design in the manufacturing industry [3]. Understand the customer demand information and reflect the customer demand information to the various stages of the © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1309–1324, 2021. https://doi.org/10.1007/978-981-15-3977-0_101
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enterprise PLM (product life cycle management) process, so that the enterprise can truly provide customers with the required products.
2 Project Design Phase in PLC The design stage of construction engineering project management is very significant [4]. In the project life cycle literature, the building design phase was deemed early on to be essential to the result of the whole stage [5]. The achievement of the building design phase has a great influence on the cost, quality and time of the project [6]. Moreover, a satisfactory design is the main objective of building design stage in term of the rule of “The customer is god’’. The information provided by the construction unit or the owner about the design they want to receive is inaccuracy and extremely limited. Furthermore, the information transmission between the designers to designers and the construction units to designers is inefficient. All of this increased the difficulty of design work. Our purpose is thus to improve our understanding of the impacts of information on design work and on design performance. More specifically, we study the status and delivery process of information in architectural design stage to provide theoretical guidance for the work of the design stage from the angle of information theory. In the manufacturing industry, the research on this aspect is relatively mature. Therefore, we introduce the concept of products of manufacturing to the whole life cycle of buildings. Considering the building entity as a product, but one-time product and one-off production line. By combining the design stage of the whole life cycle and the design stage in manufacturing, we find that the three main subjects of the design stage can be summarized as follows: 1) construction unit demand structure;2) building functional structure 3) architectural physical structure [7]. First, designers think of meeting the construction unit demand as the primary goal. Second, the information flow is transformed from the demand structure of the construction unit to the building functional structure in the construction project through the function diagram. And then the functional requirements of the construction unit are formed. Finally, in the transfer process of functional structure to physical structure, TBS modeling method is adopted to complete the transformation of functional structure to physical structure [8]. Moreover, for the further study of the impact of information in the design stage, this paper makes a quantitative analysis of the information flow structure in the transformation process. 2.1
Construction Unit Demand Structure
The first stage is construction unit demand structure, the construction unit demand mainly included: quality requirements (Q), appearance requirements (A), design reliability demand (D), life demand (L), service demand (S), price demand (P) [9]. The realization of demand structure is the common goal of design unit and construction unit. The identify of construction unit demand structure is based on the full exchange between the two parties. On the one hand, the construction unit want design unit to fully understand their intention, and they can get high quality design, on the other hand, the designer also want to be able to fully understand the requirements of the
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construction unit, thereby reducing design rework. So, the importance of information exchange is self-evident at this stage. 2.2
Building Functional Structure
The second stage is the building functional structure. The construction function structure is the abstraction, modularization and structural expression of the construction unit demand information at the functional level. Using the concept of WBS [10], the project functional structure was decomposed, and the project functional structure decomposition diagram was obtained. In the decomposition diagram, the whole project functional structure is decomposed into different functional design contents, while ensuring the integrity, logic and continuity of all functions. The decomposition process is broken down into each functional structure unit as the minimum unit. 2.3
Architectural Physical Structure
Architectural physical structure is the concrete expression of physical structure. The basic features of physical structure include: geometric structure, spatial layout and other physical structure characteristics. The geometrical structural features include the characteristics such as the area of the building, the number of floors and the type of the house. Spatial layout features include function module space layout, man-machine engineering. Other physical structure features include material structure characteristics and so on. The construction physical structure is constrained by external factors such as the demand of the construction unit and the actual production situation during the implementation process.
3 Information Status of the Building The information transferred from the demand structure of construction unit to the building functional structure, and then transferred from the building functional structure to the architectural physical structure during the project design phase of project life cycle. Information is always changed from one state to another. It reflects the liquidity of information in the project design stage. This paper uses the relevant theories of information theory to analyze the information transmission in design stage. There are two information types in the information transmission, one is the information that should be delivered itself, another is the information that needs to be consumed in the process of information transmission. The information itself in each stage is called the building information, and the information that needs to be consumed is called the information distance. The information distance represents the difficulty of information state change (information transfer) from one stage to the next in the project design phase. The information of the project design stage includes: the information itself of the construction unit demand structure, the building function structure and the architectural physical structure and the information distance of the three stages. In view of the above,
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the information entropy concept is introduced below, and the main characteristics of the three stages are analyzed. 3.1
The Complexity of Information Flow During Project Design Stage
The system of the project life cycle is a complex system with multiple participation and interwoven information. Changes in information both inside and outside the system will have an impact on the project. Accordingly, the design phase of the project life cycle also reflects its complexity. Literature [11] first proposed the use of entropy to measure information in 1948 [11]. Literature [12] points out that the complexity of the design system is that design system is difficult to be understood, description, prediction and control of the state, from the point of view of information entropy, it describes design information system each link expected need [12]. The literature [13] proves that the entropy of the system is equal to the complexity, which represents the sum of the information of each link of the system [13]. As can be seen from the above literature, measure the amount of information contained in each stage in the design phase of PLM information flow, the complexity of product design information flow can be quantitatively analyzed. Then it can achieve the forecast and control of the flow of product design information. Entropy is the measure of the disorder of the system, and information is the opposite of entropy. The availability of information reduces uncertainty, that is, to reduce the entropy of the system. According to Shannon information entropy theory, the greater the entropy of the system, the greater the uncertainty and unpredictability of the system state, the more information is needed to understand. To realize the quantitative analysis of the information in different stages of the system through the entropy measure of information flow. And then more accurately understand and control the complexity characteristics of design system. The amount of information required to describe the expected state of information flow in the design stage of PLC is called information entropy, which is called E. 3.2
Entropy Model of Information Flow in Product Design Stage
Set the discrete random variable x ¼ fx1 ; x2 ; . . .; xw g, w is the number of elements of X. x1 2 X ; 1 t w, The information entropy of x1 itself is the product of the probability pt and the probability pt . The information entropy EðxÞ of x is defined as [11]: E(X) ¼
w X
pt log2 pt
pt 0
t¼1
Xw t¼1
pt ¼ 1
Xw t¼1
log2 pt ¼ 0
If X represents a system, xt and pt ðt ¼ 1; 2; ; w) represents w passible states of this system and the probability of each states, and the EðxÞ is the information entropy of the system.
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E ðxÞ describes the uncertainty of system X and represents the degree of availability of information of this system. The increase in information is at the cost of information entropy reduction, the more information is obtained, the less information entropy is, and the greater the system certainty. From the above equation, information entropy EðxÞ has the following characteristics: When there is only one pt is 1 and all others are 0, EðxÞ ¼ 0,X is completely deterministic, and the system information entropy is the smallest. When each probability of all states of the system is equal (pt ¼ 1=wÞ, EX ¼ lg w, the maximum entropy of the system, at this point, X has the greatest uncertainty. Any system change that causes pt equalization will increase the uncertainty of the system and increase the information entropy. Set up a project design phase flow is composed of M design link node (M 1), include the i node (1 i M) with the number of state are expected to be Si , and between the state of each node are independent of each other. According to the above formula, the information entropy of node can be calculated according to the following formula: Et ¼
Si X
pij log2 pij
j¼1
Where: Si is the state number of node I; pij is the probability that the node i is in Si P state j, 1 j Si ; Et ¼ pij log2 pij j¼1
According to the characteristics of information entropy, the information entropy of the whole project design stage is: E¼
Si M X X
pij log2 pij
i¼1 j¼1
The above is the upper limit of information entropy in the project design stage. Considering that the probability of the state occurring in each stage of the project is not completely random, the actual information entropy is generally less than the upper limit value. For the information state of the project life cycle, we can calculate the information entropy of one design node to another design node, and the one design state to another design state. 3.3
The Information Distance of the State of the Project Design Stage in PLC
The project design process changes with the development of PLC during the project design process, the state of the project design information flow also changes. In addition to the information of the design links of product information flow, the whole
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process also contains the amount of information to be consumed in a certain link, the concept of information state transfer. Information state transfer refers to the situation where the subject is changed between the multiple information states that may appear. Distance of information sate transition (DIT) [14], called information distance for short. It is the measure of the obstacle that the information state of the studied object is transferred between each link. The greater the distance of information means the more difficult it is to transfer the project design, and the more information is needed [15]. Y ¼ fy1 ; y2 ; y3 ; . . .; yn g is the information state set, n is the number of information states, yt is the tth information state, t ¼ 1; 2; . . .; n 。The probability of transfer of state yt to state ys is pzts , and the distance of information state of yt to ys is the logarithm of the transfer probability. (take 2 as the logarithm base, which is consistent with the information entropy dimension): DIðyt ; ys Þ ¼ log2 1=pzts ¼ log2 ðpzts Þ t; s ¼ 1; 2; . . .; n n X
pzts ¼ 1
t;s¼1
For the transfer of multiple information states, the corresponding transfer probability matrix P and information distance matrix DI’ are defined as follows (The square brackets in the formula have the meaning of the vector, so no negative sign are added): p ¼ ½pzts nn 0
DI ¼ ½log2 pzts nn For information flow with M project design links, the yi1 state is the total initial state, and the final yij state is the final state (i 1; j 1). Let pz yi1 ; yij be the transition probability of state yi1 to state yij , and DI yi1 ; yij is the total state information distance. M Y pz yi1 ; yij ¼ pz yi1 ; yij i¼1 M X DI yi1 ; yij DI yi1 ; yij ¼ i¼1
In general, the number of service resources provided by PLC system is enough. Project design planning has multiple choices, and the number of links of information
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flow in project design is R. If the state information (distance of the ri link is dri ðri ¼ 1; 2; . . .:RÞ; and then the total information distance d is: d¼
R X
wri dri
ri¼1
wri is the weight of ri. Suppose the starting link state of the information flow of a project is y0;0 , the final link state is yR;rj , where node ari ðri ¼ 1; 2; . . .; R 1Þ has bij state, the probability of transferring from link yri;rj 1; 2; . . .; brj to link yri þ 1;rj is pwri;rj , where yri;rj is the rj state of link ri. The link ri can form a state chain, and the information distance measurement parameters are shown in Table 1.
Table 1. Information distance measurement parameters The parameter name Link node Number of nodes Information state of node ari The probability of yri;rj moving to yri þ 1;rj Link status chain
The parameter value ari ðri ¼ 1; 2; . . .; R 1Þ brj rj ¼ 1; 2; . . .; brj yri;1 ; yri;2 ; . . .; yri;brj pwri;1 ; pwri;2 ; . . .; pwri;brj y1;rj ; y2;rj ; . . .; yR1;rj
The information distance measure of information flow in the project design link is: brj X
pwri;rj ¼ 1
ri ¼ 1; 2; . . .; R 1
rj¼1 1 RY pz yri;rj ; yðri þ 1Þ;rj pz y0;0 ; yR;rj ¼ pz y0;0 ; y1;rj ri¼1 R1 X pwri;rj ¼ pz y0;0 ; y1;rj ri¼1
"
DI y0;0 ; y1;rj ¼ log2 pz y0;0 ; y1;rj
R 1 Y
# pwri;rj
ri¼1 R1 X ¼ DI y0;0 ; y1;rj þ DI yri;rj ; yðri þ 1Þ;rj ri¼1
pz ðy0;0 ; yR;rj Þ is the total transfer probability of the initial state y0;0 to the final state yR;rj . DI y0;0 ; yR;rj is the total information distance to the final state yR;rj
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In the information flow of project design, there is a multi-link information transmission, and there are rm link, the information distance of each link is rm P did ðid ¼ 1; 2; . . .; rmÞ, the weight of the first id is wid , and wid ¼ 1. The measure of the total information distance is d ¼
rm P
id¼1
wid did .
id¼1
For a variety project design information flow, there are m projects corresponding to m bar project design information flow, the information distance of the k information flow is dfk ðk ¼ 1; 2; . . .; mÞ. Among them, the weight of the information flow in the m P design of the k project is kk , and kk ¼ 1. The total information distance measure is: k¼1
df ¼
m X
kk dfk
k¼1
4 Product Model Establishment and Model Application Based on TBS Method 4.1
The Concept of TBS
In the initial stage of product design, a “basic skeleton” is constructed at the top of the design according to the functional structure of the product, which is called “top basic skeleton”(TBS) [16]. The subsequent design process is basically to copy, modify, refine and improve on the TBS, and finally complete the whole design process. TBS is the core of the top-down design process of the whole product, the bridge and the link between each sub-assembly. It is more important to capture and extract the interrelation and dependency between each assembly and parts in the initial product overall layout in the process of constructing TBS. The design process of TBS method is shown in Fig. 1. 4.2
Project Design Process Analysis
There are various and complex process in the real construction design, and the information flow cannot be accurately quantified. For the major engineering projects, it requires strict technical and complex process to ensure the quality of design for the lack of experience. The general design process is divided into three stages to complete, namely: preliminary design, technical design and construction drawing design. Moreover, there are many roles involved in the project design stage, such as architect designers and structural designers. Strictly, architect designer and structural designer are two different professional designers. Architect designer focus on the functional design of buildings, such as the structure of the modelling, the function partition and the decoration style and so on. The structural designer focus on the structural safety performance of the building to ensure the seismic grade and carrying capacity of buildings, such as the material strength and section size of beams, plates and columns.
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Fig. 1. TBS method design process
For the architect designer part, their works are highly creative and unpredictable. But there are still some design elements that we can predict and characterize. Such as design type, functional partition type and the material selected and so on. In addition, there is a certain similarity between architectural design and product design in manufacturing. We can refer to the method of product design in manufacturing industry. Combining the concept of architectural design with the concept of product design, the architectural design is abstracted into three stages. The architectural design phase includes: 1) customers demand structure; 2) building functional structure 3) architectural physical structure. The customers demand structure is the choice of customers according to their actual needs and personal preferences. The building functional structure is the function selection of the building. The architectural physical structure is the materials and facilities selected to realize the building function. Adopting TBS method to realize the transformation of functional information structure to physical information structure. Take the design of the community as an example in this paper. The architectural design in this paper includes 4 functional modules: Living function (L), Education function (E), Leisure and entertainment functions (LE), The traffic function (T) [17]. The design style of the community includes 4 kinds: British style(B), French style (F), Italian style (I), Chinese style (C) [18]. In combination with the actual situation, the following parts are needed to achieve the above functions: 1) Living function (L): master bedroom, sub-bedroom, living room, dining room, kitchen, toilet [19]. 2) Education function (E): custody, kindergarten, primary school. It is necessary to design and plan education architecture in architectural design. 3) Leisure and entertainment functions (LE): Fitness facilities landscape facilities [20]. 4) The traffic function (T): parking space, parking garage, road layout.
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Information Status of Architectural Design Process in Project Design
It is very important to specify the customer’s demand information in the process of architectural design. The client can either be the owner or the construction unit. But in fact, the customers themselves cannot specify their demand information due to the uncertainty of the market and lack of professional knowledge. Also, design changes may occur during the actual design process, resulting in increased design cycles and increased project costs. Therefore, it is significant to determine the customer’s demand information as much as possible during the architectural design process. Link one: customers demand structure. Customers can choose among the following six determinants based on their actual needs and economic conditions: quality requirements (Q), appearance requirements (A), design reliability demand (D), life demand (L), service demand (S), price demand (P). After the customer makes the key choice, the designer can make a targeted choice in the architectural design process. Link two: building functional structure. Each community is composed of a variety of different functions, these different functions are roughly: Living function (L), Education function (E), Leisure and entertainment functions (LE), The traffic function (T). Then the function structure information of the architectural design stage is converted into 4 modules: Living function (L), Education function (E), Leisure and entertainment functions (LE), The traffic function (T). The customer can select the appropriate module in the above 4 functional modules. Link three: architectural physical structure. The other functions are in combination with architectural design style, and the residential design style is mainly architectural style. And architectural style includes: British style (B), French style (F), Italian style (I), Chinese style (C). There are 4 aspects to realize the above function in the process of architectural design. The 4 aspects: 1) Living function (L): master bedroom, subbedroom, living room, dining room, kitchen, toilet; 2) Education function (E): custody, kindergarten, primary school; 3) Leisure and entertainment functions (LE): Fitness facilities and landscape facilities; 4) The traffic function (T): parking space, parking garage, road layout. The designer connected the customer demand information structure information, architectural function structure information and product physical structure information in the architectural design stage. And then the information state parameters are obtained in the architectural design process, as shown in Table 2. 4.4
Information Status Analysis of Project Design Process
The importance of information to architectural design is self-evident in the process of architectural design. The flow of information is interwoven, and the designers need to combine different information to design works that make customer satisfaction. A detailed analysis of the different situations will be given below. Situation one: The three stages of the architecture design stage of PLC: 1) customers demand structure;2) building functional structure 3) architectural physical structure. These three stages are limited by the design resources of the design unit and customer needs, and
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Table 2. Information state parameters in PLC architecture design process PLC customer demand structure(Link one) Link node PLC customer demand structure Number of 6 states State quality requirements(Q), appearance requirements(A), design reliability demand(D), life demand(L), service demand(S), price demand(P) Transition 1/6 probability Building functional structure(Link two) Link node Building functional structure Number of 4 states State Living function(L), Education function(E), Leisure and entertainment functions (LE), The traffic function(T) 1/4 Transition probability architectural physical structure(Link three) Link node TBS SBS1 SBS2 SBS3 SBS4 Number of 1 4 4 4 4 states British British British state British style style(B), style(B), style(B), (B), French French French French style(F), style(F), style(F), style(F), Italian style Italian Italian Italian style (I), style(I), style(I), (I), Chinese style Chinese Chinese Chinese (C) style(C) style(C) style(C) Transition 1/4 1/4 1/4 1/4 probability Path to the Part1 Part2 Part3 Part4 M node Number of 6 3 2 3 1 states parking Fitness custody, state master space, facilities, kindergarten, bedroom, subparking landscape primary bedroom, living garage, facilities school room, dining road room, kitchen, layout toilet Transition 1/6 1/3 1/2 1/3 1 probability
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the realization of each link itself is uncertain. The probability of the occurrence of each link state is random. For illustrative purposes, it is assumed that the probability of realization probability of customer demand structure is 0.95, the probability of building functional structure is 0.9, and the probability of building physical structure is 0.8. The structure entropy E1 of the information flow in architectural design stage is: E1 ¼
Si M X X
pij log2 pij ¼
i¼1 j¼1
1 1 1 X 95 95 X 9 9 X 8 8 log2 log2 log2 100 100 j¼1 10 10 j¼1 10 10 j¼1
0:46bit In addition, for the information distance, the customer makes a choice in the six aspects of quality requirements (Q), appearance requirements (A), design reliability demand (D), life demand (L), service demand (S) and price demand (P) in the customer demand structure stage. For illustrative purposes, the situation one assumes that the customer can only choose one of the requirements. Then the customer demand structure is reduced to C61 six ways. Customers can choose living function (L), education function (E), leisure and entertainment functions (LE) and the traffic function (T) in the architectural function structure stage. Consider that there are 15 options for customers (C41 þ C42 þ C43 þ C44 ). For convenience of calculation, the customer can only select one of the building function modules in the situation one. For the architectural physical structure, the design unit make the design according to the function choice of the customer. To facilitate the comparison of different customer needs, it is necessary to choose the analysis of the living function module information distance in the situation one. Moreover, we choose Chinese style and master bedroom for the realization of the function of living. The information distance parameter is shown in Table 3. The information distance of information flow in the architectural design stage is: Table 3. Information distance parameters of architectural design stage Name
Customer demand structure
Building functional structure
Number of states State Transition probability
6
4
Living Function module physical structure Design style Living function 4 6
ar1 ; ar2 ; . . .; ar6 1/6
br1 ; br2 ; . . .; br4 1/4
cr1 ; cr2 ; . . .; cr4 1/4
dr1 ; dr2 ; . . .; dr6 1/6
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DI1 ¼ log2 ð1=6Þ log2 ð1=4Þ log2 ð1=4Þ log2 ð1=6Þ 9:17bit Situation two: In the architectural design stage, if the customer and the designer do not communicate well, then the client’s demand is fuzzy. The ambiguity of customer demand information increases the uncertainty of the three stages in the architectural design stage. And the probability of the state of each link decreases. For situation two, it is assumed that the probability of realization probability of customer demand structure is 0.9, the probability of building functional structure is 0.8, and the probability of building physical structure is 0.7. The structure entropy E1 of the information flow in architectural design stage is: E1 ¼
Si M X X
pij log2 pij ¼
i¼1 j¼1
1 1 1 X 9 9 X 8 8 X 7 7 log2 log2 log2 10 10 10 10 10 10 j¼1 j¼1 j¼1
0:75bit At the information distance, the customer demand information that the designer obtained is as follows: The customer chose two in the six aspects of quality requirements (Q), appearance requirements (A), design reliability demand (D), life demand (L), service demand (S) and price demand (P) in the customer demand structure stage. And then there are 15 (C62 ) different situations of the customer demand. Similarly, the information of the building function structure phase is also fuzzy, so the customer may select multiple modules in 4 modules. We choose two modules in the 4 functional modules in situation two. There are 6(C42 ) different situations of the building function structure stage. For the architectural physical structure, we choose Living function (L) and leisure and entertainment functions (LE) for information distance analysis. We choose Chinese style and master bedroom for the realization of the function of living. And we choose Chinese style and landscape facilities for the realization of the function of living. The information distance parameter of situation two is shown in Table 4. Table 4. Information distance parameters of architectural design stage Name
Number of states State Transition probability
Customer demand Building structure functional structure
Living Function module physical Leisure and entertainment structure functions(LE) Design style
Wall materials
Design style
Wall materials
15
6
4
6
4
2
ar1 ; ar2 ; . . .; ar15 1/15
br1 ; br2 ; . . .; br6 1/6
cr1 ; cr2 ; . . .; cr4 dr1 ; dr2 ; . . .; dr6 er1 ; er2 ; . . .; er4 fr1 ; fr2 1/4 1/6 1/4 1/2
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The information distance of information flow in the architectural design stage is: DI1 ¼ log2 ð1=15Þ log2 ð1=6Þ log2 ð1=4Þ log2 ð1=6Þ log2 ð1=4Þ log2 ð1=2Þ 14:08bit
5 Discussion Through the above calculation, it can be found that more information needs to be consumed in the design process in the case of fuzzy demand information of customers. It is the increase of information and information distance in the design process. The increase in information on both sides will affect the design efficiency and the customer satisfaction of final work. This quantitatively illustrates the importance of information in the project design process and how does information affect the design work from the point of view of informatics. Through this example, we can see that using the method in this paper can describe the project design phase information of each link and quantitatively describe the information of information flow in product design process. Therefore, it can further grasp the operation of the building design in PLC and provide data and theoretical support for the optimization of building design.
6 Conclusion The PLC building design stage is based on three links: customer demand structure, building function structure and building physical structure. Information is passed between each link in the building design stage to form a logical flow of building information. The information of building design in PLC includes information and information distance. Through quantitative analysis of them, the complexity of information flow in the building design stage and the information transmission difficulty between each link state can be described. Because the similarity between the product design process of the manufacturing industry and the building design stage in the PLC. The transformation of functional information structure to physical information structure is effectively realized by adopting TBS method, and the design idea of top-level layout is provided for designers. Through logically and quantitatively analyze the building design information and information distance, design unit can optimize design process. Moreover, the design unit can improve design efficiency and the satisfaction of design results from the angle of information.
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The Influence of Culture Value of Civil Engineering Projects on Their Life-Span Zhuxin Tang1, Xinyuan Wang1, Xumeng Zhang1, Bingbing Hu1, Yunyi Wang1, and Jie Li2(&) 1
Nanjing Foreign Language School, Nanjing, China 2 School of Civil Engineering, Nanjing Forestry University, Nanjing, China [email protected]
Abstract. Civil engineering projects play a very important role in human’s life. They provide material basis for human’s life, promote economic development, and, carry on culture and history. However, the last culture function is often ignored by people. Therefore, short-sighted behaviors on the engineering projects often happen in China. The direct consequence is short life of projects. The average life of civil engineering projects in China is just 25-30 years. Most research shows poor quality of projects is the reason resulted in the short life. However, the authors found that people’s sloppy and mercenary attitude towards engineering projects also accounts for the short life after analyzing short-lived project cases. Therefore, the authors assume that Engineering Culture View (ECV) also plays an important role in improving life span of projects. To verify this assumption, this paper starts from analyzing engineering projects’ functions, then raise the argument whether engineering culture influence projects’ lifespan. To answer this question, both longevous and short-lived projects are selected to do comparison study to explore the reasons which influence the lifespan of projects from both perspectives of quality and culture values. The core conclusion in this paper is that quality of engineering projects is fundamentally important to life of projects. Moreover, attractive cultural features endow projects with infinite vitality and can also prolong their life. Keywords: Life span Comparative study
Civil engineering projects Culture value 4M1E
1 Introduction Civil engineering projects (in brief, engineering projects) are material basis for human’s life, e.g., they provide food, clothing, shelter/ housing and transportation – basic necessities of life. They also play an important role in promoting economy. According to the statistics of the National Bureau, during the period of 2000 * 2017, China’s fixed asset investment increased steadily, and its proportion in the country’s GDP is also becoming higher and higher (Fig. 1). However, another important role of engineering projects is often overlooked. That is the cultural value! The culture of engineering refers to the architectural art and style of the projects. As the projects grow old, their functions become degraded, materials © Springer Nature Singapore Pte Ltd. 2021 F. Long et al. (Eds.): CRIOCM 2018, Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pp. 1325–1346, 2021. https://doi.org/10.1007/978-981-15-3977-0_102
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perished, construction skills outdated, however, their cultural value increases. The cultural value of projects can be seen as (Fig. 2 and Fig. 3): (1) Engineering projects are living history books
Fig. 1. China’s fixed asset investment’s proportion in the country’s GDP
Before the invention of paper, people’s writing materials were limited. So a lot of social, historical and cultural information were not recorded. As a result, there were many blanks in the history. However, by studying ancient engineering, many gaps in history have been filled. Let us take the Dabaoen temple in Nanjing as an example. The iron box unearthed in the Underground Palace of Dabaoen temple is the largest hidden relic, which contained the Qi Bao gilded-pagoda, the largest physical tower in the world. More importantly, the rare piece of parietal-bone relic of Sakyamun in the pagada is the only surviving one in the world. The former President Mr. Puchu Zhao of China Buddhist Association once said Nanjing was the “Academic Center of Buddhism”. It is the unearthing of the parietal-bone relic of Sakyamun which strengthens the fact that Nanjing is the Southern center of Buddhism without any doubt.
Fig. 2. The iron box of qibao Ashoka
Fig. 3. The rare parietal-bone relic of Sakyamun
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(2) Engineering projects reflect people’s views and ideas The development of ancient Chinese architecture created its own style whose guiding ideology and principles are closely related to the ancient Chinese philosophy. For example, the theory that “man is an integral part of nature” is contained in the Shanxi residence (Fig. 4). Zhaobi, often set behind the main door in the yards of traditional Chinese building to hinder the vision of people outside, is consistent with the implied characteristics of Chinese (Fig. 5).
Fig. 4. Shanxi residence
Fig. 5. Zhaobi
(3) The style of engineering projects reflect unique cultural characteristics of different nationalities
Fig. 6. The Imperial Palace in Beijing
Fig. 7. The Versailles Palace in Paris
Each nation has its own characteristics. Hence, each nation’s architectures reflect the characteristics of each nation. For example, the Imperial Palace in Beijing (Fig. 6) and the Versailles Palace in Paris (Fig. 7) are both royal palaces, but their appearance styles are completely different. The cultural characteristics of the building have a high degree of recognition. No matter where you live, you will be able to recognize its architectural ancestry right after a look at it. For example, Friendship Garden in Sydney, the hall, the pavilion, the floor, the wall and the bridges in it form the typical landscape art of China (Fig. 8). That makes Chinese abroad feel like home, even though they live in foreign countries.
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Z. Tang et al.
Fig. 8. Friendship Garden in Sydney
Table 1. Cases of short-lived projects No. Name 1
Nanjing Mingyang Villa
Demolishing time 2010
2
Weishanhu Villas
2017
3
Shanghai Lotus Community
2009
4
2005
5
Hefei Vienna Forest Garden Residential Community Chongqing Milan Building
6
Wenzhou Zhongyin Manion
2003
7
Liaoning Dandong Railway Complex Building
2010
8
Nantong Railway Station
2006
9
Wuhan BodaGarden Residential Community
2009
10
Wuhan WaitanGarden Residential Community
2001
11 12
Chongqin Yongzhou Convention and Exhibition 2005 Center Shenyang Lvdao Indoor Football Field 2012
13
Haikou Thousand-year Tower
2007
2010
Life Reasons to be span demolished 0 Unreasonable urban planning 0 Poor construction quality 0 Poor construction quality 0 Unreasonable urban planning 0 Poor construction quality 0 Poor construction quality 1 Unreasonable urban planning 2 Unreasonable urban planning 3 Unreasonable urban planning 4 Unreasonable urban planning 5 Real estate exploitation 9 Unreasonable urban planning 9 Poor construction quality (continued)
The Influence of Culture Value of Civil Engineering
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Table 1. (continued) No. Name
Demolishing time 2010
14
The First People’s Hospital of Wuxi
15
Comprehensive Training Hall of Sports Training 2009 Center of Shouyi, Hubei Shanghai “First bay of Asia” 2008
16 17 18
Teaching Building NO.3 in Hubin District, Zhejiang University Nanchang Wuhu Hotel
2007 2010
19
Shenyang Summer Palace
2009
20
West Nanjing Main Road Viaduct
2011
21
Hunan Zhuzhou Road-Hongqi Road Viaduct
2012
22
2016
23
Teaching Building NO.1 of Engineering Institution of Wuhan University Shenyang Wulihe Stadium
24
Ningbo Riverside and Financial Building
2010
25
Grand Qingdao Hotel
2006
26
Qingdao Railway Building
2007
27
Beijing Kailai Hotel
2010
28
Jujin Residential Community in Jingping Streent, 2014 Fenghua, Zhejiang
29
Suzhou Sufu Road
2013
30
No. 242 old Residential Building in Xingang Road, Shanghai
2014
31
Huijing jiayuan Residential Community in Zhengzhou, Henan
2010
32
Building No.1 of Tianta Home Residential Community in Yinze District, Taiyuan
2014
2006
Life Reasons to be span demolished 10 Real estate exploitation 10 Unreasonable urban planning 11 Unreasonable urban planning 13 Real estate exploitation 13 Real estate exploitation 15 Real estate exploitation 15 Unreasonable urban planning 15 Unreasonable urban planning 16 Unreasonable urban planning 18 Poor construction quality