Proceedings of the Fourteenth International Conference on Management Science and Engineering Management: Volume 2 [1st ed.] 9783030498887, 9783030498894

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Advances in Intelligent Systems and Computing 1191

Jiuping Xu · Gheorghe Duca · Syed Ejaz Ahmed · Fausto Pedro García Márquez · Asaf Hajiyev   Editors

Proceedings of the Fourteenth International Conference on Management Science and Engineering Management Volume 2

Advances in Intelligent Systems and Computing Volume 1191

Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Advisory Editors Nikhil R. Pal, Indian Statistical Institute, Kolkata, India Rafael Bello Perez, Faculty of Mathematics, Physics and Computing, Universidad Central de Las Villas, Santa Clara, Cuba Emilio S. Corchado, University of Salamanca, Salamanca, Spain Hani Hagras, School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK László T. Kóczy, Department of Automation, Széchenyi István University, Gyor, Hungary Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA Chin-Teng Lin, Department of Electrical Engineering, National Chiao Tung University, Hsinchu, Taiwan Jie Lu, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia Patricia Melin, Graduate Program of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico Nadia Nedjah, Department of Electronics Engineering, University of Rio de Janeiro, Rio de Janeiro, Brazil Ngoc Thanh Nguyen , Faculty of Computer Science and Management, Wrocław University of Technology, Wrocław, Poland Jun Wang, Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

The series “Advances in Intelligent Systems and Computing” contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing such as: computational intelligence, soft computing including neural networks, fuzzy systems, evolutionary computing and the fusion of these paradigms, social intelligence, ambient intelligence, computational neuroscience, artificial life, virtual worlds and society, cognitive science and systems, Perception and Vision, DNA and immune based systems, self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric computing, recommender systems, intelligent control, robotics and mechatronics including human-machine teaming, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, Web intelligence and multimedia. The publications within “Advances in Intelligent Systems and Computing” are primarily proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results. ** Indexing: The books of this series are submitted to ISI Proceedings, EI-Compendex, DBLP, SCOPUS, Google Scholar and Springerlink **

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Jiuping Xu Gheorghe Duca Syed Ejaz Ahmed Fausto Pedro García Márquez Asaf Hajiyev •

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Editors

Proceedings of the Fourteenth International Conference on Management Science and Engineering Management Volume 2

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Editors Jiuping Xu Business School Sichuan University Chengdu, China Syed Ejaz Ahmed Faculty of Math and Science Brock University Hamilton, ON, Canada

Gheorghe Duca Academy of Sciences of Moldova Chisinau, Moldova Fausto Pedro García Márquez ETSI Industriales de Ciudad Real University of Castile-La Mancha (UCLM) Ciudad Real, Spain

Asaf Hajiyev Institute of Control Systems Azerbaijan Natl Academy of Sciences Baku, Azerbaijan

ISSN 2194-5357 ISSN 2194-5365 (electronic) Advances in Intelligent Systems and Computing ISBN 978-3-030-49888-7 ISBN 978-3-030-49889-4 (eBook) https://doi.org/10.1007/978-3-030-49889-4 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed 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, express 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 Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Welcome to the proceedings of the Fourteenth International Conference on Management Science and Engineering Management (ICMSEM 2020), held from 30 July to 2 August, 2020, at the Academy of Studies of Moldova. This annual conference, organized by the International Society of Management Science and Engineering Management (ISMSEM), aims to foster international research collaborations in Management Science (MS) and Engineering Management (EM) and provides a forum for presenting current research work through technical sessions and round table discussions in a relaxing convivial atmosphere. The ICMSEM has been held thirteen times since 2007 over the world: Asia, Europe, the Americas and Oceania, and has had a great influence on MS and EM research. In the past thirteen years, the ICMSEM has been successfully held in Chengdu, Chongqing, Bangkok, Chungli, Macau, Islamabad, Philadelphia, Lisbon, Karlsruhe, Baku, Kanazawa, Melbourne and Ontario. The accepted papers have been published in the proceedings of each International Conference on Management Science and Engineering Management by high-level publishing houses, being retrieved by EI or ISTP Compendex. This year, 122 papers from 18 countries, including Pakistan, Uzbekistan, Japan, Istanbul, Moldova, Canada, Turkey, Azerbaijan, USA, Spain, UK, Thailand, Russia, Iran, Romania, Malaysia, China and Morocco, have been accepted for presentation or poster display at the conference. Each accepted paper had three reviewers, each one of them providing the constructive comments and insightful suggestions to the authors, contributing to the utmost quality of the conference proceedings. The papers have been classified into six sections: Statistical Analysis, Machine Learning, Decision Analysis, Supply Chain, Strategic Planning and Industry Innovation. The key issues at the fourteenth ICMSEM covered many popular topics in MS and EM. To further encourage state-of-the-art research in these field, the ISMSEM Advancement Prize is awarded for the excellent papers which have focused on innovative practical applications for MS and EM at this conference.

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Preface

We would like to take this opportunity to thank our participants, all of whom worked exceptionally hard to ensure the success of this conference. We want to express our sincere gratitude to the following prestigious academies and institutions for their high-quality papers and great support for the ICMSEM: The Azerbaijan Academy of Sciences, Academy of Sciences of the Republic of Uzbekistan, Fuzzy Logic Systems Institute, Tokyo University of Science, Brock University, Academy of Economic Studies of Moldova and Sichuan University. We would also like to acknowledge the assistance received from the ISMSEM, Academy of Economic Studies of Moldova and Sichuan University in organizing this conference. We also appreciate the Advances in Intelligent Systems and Computing (AISC) of Springer for the publication of the proceedings. We are grateful to Professor Gheorghe Duca as the General Chair, Professor Grigore Belostecinic, Dr. Lidia Romanciuc, Dr. Nina Roscovan, Dr. Igor Serotila as the Organizing Committee Chairs. We appreciate the great support received from all the members of the Organizing Committee, the Local Arrangement Committee, and the Program Committee as well as all the participants. Finally, we would like to thank all the authors for their excellent conference papers, which have great value for both educational and research purposes. The conference papers and recommendations can also serve as guiding materials for the administration/managing of institutes, enterprises, as well as the drafting or amending the relevant laws by politicians and managing authorities. As MS and EM research is in continuous development and many new trends have emerged, our work needs to continue to focus on the latest MS and EM development, so that we can encourage greater and more innovative activity. Next year, we plan to continue the innovative and successful ICMSEM and intend to increase our efforts in improving the quality of the proceedings and recommending more excellent papers for the ISMSEM Advancement Prize. The Fifteenth International Conference on Management Science and Engineering Management will be hosted by the University of Castilla-La Mancha (UCLM), Spain, in July 2021. Professor Fausto Pedro Garca Márquez has been nominated as the Organizing Committee Chair for the 2021 ICMSEM. We sincerely hope you can submit your new MSEM findings and share your wisdom in Moldova in 2020 and Spain in 2021. March 2020

Jiuping Xu Gheorghe Duca Syed Ejaz Ahmed Fausto Pedro García Márquez Asaf Hajiyev

Organization

ICMSEM 2020 was organized by the International Society of Management Science and Engineering Management (ISMSEM), Sichuan University, Moldova Research and Development Association and Academy of Economic Studies of Moldova. It was held in cooperation with Lecture Notes on Advances in Intelligent Systems and Computing (AISC) of Springer.

Executive Committee General Chairs Jiuping Xu Gheorghe Duca

Sichuan University, China Academy of Sciences of Moldova, Moldova

Program Committee Chairs Benjamin Lev Asaf Hajiyev V. Cruz Machado Mitsuo Gen Ion Aurel Pop Veceslav Khomici Fang Lee Cooke Syed Ejaz Ahmed

Drexel University, Philadelphia, USA Institute of Systems Control, National Academy of Sciences, Baku, Azerbaijan Universidade Nova de Lisboa, Lisbon, Portugal Tokyo University of Science, Japan Romanian Academy Russian Academy of Science Monash University, Australia Brock University, Canada

Organizing Committee Chairs Grigore Belostecinic Lidia Romanciuc

Academy of Economic Studies, Moldova Moldova Research and Development Association, Moldova

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Nina Roscovan Igor Serotila

Organization

Academy of Economic Studies of Moldova, Moldova State University Dimitrie Cantemir, Moldova

Program Committee Mohammad Z. Abu-Sbeih Joseph G. Aguayo Basem S. Attili Alain Billionnet Borut Buchmeister Daria Bugajewska Saibal Chattopadhyay Edwin Cheng Anthony Shun Fung Chiu Jeong-Whan Choi Kaharudin Dimyati Behloul Djilali Eid Hassan Doha O’Regan Donal Siham El-Kafafi Christodoulos A. Floudas Masao Fukushima Oleg Granichin Bernard Han Rene Henrion Voratas Kachitvichyanukul Arne Løkketangen Andres Medaglia Venkat Murali Shmuel S. Orenş Turgut Öziş Panos M. Pardalos Gianni Di Pillo Nasrudin Abd Rahim Celso Ribeiro Hsin Rau Jan Joachim Ruckmann Martin Skitmore Frits C. R. Spieksma Yong Tan

King Fahd University of Petroleum and Minerals, Saudi Arabia University of Concepcion, Chile United Arab Emirates University, United Arab Emirates Ecole National Superieure Informatics for Industry and Enterprise, France University of Maribor, Slovenia Adam Mickiewicz University, Poland Indian Institute of Management, India Hong Kong Polytechnic University, Hong Kong De La Salle University, Philippines Department of Mathematics, Republic of Korea University of Malaya, Malaysia University of Sciences and Technology Houari Boumediene, Algeria Cairo University, Giza, Egypt National University of Ireland, Ireland Manukau Institute of Technology, New Zealand Princeton University, USA Kyoto University, Japan Sankt-Petersburg State University, Russia Western Michigan University, USA Humboldt University, Germany Asian Institute of Technology, Thailand Molde University College, Norway University of the Andes, Colombia Rhodes University, South Africa University of California Berkeley, USA Ege University, Turkey University of Florida, USA Sapienza University of Rome, Italy University of Malaya, Malaysia Fluminense Federal University, Brazil Chung Yuan Christian University, Taiwan University of Birmingham, UK Queensland University of Technology, Australia Katholieke University Leuven, Belgium University of Washington, USA

Organization

Albert P. M. Wagelmans Desheng Dash Wu Hong Yan

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Erasmus University Rotterdam, Netherlands University of Toronto, Canada Hong Kong Polytechnic University, Hong Kong

Secretary-General Zhineng Hu

Sichuan University, China

Under-Secretary Tingting Liu

Sichuan University, China

General Zongmin Li Secretaries Ruolan Li Yidan Huang Rongwei Sun Mengyuan Zhu Zhiwen Liu

Sichuan University, China

Contents

Advancement of Supply Chain, Strategic Planning and Industry Innovation Based on the Fourteenth ICMSEM Proceedings . . . . . . . . . Jiuping Xu

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Part I: Supply Chain The Traveling Salesman Problem: Route Planning of Recharging Station-Assisted Drone Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deguo Sun, Xinying Peng, Rui Qiu, and Yidan Huang

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The Vehicle Routing Problem with Drone for the Minimum CO2 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xinying Peng, Deguo Sun, and Zhiyi Meng

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A Two-Stage Stochastic Programming Model for Pre-positioning of Relief Supplies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yusheng Wang, Zaiwu Gong, and Benjamin Lev

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A Metaheuristic Approach for Quantifying the Effects of the Structural Complexity in Facility Location Problems . . . . . . . . . . Alberto Pliego-Marugán, Jesús María Pinar-Pérez, and Diego Ruiz-Hernández The Battle to Decrease the Impact of the Structural Complexity in Supply Chains: An Algorithmic Approach . . . . . . . . . . . . . . . . . . . . . Jesús María Pinar-Pérez, Alberto Pliego-Marugán, and Diego Ruiz-Hernández Presale Scheme Optimization of Short Life Cycle Products Considering Reference Price Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qiyang Zhou and Chunxiang Guo

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Supply Chain Design Optimization Considering Consumers’ Low-Carbon Awareness Under Carbon Tax Regulation . . . . . . . . . . . . Zhimiao Tao

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Optimal Pricing of the Dual-Channel Closed-Loop Supply Chain in Advance Selling Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xinyuan Cui, Jiayi Wang, Yuyu Geng, and Chunxiang Guo

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When Barriers Need Attention: Adoption of Knowledge Management in Sustainable Supply Chain . . . . . . . . . . . . . . . . . . . . . . . 106 Muhammad Nazam, Muhammad Hashim, Waseem Ahmad, and Sajjad Ahmad Baig Smart Farming: Intelligent Management Approach for Crop Inspection and Evaluation Employing Unmanned Aerial Vehicles . . . . . 119 Carlos Quiterio Gómez Muñoz, Christian Paredes Alvarez, and Fausto Pedro Garcia Marquez Learning Resource Management from Investigating Intrinsic Motivation in Various Learning Environments . . . . . . . . . . . . . . . . . . . 131 Elena Railean, Victoria Trofimov, and Daiva Aktas Risk Management - Performing Instrument in The Development of Economic Expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Gheorghe Avornic and Cristina Copǎceanu Review on the Development of Enterprise Risk Management . . . . . . . . 154 Yanfei Deng, Huichao Liu, Xulian Xie, and Lei Xu Does Commercial Housing Have Better Access to Public Service Than Affordable Housing? – An Empirical Study for Accessibility to Public Service of Different Housings in Chengdu . . . . . . . . . . . . . . . . 167 Chao Huang and Jiaqi Fan The Identification of Toxic Substances in Some Cosmetic Products Sold in Republic of Moldova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Valentina Calmâş, Svetlana Fedorciucova, Ghenadie Şpac, and Olga Tabunscic Renewable Energy Consumption-Economic Growth Nexus: Empirical Evidence from Morocco . . . . . . . . . . . . . . . . . . . . . . . 189 Mounir El-Karimi and Ahmed EI Ghini Construction of Evaluation Index System for the Ecological Civilization in Rural Tourism Destinations . . . . . . . . . . . . . . . . . . . . . . 200 Hanmei Zheng, Qifeng Yin, Xiaoping Li, and Xiaowen Jie Health Promotion Through Sports and Medical Treatment Integration - A Practice Path in China Based on Synergy Theory . . . . . 215 Yuanli Chen and Tianyu Liu

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Impact of Government Guidance Modes on Fundraising Effects . . . . . . 226 Qilin Cao, Jialu Chen, Pengxue Fu, and Youjia Mao Part II: Strategic Planning A Study on the Impact of Customer Expertise on Customer Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 Jingdong Chen, Jiawei Liu, and Mo Chen Research on the Influence of Regional Culture of Agricultural Products on Customers’ Purchase Behavior . . . . . . . . . . . . . . . . . . . . . . 259 Mo Chen, Jingdong Chen, and Yuezhen Wan The Influence of Post-90s Employees’ Work Value Realization Degree on Work Performance: The Intermediary Role of Employee Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Qingsong Zhu, Lan Li, and Tingting Li An Empirical Analysis of the Impact of Absorptive Capacity and Spillover Effects on China’s Regional Innovation Capability . . . . . . 285 Kun Wang, He Xu, Xuanming Ji, and Yingkai Tang A Study on the Impact of Apparel Industry Product Image on Customer Purchase Intention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 Mo Chen, Jingdong Chen, and Han Zheng Impact of Compensation Practices on Employee Job Performance: An Empirical Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 Muqaddas Zafar, Adnan Sarwar, Aqsa Zafar, and Alia Sheeraz Research on the Influence Mechanism of Strategic Flexibility on Business Model Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Guangjin Li and Rongyao Zhuo Executive Overconfidence and Performance of Corporate Cross-border Mergers and Acquisitions . . . . . . . . . . . . . . . . . . . . . . . . . 339 Haiyue Liu, Dongmei He, Jie Duan, and Yile Wang Host Country Political Risk and Chinese Firms’ Cross-border M&A Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 Haiyue Liu, Qiao Guo, Yufan Bai, and Fei Wang Technical Executives, Executive Shareholding and Innovation Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380 Shuanghai Li and Taowenyu Fang Neuromarketing Strategic Engineering: Global, Local, and Transnational . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 Zorina Siscan

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Contents

An Empirical Analysis of Executives’ Overseas Background on Corporate Performance-Based on China’s Listed Real Estate Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 Qiang Jiang, Qing Huang, Pengxue Fu, and Ziming Ye Directors’ and Officers’ Liability Insurance and Overinvestment: Evidence from China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 420 Kun Li and Xiaoxiu Chen Strategic Approach Towards Organizational Performance: Modern Practices over Human Resource Management . . . . . . . . . . . . . 436 Abdullah Khan and Shariq Ahmed The Time: A Cultural, Philosophical and Psychological Approach . . . . 445 Gheorghe Duca, Grigore Belostecinic, Ion Petrescu, and Dragomir Camelia-Cristina Analyst Following, Internal Control Quality, and Debt Financing Costs: Empirical Evidence from China . . . . . . . . . . . . . . . . . . . . . . . . . 456 Qilin Cao, Xiyue Xiong, Yelin Ren, and Tingting Liu Financial Asset Allocation, CEO’s Financial Background and Core Business Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472 Jia He, Xuxian Wan, and Luyang Zhang How Does Organic Organizational Structure Boost Employees’ Task Performance: The Mediating Role of Rules Perception . . . . . . . . . 487 Han Ren, Charles Weizheng Chen, and Zhengqiang Zhong What is “Effective Science Management”? - Part 1 . . . . . . . . . . . . . . . . 500 Gheorghe Duca and Sergey Travin What Is “Effective Science Management”? - Part 2 . . . . . . . . . . . . . . . . 512 Gheorghe Duca and Sergey Travin Science Governance in an Intertwined Historical Perspective of Moldo-Romanian Academic Cooperation . . . . . . . . . . . . . . . . . . . . . . 524 Igor Serotila, Silvia Corlǎteanu-Granciuc, Gheorghe Duca, and Victor Spinei Impact of China-Pakistan Economic Corridor (CPEC) on Agricultural Sector of Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 538 Asif Kamran, Nadeem A. Syed, S. M. Ahsan Rizvi, Bilal Ameen, and Syed Nayyer Ali

Contents

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Part III: Industry Innovation Practical Dilemma and Upgrading Path of Rural Home-Stay Tourism Industry: Taking Danba Ethnic Area of Sichuan Province as the Research Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553 Sha Sha Research on the Job Satisfaction of the Petition Staffs: An Empirical Analysis Based on Petition Center of Fuquan City, Guizhou Province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 568 Lindan Tan, Fengchun Fan, Limei Ou, Tian Zhang, and Ling Yuan Quality Management of Wines and Redox Processes . . . . . . . . . . . . . . . 583 Rodica Sturza, Iurie Scutaru, and Gheorghe Duca Building Resilient City: The Resilience Assessment of Deyang City . . . . 592 Yongfang Yang and Yi Lu A Comparative Study of Garbage Classification Practice in Different Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603 Yaqi Wen and Yi Lu Assessment of Energy Disparity and Financial Development Nexus in Environmental Kuznets Curve Framework . . . . . . . . . . . . . . . . . . . . 613 Yang Li, Hui Peng, Muhammad Hafeez, and Haseeb Ahmad Technological Innovation Behaviors of Public Sectors and Social Organizations in PPTIN: An Evolutionary Game Research . . . . . . . . . . 627 Liming Zhang, Tingting Wang, Wendi Liu, Kuankuan Luo, and Guichuan Zhou A Case Study on R&D Investment of Technology-Intensive Private Enterprise in Sichuan Province of China . . . . . . . . . . . . . . . . . . . . . . . . 647 Weili Zhen, Jiamei Li, Mingtao Zhang, Zhaobohan Zhang, and Yuxi He Energy Analysis of Cascade Utilization of Dimeite Geothermal Power System in Ruili City . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663 Liu Shi, Qiongmei Wang, and Ting Ni The Development of Human Creativity as a Way to Compete Globally and Make Knowledge Economy More Inclusive . . . . . . . . . . . 676 Elina Benea-Popuşoi and Svetlana Duca Impact of Enterprise Innovation Network Characteristics on Relationship Learning: Mediating Effect of Absorptive Capacity . . . . . . 687 Xue Yang, Huan Wang, and Xin Gu Application Research on the BIM and Internet of Things Technology in Construction Logistics Management in the Period of Big Data . . . . . 704 Ling Wan and Yue Bai

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Contents

Evaluating the Trustworthiness in Sharing Economy: A Case Study of DiDi Users in Shanxi, China . . . . . . . . . . . . . . . . . . . . 717 Guohao Zhao, Junaid Jahangir, Muhammad Waqas Akbar, Muhammad Hafeez, and Haseeb Ahmad 5W Mode Analysis of the Media Communication Strategies of Online Video-Produced Variety Shows Using the Chinese Variety Show U Can U BiBi as an Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . 730 Yuheng Chen and Xin Liu Clusters as an Environment of Competitive Collaboration. A Case Study on the Emerging Apparel Economic Cluster in the Republic of Moldova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 742 Elina Benea-Popuşoi and Ecaterina Rusu Effect Mechanism of New Varieties and Technologies on Greening Development of Tartary Buckwheat Industry . . . . . . . . . . . . . . . . . . . . 755 Jingwei Huang, Peng Wang, Liang Zou, Yan Wan, and Gang Zhao The Impact of Video Information and Publisher’s Characteristics in Tik Tok Platform on the Spreading Effect of Poverty Alleviation by E-Commerce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 763 Jinjiang Yan, Yunjie Zhang, Lingling Chen, Lu Huang, and Yong Huang Perspectives on the Future of Higher Education . . . . . . . . . . . . . . . . . . 778 Grigore Belostecinic, Igor Serotila, and Maria Duca New Approaches on Maintenance Management for Wind Turbines Based on Acoustic Inspection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 791 Pedro José Bernalte Sánchez and Fausto Pedro Garcia Marquez A Review of the Policy Incentive on Electric Vehicle Market Based on Citespace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 801 Wen Zhang, Lurong Fan, Guojiao Chen, and Hao Ye Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 817

Advancement of Supply Chain, Strategic Planning and Industry Innovation Based on the Fourteenth ICMSEM Proceedings Jiuping Xu(B) Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, People’s Republic of China [email protected]

Abstract. Management Science and Engineering Management (MSEM) has made a great contribution to the development of economy and society at the level of management and control. In this paper, the basic concepts covered in the fourteenth ICMSEM proceedings Volume II are discussed, after which a review is conducted on engineering management (EM) research to identify the key areas, the most widely discussed research areas for which have been supply chain, strategic planning and industry innovation. The final dataset consisted of articles from scientific journals published in the years from 1990 to 2020. After an analysis of the key research achievements in these three areas, the related research studies in Proceedings Volume II are described. The research trends from both MSEM journals and the ICMSEM are then summarized using CiteSpace. As always, ICMSEM is committed to providing an international forum for academic exchange and communication.

Keywords: Supply chain

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· Strategic planning · Industry innovation

Introduction

Management science and engineering management (MSEM) focuses on the theories, methods and engineering practices related to complex management decisions, which combines data science with modern management concepts to guide management practice. By emphasizing analysis, decision making, strategic execution and innovation, MSEM research and development over the past few decades has brought new vitality to management and engineering practice. MSEM has a broad research focus that combines complex management theories and practical engineering solutions to successfully solve management practice problems. This kind of cross-functional, multidisciplinary research, therefore, supports real world management execution, improves management efficiency, and contributes to energy conservation. A variety of fields demonstrates the need to organize the research activity related to EM in the field of management sciences c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 1–10, 2021. https://doi.org/10.1007/978-3-030-49889-4_1

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J. Xu

[5]. Therefore, to identify the major and emerging trends in the field of management science, citespace will be used to cluster keywords in this field. After analyzing 3,071 literatures, keyword clustering will be adopted, shown as in the Fig. 1

Fig. 1. Keywords clustering diagram in MSEM

As shown in Fig. 1, MSEM research has been widely applied to management problems that involve extensive engineering concepts. In volume I, management science and its trends are systematically analyzed, and in volume II, Engineering Management (EM) and its trends are focused on. Kocaolgu defined EM as a project management inspection that uses a comprehensive approach to achieve optimal engineering management results, improve organizational structures and strategies, optimize resource allocation, and achieve effective organizational development [4]. Therefore, Volume II of the ICMSEM meeting record focuses on three key emerging EM areas: Supply Chain, Strategic Planning and Industry Innovation. The remainder of this paper is organized as follows. In Sect. 2, the relevant research in the key three areas is reviewed, in Sect. 3, the central issues in Proceedings volume II are discussed, in Sect. 4, the EM and ICMSEM development trends are analyzed, and in Sect. 5, the conclusions and future research directions are given.

Advancement of Statistical Analysis

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Literature Review

Figure 1 identifies the most pertinent research fields and possible research directions are identified, from which it can be seen that supply chain, management, strategic planning and industry innovation have been the most widely studied. In this section, the recent EM research in these three areas in recent is reviewed to analyze the specific development tracks. 2.1

Supply Chain

Supply chain include a core enterprise, intermediate product and final product producers, retailers and consumers, and basically connects suppliers, manufacturers, distributors and end users into a functional network chain. Based on supply chain, many theories and practices have been studied. Wang et al. proposed a novel theory for managing a holistic supply chain network, for proactive resilience. A holistic or inter-industrial supply chain network (H-SCN for short) is when several supply chain networks are intertwined due to inherent inter-dependencies to form a more sophisticated network [13]. Nunes studied the supply chain management models in biomass for energy, analyzing several models presented by recent research that approach different situations and scenarios. And the result shows that biomass for energy supply chain models must include the analysis of several different variables and include the main disadvantages of its use as well [6]. Based on direct cooperation and game at each node in the supply chain, B. Sarkar et al. developed a successful co-op advertisement collaboration policy, between the suppliers, manufacturers, and retailers [7]. Scavarda, Annibal et al. proposed a healthcare supply chain management framework for emerging economies with the sustainable lenses including the theory, practice and policy [8]. Supply chain is an emerging research topic in recent years, which has great potential to improve the efficiency of different organizations [9]. Therefore, these ample scope and open doors for the development of SC should be investigated with the help of advanced quantitative modeling approaches, highly developed optimization techniques, integrated multi-criteria decision making techniques, and proficient algorithms. 2.2

Strategic Planning

Contemporary strategic planning is an agile, creative, generative, and iterative process that integrates diverse perspectives with Effective strategic planning requiring decisions about the factors and approaches that can ensure future organizational success. Strategic planning is particular important in uncertain and turbulent times [15]. Barak et al. built a model using a novel interval-valued fuzzy quantitative strategic planning matrix (QSPM) and multiple criteria decision making (MCDMs) to solve the problem in managing strategic decisions within the outsourcing process [2]. Teixeira et al. developed a strategic planning method to guide, facilitate and accelerate the sustainability integration in the product development process by making changes to the strategic planning

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J. Xu

and the continuous improvement business management process [10]. Therefore, strategic planning plays an important role in enterprise management and operations. With the continued emphasis on scientific management, greater emphasis is being placed on forward-looking enterprise strategies that include environmental uncertainty considerations. 2.3

Industry Innovation

Social, economic, and environmental challenges have become increasingly complex, which in turn have forced organizations to innovate, manage change, and adopt new processes [11]. Therefore, a great deal of recent research has been focused on applying management science to a range of industries to promote industry development and innovation. Aron et al. explored the technological trajectories of natural resource companies to analyze the main development and integration factors associated with their respective mining value chains to ensure industry sustainability [1]. Martin-Rios et al. examined possible food waste management practices to determine radical food sector innovations to mitigate food waste, finding that these methods had positive significance for the sustainable development of the food industry [3]. Research into service industry management innovation has also been found to have significant practical applications. Wallenburg et al. developed a model to study the alignment mechanisms for supplier-initiated innovation in the logistics service industry [12]. In the future, innovations could be used to enhance the soft power of both individual companied and overall industries.

3

Central Issues in the Proceedings Volume II

The above brief analysis highlighted the key areas in Proceedings Volume II associated with supply chain, strategic planning, and industry innovation related to Sustainable and pro-environmental concepts. In this section, the papers in related fields that are included in volume II are analyzed. Supply chain researchers have proposed many models to promote better and more sustainable management and development. Qiu proposed a mixed integer linear programming (MILP) formulation to solve a package delivery route planning problem for a single drone and truck in the construction of recharging stations. With a focus on unmanned aerial vehicles, Meng et al. developed a mixed integer model based on a dual drone and a truck parcel delivery situation to determine the route that produced the least CO2 emissions. Based on fuzzy AHP methods and focused on sustainable supply chain perspectives, Muhammad Nazam et al. identified key barriers in the food sector in a developing economy scenario to concentrate on prioritizing the essential factors, finding that decision makers needed to first identify the barriers, then enhance the organizational performances and sustainability. Pinar-Perez et al. presented an optimization approach for a location problems that mitigated the impact of the structural complexity and different algorithms.

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5

Strategic planning is critical to organizational management. In this section, Li et al. studied the influencing mechanisms in strategic flexibility in business model innovation, based on an empirical analysis of enterprise questionnaire data, and found that the more dynamic the environment, the more resource flexibility promoted business model innovation. Liu et al. investigated the impact of executive overconfidence on cross-border M&A performances, finding that executive overconfidence undermined both short-term and long-term cross-border M&A performance, and an overseas executive background played a positive moderating role in the correlations between executive overconfidence and short-term cross-border M&A performances, which had practical implications for corporate governance and talents hiring policies. Based on an extensive literature review, and a deduced holistic and synergetic approach to human brain functioning, Zorina Siscan argued for the necessity of developing neuromarketing strategic engineering (NSE) as a system. The last section in Volume II focuses on the developments in industry innovation. Zhang et al. constructed a technological innovative behavior evolutionary game model for public sector and social organizations to reveal the evolutionary stable strategies for both types of stakeholders under different parameters, and through simulations, verified the evolutionary trends under different initial strategies and parameters. With a focus on urban disaster resistance, Lu et al. proposed a resilience assessment framework from the technical, economic, ecological, and social dimensions, and then analyzed the resilience in Deyang City, one of the four cities participating in the 100 Resilient Cities’ (100RC) project in China. From a detailed analysis of the relationships between the innovation network characteristics, enterprise absorptive capacity and relationship learning, X. Yang et al. constructed a theoretical model focused on the impact of enterprise innovation network characteristics on relationship learning, and then introduced absorptive capacity as a mediating variable to examine the mechanisms, from which it was found that the relationship strength and relationship qualities had a positive impact on relationship learning and could assist enterprises improve their absorptive capacities, and promote a rise in their relationship learning efficiency.

4

Evaluation of the EM and ICMSEM Development Trends

In this section, the EM and ICMSEM development trends are evaluated. As an information visualization technology developed by Chen, CiteSpace supports structural and temporal analyses of a variety of networks derived from scientific publications, including collaboration networks, author co-citation networks, and document co-citation networks. An “Advanced search” function with “Engineering management” as the key word search string was conducted in March, 2020 using the Web of Science databases (WOS) with the timespan set from 2000 to 2020. The initial retrieval

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J. Xu

results included many duplicate references. Therefore, to refine the research selection and increase the accuracy, paper types, articles and proceedings were then selected, which reduced the paper numbers to 3,151. After some papers were eliminated because they had an indirect relationship to EM, 2,689 articles were finally extracted and put into CiteSpace, which transformed the data into a format that could be identified by the software to allow for parameter selection. The time span was set from 2000 to 2020 with the time slice set at one year and with the theme selection based on the titles, abstracts, identifiers and keywords to allow for node selection. Then, each zone with the highest keyword records were clustered and analyzed, from which a map was drawn for the minimum spanning tree. 4.1

The Development of EM

As shown in Fig. 2, the highest ranked areas were supply chain, engineering, strategy, risk management, and model and system, which highlighted the most current popular engineering management research fields and the future EM development trends. There has been significant research development on supply chain, especially concentrating more on environmental uncertainty and sustainability [14]. What’s more, it also can be seen that the environment, engineering, strategy and innovation were the main research points, as was expected. The timezone view for the related keywords is shown in Fig. 3. With the increasing emphasis on integrated development and the continuous development of big data, management innovation and especially enterprise management innovations have been relying more on data analysis and computing science. There has also been an increase in research on strategic planning and industry innovation, with artificial intelligence, big data and computing science emerging as the latest research trends. With a reference frequency running from high to low, the top thirty were analyzed from the 378 keywords, which has been shown in Table 1. The keywords, such as supply chain, strategic planning and the industry innovation, had a relatively high centrality. The analysis of the top most frequent words found that supply chain, strategic planning, industry innovation, environmental science, and project management are currently the most popular research areas. 4.2

Further Development Prediction

To further understand the engineering management field, high frequency research was included in the timezone view, from which it was found that these words had been associated with key research areas for many years. Through the analysis of the most common words, it was found that project management, supply chain, strategic planning and industry innovation remained the most popular EM research areas.

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Fig. 2. Analysis on co-occurring keywords

Fig. 3. The timezone view of related keywords

7

8

J. Xu Table 1. The results of top categories Frequency Centrality Keyword

Year

231

0.24

Management

2002

135

0.19

Supply chain

2000

115

0.16

Model

2000

115

0.15

Strategic planning

2000

102

0.11

Supply chain management 2001

81

0.14

Industry innovation

2002

81

0.08

System

2000

74

0.08

Simulation

2003

68

0.05

Sustainability

2004

45

0.03

Decision making

2003

41

0.1

Risk management

2008

39

0.06

Industry

2005

37

0.01

Algorithm

2005

31

0.15

Strategy

2009

29

0.05

Impact

2010

26

0.08

Uncertainty

2007

26

0.08

Optimization

2009

25

0.02

Framework

2011

23

0.04

Performance

2012

22

0.13

Integration

2010

21

0.01

Innovation

2009

20

0.02

Industry

2000

20

0.02

Life cycle assessment

2008

19

0.06

Construction

2006

18

0.03

Technology

2002

17

0.04

Logistics

2009

17

0.06

Environment

2007

17

0.04

Network

2008

16

0.04

Supply chain design

2007

16

0.04

Perspective

2006

We believe that EM should focus on the study of specific EM problems as well as popularizing MS knowledge. Engineering Management is wide in scope with an inter-disciplinary background. It not only requires knowledge of Engineering, but also requires the scientific management that is the core of Engineering Management. There is a general trend indicating that the range of EM will be expanded. With in-depth research of Engineering Management, more and more

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9

fields of Engineering Management will be permeated with the concept of Scientific management. The EM applications will continue to widen and deepen in the future, with a greater focus being placed on low carbon emissions, environmental protection, big data, artificial intelligence, and other popular EM issues.

5

Conclusion

This paper reviewed the recent research associated with Management Science and Engineering Management and predicted the possible research development trends. To date, Management sciences were classified as significant, with a share of over a dozen percent of the total research [16], in which, the engineering management has always been the leading topic and is a growing area of research within management sciences. Additionally, Engineering Management is the application of management to engineering and is also the discipline that brings together the technological problem-solving savvy of engineering and the organizational, administrative, and planning abilities of management to oversee the operational performance of complex engineering driven enterprises. To analyze the EM and ICMSEM development trends, in this brief introduction, the main search terms and keywords were identified using CiteSpace, which highlighted the current EM trends, which we hope is able to provide some direction for researchers. EM research is continually developing with new topics are appearing every year, however, more engineering management research is needed to deepen its influence of EM and provide a more active research forum. Acknowledgements. The author gratefully acknowledges Tingting Liu and Ruolan Li’s efforts on the paper collection and classification, Zongmin Li and Yidan Huang’s efforts on data collation and analysis, and Rongwei Sun and Zhiwen Liu’s efforts on the chart drawing.

References 1. Aron, A.S., Molina, O.: Green innovation in natural resource industries: The case of local suppliers in the Peruvian mining industry. The Extractive Industries and Society (2019) 2. Barak, S., Javanmard, S.: Outsourcing modelling using a novel interval-valued fuzzy quantitative strategic planning matrix (QSPM) and multiple criteria decision-making (MCDMs). Int. J. Prod. Econ. 222, 107494 (2019) 3. Carlos, M.R., Christine, D.M., G¨ ossling, S., et al.: Food waste management innovations in the foodservice industry. Waste Manag 79, 196–206 (2018) 4. Farr, J.V., Buede, D.M.: Systems engineering and engineering management: keys to the efficient development of products and services. Eng. Manag. J. 15(3), 3–9 (2003) 5. Kotnour, T., Farr, J.V.: Engineering management: past, present, and future. Eng. Manag. J. 17(1), 15–26 (2005) 6. Nunes, L., Causer, T., Ciolkosz, D.: Biomass for energy: a review on supply chain management models. Renew. Sustain. Energy Rev. 120(109), 658 (2020)

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7. Sarkar, B., Omair, M., Kim, N.: A cooperative advertising collaboration policy in supply chain management under uncertain conditions. Appl. Soft Comput. 88(105), 948 (2020) 8. Scavarda, A., Da´ u, G.L., Scavarda, L.F., et al.: A proposed healthcare supply chain management framework in the emerging economies with the sustainable lenses: the theory, the practice, and the policy. Resour. Conserv. Recycl. 141, 418–430 (2019) 9. Swapnil, L., Ravi, K., Ravi, S.: Circular supply chain management: a state-of-art review and future opportunities. J. Clean. Prod. 258(120), 859 (2020) 10. Teixeira, G.F.G., Junior, O.C.: How to make strategic planning for corporate sustainability? J. Clean. Prod. 230, 1421–1431 (2019) ˇ 11. Vrchota, J., Rehoˇ r, P.: Project management and innovation in the manufacturing industry in Czech Republic. Procedia Comput. Sci. 164, 457–462 (2019) 12. Wallenburg, C.M., Johne, D., Cichosz, M., et al.: Alignment mechanisms for supplier-initiated innovation: results from the logistics service industry. J. Purch. Supply Manag. 25(5), 100575 (2019) 13. Wang, J., Dou, R., Muddada, R.R., et al.: Management of a holistic supply chain network for proactive resilience: theory and case study. Comput. Ind. Eng. 125, 668–677 (2018) 14. Wang, Y., Chen, S., Lee, Y., et al.: Developing green management standards for restaurants: an application of green supply chain management. Int. J. Hosp. Manag. 34, 263–273 (2013) 15. Weston, M.J.: Strategic planning in an age of uncertainty: creating clarity in uncertain times. Nurse Lead. 18(1), 54–58 (2020) 16. Zemigala, M.: Tendencies in research on sustainable development in management sciences. J. Clean. Prod. 218, 796–809 (2019)

Part I: Supply Chain

The Traveling Salesman Problem: Route Planning of Recharging Station-Assisted Drone Delivery Deguo Sun1 , Xinying Peng2 , Rui Qiu3(B) , and Yidan Huang3 1

College of Civil Engineering, Sichuan Agriculture University, Dujiangyan 611830, People’s Republic of China 2 College of Architecture and Urban-Rural Planning, Sichuan Agriculture University, Dujiangyan 611830, People’s Republic of China 3 Business School, Sichuan University, Chengdu 610065, People’s Republic of China [email protected]

Abstract. The far-reaching distribution distance is a challenging problem in the rural UAV logistics market. With the use of UAV recharging stations, the maximum flight distance of the UAV can be extended, which greatly reduces the total time to complete the truck delivery. This paper mainly discuss a route planning problem of a single drone and truck under the construction of recharging stations during the package delivery, which is a single-objective optimization process. A mixed integer linear programming (MILP) formulation is proposed to solve the above problem. Finally, the results of an illustrative instance are calculated to show the feasibility and accuracy of our model.

Keywords: Drone

1

· Recharging station · Logistics · MILP formulation

Introduction

To solve the problem of difficult Logistics transportation in rural and remote area, the transportation of using drones to delivery packages have gradually aroused attention of correspond Logistics companies. Amazon CEO Jeff Bezos first announced that using unmanned aerial vehicles (UAVs) to delivery little packages [11]. Google also launched the same drone delivery project “Wing”, and would officially start in 2017 [5]. One week after the announcement of “Prime Air”, DHL began the drone delivery test, which delivered medical supplies and food to the area with poor transportation [4]. Zipline has cooperated with the government to start using drones in Rwanda to deliver medicines, blood and other supplies to hospitals and medical centers [13]. In China, the first UAV operation dispatch center was officially completed and put into use in Suqian in the world, marking the normal operation of JD UAVs [14]. With the popularity of “Internet+”, Chinese rural logistics developed rapidly, and a large number c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 13–23, 2021. https://doi.org/10.1007/978-3-030-49889-4_2

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of goods were sold to the countryside. For the poor road condition in rural area and some customer nodes are far away from the distribution main route of the truck, it will cost a lot of time and money to complete delivery work for the truck and even that the truck cannot make it. Drones can successfully deliver the goods to above nodes and return safely ignoring the restriction and condition of transportation. Moreover, drones can save vast time and delivery costs. Therefore, using drones for “last-mile” parcel delivery in rural area is of great significance. Drones are powered by batteries and have to be replenished when batteries are depleted. Drones own their highest battery level which limits their flight endurance and range. As a mobile charging station, the truck can replenish the drone for the next flight. This transportation system that consists of a drone and truck can meet most of customers’ demands in rural areas. However, a single drone’s flight is still affected by the causes of weather, payload and so on [7]. Under the condition of ensuring sufficient power to return, the flight time of the drone is limited after a fully single charge in the truck, and the area that can be reached is limited which leads to not meet some special nodes’ needs. So, it is not enough for the drone to recharge by the truck. Another way to extend the drone’s flight and keep drones’ safety is to construct a stationary recharging station during drones’ flight process in Fig. 1. So, transportation system consists of drone, truck and recharging station is more in line with the distribution needs of rural customers. To meet rural customers’ needs and keep pace with the rapid development of Chinese village e-commerce, It is necessary to put drones into use in logistics distribution. JD Logistics start the first normal operation pilot of the drone distribution in Guangan, Sichuan. Taking the location of Xiexing town as an example, the drone can complete one quarter of the daily average orders, which can save nearly half of the total delivery time [8]. In order to extend the maximum transport distance of the drone and reduce the total delivery time under

Fig. 1. The drone charging infrastructure of Skysense (source: youuav.com)

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15

the combined mode of a drone and truck, the charging station can play a key role. At present, we know that the main UAV model of JD used in Guangan is the Y-3 model in Fig. 2, with a maximum load of 10 kg and a maximum flight distance of 10 km from JD X Division. However, the distance between some customer nodes in rural China is far beyond the endurance of the drone. After its work is completed, the drone does not have enough remaining power to return to the truck for recharging. Therefore, the drone-truck-recharging station transportation system can play an important role in the JD logistics distribution in Villages. There exist a host of papers about the drone delivery. Murry and chu (2015) first propose “the flying sidekick problem of traveling salesman problem” (FSTSP) [9], which allows drones to charge in the truck. And they also propose two heuristic solutions and two mathematical programming models. Ponza (2016) solves the mixed integer mathematical programming model of FSTSP by simulating annealing element heuristic algorithm [10]. Agatz et al. (2016) propose “traveling salesman problem with drone” (TSP-D), which allows the drone return to original nodes where launches the drone [1]. And later, Bouman et al. (2017) Propose an accurate solution based on dynamic programming for TSP-D which can solve a broader problem [2]. Ha et al. (2018) study the TSP-LS and GRASP algorithms to reduce the total costs of completing the drone-truck combination transportation system and the time costs created by the truck or drone waiting for each other [6]. Above papers all study logistics distribution using the drone-truck combination transport system. There is also a part of papers on the research of a single drone for logistics, and the drone can complete the replenishment of electricity on the way for flying further. Sundar and Rathinam (2014) propose an approximate algorithm and a fast heuristic algorithm for planning the flight path of a single drone [12]. And a hybrid integer linear programming formula is also proposed. Doring et al. (2016) conduct path planning to minimize costs and delivery time considering battery weight, payload weight and reuse of drone [3]. Yu et al. (2017) propose an optimization algorithm for the path and sequence of accessing nodes using a single drone combined with a single mobile charging station

Fig. 2. JD’s electric multi-rotor Y3 drone (source: x.jdwl.com)

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combination system [15]. Hong et al. (2018) propose a drone delivery recharging location model (DDRLM) in order to optimize the position of the fixed recharging station during the flight of the drone [7]. This innovative work has promoted the development of drones in the delivery work, and played a significant role in the application of drones. However, until now, there exists little research on the use of drone-truck-recharging station combination transport system. The main contribution of this paper is to introduce the drone-truckrecharging station combination transport system, which allows the drone to land on the recharging station for replenishment during its flight. A mathematical mixed integer linear programming (MILP) formulation is proposed, and then a practical example of Sichuan Guangan is solved. The remaining structure of this paper is as follows: the second section describes the model, the third section carries out the case solving calculation, and the fourth section is the conclusion and provides suggestions for future research.

2

Modeling

In this section, we first give assumptions of the drone-truck-recharging station combination transport system, and then propose a MILP formulation. 2.1

Assumptions

The follow conditions may be concerned during the process of the drone’s delivery: 1. the drone’s maximum safe flight distance; 2. the recharging station’s coverage; 3. running rules of the drone-truck-recharging station transportation system. The maximum flight distance is a critical cause for deciding the customer nodes that can be assigned to drone services. The maximum distance is affected not only the drone types and flying speed, but also the payload, weather conditions and so on. Allocating the appropriate customer nodes to the drone according to the maximum safe flight distance of the drone can effectively reduce the total running time. With the help of the recharging station, the single delivery range of the drone increases. The recharging station is established in the flight process of the drone, and the drone must land on the charging station for battery recharging when its power is exhausted. If the remaining power is enough to return to the truck after the drone has finished delivering the goods, the drone does not need to land during the flight. In other words, the total number of times the drone can be recharged during the flight is 0 or 1 time. In this way, the range of customer nodes that the drone can serve is twice times, which is of great significance for improving the transportation efficiency and reducing the running time of the whole process. In this drone-truck-recharging station transportation system, all the customer nodes’ needs should be met and at most once. The delivery service finished by the drone is called the drone-delivery, while by the truck is called the

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17

truck-delivery [6]. We use to denote drone delivery, where is a launch node, i is a customer node serviced by the drone, c is a rendezvous node. j is a rendezvous node. We use to denote truck delivery. When drone delivery begins, the truck and drone are separated from each other at i node, and then each serves the assigned customer nodes and finally rendezvouses at j node. When the drone launched from the truck, it must be fully charged. When the power is exhausted, the drone must land on the recharging station during the flight. In order to ensure that the drone flys according to the specified route, the drone must first return to the truck on the rendezvous node and then start the next delivery. The truck can serve multiple customer nodes before the rendezvous nodes to rendezvous with the drone in Fig. 3. If the truck arrives at the rendezvous nodes before the drone, the truck will wait at the rendezvous nodes for the drone to land on and recharge it. Only the drone is fully recharged, the drone and the truck begin the next delivery at j node. If the drone delivery does not exist, the drone runs along with the truck without power consumption. 2.2

Notations

The definitions of the indexes, sets, parameters and decision variables are as follows: Indices: i, j: node. c: position. Sets: C: Nf : Ni : T R: DR:

set set set set set

of of of of of

customer nodes. launch node, where the truck can launch the drone. rendezvous node, where the truck can receive the drone. truck delivery routes. drone delivery routes.

Fig. 3. Illustration of an infeasible drone-delivery.

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D. Sun et al.

Parameters: n: M: qi : qi : r: v: w: E: e: Dij : Aicj : Yicj : Sj :

the number of customer nodes in the delivery work. an infinite number. the time when the truck leaves i. the time when the drone leaves i. running speed of the truck. flying speed of the drone. the amount of power consumed by the drone at a maximum speed of 1 km. the charging speed of the drone on the truck. the fully recharging time of the drone needed on the recharging station. the length of the truck delivery route . the length of the drone delivery route . the recharging times of drone on the recharging station in . the total transport time of truck.

Decision Variables: Sij : binary variable which takes 1 if is traveled by the truck and 0 otherwise. Picj : binary variable which takes 1 if is traveled by the drone and 0 otherwise. 2.3

MILP Model

This MILP formulation is based on the one proposed by Murry and Chu [9]. We add the recharging station element to the drone delivery, which expands the range of customer service of the drone, and is more in line with the actual situation in Chinese rural areas. Our purpose is to minimize the total time cost of the truck to leave from 0 node to n + 1 node. The objective function and constraints of the MILP formulation are as follows: min sj Djn+1 Sjn+1 ≤ sj + M (1 − Sjn+1 ), ∀j ∈ N/ r    Sic + Picj = 1, ∀c ∈ C

qj +

i ∈ Nf i = c

i ∈ Nf c = j

(1)

(2) (3)

i ∈ Nl ∈ DR



S0j = 1

(4)

Sin+1 = 1

(5)

∀j∈Nl

 ∀i∈Nf

The Traveling Salesman Problem



Sic =

i ∈ Nf i = c

2Picj ≤



Sih +

h ∈ c i = h





Scj , ∀c ∈ C

19

(6)

j ∈ Nl c = j

Slj , ∀i ∈ Nf , j ∈ {N/ , ∈ DR}, c ∈ C

(7)

l ∈ Nf l = j





Picj ≤ 1, ∀i ∈ Nf

(8)

Picj ≤ 1, ∀j ∈ Nf

(9)

c ∈ C j ∈ Nl c = i = DR

qj ≥ qh +





i ∈ Nf i = j

c ∈ C ∈ DR

Dhj Aicj w − Yicj − M (1 − Shj ) + Picj , ∀i ∈ Nf , c ∈ C, h ∈ C, j ∈ {N/ : h = j} r E

(10)

qj ≥ qi − M (1 − Shj ) + (

Aicj Aicj w − Yicj + Yicj e + )Picj , ∀i ∈ Nf , c ∈ C, j ∈ {N/ : j = i} v E

(11)

qi = qi , ∀i ∈ Nf

(12)

q0 = 0

(13)

q0 = 0

(14)

qi >= 0, ∀i ∈ N/

(15)

qi >= 0, ∀i ∈ N/

(16)

Picj ∈ {01}, ∀i ∈ Nf , c ∈ {Cc = i}, j ∈ {N/ : } ∈ DR

(17)

Sij ∈ {0, 1}, ∀i ∈ Nf , j ∈ {N/ : j = i}

(18)

The objective is to minimize the total transport time of truck including the customers are all served and finally the truck goes back to the warehouse at n+1 node.

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• Constraint (2) is the specific expression of the truck’s total transport time. • Constraint (3) indicates that each node is visited once by the truck or drone. • Constraint (4) and (5) state that the truck starts at 0 node and ends at n + 1 node. • Constraint (6) indicates that if the truck visits the c node, then starts at c node for the next delivery. • Constraint (7) combines the drone route with the truck route. If drone delivery exists, the truck has to arrive at i node to launch the drone, and arrive a j node to receive the drone. • Constraint (8) and (9) indicates that the drone is launched or received only once at the launch or rendezvous nodes. • Constraint (10) and (11) ensure that the expression of time when the truck leaves j node. If the truck delivery exists and the truck arrives at j node at the same time as the drone or behind, the time of the truck leaves j node is the time of the truck leaves h node plus the running time of the truck route and the recharging time for the drone after receiving. If the drone delivery exists and the drone arrives at j node behind the truck, the time of the truck leaves j node is the time of the drone leaves node plus the flying time of the drone route and the recharging time on the recharging station and the truck at j node. • Constraint (12) ensures that the truck and drone leaves i node at the same time. • Constraint (13) and (14) ensures that the time when the truck and drone leaves 0 node is 0 h. • Constraint (15) and (16) denotes that the time when the truck and drone leave i node is bigger than 0 h. • Constraint (17) and (18) specify the decision variable definitions.

3

Practical Application

In this section, in order to show the feasibility and quality of our MILP model, we randomly choose seven logistics outlets set up by JD logistics in Guangan as a practical application case. We first randomly choose two warehouses as the starting node and ending node. Under the drone-truck-recharging station system, we complete the transportation route planning of the truck with the drone through corresponding numerical calculations to ensure the minimized time costs. We stipulate that the drone in the starting warehouse is already fully charged on the truck and leaves the starting warehouse at the same time as the truck. The truck runs from the starting warehouse to the final warehouse, waits for the drone to land in the receiving node and completes tasks such as recharging and loading. The drone will not start the next transport until is fully charged in the receiving node. When the truck waits for the drone in the receiving node, a part of the waiting time will be generated. This part of the waiting time also belongs to the total transportation time of the truck. When the truck arrives at the warehouse, the total transportation of the truck is over. If the drone does not

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return to the truck, this part of the waiting time does not need to be included in the total transportation time of the truck. Therefore, assigning some distant customer nodes to the drone is beneficial to reducing the total transportation time of the truck. In order to minimize the total time required for the drone-truck-recharging station combined transportation system to complete the whole distribution, the reasonable drone and truck delivery routes must plan well advanced. Reduce the time spent on the drone and truck in receiving nodes waiting for each other, and assign as many nodes as possible to the drone delivery. According to the Amap, we randomly set up two customer nodes as the starting node (0 node) and the ending node (6 node), and regard them as warehouses, which are JD expresses in the Zaoshan town and Forward area. The different operating speeds of the drone and truck can lead to the final different results. Considering the actual roads and traffic condition in Chinese rural areas, we assume that the truck runs in a 25 km/h speed and the drone in a 40 km/h speed. The drone’s battery life is limited to 30 min, and with the help of the recharging station, a drone’s single delivery maximum distance is 40 km including return distance, which can be used to eliminate the vast majority of the possible drone paths and reduce calculations. According to the report of the UAV network, we limit the total time required for the drone to be fully recharged on the recharging station and the truck to 0.5 h. In addition, the truck running distance data between the two customer nodes is derived from the Amap, and the arrival distances of the drone and truck are different. During the operation of the truck, obstacles need to be avoided, and the drone flight distance is a straight distance between two customer nodes. Therefore, the running distance of the truck between the two customer nodes is greater than the flying distance of the drone. Considering the drone’s recharge at the recharging station, we calculate all possible drone and truck routes, and corresponding total transit times. By comparing the total time consumed by the truck delivery service, we draw the conclusion and assign the customer nodes to the drone and truck respectively: the

Fig. 4. Optimal solution to the illustrative example.

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minimum time taken for the drone-truck-recharging station to reach 6 node from 0 node is 4.79 h, where the drone operation path is and , and the truck operation path is , , . We draw the drone and truck movement paths in Fig. 4.

4

Conclusions and Future Research

Drones can provide long-distance transportation services that are faster, safer, and consume less energy, but they must guarantee the power required to fly between two customer nodes. Road conditions in Chinese rural areas are poor and the distance between the two customer nodes is long. Considering the limited battery capacity of drones, secondary power supply may be needed midway through the delivery of drones. This paper gives the definition of a combined drone-truck-recharging station combined transport system. The recharging station can charge the drone in time, and solve the problem that the cargo can not be transported due to factors such as limited battery capacity of the drone itself and the impact of external environmental conditions during long-distance transportation. The recharging station extends the flight distance of the drone while ensuring the safety and reliability of cargo transportation. In this paper, we discuss the important role played by the drone and recharging station in the truck logistics. Drones are more suitable for long-distance transportation service because of their fast flight speed and low energy consumption. Recharging stations also ensure that the drones are recharged during the longdistance flight. Studies have also shown that the use of the drones and recharging station can greatly reduce the overall transportation time of truck logistics and improve transportation efficiency. Therefore, the drone-truck-recharging station combination transport system can play an important role in the Chinese rural marketaˇ c. In this paper, the goal is to minimize the total time of truck transportation. A mathematical planning model is proposed to put the drone charging station into use, allowing the drone to land on the charging station and charge during the flight and charge. Furthermore, the MILP model realize the path planning of trucks and drones. To show the feasibility and practicality of the model, we give a numerical experiment. In the future research, we will consider other methods to improve the drone delivery efficiency, such as the drone’s multiple recharging during the flight, the drone’s single delivery with multiple packages, and some more effective algorithms. Moreover, with the development of drone technology, drone energy can change from electrical energy to solar energy, hydrogen energy or other energy sources. Drone operation can reduce more energy consumption and extend the life cycle. The goal can turn to minimize energy consumption.

References 1. Agatz, N., Bouman, P., Schmidt, M.: Optimization approaches for the traveling salesman problem with drone. Transp. Sci. 52(4), 965–981 (2018)

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2. Bouman, P., Agatz, N., Schmidt, M.: Dynamic programming approaches for the traveling salesman problem with drone. Networks 72(4), 528–542 (2018) 3. Dorling, K., Heinrichs, J., et al.: Vehicle routing problems for drone delivery. IEEE Trans. Syst. Man Cybern. Syst. 47(1), 70–85 (2016) 4. Elliot, D.: DHL testing delivery drones. CBS News (2013) 5. Grothaus, M.: This is how Google’s project wing drone delivery service could work. Fast Company (2016) 6. Ha, Q.M., Deville, Y., et al.: On the min-cost traveling salesman problem with drone. Transp. Res. Part C Emerg. Technol. 86, 597–621 (2018) 7. Hong, I., Kuby, M., Murray, A.T.: A range-restricted recharging station coverage model for drone delivery service planning. Transp. Res. Part C Emerg. Technol. 90, 198–212 (2018) 8. Jiang, Y.: The JD drone sent the first item of normalized delivery in the southwest China: an uncle nearly eighty years old received the goods for the spring festival (2019) 9. Murray, C.C., Chu, A.G.: The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp. Res. Part C Emerg. Technol. 54, 86–109 (2015) 10. Ponza, A.: Optimization of drone-assisted parcel delivery (2016) 11. Rose, C.: Amazon’s jeff bezos looks to the future. CBS News 1 (2013) 12. Sundar, K., Rathinam, S.: Algorithms for routing an unmanned aerial vehicle in the presence of refueling depots. IEEE Trans. Autom. Sci. Eng. 11(1), 287–294 (2013) 13. Toor, A.: This startup is using drones to deliver medicine in Rwanda. The Verge (2016) 14. Wen, J.: JD built the world’s first unmanned drone operation dispatch center (2017) 15. Yu, K., Budhiraja, A.K., Tokekar, P.: Algorithms for routing of unmanned aerial vehicles with mobile recharging stations. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 1–5. IEEE (2018) 16. Yurek, E.E., Ozmutlu, H.C.: A decomposition-based iterative optimization algorithm for traveling salesman problem with drone. Transp. Res. Part C Emerg. Technol. 91, 249–262 (2018)

The Vehicle Routing Problem with Drone for the Minimum CO2 Emissions Xinying Peng1 , Deguo Sun2 , and Zhiyi Meng3(B) 1

College of Architecture and Urban-Rural Planning, Sichuan Agriculture University, Dujiangyan 611830, People’s Republic of China 2 College of Civil Engineering, Sichuan Agriculture University, Dujiangyan 611830, People’s Republic of China 3 Business School, Sichuan University, Chengdu 610064, People’s Republic of China [email protected]

Abstract. The unmanned aerial vehicle (UAV), also called as drone, has developed fast in the civilian field. Not only it has high speed, low cost and no road restriction, but also it takes a positive role in CO2 emissions. The drone’ s light total mass and the lithium battery that as the power producer make it has less energy consumption and CO2 emissions. It could replace the truck to serve for some customers who need light parcels to reduce fuel consumption and time cost besides the influence to environment. However, for some heavy parcels, the truck is necessary to deliver. This paper assumed a situation that a drone and a truck delivering parcels in a route together, the aim is to find out the route that the vehicles produced the minimum CO2 emissions through building a mixed integer liner model. And one of the drones’ warehouses of JD in Guang’an, Sichuan was chosen as the realistic example. The analysis resulted that the distance of the truck was the major decision element to reduce the total CO2 emissions. In this case, the minimum total emissions are less 4.31 kg CO2 than the emissions of the truck serving all nodes. Keywords: Drone · The minimum CO2 emissions route · Logistics · Environmental impact

1

· Optimizing

Introduction

Drones, which can scout ground, monitor air pollution and disaster, photograph aerial, irrigate crops, deliver medical supplies urgently and so on. At the situation the logistics industry develop fast, in the link of delivering parcels, the drone has a preponderance in delivering small parcels because of its fast speed, low cost and no road restrictions, for why it became a potential untraditional transport tool in logistics industry. In 2013, Amazon published the Prime Air plan aimed to deliver parcels to customers in 30 min by using drones. The companies such as UPS, DHL, Google, China, S.F. Express, JD, raced to join the researching c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 24–34, 2021. https://doi.org/10.1007/978-3-030-49889-4_3

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and applying of drones. The aerial management and policies about drones are pushing and improving from earlier forbidding to now. In 2014, DHL used drones to deliver medicines in Yuster of Germany’s north sea under the Germany’s government supports. In June 2017, S.F. Express completed drone test flight in Jiangxi, Ganzhou and obtained the first legal flight right of drones logistics. On January 8, 2019, JD Logistics officially started the normal operation of drones in the Guang’an business department of Sichuan. In July of the same year, UPS Flight Forward Inc., a newly registered subsidiary of UPS, applied for FAA section 135 certification and was expecting to be one of the first fully certified operators in the U.S. to use drones for commercial transportation. As drones’ technology improving and policies breaking through, drones logistics will have more obvious competitive advantages than traditional logistics. When the technology of the drone isn’t mature enough, there have been some studies about drones delivering routes. In the studies drones deliver alone, Sundar and Rathinam (2014) studied to optimize drone-routes through taking advantage of charging facilities in multiply warehouses [11]. Hong et al. (2018) considered to deploy charging station network to enlarge the drone flight coverage area from the warehouse [6]. Except drone delivering alone, more is a series of studies on the combination of the drone and truck as shown in Fig. 1. The truck is not only as a delivery tool but also a mobile charger for the drone. Murray and Chu (2015) came up with a problem, which named “Flying Sidekick Traveling Salesman problem” (FSTSP) [9]. Its purpose is to minimize the time that deliver goods for all customers by a truck and a drone. The model they described is that the drone could be launched in a node from the truck, then they both delivered parcels in different way, gathered in another node. Agatz et al. (2016) studied a problem called “travel salesman problem with drone” (TSP-D), which the difference between FSTSP is it allows the drone return the launch node [1]. Ha et al. (2018) modeled a new variant of TSP-D added the waiting time between the two vehicles [5]. It aimed to minimize the total transportation cost including the cost of waiting time. Poikonen, S., and Golden, B. (2020) proposed a combined way about a truck and k drones to minimize the delivery time, in which the drone can carry multiple different packages in particular, and the results show the speed and number of drones affects highly the target value [10]. Karak, A., and Abdelghany, K. (2019) proposed a problem named the hybrid vehicle-drone routing problem (HVDRP), aimed to minimize the vehicle and drone routing cost to serve all customers [7]. And they expanded the classic Clarke and Wright algorithm to solve the HVDRP, in which had a more efficient and faster solution to both small and large instances. The studies mentioned above discussed mostly how to optimize the route in the angle of concerning cost. But from the perspective of the environment, CO2 emissions are always a current topic in logistics transportation. Wygonik et al. (2012, September) compared the CO2 emissions between personal vehicle travel and delivery service in grocery shopping in Washington, found that vehicle-miles traveled (VMT) and CO2 emissions of shared-use vehicles reduced significantly than personal vehicle travel [13]. In this study, it decreased 80%–90% emissions

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(a). The Y3 model in JD series drones (source: x.jdwl.com)

(b). The light truck (jmc.com)

Fig. 1. The drone and truck of collaborative delivery

mostly if arranged reasonable route. And the environmental influence of delivery service would be more positive in low density population areas such as villages. In terms of the environmental impact of the energy supply of transport vehicles, Kim et al. (2016) evaluated and analyzed Cradle-to-gate emissions for lithium batteries, and concluded that the battery electric vehicle (BEV) has great potential to reduce greenhouse gas (GHG) emissions and provide local emission-free mobility throughout its lifecycle [8]. While most drones which use lithium batteries have a friendly environmental impact. Some papers analyzed whether the drone had an advantage in energy consumption and CO2 emissions or not by comparing the drone and the truck. Figliozzi, M. A. (2017) studied drones’ emission efficiency of CO2 lifecycle, which including vehicle utilization phase and vehicle production/disposal phase, comparing with conventional diesel vans, electric trucks, electric vans, and tricycles in different routes and customer configuration [3]. The results through modeling indicated drones had less emissions per unit distance than diesel vans with a small payload. Goodchild, A., and Toy, J. (2018) adopted several ArcGIS tools and the CO2 emission standard to evaluate CO2 emissions of a drone and a truck in ten varying delivery conditions and drone energy requirements, analyzed the drone was more efficient if the depot was closer and customers were less in the same energy requirements [4]. Companies should consider the environmental impact besides the economic efficiency that drones bring. For example, At RE: MARS conference in May 2019, Amazon’s CEO Jeff Wike proclaimed their vision was to make all the shipments of Amazon can reach zero emissions, and 50% shipments reach zero emissions by 2030. And the electric drones can be considered referring to sustainable development. In terms of emissions and energy efficiency, the electric drone had a big improvement than road vehicles [12]. According to the above studies, drones have a more positive impact than fuel trucks in certain situations. Some of them studied the way of drones and trucks’ joint delivery, Some considered the minimum cost in the corresponding delivery combination, others focused on the CO2 emission or energy consumption that drones compared with trucks. There is no study about the CO2 emissions when considered a drone and a truck delivery together. This paper choose FSTSP proposed by Murray and Chu (2015) as a

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reference to study the optimal route of minimum total CO2 emissions of a drone and a truck, studies if there are better environmental impact effects under the combination of the advantages and disadvantages of the two vehicles. The main contribution of this paper builds a MILP which the object is to minimize total CO2 emissions to solve the optimum route, chooses the JD’s regular drone operation in Guang’ an, Sichuan, China as an realistic example to calculate the result in a small delivery scale. According to the calculation results, it is concluded that the addition of drone can indeed reduce the total CO2 emission, but the amount of carbon reduction is ultimately determined by the distance the truck travels. The rest of this paper is as follows: Sect. 2 describes the model, Sect. 3 is the establishment of the MIPL model, Sect. 4 is the instance solution and result analysis, Sect. 5 is the conclusions.

2

Modeling Description

2.1

Modeling the CO2 Emissions of the Truck and the Drone

The models are according to the lifecycle modeling of CO2 emissions built by Figliozzi, M. A. (2017) [3]. The lifecycle included material extraction, material processing, production, utilization and final recycling. All of these processes were divided to two phases, namely vehicle utilization and vehicle production/disposal. The phase named vehicle utilization includes well-to-tank (WTT) and tank-to wheel (TTW) for the truck, while for the drone, vehicle utilization includes generation-to battery (GTB) and battery-to-propeller (BTP). According to his analysis results, the vehicle production/disposal phase of the truck account for a negligible proportion in every delivery process, while the drone’s CO2 emissions of vehicle production/disposal phase can account for half of the vehicle utilization phase’s emissions. Therefore, in the modeling of drone’s CO2 emission, the modeling of vehicle production/disposal phase is not built separately, but its proportion in the vehicle utilization phase is directly introduced.

Ec =

1 fc (ewtt + ettw ) . 100

(1)

Ec = CO2 emissions per unit distance of the fuel truck (kgCO2 /km) fc = fuel consumption (L/100 km) ewtt = emissions of WTT phase (kgCO2 /L) ettw = emissions of TTW phase (kgCO2 /L)

Eu = 1000(1 + α) (egtb + ebtp ) fkwh (m + q)

g . ϑ(s)ηp ηr

(2)

Eu = CO2 emissions per unit distance of the drone (kgCO2 /km) α = proportion of the drones’ production/disposal phase to the vehicle utilization phase = 0.5

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egtb = emissions of GTB phase (kgCO2 /kwh) ebtp = emissions of BTP phase (kgCO2 /kwh) fkwh = conversion factor from Joule to kWh = 2.7778e−7 m = drone empty mass (kg) q = drone load mass (kg) g = gravity acceleration (m/s2 ) θs = lift-to-drag ratio ηp = total power conversion efficiency ηr = battery charging efficiency

3

Description of the Delivery Route

The route refers to FSTSP proposed by Murray and Chu is descripted as follows: • The drone and the truck have to depart from the depot return to it, and the both probably depart from and return to the depot respectively. • The drone can load in the truck or flight alone. When the drone leaves the truck to deliver a parcel, the truck is going to deliver for other customer nodes. Meanwhile, the drone can only serve for one customer node in a flight, but the truck can meet several customer nodes. • The drone must not launch or land more than once at node i. • Every node has to be visited for only once except the depot. This modeling defines in a complete route graph G = (N, A), in which A are the arc set between each node and N = {0, 1, 2, ..., n, n + 1} represent all the nodes. The drone and the truck deliver goods in this graph. 0 and n + 1 represent the same depot node, 0 means the truck and the drone start from the depot, n + 1 means they return to the depot, thus forming a closed route. While Nc = {1, 2, ..., n} represent all customer nodes, that is all customer nodes that the drone or the truck must visit and can only visit once. It is worth emphasizing that, for meeting the real logistics situation in high dens population, every customer node maybe have more than one customer, because it is used as a centralized acceptance node, which perhaps is a parcel convenience store or a village center. Due to the limited load weight and flight endurance of the drone, the nodes which need large amount of goods or remote client can only be arrived at by  the truck, so Nc represent the nodes that can be visited by the drone, in which  Nc ⊆ Nc . N0 = {0, 1, 2, ..., n} represent the nodes where the departure nodes of the truck, and also the nodes where the drone can launch independently, either from the truck or from the depot. N+ = {1, 2, ..., n, n + 1} represent the nodes of truck’s arrival nodes, also represents the drone landing nodes, which can meet with the truck, or may directly return to the depot node. The distance of the truck from the leaving node i ∈ N0 to the arrival node j ∈ N+ is expressed as dij , and the distance of the drone that launches from the leaving node i ∈ N0  to the arrival node j ∈ N+ is dij . Regarding the distribution route of the drone, its continuous mileage is limited due to its lithium battery energy supply property. We define a triplet ; i, j, k ∈ N, i = j, j = k, i = k, dij + djk ≤ e that represents the drone leaving from node i to delivering parcels at node j and then landing at node k, in which e represents the maximum mileage. We define E as the set of G = (N, A) so that it meets the maximum distance of drone flight:    E = {: i, k ∈ N, j ∈ Nc , i = j, j = k, i = k, dij + djk ≤ e}

4

The Mixed Integer Liner Programming

The minimum total CO2 emissions of this route are represented by a mixed integer linear programming. The decision variables are: xij ∈ {0, 1} taking value 1 when the truck leaves from node i ∈ N0 to node j ∈ N+ , otherwise 0. yijk ∈  {0, 1} taking value 1 when the drone leaves from node i ∈ N0 to node j ∈ Nc to node j ∈ N+ , otherwise 0. The remaining parameters have been mentioned above, and the established mixed integer linear programming model is as follows: Min





i∈N0

j∈N+ i=j

(1 + α)

g ϑ(s)ηp ηr

1 f 100 c



(ewtt + ettw ) dij xij +



    1000 (m + qj ) dij + mdjk

i∈N0 k∈N+ i=j i, j, k∈E

(egtb + ebtp ) fkwh yijk

(3) s.t 



xij +

i∈N0 i=j



yijk = 1 ∀j ∈ Nc .

(4)

i∈N0 k∈N+ i=j i, j, k∈E 

x0j = 1.

(5)

xi,n+1 = 1.

(6)

j∈N+

 i∈N0



xij =

i∈N0 i=j 



xjk ∀j ∈ Nc .

(7)

k∈N+ j=k 

j∈Nc k∈N+ j=i i, j, k∈E

yijk ≤ 1 ∀i ∈ N0 .

(8)

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yijk ≤ 1∀k ∈ N+ .

(9)

i∈N0 j∈Nc i=k i, j, k∈E 2yijk ≤

 h∈N0 h=i



xhi +

xfk ∀i ∈ Nc , j ∈ {Nc |i = j }, k ∈ {N+ |i, j, k ∈ E }.

f∈Nc f=k (10) y0jk ≤



xhk j ∈ Nc , k ∈ {N+ |i, j, k ∈ E }.

(11)

h∈N0 h=k h=j 



qj yijk ≤ Q∀j ∈ Nc .

(12)

xij ∈ {0, 1} ∀i ∈ N0 , j ∈ {N+ |i = j } .

(13)

yijk ∈ {0, 1}∀i ∈ N0 , j ∈ {N+ |i = j }, k ∈ {N+ |i, j, k ∈ E }.

(14)

qj ≥ 0∀j ∈ Nc .

(15)

i∈N0 k∈N+ i=j i, j, k∈E

It aims to minimize the total CO2 emissions when the truck and the drone serve for all customers and return to the depot. The remaining constraints are interpreted as: Eq. (4) indicates that every customer node Nc must be accessed and only once. Equation (5) and Eq. (6) respectively indicate that the truck must leave the depot and return to it. Equation (7) indicates that the truck must leave after arriving at any customer node Nc . Equation (8) and Eq. (9) indicate respectively that the drone can only launch once at any node i ∈ N0 and land once at any node k ∈ N+ . Equation (10) means that if the drone takes off from node i, deliver the parcel to node j, then return to node k, then the truck must travel from node i to node k. Equation (11) means that if the drone delivers from the depot to node j and arrive at node k, then the truck must reach node k. Equation (12) means the cargo quality of the drone cannot exceed the maximum load-bearing quality.

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The Realistic Example Calculating and Analyzing The Background of the Realistic Example

In China, JD logistics has got a great improvement in the aspect of drones. On January 8, 2019, JD Logistics officially opened the drone normal operation in Sichuan Guang’an Sales Department, which is the first normal operation pilot of drone distribution in southwestern China. Because of the limitation of Sichuan’s terrain factors, some places with straight lines are close, but it takes a long time for the courier to deliver goods safely. With the drone, the space is not restricted, and it is more free and convenient. This paper selects one of JD’s depot nodes set up in Guang’an, as well as assuming customer nodes around, as a distribution example. 5.2

The Data Assuming

The realistic delivery place of this case is the depot node at the second group of Bayi Village, Guang’an, Sichuan, with six customer nodes around it, as shown in Fig. 2, in which the red circle indicates customer node that meets the drone delivery conditions and the yellow triangle represents the customer node that can only be serviced by the truck. And the parameters’ reference value are shown in Table 1 (the numbers have been rounded to two decimal places).

Fig. 2. The nodes assuming around Bayi Village, Guang’an, Sichuan

Table 1. The parameter reference values Parameters fc m θs Values

etap ηr

ewtt ettw egtb ebtp

10 12 4.25 90% 98% 0.61 2.73 0.56 0

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The Results Analyzing

According to the data results and the minimum total CO2 emissions route in Fig. 3, there are several characteristics of total CO2 emissions from the drone and the truck as follows: 1) In this case, The total CO2 emissions are 0.6342 kg less on average when the drone delivers once than if only the truck deliver parcels. And the total CO2 emissions are 3.5708 kg less on average when the drone delivers twice than once. It shows that the drone have greatly roles in reducing the total CO2 emissions throughout the logistics distribution. 2) The CO2 emissions ratio of truck to drone when the drone acts once is 161:1, and the CO2 emissions ratio of truck to drone when the drone acts twice is 59:1. It indicates that the truck account for a large proportion of the total CO2 emissions, but as the number of drone service times increases, the trucks’ CO2 emissions account for a smaller proportion of the total CO2 emissions. 3) The total CO2 emissions mostly depend on the distance traveled by the truck. 4) The more customer nodes the drone serve for, the smaller the total CO2 emissions. In the case, the average total CO2 emissions of two delivery nodes served by the drone is 5.4094 kg less than the average total CO2 emissions of a single drone delivery node. 5) When the distance traveled by the truck is the same, the minimum drone flight distance and the minimum drone load weight can get the minimum total CO2 emissions. 6) If a node is serviced by a drone, and the truck is very close to this node on its way to another node, then even if the CO2 emissions of the drone are small, the CO2 emissions of the truck are not be reduced a lot for the reason that the distance traveled by the truck did not decrease significantly. In general, the truck’s driving distance is the biggest determinant in the case of delivery goods to all customers, the smaller the truck’s driving distance, the less CO2 emissions, the more times the drone launches. However, there are always some customer nodes which distance is greater than the maximum flight endurance distance of the drone, and the required load weight also exceeds the load-bearing range of the drone, so the minimum CO2 emission value is limited. If the route is arranged according to the goal of minimum CO2 emissions in reality, the total carbon footprint should be smaller, so the more customer nodes the drone replaces the truck service, the more times and the time it takes to fly, meaning it needs the number of times the battery is replaced or charging and the time the truck waits for the drone is more. The pros and cons of it are relative at different angles. It is applicable in analyzing the environmental impact, but for companies that need economic profit, the minimum total CO2 emissions can only provide a reference. This paper establishes a mixed integer linear programming model for solving the optimal route with the goal of minimum total CO2 emissions under the combined distribution mode of a truck and a drone. Combining the simple case of six customer nodes, it analyzes that as long as the drone can deliver as much as

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Fig. 3. The optimal route of the minimum total CO2 emissions

possible to the customer nodes which meet the drone distribution requirements, reducing the truck travel distance can effectively reduce the total CO2 emissions. In total CO2 emissions, the trucks’ CO2 emissions always account for a large part, if the technology development makes the truck fuel consumption lower, ewtt and ettw are smaller, then the total CO2 emissions will also decrease. In addition, with the development of electric vehicles in recent years, if electric vehicles can meet the low purchase price, sufficient mileage, and enough customer to service, the electric trucks are more competitive than traditional trucks [2], combining electric vehicles with drones, the CO2 emissions can achieve a more ideal state. Although the drone’s CO2 emissions in multi-customer distribution are not superior to electric vehicles, its straight-line flight makes it always be faster than ground vehicles. So it’s still irreplaceable in the place where roads are blocked or traffic conditions are poor, the combination of the two kinds of vehicles can be developed both environmentally and economically. For the optimal route with the goal of minimum CO2 emissions or the goal of minimum cost, logistics companies must tend to opt the second goal. However, with more and more people paying attention to the global environment, if logistics companies can balance cost and CO2 emissions and develop green logistics, this will not only respond to the corresponding environmental protection policies, but also make customers have a shopping experience that is both efficient and environmentally friendly. If through analyzing the similarities and differences between the minimum cost and the minimum CO2 emissions to find a balance between cost and environment to meet the bilateral benefits maximization, it is also a problem worth considering. Besides, the models and cases in this paper are relatively simple. If there are hundreds of customer nodes, it is also possible to consider multiple trucks and multiple drones to form a large route network, and adopting algorithms to solve the model. Data analysis of CO2 emissions in this case may also vary. Acknowledgements. This research was supported by the National Natural Science Foundation of China (Grant No. 71903139), by the Humanities and Social Sciences Foundation of the Ministry of Education of China (Grant No. 16YJC630089).

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It was also support by the Soft Science Program of Sichuan Province (Grant No. 2019JDR0155) and Basic scientific research service fee project of central universities of sichuan university (no. 2019 Self Research-BusinessC03). We appreciate this organization for its support in both finance and spirit. Further, we would like to thank all of the interviewees who showed great patience in answering the questionnaires. We are grateful for the time and efforts of the editors and reviewers.

References 1. Agatz, N., Bouman, P., Schmidt, M.: Optimization approaches for the traveling salesman problem with drone. Transp. Sci. 52(4), 965–981 (2018) 2. Davis, B.A., Figliozzi, M.A.: A methodology to evaluate the competitiveness of electric delivery trucks. Transp. Res. Part E Logist. Transp. Rev. 49(1), 8–23 (2013) 3. Figliozzi, M.A.: Lifecycle modeling and assessment of unmanned aerial vehicles (drones) CO2e emissions. Transp. Res. Part D Transp. Environ. 57, 251–261 (2017) 4. Goodchild, A., Toy, J.: Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry. Transp. Res. Part D Transp. Environ. 61, 58–67 (2018) 5. Ha, Q.M., Deville, Y., Pham, Q.D., H` a, M.H.: On the min-cost traveling salesman problem with drone. Transp. Res. Part C Emerg. Technol. 86, 597–621 (2018) 6. Hong, I., Kuby, M., Murray, A.T.: A range-restricted recharging station coverage model for drone delivery service planning. Transp. Res. Part C Emerg. Technol. 90, 198–212 (2018) 7. Karak, A., Abdelghany, K.: The hybrid vehicle-drone routing problem for pick-up and delivery services. Transp. Res. Part C Emerg. Technol. 102, 427–449 (2019) 8. Kim, H.C., Wallington, T.J., Arsenault, R., Bae, C., Ahn, S., Lee, J.: Cradle-togate emissions from a commercial electric vehicle Li-ion battery: a comparative analysis. Environ. Sci. Technol. 50(14), 7715–7722 (2016) 9. Murray, C.C., Chu, A.G.: The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp. Res. Part C Emerg. Technol. 54, 86–109 (2015) 10. Poikonen, S., Golden, B.: Multi-visit drone routing problem. Comput. Oper. Res. 113(104), 802 (2020) 11. Sundar, K., Rathinam, S.: Algorithms for routing an unmanned aerial vehicle in the presence of refueling depots. IEEE Trans. Autom. Sci. Eng. 11(1), 287–294 (2014) 12. Wilke, J.: A drone program taking flight: amazon moves closer to its goal of a drone delivery solution that scales to meet the needs of customers (2019). https:// blog.aboutamazon.com/transportation/a-drone-program-taking-flight 13. Wygonik, E., Goodchild, A.: Evaluating the efficacy of shared-use vehicles for reducing greenhouse gas emissions: a us case study of grocery delivery. J. Transp. Res. Forum, 51 (2012)

A Two-Stage Stochastic Programming Model for Pre-positioning of Relief Supplies Yusheng Wang1(B) , Zaiwu Gong1 , and Benjamin Lev2 1 School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, People’s Republic of China [email protected] 2 Drexel University, Philadelphia, PA, USA

Abstract. Pre-positioning and distribution of emergency supplies are important activities in the preparedness and response stages for disasters. The goal of this paper is to address the joint decision-making of pre-positioning and distribution of relief supplies under uncertain environment. A two-stage stochastic programming model with the objective of the minimizing total cost is formulated and the uncertainties of disasters are taken into account. A case study focusing on addressing hurricane threats in the Gulf Coast area of the US is conducted to illustrated the application of the proposed model. The results analysis provides managerial insights for relief agencies.

Keywords: Pre-positioning strategies logistics · Stochastic programming

1

· Facility location · Relief

Introduction

In recent years, the rate and casualty of natural disasters have significantly increased. According to the most recent statistics from the Centre for Research on the Epidemiology of Disasters (CRED), from 2008 to 2017, a yearly average of 348 natural disaster events were reported, which annually caused 67,572 deaths and US$166.7 billion economic damage, and affected 198.8 million people on average [13]. A recent example is Super Typhoon Mangkhut in September 2018, which caused more than 150 deaths and 70 billion in economic losses, affecting most provinces in southeastern China and the Philippines. These facts reveal the importance of disaster management in mitigating the negative effects of the disaster [12]. Pre-positioning of relief supplies is an effective strategy to help relief agencies improve their capacity of preparedness and emergency response to various natural disasters. There is rich literature that focused on the pre-positioning of relief c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 35–44, 2021. https://doi.org/10.1007/978-3-030-49889-4_4

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supplies. Rawls and Turnquist presented a two-stage stochastic mixed integer programming model to determine relief facility locations and quantities of various types of relief supplies to be pre-positioned at the relief facilities while considering the uncertainty about disasters and the availability of the transportation network [10]. Duran et al. evaluated the effect that pre-positioning relief items would have on CARE’s average relief-aid emergency response time [4]. Galindo and Batta investigated pre-positioning of supplies in preparation for a hurricane considering potential destruction of pre-positioned supplies during the disaster event [5]. Rezaei-Malek et al. presented an interactive approach to designing a robust disaster relief logistics network for perishable commodities [11]. Chen et al. presented a newsvendor approach to modeling the pre-positioning of relief inventories decisions for non-profit organizations taking social donation and emergency spot purchasing into account [3]. Ni et al. proposed a min-max robust model to optimize the decisions of facility location and emergency inventory pre-positioning for disaster response operations [9]. Hu and Dong integrated supplier selection into pre-positioning of relief supplies while considering price discounts and disruption risks to the relief supplies [6]. Disaster situations can be divided into two stages: pre-disaster stage and post-disaster stage [1]. Accordingly, disaster management has a two-stage nature: determining the level of preparedness (e.g. location and inventory level of relief supplies) before the disaster occurs, and then reacting once the disaster occurs [8]. Therefore, two-stage stochastic models are commonly utilized in many applications related to disaster management [6,7,10]. Moreover, disasters are stochastic in their nature: both their occurrence (e.g., hit time, geographic location and intensity) and their consequences are not easily anticipated. As a viable tool to handle uncertainty by probabilistic scenarios to represent disasters and their outcomes in the preparedness phase, stochastic programming has been widely in the pre-positioning research [2,6,8]. Inspired by these existing literature, we developed a two-stage stochastic programming model to pre-position and distribute relief materials in humanitarian logistics. In the first stage (the preparedness phrase), the relief agency needs to determine the locations of relief facilities as well as the amount of relief supplies pre-positioned at these relief facilities. In the second stage (the response phrase), the relief agency needs to transport certain quantity of relief supplies from the relief facility to victims. The second-stage decisions are conditional on the first-stage decisions. One of the major contributions of our paper is to consider the occurrence probability of natural disasters and the uncertainty about the demand for relief supplies in the preparedness phrase. The rest of the paper is organized as follows. The problem is described in Sect. 2 and the mathematical model is developed in Sect. 3. A case study is present and the results is analyzed in Sect. 4. Finally, we conclude our work and discuss possible future research directions in Sect. 5.

A Two-Stage Stochastic Programming Model

2

37

Problem Description

We consider a humanitarian logistics system consisting of three echelons, namely, the central warehouse, storage facilities and demand points. In the aftermath of a disaster, there will be demands for relief supplies at specific locations. At the planning stage, the demand for a certain relief supply at a certain location is uncertain, since it is not yet known whether, or where a disaster will occur. A set of discrete scenarios are used to denote the uncertainty. The definition of a scenario includes the location and the scale of a disaster, as well as the demand for each type of relief supply. To respond to the possible natural disasters as soon as possible, a set of relief supplies can be pre-positioned at storage facilities. A fixed cost will be incurred if a storage facility is made available. At the same time, the quantity of the relief supplies pre-positioned should be subject to the capacity limits of the storage facilities. Moreover, some or all of the relief supplies pre-positioned at a given storage facility may be destroyed by the disaster. The degree of damage can be revealed by a risk parameter, whose specification is also a part of the scenario definitions. After a disaster occurs, the surviving stock of the relief supplies are distributed across a transportation network to meet demands. Each demand point is assigned to only one storage facility and the stocks on hand are used to satisfy the assigned demands first. If the demand for a particular relief commodity cannot be satisfied, a penalty cost for the shortage of this commodity will be incurred. The objective of this study is to identify an optimal strategy that combines decisions on storage facility locations, stocking levels for relief supplies, and distribution of those relief supplies to multiple demand points after a disaster, with uncertainty about demand and survival of pre-positioned stocks of relief supplies.

3

Modelling

The problem described above is formulated as a two-stage stochastic mixed integer program. The first-stage decision variables includes the location and size of storage facilities, as well as stocking decisions for various types of relief supplies pre-positioned at the facilities. These decisions have to be made in the presence of uncertainty about future demands. The second-stage decision variables involve the distribution of available relief supplies in response to specific scenario disasters. These decisions are made after the realization that the uncertainty is known, and are conditional on the first-stage decisions. The notations for the model are presented as follows. Sets: I Set of candidate locations for relief storage facility, indexed by i; J Set of demand locations, indexed by j; S Set of possible disaster scenarios, indexed by s.

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Parameters: Qsj Demand for relief materials at location j in scenario s; Ps Occurrence probability of scenario s; Dij Distance between location i and location j; R Maximum distance for the relief materials to travel; Θ Storage capacity of a relief facility to stock materials; Cfi Unit fixed cost incurred by opening a relief facility in location i; Ca Unit acquisition cost for the relief materials; Ct Unit transport cost for the relief materials; Cp Unit penalty cost for the shortage of the relief materials; ρsi Proportion of stocked relief materials at location i remaining usable after a disaster in scenario s; M A big enough positive number. Decision Variables: yi Binary decision variable which indicates if a relief facility is built at location i (value 1) or not (value 0); qi Quantity of relief materials pre-positioned at location i; xsij Quantity of relief materials transported from relief facility i to demand location j in scenario s; s Binary decision variable which indicates if demand location j is assigned to zij relief facility i in scenario s (value 1) or not (value 0); usj Unsatisfied demand for relief materials at location j in scenario s. The complete two-stage stochastic mixed integer programming model is provided in Eqs. (1)–(10). min C =



(Cfi yi + Ca qi ) +

i∈I

Subject to:



Ps

s∈S



xsij + usj = Qsj



Ct Dij xsij +

i∈I j∈J



Cp usj

 (1)

j∈J

∀j ∈ J, s ∈ S

(2)

i∈I



xsij ≤ ρsi · qi

∀i ∈ I, s ∈ S

(3)

∀i ∈ I, j ∈ J, s ∈ S

(4)

j∈J s Dij · zij ≤R

qi ≤ Θ · yi ∀i ∈ I  s zij = 1 ∀s ∈ S, j ∈ J

(5) (6)

i∈I



s zij ≤ M · yi

∀i ∈ I, s ∈ S

j∈J s xsij ≤ M · zij ∀i ∈ I, j ∈ J, s ∈ S s s s xij , wi , vi , qi ≥ 0 ∀i ∈ I, j ∈ J, s ∈ s yi , zij ∈ {0, 1} ∀i ∈ I, j ∈ J, s ∈ S

(7) (8) S

(9) (10)

A Two-Stage Stochastic Programming Model

39

The objective function (1) minimizes the expected costs over all scenarios resulting from the selection of the pre-positioning locations, the relief materials acquisition and stocking decisions, the shipments of the supplies to the demand points, unmet demand penalties and holding costs for unused material. Constraint (2) represents conservation of flow in the network at each location, for every commodity and every scenario. Constraint (3) ensures that the available amount of relief materials pre-positioned at an opened relief facility is sufficient to meet total demand assigned to that relief facility. Constraints (4) limits the travel distance of relief materials. Constraint (5) makes certain that stocked relief materials do not exceed the facility capacity. Constraint (6) makes sure that each demand location j is assigned to only one relief facility. Constraint (7) ensures that a demand location only can be assigned to a relief facility that is opened. Constraint (8) ensures that relief materials cannot be sent from a relief facility to a demand location unless that demand location is assigned to that relief facility. Constraints (9) and (10) define restrictions on decision variables.

4

Case Study

In this section, a case study based on real-world hurricanes in the Gulf of Mexico region of the southeastern United States, as shown in Fig. 1, is used to illustrate the two-stage stochastic programming model as well as provide managerial implications.

Fig. 1. The map of Gulf of Mexico.

4.1

Data Preparation

The data of the case study are based on the research network from the work of [10], and 10 nodes were selected as demand locations as well as candidate locations for storage facilities. Table 1 lists the index and the corresponding location

40

Y. Wang et al.

name of these nodes. Therefore, sets I and J contain 10 elements, respectively. Distances between each pair of nodes are obtained from Google Maps. The maximum distance for relief commodities to travel is assumed to be 500 miles. Table 1. Node indices and the corresponding location names. Index Location

Index Location

1

Corpus Christi, TX

6

Mobile, AL

2

San Antonio, TX

7

Tallahassee, FL

3

Houston, TX

8

Orlando, FL

4

Beaumont, TX

9

Tampa, FL

5

New Orleans, LA

10

Miami, FL

The relief material discussed here is drinking water, and its unit is assumed to be 1,000 gallons. The unit costs for purchasing and transporting these supplies are estimated to be 650$ and 0.3$/mile. The unit penalty cost is assumed to be 10 times the purchase prices. The fixed cost to build a relief facility is assumed to be 20,000$, and its storage capacity is to store 2,500 units of drinking water. Based on the historical records, a set of 10 scenarios was constructed to represent potential demands and network damage in the case study. In these scenarios, the relief materials stocked at the hurricane landfall nodes are assumed to be damaged, and the damage degree is proportional to the hurricane scale. Specifically, we assume that a major hurricane would destroy all relief materials pre-positioned at the landfall nodes, and a 50% loss would be incurred by a minor hurricane. Table 2 lists the characteristics of these scenarios, including the occurrence probability, landfall nodes, scale, and the demands for drinking water at each node. Table 2. Characteristics of scenarios. Scenario no.

Occurrence probability

Landfall node

Scale Demands for drinking water at each node 1 2 3

4 5

6 0

7

8

9

10

1

0.155

3

Minor 24 80 201 5

0

0

0

0

0

2

0.155

3

Minor 24 80 201 5 296 44

0

0

0

0

3

0.155

10

Major 0 0

0 37 666

0 819 1997 3860

4

0.155

5

Minor 0 0

0 0 543 121 107

5

0.128

5

Major 0 0

0 93 1680

0

0 819 1997 3860

6

0.042

9

Minor 0 0

0 37 962 44

0 819 1997 3860

7

0.042

5

Minor 0 0

0 0 839 165 107

8

0.042

9

Minor 0 0

0 37 1209 121 107 819 1997 3860

9

0.063

10

Major 0 0

0 0 590 117

0

0

0 1527

10

0.063

10

Major 0 0

0 0 1133 238 107

0

0 1527

0

0

0

0

0

0

0

A Two-Stage Stochastic Programming Model

4.2

41

Results Analysis

The established two-stage stochastic programming model was programmed in AMPL and solved using the commercial solver CPLEX 12.4. All numerical experiments were run on a desktop with 4 GB of RAM and 3.50 GHz of APU under a Windows 7 environment. There were 2,410 constraints and 2,120 variables (including 490 binary variables). The results of the first-stage decision variables are summarized in Table 3. It requires to open five storage facilities, distributed widely across the network. A total of 7.1 million gallons of water are pre-positioned at these storage facilities. The amount of drinking water pre-positioned at each facility varies greatly from 104,000 gallons to 2.5 million gallons. Specifically, the facility located in Orlando can make full use of its space, however, the space utilization rate of the facility located in San Antonio is less than 5%. Table 3. Results of the first-stage decision variables. Node City

Water (1000 gals) Space utilization rate

2

San Antonio

104

4.16%

6

Mobile

1680

67.20%

7

Tallahassee

1997

79.88%

8

Orlando

2500

100%

9

Tampa

819

Total =

7100

32.76%

Among the second-stage decision variables, we put the emphasis on the distribution of relief supplies. Table 4 presents the distribution of drinking water, where “arc” represents the traffic flow from storage facilities to demand nodes. Combined with Fig. 1, it is clear that those demand points are usually serviced by the nearest storage facilities. In addition, some storage facilities also may be demand nodes in some cases. For instance, 1,997 units of drinking water were transported from # 7 facility in Tallahassee to # 9 facility in Tampa in scenarios # 3, 5, 6 and 8, respectively. The reason behind this is that the relief materials pre-positioned at each facilities need to satisfy its own demands first. If its own demand cannot be satisfied by the pre-positioned relief materials, it needs to “borrow” relief materials from the facility nearby. The overall objective function value for this solution is approximately 8.4 million dollars, which is made up of the fixed cost to build five storage facilities at $100,000, the acquisition cost of the pre-positioned drinking water at $4,615,000, the shipment cost at $190,251, and the expected penalty cost for unmet demand at $3,467,870, as shown in Fig. 2. Note that the second largest part in the total cost is the penalty cost for the unsatisfied demand, which accounts for approximately 60% of the total cost.

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Table 4. The distribution of drinking water from storage facilities to demand nodes. Scenario no.

Arc

Amount Scenario no.

Arc

Amount Scenario no.

Arc

Amount

1

(2, 1)

24

1

(6, 3)

201

4

(6, 5)

543

7

(6, 5)

839

5

(2, 4)

93

8

(2, 4)

1

(6, 4)

37

5

5

(6, 5)

1680

8

(6, 5)

2

1209

(2, 1)

24

5

(7, 9)

1997

8

(6, 7)

107

2

(6, 3)

201

5

(8, 10) 2500

8

(7, 9)

1997

2

(6, 4)

5

5

(9, 8)

819

8

(8, 10) 2500

2

(6, 5)

296

6

(2, 4)

37

8

(9, 8)

409.5

3

(2, 4)

37

6

(6, 5)

962

9

(6, 5)

590

3

(6, 5)

666

6

(7, 9)

1997

9

(8, 10) 1527

3

(7, 9)

1997

6

(8, 10) 2500

10

(6, 5)

3

(8, 10) 2500

6

(9, 8)

10

(8, 10) 1527

3

(9, 8)

409.5

1133

819

Fixed cost 1%

Penalty cost 42% Acquisition cost 55%

Shipment cost 2%

Fig. 2. Composition of total cost.

The huge penalty cost results from the distribution characteristics of demands across scenarios. In most scenarios, the demand for relief supplies is in a relatively low level. However, on rare occasions, there is a relatively high demand for relief supplies with a very low probability. The out-of-stock penalty cost is directly proportional to the gap between the actual demand and the pre-positioned stock level. If the pre-positioned stock can satisfy the highest demand, the out-of-stock penalty cost will be reduced to zero. However, in that situation, due to the very low occurrence probability of high demand, a high hold cost will be incurred with a high probability and the acquisition cost will increase accordingly.

A Two-Stage Stochastic Programming Model

43

The proposed model can find an optimal trade-off between the out-of-stock penalty cost and the holding cost.

5

Conclusions

In this study, a two-stage stochastic programming model is formulated to address the joint decision-making of pre-positioning and distribution of relief supplies under uncertain environment. The proposed model minimizes the overall cost (including the fixed cost, procurement cost, transportation cost, and out-of-stock penalty cost) and considers the uncertainties of disasters. These uncertainties include the occurrence probability, landing points, the power of destruction, as well as the corresponding demands for relief materials, and all these uncertainties are defined in a set of scenarios. A case study addressing hurricane threats in the Gulf of Mexico region of the southeastern United States has been conducted to illustrate the proposed two-stage stochastic programming model in a practical context. There are several possible extensions to this study. First, the priority of demand points should be considered. In practice, the situation in some demand points is more urgent and should be served firstly. Furthermore, the priority of demand points will change dynamically with the progress of the rescue work. Second, carrier selection can be integrated into our present model in the future research. How to schedule vehicles to deal with a surge of demand is a challenge for humanitarian relief. Taking advantage of high technologies (e.g., electric vehicle) is also a trend. Acknowledgements. This work was supported by the National Natural Science Foundation of China (Grant No. 71801135), the Natural Science Foundation of Jiangsu Province (Grant No. BK20180792), the University Natural Science Research Foundation of Jiangsu Province (Grant No. 18KJB580011), and the Startup Foundation for Introducing Talent of NUIST (Grant No. 2017r061).

References 1. Boonmee, C., Arimura, M., Asada, T.: Facility location optimization model for emergency humanitarian logistics. Int. J. Disaster Risk Reduct. 24, 485–498 (2017) 2. Chang, M.S., Tseng, Y.L., Chen, J.W.: A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transp. Res. Part E Logist. Transp. Rev. 43(6), 737–754 (2007) 3. Chen, J., Liang, L., Yao, D.Q.: Pre-positioning of relief inventories for non-profit organizations: a newsvendor approach. Ann. Oper. Res. 259(1–2), 35–63 (2017) 4. Duran, S., Gutierrez, M.A., Keskinocak, P.: Pre-positioning of emergency items for care international. Interfaces 41(3), 223–237 (2011) 5. Galindo, G., Batta, R.: Prepositioning of supplies in preparation for a hurricane under potential destruction of prepositioned supplies. Socio Econ. Plan. Sci. 47(1), 20–37 (2013) 6. Hu, S., Dong, Z.S.: Supplier selection and pre-positioning strategy in humanitarian relief. Omega 83, 287–298 (2019)

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7. Hu, S.L., Han, C.F., Meng, L.P.: Stochastic optimization for joint decision making of inventory and procurement in humanitarian relief. Comput. Ind. Eng. 111, 39– 49 (2017) 8. Mete, H.O., Zabinsky, Z.B.: Stochastic optimization of medical supply location and distribution in disaster management. Int. J. Prod. Econ. 126(1), 76–84 (2010) 9. Ni, W., Shu, J., Song, M.: Location and emergency inventory pre-positioning for disaster response operations: min-max robust model and a case study of Yushu earthquake. Prod. Oper. Manag. 27(1), 160–183 (2018) 10. Rawls, C.G., Turnquist, M.A.: Pre-positioning of emergency supplies for disaster response. Transp. Res. Part B Methodol. 44(4), 521–534 (2010) 11. Rezaei-Malek, M., Tavakkoli-Moghaddam, R., Zahiri, B., Bozorgi-Amiri, A.: An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Comput. Ind. Eng. 94, 201–215 (2016) 12. Rivera-Royero, D., Galindo, G., Yie-Pinedo, R.: A dynamic model for disaster response considering prioritized demand points. Socio Econ. Plan. Sci. 55, 59–75 (2016) 13. Yaghmaei, N.: Disasters 2018: year in review. Technical report, Centre for Research on the Epidemiology of Disasters (CRED) (2019)

A Metaheuristic Approach for Quantifying the Effects of the Structural Complexity in Facility Location Problems Alberto Pliego-Marug´ an1(B) , Jes´ us Mar´ıa Pinar-P´erez1 , and Diego Ruiz-Hern´ andez2

2

1 CUNEF-Ingenium, Madrid, Spain {alberto.pliego,jesusmaria.pinar}@cunef.edu Sheffield University Management School, Sheffield, UK

Abstract. The proliferation of products, distribution channels and markets increase the structural complexity of the supply chains. Structural complexity generates (frequently hidden) costs that should be considered before making management decisions. Facility location is a field where the structural complexity has significant effects. The impact of structural complexity on the facility location problem is presented as a novelty in this paper. An entropy-based measure has been used for the analysis of structural complexity. Unfortunately, the integration of structural complexity in facility location problems generates new scenarios where conventional solution methods may be inappropriate due to the inherent non-linearity of the formulation. In this paper, a genetic algorithm is proposed in order to find a solution to facility location problems when structural complexity is embedded in the formulation. Moreover, the impact of the structural complexity in the original facility location problems is studied by comparing several scenarios. Keywords: Management decisions · Structural complexity · Uncapacitated facility location · Capacitated facility location

1

Introduction

The increasing competitiveness of the markets results in the need for a fast adaptation of companies to changing scenarios. Fast responses to new situations generate competitive advantages, however, such responses must be accompanied by an adequate decision management. The competitive advantages that arise from a properly conducted decision management can determine the succeed of a firm. New data analysis techniques and decision support systems help the decision makers to handle information that facilitates the work, or at least, allows more informed decision to be made. These modern techniques can optimize the performance of companies in most areas, including the design of supply networks. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 45–56, 2021. https://doi.org/10.1007/978-3-030-49889-4_5

46

A. Pliego-Marug´ an et al.

Supply networks are constantly increasing their size, generating massive data and becoming more complex. For this purpose, new heuristics and metaheuristic techniques are employed to achieve efficient networks. These new techniques address difficult problems that cannot be solved by conventional methods, such as the facility location problems. When the supply network increases the number of products, markets or channels, some hidden costs can appear due to the so-called structural complexity [9]. These costs are not easy to quantify since, unlike transportation costs, they cannot be exactly calculated. For this purpose, several authors have proposed solutions for estimating these complexity costs. Two types of research lines can be distinguished, i.e. exploratory studies and entropy-based studies. On one hand, the solutions based on exploratory studies do not consider an analytical expression to quantify the complexity, but an exhaustive study of specific indicators that affect to complexity, with the subsequent impact on the global costs. For instance, Fan et al. [6] proposed an operation-based approach to estimate the configuration complexity of a manufacturing system; Hendricks and Singhal [8] studied the impact on prices caused by supply chain disruptions. They argue that many disruptions are associated to the increased complexity due to global sourcing, the large number of partners or long lead times; Novak and Eppinger [18] demonstrated that vertical integration is very positive for product complexity; other related studies were proposed by Jacob [12], Bozarth et al. [3] or de Leeuw et al. [16]. On the other hand, the entropy-based studies are aimed to provide a quantification of the structural complexity by measuring the entropy of the system. In this field, Isik [10] proposed two approaches for structural and operational complexity based on Shannon’s entropy measure. He associated the complexity to the information and material flows in the supply chain. Sivadasan et al. [23] demonstrated, through an entropy-based methodology, that the operational complexity can increase when two companies decide to integrate more closely. Frizelle et al. [5] employed several entropy rates to measure the complexity in three case studies about manufacturing and commercial industry. In addition, other entropy-based studies of complexity can be found in references [13,27] and [11]. Special mention is given to the work published by Ruiz-Hern´ andez et al. [21] who proposed an entropybased expression to estimate the structural complexity. They proved the external and internal consistency of the measure by applying it to several business units of a large firm. Due to its consistency, this measure represents the starting point to develop the approach proposed in this paper. The main objective of this paper is to solve the discrete facility location problem including the hidden costs of structural complexity. For this purpose, a novel formulation of the facility location problem is done. Since this novel formulation increases the computational complexity of the facility location, a metaheuristic approach is proposed to find feasible and good solutions. Regarding the research direction in this area, it must be remarked that the addition of structural complexity in the FLP is a novel idea treated before in reference [20]. Moreover, the formulation of structural complexity in capacitated FLP is a novelty of this paper, that seeks for a more realistic interpretation of this mathematical problem.

A Metaheuristic Approach for Quantifying the Effects

47

This paper is divided into six sections. Section 1 presents the motivation of the paper. In Sect. 2, the facility location problem is presented together with some of its most important variants. Section 3 explains the complexity measure and its integration into the facility location problem. Section 4 shows the methodology employed for obtaining feasible solutions in the new formulation. This methodology is applied in Sect. 5 in a case study. Finally, some conclusions are extracted and discussed in Sect. 6.

2

Facility Location Problem

Facility location problems are combinatorial problems where a cost function is minimized by locating a set of facilities that allows to meet the total demand. In the original formulation, the costs for opening the facilities and transportation costs are fixed. If potential locations of the facilities are continuous regions, then the problem is called continuous facility location problems. However, when only some discrete locations are candidate to place a facility, the problem is called Discrete Facility Location Problems (FLP) [25]. This paper focuses on the last type of problem. According to the capacity of the facilities, there are two variations of the FLP. On one hand, if each facility can produce an infinite amount of product, the problem is called Uncapacitated Facility Location Problem (UFLP) [26]. In a UFLP, facilities can supply an infinite demand and, therefore, they can satisfy the complete demand of all the nodes. In this context, it is always optimal to satisfy the demand of one node from the closest facility. On the other hand, if the capacities of the facilities are constrained, the problem is called Capacitated Facility Location Problem (CFLP). In this case, the demand of some nodes could be met by several facilities. A simple formulation of the CFLP was proposed by Balinski [1], as follows: Z = min

 k∈K i∈N

cik xik +



φk y k

(1)

k∈K

Subject to 

xik = 1, ∀i ∈ N

(2)

wi xik  Sk yk , ∀i ∈ N, ∀k ∈ K

(3)

k∈K

 i∈N

 k∈K

Sk y k 



wi , ∀i ∈ N, ∀k ∈ K

(4)

i∈N

xik − yik  0, ∀i ∈ N, ∀k ∈ K

(5)

48

A. Pliego-Marug´ an et al.

0  xik  1, ∀i ∈ N, ∀k ∈ K

(6)

yk ∈ {0, 1}, ∀k ∈ K,

(7)

where N is a set of demand nodes and K the set of potential facility locations, being K a subset of N . Variable cik is the cost of supplying the total demand wi from the facility k; xik the fraction of the total demand met by the facility k; parameter φk represents the fix cost of opening the facility k; the binary variable yk is 1 if facility k is opened and 0 otherwise; Sk is the total capacity of the facility k. Equation (1) is the cost function to minimize. Constraint (2) ensures that the demand of all the nodes is met; Eq. (3) considers the maximum capacity of the facilities and Eq. (4) is the aggregate capacity constraint. Finally, Eq. (5) prevents the demand to be met from no facility and Eqs. (6), (7) establish some characteristics of the variables. The FLP has been widely studied and due to their complexity, there are numerous approaches and algorithms to solve it. Many methods and algorithms can be found in several literature reviews, e.g. Farahani et al. [4], Melo et al. [17] or Owen and Daskin [19]. The current increasing of complexity in the supply networks causes the need for solving bigger and more complex FLPs. In this task, metaheuristic approaches have been demonstrated to be useful [2], being genetic algorithms the most effective approaches [24]. Therefore, a genetic algorithm will be proposed to solve the case study of this paper.

3

Formulation with Structural Complexity

This paper is aimed at studying the effects of the structural complexity in the variants of the FLP. The complexity measurement considered in this work was presented by Ruiz-Hern´ andez et al. in reference [21], where authors propose an entropy-based measurement for quantifying the structural complexity in the supply chain. This measurement assumes that the amount of information generated from stock keeping units (SKU), channels and markets can be employed to estimate the complexity. Based on the Shannon information measurement [22], the structural complexity Cp is defined by Eq. (8): Cp (ω) =

 i

ωi log2

1 , ∀i ∈ ℘, ωi

(8)

where ωi represent a proportion of the total revenue generated by triplet i. The products family in a supply chain is characterized by a collection ℘ of triplets (SKU, Market, Channel). Some important properties of Cp can be found in reference [21]. It is demonstrated that Cp is maximum when demands are evenly distributed. Further on, it will be demonstrated that this property is important for minimizing the system complexity.

A Metaheuristic Approach for Quantifying the Effects

49

This measurement was also employed in reference [20] to determine the effect of complexity in ULFPs. In that paper, the K-MedianPlex problem presented, i.e. a variant of the p-median problem including the complexity measure. In this case, the complexity formulation was reinterpreted by considering that ωi is the proportion of demand of the node i node, with respect to the total demand served by the facility k. For example, if K1 is a facility that meets three demands W1 , W2 and W3 , then, the complexity associated to the facility K1 is given by Eq. (9): CpK1 =

 i

ωi log2

1 WT WT WT W1 W2 W3 = log2 + log2 + log2 , ωi WT W1 WT W2 WT W3

(9)

where WT = W1 + W2 + W3 . The CFLP presents additional constraints, since the capacity of the facilities is limited and therefore, some demands must be satisfied by several facilities. The reformulation of this CFLP is one of the main contributions of this work. Following the formulation of reference [20], the CFLP is reformulated by including the complexity measure and the transport costs in the definition of the system profits. Equation (10) evaluates the absolute revenue generated by the facility k in the demand node i: Rik = (r − γdik )(1 − αCp(k) )Wik , ∀i ∈ N, ∀k ∈ K,

(10)

where r is the revenue per unit sold; γ is the transportation cost per unit of distance; dik is the distance between the facility k and the node i; α is a loss factor connected to the complexity. Finally, Wik is the demand met from the facility k to the node i The absolute revenue (Rik ) can be evaluated through three factors: first, the difference between the incomes and transportation costs; second, a number between 0 and 1 given by the structural complexity costs and; third, the absolute demand met by facility k at the node i. Since the main objective of this paper is to determine the influence of the complexity in the CFLP, some constraint relaxations will be assumed. For instance, all the facilities will be considered as equally capacitated (s). In addition, opening costs (φ) will be equal for all the facilities. According to this, the new formulation of the mixed-integer programing program is:   Rik − φk y k (11) Z = max k∈K i∈N

k∈K

Subject to Eqs. (1)–(7) and αCp(k) ≤ 1

(12)

50

A. Pliego-Marug´ an et al.

Equation (11) is the new objective function of the FLP. In this case, unlike Eq. (1), the objective is to maximize the total revenue instead of minimizing costs. The total revenue is the sum of the absolute revenues for all the facilities and demand nodes, subtracting the total costs for opening facilities. The constraints of the original CFLP (Eq. (1)–(7)) remain unchanged. Equation (12) add a new constraint that ensures the complexity cost will suppose a reduction factor for the revenue. The CFLP is a NP Hard problem and the inclusion of the complexity costs into the objective function increase the computational costs of the problem. Therefore, some constraints may be relaxed during the resolution of the problem.

4

Methodology

The approach proposed is not intended to achieve an optimal solution of the CFLP but to evaluate quantitatively the effects of including the complexity in the FLP. With this purpose, given the NP-Hard nature of the proposed problems, a genetic algorithm has been developed. The main objective is to compare the solutions obtained depending on whether the complexity cost is considered or not. The optimality of the solutions is not essential to estimate the effect of the complexity into the problems. Figure 1 shows a flowchart where the procedure proposed in this paper is detailed.

Coordinates

Set initial profits Z=0

Set number of facilities p=1

Demands

P-Median solution

Refresh number of facilities p=p+1

Initial solution

Genetic algorithm for UFLP

NO

better than Iiteration t-1?

- Determination of facilities -Discrete combinatorial optimization -Posible local optimum

Solution cost (Iteration t)

Genetic solution for UFLP

YES Transportation costs

Facility co sts

UFPL objective function

Complexity co sts

Cap acity of facilities

Feasible for CFLP?

NO

Refresh number of facilities p=p+1

YES

Need for new facilities?

Cap acity limit reached in facilities

NO

Distribution of demands served by facilities

Fig. 1. Methodology flowchart

YES

Initial solution

Genetic algorithm for CFLP

A Metaheuristic Approach for Quantifying the Effects

51

Given the endogenous data associated to the problem (coordinates, demands, opening costs of facilities, complexity-related cost and capacity of facilities), the algorithm starts addressing the p-median problem, which is solved for different transportation-complexity costs rates. P-median problem [7] is a variant of UFLP that consists on the location of p facilities in order to minimize the transportation costs meeting all the demand. It has two main differences from the UFLP: First, the costs of opening facilities is not considered and, second, there is an upper threshold on the number of facilities [14]. The p-median is iterated until reaching the optimal number of facilities. Then, in order to obtain a first comparison, the solution of the p-median problem is analyzed by considering the cost of complexity. The next step is to achieve a solution for the UFLP by considering the solutions of the p-median problem as part of the initial population of the genetic algorithm. The hyperparameters for the genetic algorithms has been selected by following reference [15]: the mutation rate is set to 0.05; the crossover parameter is 0.85; the population number is 40. The solutions given by the genetic algorithm are evaluated under different values of structural complexity cost. Finally, the CFLP is addressed with other genetic algorithm. The best solutions of the previous step are a subset of the initial population of the new genetic algorithm. Again, this genetic algorithm is run using different values of the complexity coefficient (α) to evaluate the effect of the complexity in this problem.

5

Case Studies and Results

A case study with a set of 125 demand nodes is proposed for the first study of the p-median and the UFLP. This case study can be found in reference [20], where Pinar et al. proposed some algorithms to reduce the effects of complexity into the whole system. The demand nodes and the facility locations are shown by Fig. 2. In this case, the optimal solution of the p-median problem is achieved with 7 facilities. Figure 3 shows the solution of the p-median problem for different values of the complexity coefficient (α) and the marginal revenue - transportation costs rate (Tr ). It can be gathered that Tr is much more influential than the complexity coefficient for small values of both parameters. However, when the marginal revenue is large enough to reduce the significance of transportation costs, the influence of the complexity decreases. Considering the ratio between α and Tr , Fig. 4 shows the percentual variations of the profit for α ranging from 0 to 1. It is demonstrated that variations of α affect more the final profit when Tr values are low. The p-median algorithms do not consider the effect of complexity and, therefore, they will be inadequate when the coefficient α increases. The next step is to solve the UFLP through the genetic algorithm. This algorithm has been run for different values of Tr and complexity coefficient. Some of the solutions obtained are presented in Table 1.

A. Pliego-Marug´ an et al.

Y coordinates

52

Profit (monetary units)

Fig. 2. Demand nodes (blue) and facility locations (red)

Fig. 3. Solution of the p-median problem in function of α and Tr .

Fig. 4. Percentual variation of profit α vs Tr .

The results obtained in this case study by using the genetic algorithm are compared with the solution of the p-median problem. It is observed that the genetic algorithm usually improves the solution. This improvement becomes more significant when the complexity coefficient increases. Moreover, it can be gathered from the data that, for normal values of the complexity coefficient, the improvement is more significant when Tr decreases. It must be stated that some values of the complexity coefficient would not meet the constraint in Eq. (10). These abnormal values are only considered in this paper to study the effect of complexity in the solutions.

A Metaheuristic Approach for Quantifying the Effects

53

Table 1. Experimental results for genetic algorithm. Comparison with p-median solution. α

0

0.05

0.15

0.3

0.5

0.8

Tr Objective function Objective function Difference [cts/km x (Genetic solution) (p-mean solution) [cts] ton] [cts] [cts]

Improvement [%]

5

8,87E+06

8,82E+06

5,14E+04

0,58%

10

1,12E+07

1,12E+07

2,57E+04

0,23%

15

1,20E+07

1,20E+07

1,71E+04

0,14%

20

1,24E+07

1,23E+07

1,29E+04

0,10%

5

8,70E+06

8,64E+06

5,71E+04

0,66%

10

1,10E+07

1,09E+07

3,27E+04

0,30%

15

1,17E+07

1,17E+07

2,46E+04

0,21%

20

1,21E+07

1,21E+07

1,49E-08

0,00%

5

8,35E+06

8,29E+06

6,85E+04

0,83%

10

1,05E+07

1,05E+07

4,67E+04

0,44%

15

1,13E+07

1,12E+07

3,94E+04

0,35%

20

1,16E+07

1,16E+07

3,58E+04

0,31%

5

7,84E+06

7,75E+06

8,55E+04

1,10%

10

9,90E+06

9,83E+06

6,77E+04

0,69%

15

1,05E+07

1,05E+07

2,44E+02

0,00%

20

1,10E+07

1,09E+07

1,16E+05

1,06%

5

7,14E+06

7,03E+06

1,08E+05

1,54%

10

9,10E+06

8,93E+06

1,62E+05

1,81%

15

9,61E+06

9,57E+06

4,09E+04

0,43%

20

1,05E+07

9,88E+06

6,45E+05

6,53

5

6,10E+06

5,96E+06

1,42E+05

2,39%

10

8,15E+06

7,59E+06

5,59E+05

7,37%

15

9,13E+06

8,14E+06

9,95E+05

12,23%

20

1,02E+07

8,41E+06

1,75E+06

20,81%

Figure 5 shows the solutions provided by the genetic algorithm (red surface), with α between 0 to 0.8 and Tr ranging from 1 to 20. The same parameters have been considered for solving the p-median problem (blue surface). It is observed that the blue surface is usually below the red one. Since genetic algorithms do not operate with an analytical function, different results can be obtained under the same parametric conditions. Therefore, those points where the blue surface surpasses the red one may be eliminated by the repetition of the genetic algorithm. For certain values of α, the genetic algorithm begins to improve substantially the solutions provided by the p-median. This value decreases when the ratio between marginal revenue and transportation costs increases. Once the previous solutions have been achieved, they can be inputted into the genetic algorithm for CFLP. However, given the huge computational costs of the CFLP, a smaller case study has been designed. The results for a large CFLP

A. Pliego-Marug´ an et al.

Profit

54

Fig. 5. Solutions of the UFLP through p-median and genetic algorithm.

may not be accurate and they could distort the real effects of the complexity cost. In this case, 10 demand nodes and 5 facilities has been considered. To highlight the effect of complexity alpha has been set to 0.75. The capacity of all the facilities are equal. All the demands have been set to 100 units per node. Figure 6 shows the results achieved for two scenarios, including and not including complexity. The bar graphs show the demand in the node i that is met by the facility k. Complexity not included

Complexity included

Fig. 6. Solution of CFLP through genetic algorithm: with and without structural complexity

The genetic algorithm does not guarantee an optimal solution, but the solution provided is good enough to evaluate the effects of including complexity costs. Figure 6 shows that the complexity costs reduces the number of nodes served by each facility. This conclusion is strongly related with a property (see reference [21]) that demonstrates the Cp of a facility is maximum when the demands are evenly distributed. This observation can be a key factor for a good design of the supply network. In addition, from the perspective of customers (demand nodes) it is observed that the complexity also causes a reduction in the amount of facilities that supply them.

A Metaheuristic Approach for Quantifying the Effects

6

55

Conclusions

This paper presents a methodology to consider the structural complexity in uncapacitated and capacitated facility location problem. These problems have been reformulated to consider the hidden costs that usually arise due to the growing of the supply networks. The reformulation of capacitated facility location is a novelty of this paper. A case study with a set of 125 demand nodes is proposed for the first study of the uncapacitated facility location problem with complexity. This problem has been solved by considering different scenarios regarding the complexity coefficient (α) and marginal revenue-transport costs rate (Tr ). Two different solutions have been analyzed, the p-median problem solution and the solution of the facility location problem provided by a genetic algorithm. In first place, the solution of the p-median problem shows that, under normal conditions, the parameter Tr has more influence in the final solution than the complexity coefficient. However, when the marginal revenue is large enough to attenuate the influence of transportation costs, the impact of the complexity decreases. It can be affirmed that the p-median solution is more adequate for small values of Tr . On the other hand, the genetic algorithm improves the solution obtained by solving the p-mean problem. Moreover, this improvement becomes more significant when the complexity coefficient increases. Finally, another genetic algorithm has been employed to solve the capacitated facility location problem. A smaller case study has been considered to study the effects of structural complexity costs. The capacitated facility location problem has been solved both considering a high complexity coefficient and without considering the complexity costs. The comparison of these solutions leads to conclude that the complexity measure reduces both the number of nodes served by each facility and the number of suppliers at each demand node.

References 1. Balinski, M.L.: Integer programming: methods, uses, computations. Manage. Sci. 12(3), 253–313 (1965) 2. Basu, S., Sharma, M., Ghosh, P.S.: Metaheuristic applications on discrete facility location problems: a survey. Opsearch 52(3), 530–561 (2015) 3. Bozarth, C.C., Warsing, D.P., et al.: The impact of supply chain complexity on manufacturing plant performance. J. Oper. Manage. 27(1), 78–93 (2009) 4. Farahani, R.Z., Asgari, N., et al.: Covering problems in facility location: a review. Comput. Ind. Eng. 62(1), 368–407 (2012) 5. Frizelle, G., Suhov, Y.: The measurement of complexity in production and other commercial systems. Proc. R. Soc. A Math. Phys. Eng. Sci. 464(2098), 2649–2668 (2008) 6. Guoliang, F., Aiping, L., et al.: Operation-based configuration complexity measurement for manufacturing system. Procedia CIRP 63, 645–650 (2017) 7. Hakimi, S.L.: Optimum locations of switching centers and the absolute centers and medians of a graph. Oper. Res. 12(3), 450–459 (1964)

56

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8. Hendricks, K.B., Singhal, V.R.: An empirical analysis of the effect of supply chain disruptions on long-run stock price performance and equity risk of the firm. Prod. Oper. Manage. 14(1), 35–52 (2005) 9. Heywood, S., Spungin, J., Turnbull, D.: Cracking the complexity code: there are two types of complexity. Understanding where to intervene is the key to managing them to create value. McKinsey Q. 2, 84 (2007) 10. Isik, F.: An entropy-based approach for measuring complexity in supply chains. Int. J. Prod. Res. 48(12), 3681–3696 (2010) 11. Isik, F.: Complexity in supply chains: a new approach to quantitative measurement of the supply-chain-complexity (Chapter 19). In: Li, P. (ed) Supply Chain Manage pp. 417–432. IntechOpen, Rijeka, Croatia (2011) 12. Jacobs, M.A.: Complexity: toward an empirical measure. Technovation 33(4–5), 111–118 (2013) 13. Jacobs, M.A., Swink, M.: Product portfolio architectural complexity and operational performance: incorporating the roles of learning and fixed assets. J. Oper. Manag. 29(7–8), 677–691 (2011) 14. Jakob, K., Pruzan, P.M.: The simple plant location problem: survey and synthesis. Eur. J. Oper. Res. 12, 36–81 (1983) 15. Klose, A., G¨ ortz, S.: An exact column generation approach to the capacitated facility location problem. In: Distribution Logistics, pp. 3–26 . Springer (2005) 16. de Leeuw, S., Grotenhuis, R., van Goor, A.R.: Assessing complexity of supply chains: evidence from wholesalers. Int. J. Oper. Prod. Manage. 33(8), 960–980 (2013) 17. Melo, M.T., Nickel, S., Saldanha-Da-Gama, F.: Facility location and supply chain management-a review. Eur. J. Oper. Res. 196(2), 401–412 (2009) 18. Novak, S., Eppinger, S.D.: Sourcing by design: product complexity and the supply chain. Manage. Sci. 47(1), 189–204 (2001) 19. Owen, S.H., Daskin, M.S.: Strategic facility location: a review. Eur. J. Oper. Res. 111(3), 423–447 (1998) 20. Pinar P´erez, J.M., Ruiz Hern´ andez., D., Menezes, M.B.: Structural complexity mitigation in network design and rationalization. In: 13th International Conference on Industrial Engineering and Industrial Management, Servicio de Publicaciones de la Universidad de Oviedo (2019) 21. Ruiz-Hern´ andez, D., Menezes, M.B., Amrani, A.: An information-content based measure of proliferation as a proxi for structural complexity. Int. J. Prod. Econ. 212, 78–91 (2019) 22. Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379–423 (1948) 23. Sivadasan, S., Smart, J., et al.: Operational complexity and supplier-customer integration: case study insights and complexity rebound. J. Oper. Res. Soc. 61(12), 1709–1718 (2010) 24. Tohyama, H., Ida, K., Matsueda, J.: A genetic algorithm for the uncapacitated facility location problem. Electron. Commun. Jpn. 94(5), 47–54 (2011) 25. Ulukan, Z., Demircioglu, E.: A survey of discrete facility location problems. Int. J. Soc. Behav. Educ. Econ. Bus. Ind. Eng. 9(7), 2487–2492 (2015) 26. Verter, V.: Uncapacitated and capacitated facility location problems. In: Foundations of Location Analysis, pp 25–37. Springer (2011) 27. Wu, Y., Frizelle, G., Efstathiou, J.: A study on the cost of operational complexity in customer-supplier systems. Int. J. Prod. Econ. 106(1), 217–229 (2007)

The Battle to Decrease the Impact of the Structural Complexity in Supply Chains: An Algorithmic Approach Jes´ us Mar´ıa Pinar-P´erez1(B) , Alberto Pliego-Marug´ an1 , and Diego Ruiz-Hern´ andez2 1

2

CUNEF-Ingenium, Madrid, Spain [email protected] Sheffield University Management School, Sheffield, UK

Abstract. Companies, aimed at improving profits, seek to capture a larger market share. Therefore, they expand their networks to reach new markets. But soon find out that their supply chain becomes less efficient returning less benefits than expected due to hidden costs. This is because managers did not take into account the structural complexity of their networks. Structural complexity in supply chains is related to the negative effect of the proliferation of products, distribution channels and markets. In this work, an alternative formulation of the traditional p-median problem that includes a complexity parameter in the model’s formulation is used. Four strategic approaches to battle the impact of the structural complexity are analyzed in this work to support the managers’ decision making. A case study based on different cities located in France is used to carry out some experiments showing improvements for the proposed strategies. Keywords: Structural complexity · Supply chain management Facility location · Allocation management · Algorithm

1

·

Introduction

When seeking of profit opportunities, companies often trigger successive network expansions (aiming at capturing a larger market share), but soon find out that their supply chain becomes less efficient returning less benefits than expected. This is because of the appearance of hidden costs that hinder the capacity of the supply chain for translating revenue into bottom-line benefits [5,14,18]. We refer to this as the course of complexity. Structural complexity in supply chains is related to the negative effect of the proliferation of products, distribution channels and markets [23]. This complexity comes from strategic choices, for example, by moving into a new geography or location, serving a new customer, or opening a new manufacturing location [15]. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 57–67, 2021. https://doi.org/10.1007/978-3-030-49889-4_6

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Locational complexity appears when companies, to reach more demand share, expand their networks adding new facilities or distribution channels and increasing their production. A continuous network expansion drives the company to overtake the limits of profitability and to collapse their chains under their own weight [11]. Reference [13] presents a discussion of location complexity as imperfect information for the Spanish banking sector. Experts suggest companies to stop opening new facilities [11] and to reduce the complexity by removing sources of operational complexity that do not add value [10,17]. To be competitive and to survive in the marketplace, a great number of companies from different sectors have tried to reduce their networks. For instance, Debenhams and Marks & Spencer will close 50 and 17 stores respectively in U.K. [1,22]. Carrefour announced its new global strategy of network rationalization to reduce the complexity of its facilities and increase the operational efficiency [6]. The UK banking sector is carrying out a stronger rationalization strategy for its branches, to June 2018, 2900 offices had been closed in the last three years [21]. This suggests that managers must take into account structural complexity in their network when developing optimization models for their growth strategies. Literature collects different research works for supply chain complexity, most of them are focus on the design of the measure of complexity [7,12,16,24] or studying complexity based on the product [2,4,8,19]. But there is a little contribution to the Locational complexity in the literature, e.g., reference [3] quantify the complexity of an industrial network. In this work, an alternative formulation of the traditional p-median problem that includes a complexity parameter in the model’s formulation is presented. An entropy-based measure for structural complexity, developed by Ruiz-Hernandez et al. [20], is included in the model formulation. Due to the strongly combinatorial nature and non-linearity of the objective function, an algorithmic approach is proposed. Different strategies to battle the impact of the structural complexity are analyzed in this work to support the managers’ decision making. The first strategy is related to the re-design of the network, reallocating demand nodes among facilities and re-centering the facilities involved. The second one addresses the rationalization of the network, removing those demand nodes that do not contribute to the profits. The third strategy is a mix of the previous two strategies. Finally, the fourth strategy consists on the decomposition of the facilities with high complexity incorporating a new satellite-facility. Several numerical experiments have been carried out on networks designed over the 125 largest cities in France. Experimental results show improvements by reallocating demand nodes among facilities, removing some demand nodes and decomposing facilities to reduce the impact of complexity.

2

Methodology

Facility location problems are combinatorial problems where the costs incurred to serve certain demand (nodes) from a set of facilities have to be minimized

The Impact of the Structural Complexity in Supply Chains

59

[9]. This paper focus on satisfied the demand in a region by finding the optimal location, number of facilities and the demand nodes assignment for each facility. In this section, we present the K-Median Complexity problem, a modified version of the well-known p-median problem that includes a complexity parameter in its formulation. The measure of complexity developed in reference [20] has been used in this problem. This measure, based on the entropy’s concept, is developed by considering the three basis characteristics that define a family of products in a supply chain. These three characteristics are the SKU, Market and Channel and its represented in this work by triplet ℘ , Cp (℘) (Eq. (1)) represents the structural complexity of a system (note that Cp (℘) = Cp (ω) is continuous and concave). Cp (ω) =

 i

 ωi log2

1 ωi

 i∈℘

(1)

where ω is the vector of weights (the proportion of total revenue generated by triplet i ∈ ℘, ωi , for i = 1, ..., |℘|. The total complexity of a network with K facilities (Eq. (2)) can be calculated as:    K K  1 Cp (Γ ) = qτ log2 qτ Cp (Aτ ) (2) + qτ τ =1 τ =1 where qτ is the part of the total demand served by facility τ and Aτ is the sub-network composed by facility τ and its demand nodes. Equation (3) represents the objective function for the K-Median Complexity Problem that maximizes the benefit of the company taking into account the cost of the structural complexity and finding the optimal number of facilities, their location and the assignment of the demand nodes. We use the following notation: N: S ⊂ N: Nk: (k) Cp : α: φ: r: γ: i ωi = WW i

set of demand nodes. set of open facilities. set of nodes allocated to facility, k ∈ S. complexity associated to facility k. (k) the complexity cost factor, satisfying, αCp < 1, k ∈ S. fix facility opening cost. revenue per unit sold. generic transportation cost per distance unit. for all i ∈ N .

Wi:

the weight of demand node, i ∈ N .

i∈N

The optimization problem:

  (k)  (k) 1 − αCp − φK max ZPKlex = R S⊂N :|S|=K k∈S  |S| = K s.t. |{k : i ∈ Nk }| = 1, i = 1, ..., N

(3)

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J. M. Pinar-P´erez et al.

where R(k) is the profit obtained from facility k (see Eq. (4));  (r − γdij ) Wi , k ∈ S R(k) =

(4)

i∈k

The objective function of the K-Median Complexity Problem is a highly combinatorial problem with non-convexity and non-linearity. These characteristics make hard to find a solution of our problem for real cases. Therefore, an algorithmic approach is proposed in this work to find close solutions to the KMedian Complexity Problem. The algorithm evaluates different facility locations  (Eq. (3)), the (S  ) and their demand allocation (N |S | ) on the objective function    value of each configurations (S  , N |S | ) is denoted by Z P lex N |S | , S  .

Fig. 1. Profits for location problems when structural complexity is considered or not

Figure 1 shows different profit curves for different number of facilities (K). The highest profits curve represents the solution of the classic K-Median problem (Z K ) for K* facilities, i.e. the expected values of the objective function without complexity. The lowest profits curve depicts the real values observed by the firm. This curve takes into account the complexity of thenetwork and it was calculated  S | P lex | , S  to the solutions for different by using the algorithm proposed Z N number of facilities (K) given by the K-Median problem (the upper curve in this graph). The difference between the upper curve and the lower curve is the sum of two different costs, the inherent cost of the complexity that cannot be avoided and the cost of do not take into account the hidden costs of complexity (the firm can fight to reduce this cost). Finally, the mid profit curve (dashed line), denoted by ZPKlex , (for K** facilities) shows the values of profits if the complexity is taking into account and the firm improves the network finding the best balance for the network complexity.

The Impact of the Structural Complexity in Supply Chains

3

61

Strategic Approaches to Mitigate the Impact of Complexity

To improve the profit values observed by firms and based on the proposed algorithmic approach, this paper analyses four different strategic approaches. The aim of these four strategies is to mitigate the impact of complexity in location networks in terms of profits. First, the paper addresses the problem of reconfiguring a network, we refer to this algorithm as Re-assignation algorithm. A typical location model does not consider the hidden costs related to structural complexity. Therefore, the profitability of the resulting networks is overestimated. We consider that this algorithm will improve the results of Z P lex by reducing the cost of ignoring complexity. This strategy finds profit improvements by changing the demand node assignation across facilities of a given network and finally re-centering the facilities applying 1-Median problem for each facility. These profit improvements arise with the re-balance between transportation costs and complexity costs. Locational complexity is a problem that appears from successive network expansions finding profit growth [11]. These network expansions increase complexity costs. Currently, firms involved in this problem try to reduce complexity by reducing their presence in non-profitable markets. Examples of this rationalization strategy are the cases of Debenhams and Carrefour [6,22]. Therefore, the second strategy proposed in this work is related with the rationalization of an oversized network by removing those non-profitable demand nodes and finding the best balance of the network taking into account the structural complexity. We refer to this algorithm as Demand Removal algorithm. After developing the two previous strategies separately, we look for improvements of the results by applying both strategies to a given network. Therefore, the third strategy is a Mix algorithm from the previous two. This algorithm applies the Demand Removal algorithm to a network resulting of the Re-assignation algorithm for a better balance of the complexity. Finally, the Facility’s Decomposition algorithm consists on divide the demand of one facility, of a given network, in two facilities applying a 2-median procedure. This strategy tries to reduce the weight of the complexity of a facility distributing the demand by adding a satellite-facility to the network. Additionally, two managerial points of view are applied where the complexity is attributed a) to the central manager or b) the local facility managers. The optimization problem (Eq. (3)) is developed taking into account the local managers. The objective function for the case of the central manager can be modeled as Eq. (5):  R(k) − φK (5) max ZP∗K lex = (1 − αCp (S)) S⊂N :|S|=K

k∈S

where Cp (S) is the total complexity of the system. Numerical assessment of the efficiency of these strategies and managerial point of views are presented in the next section.

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Case Study and Results

To analyze the strategies mentioned in the previous section to reduce the impact of a network’s complexity on profits, several numerical experiments have been carried out over the 125 most populated cities in France. The k-median and allocation problems have been solved using CPLEX 12.6.1 connector for MATLAB. Maps have been obtained using a google API (static map). Road distances between nodes used in the calculus were acquired from google. The values of the experiments have been calibrated based on the empirical results obtained by reference [20]. The experiments for the managerial case where the complexity is attributed to the central manager did not reach any improvements by the proposed strategies. In the case where the complexity is attributed to the local managers, the results of the experiments for the strategies are presented below. 4.1

Re-assignation Algorithm

Figure 2 depicts the graphical representation for the case of 6 facilities when the Re-assignation strategy is carried out. The a) subplot is the result of the Z P lex approach to solve the Eq. (3) when the complexity is taken into account; the subplot b) shows the new configuration of the network and improvement reached by re-assigning demand nodes to the facilities given by the Z P lex approach; finally, subplot c) depicts the configuration of the network by re-centering the facilities that can contribute to profita¨ as improvements (color in blue). In general, the experiments conducted by the Re-assignation algorithm present a positive impact on profits with improvements up to 8% for all established values of α and transportation costs. Table 1 shows the values of Z P lex the Re-assignation algorithm and Improvement ratio for different number of facilities (K) where α = 0.125 and transportation costs = 0.67 e/km · ton. Figure 3 reveals that the positive effect on profits is larger when the complexity factor is higher. 4.2

Demand Removal Algorithm

The demand nodes removal or rationalization algorithm outperforms the Z P lex values for only large values of α. In this case, the improvements are larger for networks with low number of facilities K (see Table 2). Figure 4a) shows the network resulting by applying the Z P lex approach taking into account the complexity and b) shows the network obtained by the Demand Removal algorithm. In this case, 25 nodes were removed from the total demand generating better profits.

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Fig. 2. Re-assignation network maps (6 facilities, Transport Costs = 0.67 e/km · ton and α = 0.125) for: a) Z P lex approach, b) Nodes re-assignation, c) Nodes re-assignation + re-centering Table 1. Re-assignation results (α = 0.125, Transportation costs = 0.67 e/km · ton) K

Z P lex (m.u) Re-assignation algorithm (m.u.) Improvement ratio

2 471506.15

498959.67

5.50%

3 610492.70

645449.43

5.42%

4 700886.98

738348.24

5.07%

5 753763.08

805933.79

6.47%

6 795219.62

861864.81

7.73%

7 861650.40

923897.48

6.74%

8 891304.85

959779.77

7.13%

9 912443.44

985081.10

7.37%

10 953114.42

1022102.02

6.75%

11 969893.96

1046126.56

7.29%

12 1019975.32 1076992.16

5.29%

13 1034195.37 1093224.59

5.40%

14 1053991.76 1135293.03

7.16%

15 1067006.38 1152919.50

7.45%

16 1075709.31 1164512.46

7.63%

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Fig. 3. Re-assignation’s improvements for different α and transportation costs in a 6-facility network. Table 2. Demand Removal results (Transport Costs = 0.67 e/km · ton and α = 0.15) K

2

Improvement ratio

37.4% 12.0% 6.3% 5.5% 4.4% 2.0% 1.8% 1.7% 1.2% 1.1% 0.4% 0.3% 0.2% 0.2% 0.2%

3

4

5

6

7

8

9

10

11

12

13

14

15

16

Fig. 4. Demand Removal network maps (6 facilities, Transport Costs = 0.67 e/km · ton and α = 0.15) for: a) Z P lex approach, b) Demand removal algorithm

4.3

Mix Algorithm

The Mix algorithm matches the results of the Re-assignation algorithm outperforming those values where the Demand removal algorithm is useful, i.e., the cases of networks up to 5 facilities and using large values of α (see Table 3). Figure 5 reveals the network configuration differences when the mix algorithm is applied for a case of 5 facilities. Table 3. Mix algorithm results (Transport Costs = 0.67 e/km · ton and α = 0.15) K

2

3

4

5

Improvement ratio 37.5% 14.1% 10.4% 11.8%

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Fig. 5. Mix strategy network maps (5 facilities, Transport Costs = 0.67 e/km · ton and α = 0.15) for: a) Z P lex approach, b) Mix algorithm

4.4

Facility’s Decomposition Algorithm

To compare the results of the decomposition algorithm with the results of the Z P lex approach at the same level (same number of facilities), an organic growth for Z P lex has been developed, i.e., an algorithm conducting a K-median problem where the last K–1 facilities are fix. The experiments show improvements for all values α of, but there is not a clear pattern (see Fig. 6). Therefore, positive results depend on the configuration and characteristics of the network.

Fig. 6. Decomposition algorithm results (Transport Costs = 0.67 e/km · ton)

5

Conclusions

The aim of this paper is double, a) to create awareness among managers to incorporate the structural complexity concept to facility location problems and b) to develop strategies to reduce the impact on profits due to complexity. Therefore, an optimization approach for location problems taking into account the structural complexity and different algorithms to mitigate the impact of complexity were presented in this work. Results suggest that higher profits can be attained

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by reallocating demand nodes across facilities for every value of the complexity factor and transportation costs taken into account. Improvements on profits were found by removing non-profitable demand nodes for large complexity factors. These improvements were high for networks with few facilities. Finally, higher profits were found by decomposing a large complexity facility for large values of the complexity factor. In this case improvements on profits only appear for networks with some number of facilities depending on the characteristics of the network. Additionally, the experiments show that there are improvements on profits only when the complexity is attributed to the local facility managers. These findings support the managers’ decision making in the design or re-design of their supply chains.

References 1. BBC News. M&S names next 17 stores it wants to close (2019). https://www.bbc. com/news/business-4687674 2. Alfaro, J.A., Corbett, C.J.: The value of SKU rationalization in practice (the pooling effect under suboptimal inventory policies and nonnormal demand). Prod. Oper. Manag. 12(1), 12–29 (2003) 3. Battini, D., Persona, A., Allesina, S.: Towards a use of network analysis: quantifying the complexity of supply chain networks. Int. J. Electron. Cust. Relat. Manag. 1(1), 75–90 (2007) 4. Blecker, T., Abdelkafi, N.: Complexity and variety in mass customization systems: analysis and recommendations. Manag. Decis. 44(7), 908–929 (2006) 5. Bode, C., Wagner, S.M.: Structural drivers of upstream supply chain complexity and the frequency of supply chain disruptions. J. Oper. Manag. 36, 215–228 (2015) 6. Carrefour. Notas de prensa Carrefour (2018). https://www.carrefour.es/grupocarrefour/sala-de-prensa/noticias2015.aspx?tcm=tcm:5-46221 7. Cheng, C.Y., Chen, T.L., Chen, Y.Y.: An analysis of the structural complexity of supply chain networks. Appl. Math. Model. 38(9–10), 2328–2344 (2014) 8. Closs, D.J., Jacobs, M.A., Swink, M., et al.: Toward a theory of competencies for the management of product complexity: six case studies. J. Oper. Manag. 26(5), 590–610 (2008) 9. Daskin, M.S.: Network and Discrete Location: Models, Algorithms, and Applications, vol. 22, pp. 294–360. Wiley, Hoboken (2013) 10. Ekinci, E., Baykaso˘ glu, A.: Complexity and performance measurement for retail supply chains. Ind. Manage. Data Syst. 119(4), 719–742 (2019) 11. Fisher, M., Gaur, V., Kleinberger, H.: Curing the addiction to growth. Harvard Bus. Rev. 95(1), 66–74 (2017) 12. Frizelle, G., Woodcock, E.: Measuring complexity as an aid to developing operational strategy. Int. J. Oper. Prod. Manag. 15(5), 26–39 (1995) 13. Fuentelsaz, L., G´ omez, J.: Multipoint competition, strategic similarity and entry into geographic markets. Strateg. Manag. J. 27(5), 477–499 (2006) 14. George, M.L., Wilson, S.A.: Conquering Complexity in Your Business: How WalMart, Toyota, and Other Top Companies Are Breaking Through the Ceiling on Profits and Growth: How Wal-Mart, Toyota, and Other Top Companies Are Breaking Through the Ceiling on Profits and Growth, pp. 25–45 (2004)

The Impact of the Structural Complexity in Supply Chains

67

15. Heywood, S., Spungin, J., Turnbull, D.: Cracking the complexity code: there are two types of complexity. Understanding where to intervene is the key to managing them to create value. McKinsey Q. 2, 84 (2007) 16. Isik, F.: An entropy-based approach for measuring complexity in supply chains. Int. J. Prod. Res. 48(12), 3681–3696 (2010) 17. Kearney, A.: The complexity challenge: A survey on complexity management across the supply chain. AT Kearney Publications (2004). https:// www.atkearneyde/content/misc/wrapperphp/id/49230/name/pdf complexity management s 1096541460ee67.pdf 18. Mariotti, J.L.: The Complexity Crisis: Why Too Many Products, Markets, and Customers are Crippling Your Company–and What to do About it, pp. 22–31. Platinum press, Avon, Massachusetts (2007) 19. Novak, S., Eppinger, S.D.: Sourcing by design: product complexity and the supply chain. Manage. Sci. 47(1), 189–204 (2001) 20. Ruiz-Hern´ andez, D., Menezes, M.B., Amrani, A.: An information-content based measure of proliferation as a proxi for structural complexity. Int. J. Prod. Econ. 212, 78–91 (2019) 21. BBC News. Banks close 2,900 branches in three years, says which? (2018). https:// www.bbc.com/news/business-44483304 22. Butler, S.: Debenhams to close up to 50 stores, putting 4,000 jobs at risk (2018). https://www.theguardian.com/business/2018/oct/24/debenhams-toclose-up-to-50-stores-in-further-blow-to-high-streets 23. Saeed, B., Young, D.: Managing the hidden costs of complexity. Opportunities for Action, Boston (MA) pp 1–3 (1998) 24. Sivadasan, S., Efstathiou, J., Frizelle, G., et al.: An information-theoretic methodology for measuring the operational complexity of supplier-customer systems. Int. J. Oper. Prod. Manag. 22(1), 80–102 (2002)

Presale Scheme Optimization of Short Life Cycle Products Considering Reference Price Effect Qiyang Zhou and Chunxiang Guo(B) School of Business, Sichuan University, Chengdu 610064, People’s Republic of China [email protected] Abstract. Faced with the uncertainty of demand in the market, more and more retailers prefer to adopt the new selling method known as presale, especially premium presale. Based on the behavioral characteristics of strategic and myopic consumers, this paper firstly establishes a twostage model of presale and spot sale, then investigates the influence of the reference price effect on retailer’s decision-making behavior. Secondly, we research a new optimized presale scheme with dual-driven factors of price and advertising. We express the only presale price to maximize the profit of the retailer in different scenarios. And we find that the retailer’s profit is deeply affected by the intensity of reference price effect. Weak reference effect is harmful to the retailer’s profit while high level of it is inversely profitable. Besides, increasing the reference price by advertising indeed improves the retailer’s profit. And the retailer will benefit from consumers’ strategic waiting behavior adopting this dual-driven strategy if the quantity of strategic consumers in the market is sufficient. Keywords: Supply chain Advertising

1

· Presale · Reference price effect ·

Introduction

Since 2009, Taobao.com has held a grand “Double 11 Shopping Carnival” on November 11th every year. This is the largest and most successful presale activity in China. Its all-day turnover rose rapidly from 52 million yuan in the first year to 268.4 billion yuan in 2019. With the development of Internet technology, each link of the presale activity has been fully optimized. Therefore, today presale strategy has been widely used in retail, manufacturing and service industries [2]. There are various modes of presale strategy and the most common one is discount presale. Consumers are able to pre-order the product at a lower price in presale period and actually acquire the product in the spot sale period afterward [16]. But premium presale strategy in which the presale price is higher than the spot sale price has also been gradually adopted by many retailers. For example, when Amazon launched Kindle 2, the presale price claimed by its official website was $359, but the same products were sold at $299 in the spot sale season. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 68–80, 2021. https://doi.org/10.1007/978-3-030-49889-4_7

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Similarly, Mi.com Group released a new “mi 9” series of mobile phones at the end of February 2019. And a large number of retailers sold the“6+128G” model in various channels at a premium price that is 500 yuan higher than the official spot sale price. What’s more, Videogame giants Nintendo and Sony also charge a premium for pre-orders for the Wii and PlayStation 3 [3]. There are some common features of these products. The first is the short life cycle, which means frequent upgrade of products. And their values usually decrease rapidly over time. The supply of them often falls short of demand at the beginning of their launches. Some consumers with high WTP (willingnessto-pay) are likely to accept a higher price to ensure that they can obtain the product at the first time [8]. Thus, retailers can get considerable profits from premium presale scheme. As the market changes, consumers also become much more rational. In particular, the emergence of strategic consumers has brought lots of new problems to retailers. Unlike traditional myopic consumers, the strategic consumers tend to make the decision after comparing the purchase utility of the presale and the spot sale periods. After that, they decide to buy right now or wait until the spot sale begins. The retailers who adopt the premium presale strategy usually announce the prices of two selling seasons at the beginning of the presale period. As a result, the strategic consumers will form a new psychological reference price in their minds which directly influences the purchasing decisions [15]. Therefore, retailers manage to create various strategies to avoid loss of the profit caused by the strategic waiting behavior and price-reference behavior of strategic consumers. And advertising is one of the proven and effective methods. In recent years, with the booming development of TV media, social network media (Microblog and WeChat Public Platform) as well as other video websites, it has become a popular operational method with lower cost and greater efficiency, by which the retailers can indirectly affect the consumers’ purchasing behavior. Thus, this paper mainly studies (1) How does the reference price effect affect the retailer’s decision? (2) Whether the dual-driven strategy of price and advertising is superior? We find that retailers ignoring the price-reference behavior of strategic consumers will lead to the loss of profit when reference price effect is relatively low. But the retailers will inversely benefit from high level of reference price effect. And it is also found that increasing the reference price through advertising can enhance the retailers’ profits. Moreover, strategic consumers are not always harmful to retailers’ profits. As long as the advertising investment level of retailers is appropriate, the strategic behavior of consumers can be turned into an advantage to create profits.

2

Literature Review

This paper is related to the following literatures. (1) Presale: Xie and Shugan [17] first comprehensively studied the issues related to presale, including the implementation conditions of presale, factors affecting the final results, presale pricing and inventory issues, etc. On this basis,

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later scholars studied more specific presale problems. For example, free gifts in presale strategy [7], the influence of both price and advertisement [2], the optimal presale strategy for old and new products [5], price guarantee [12] and presale strategy of perishable goods [19]. After long-time research and practice, scholars put forward a variety of presale strategies which are not fundamentally different from the discount presale strategy, but lack the study for premium presale strategy. Presale with a premium can be a huge success for specific categories of products and target consumers [10]. Therefore, the research on premium presale is indispensable. This paper aims to make some contributions to fill this gap. (2) Reference price effect: The research on the reference price effect mainly focuses on the formation mechanism and effect of reference price. According to the Adaptation Level Theory [6], most scholars assume that the reference price is the exponential smoothing value of the initial reference price and the current price [4,14,20,21]. Nasiry and Popescu [13] proposed a new reference price model based on the peak-end law, believing that consumers tend to be impressed by the lowest price. Another part of scholars divided the reference price into internal reference price and external reference price. Internal reference prices are associated with memory and consumers are more impressed by recent prices. Zhang et al. [23] and Chenavaz and Paraschiv [1] assume that the reference price is a differential equation concerning memory parameters, reference prices and current prices. And external reference price is mainly affected by external stimulus. Zhang [22], Lu [11] and Zhou [24] studied the advertising and pricing strategies of enterprises considering the positive impact of advertising on the reference price. As for the influence of the reference price effect, it is found that the reference price effect affects the retailers’ pricing and ordering strategies and the upstream manufacturers’ production decisions by influencing consumers’ purchasing behaviors. Li and Teng [9] assumed that demand was a multivariate function of selling price, reference price, product freshness and display inventory. Xu and Liu [18] studied the influence of reference effect on closed-loop supply chain. Considering the retailer as the Stackelberg leader, the influence of three recycling channels on the retailer’s decision-making is analyzed and discussed. This paper mainly studies the effect of reference price on retailers’ premium presale strategy. The strategic consumers in the market are also considered. We further optimize the presale scheme and study the impact of the retailer’s advertising investment.

3

Model

We consider a monopoly retailer who sells a short-life-cycle product to customers through a two-period selling model in the way of premium presale, which means the presale price is higher than that of spot sale period. And there are two types of customers in the market-myopic and strategic. Before the presale starts the retailer should decide two-period prices respectively as well as order quantity. When the presale activity begins, the different prices of two periods should be announced at the same time and the customers start to enter the market.

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The related notations are summarized in Table 1. Table 1. Summary of notations Symbol Definition v

Product value to the consumers, complying with uniform distribution of [0, vm ]

N

Potential market size

θ

The proportion of strategic consumers (0 ≤ θ ≤ 1)

UijA/S

The purchasing utility of consumers j ∈ {1, 2}, 1 represents myopic customers while 2 represents strategic customers i ∈ {1, 2, 3}, represents different scenarios

c

Unit cost

x

Presale price (x > p)

p

Spot sale price

λ

The anticipated availability of the product in spot sale period

α

Reference effect factor

ij DA

Demand in presale period

DSij

Demand in spot sale period

Myopic customers will buy the product only in presale period when the utility Ui1 A ≥ 0, otherwise leave the market. As for strategic customers, they will buy i2 i2 the product when purchasing utility in presale period Ui2 A ≥ 0 and UA ≥ US , otherwise they choose to wait. In spot sale period, they will buy the product only when Ui2 S ≥ 0, otherwise they just leave. The decision tree of customers’ purchasing process is as follows in Fig. 1.

Fig. 1. Decision tree of customers’ purchasing process

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Price Driven Strategy Without Reference Effect

The purchasing utility of myopic customers in presale period: U11 A = v − x. The purchasing utility of strategic customers in presale period: U12 A = v − x. The purchasing utility of strategic customers in spot sale period: U12 S = λ(v − p). ≥ 0, then v ≥ v = x. Therefore, when For myopic customers, If U11 11 S v11 ≤ v ≤ vm , myopic customers choose to buy this product in presale period, 11 = N (1 − θ)(vm − v11 )/vm . the demand for it is DA For strategic customers, If UA12 ≥ US12 , then v ≥ v12 = (x − λp)/1 − λ; if UA12 ≥ 0 then v > v13 = x; if US12 ≥ 0, then v ≥ v14 = p. For x > p, then v12 > v13 > v14 . Therefore, strategic customers will buy the product in presale period only when v ≥ v2 , which means UA12 ≥ US12 and UA12 ≥ 0. The demand for 12 = N θ(vm −v12 )/vm Otherwise, when v14 < v < v12 , that can be expressed as DA 12 12 which indicates UA < US and US12 ≥ 0, they would rather wait and purchase after spot sale starts, the demand is DS12 = N θ(v12 − v14 )/vm . The total demand in presale period and in spot sale period can be expressed as: 1 11 12 = DA + DA =N DA

(1 − λ)(vm − x) − θλ(x − p) (1 − λ)vm

DS1 = DS12 = Nθ(x − p)/(1 − λ)vm

(1)

(2)

The profit function for the retailer is: 1 π(x) = (x − c)DA + (p − c)DS1

=

N (x − c)[(1 − λ)(vm − x) − θλ(x − p)] N θ(p − c)(x − p) + (1 − λ)vm (1 − λ)vm

and the decision model is stated as: π1∗ = max π1 (x) s.t.p ≤ x ≤ vm 3.2

Price Driven Strategy with Reference Effect

Myopic customers’ purchase decision is merely related to the WTP for the product and the presale price. Thus, the purchasing utility of them in presale period remains unchanged considering reference effect (RE). However, it is quite different for strategic customers. Because of observing presale price and spot sale price simultaneously, they form a new reference price in their minds. According to Transaction Utility Theory [15], the total utility for consumers is the sum of acquisition utility and transaction utility that is U = U1 (v, x) + U2 (γ, p). Given previous literatures, we define the reference price complies with the weighted average function of the presale price and the spot sale price γ = kx + (1 − k)p, k(0 ≤ k ≤ 1), indicates how much the reference price is

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73

influence by the presale price. We use reference effect factor α to demonstrate the impact of reference effect on purchasing utility of strategic customers. For simplification, we assume that all the consumers are neutral to loss, which means the reference effect factor are the same in two periods. For premium presale, there is x ≥ γ ≥ p. The purchasing utility of myopic customers in presale period: UA21 = v − x. The purchasing utility of strategic customers in presale period: UA22 = v − x + α(γ − x). The purchasing utility of strategic customers in spot sale period: US22 = λ(v − p) + α(γ − p). By comparing UA21 , UA22 and US22 , there are v21 = x, v ≥ v23 = x + α(x − γ), v ≥ v22 = [x − λp + α(x − p)]/(1 − λ) and v ≥ v24 = [λp + α(p − λ)]/λ. Then the total demand in presale period and in spot sale period can be expressed as: 2 = DA

N [(1 − λ)(vm − x) − θ(x − p)(λ + α)] (1 − λ)vm

(3)

N θ(x − p)[λ + λα + kα(1 − λ)] λ(1 − λ)vm

(4)

DS2 =

The profit function for the retailer is: 2 2 π2 (x) = (x − c)DA + (p − c)DS

=

N (x − c)[(1 − λ)(vm − x) − θ(x − p)(λ + α)] N θ(p − c)(x − p)[λ + λα + kα(1 − λ)] + (1 − λ)vm λ(1 − λ)vm

and the decision model is stated as: π2∗ = max π2 (x) s.t.p ≤ x ≤ vm 3.3

Price and Advertising Dual-Driven Strategy with Reference Effect

In this chapter, we study the dual-driven strategy of price and advertising. We define β(0 ≤ β ≤ 1) which shows the impact of advertising on reference price. The cost of advertising for the retailer is expressed as 0.5μ2 , μ is the retailer’s investment level of advertising. The reference price becomes γ , = kx + (1 − k)p + βμ, for x ≥ γ , ≥ p. 21

The purchasing utility of myopic customers in presale period: U A = v − x. 22 The purchasing utility of strategic customers in presale period: U A = v − x + , α(γ − x). 22 The purchasing utility of strategic customers in spot sale period: U A = λ(v − p) + α(γ , − p).

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Similarly, the total demand in presale period and in spot selling period can be expressed as: (1 − λ)(vm − x) − θ(x − p)(λ + α) (1 − λ)vm

(5)

(x − p)(λ + λα + kα − λkα) + α(1 − λ)βμ λ(1 − λ)vm

(6)

2

DA = N 2

DS = N θ

The profit function for the retailer is: 2

2

π3 (x) = (x − c)DA + (p − c)DS − 0.5μ2 (1 − λ)(vm − x) − θ(x − p)(λ + α) (1 − λ)vm (x − p)(λ + λα + kα − λkα) + α(1 − λ)βμ μ2 + N θ(p − c) − λ(1 − λ)vm 2 = N (x − c)

and the decision model is stated as: π3∗ = max π3 (x) s.t.p ≤ x ≤ vm

4

Result

4.1

Price Driven Presale Strategy

Theorem 1. When the retailer doesn’t consider the reference price effect, there is only one optimal presale price: x∗1 =

(1 − λ)vm + θλp + θ(p − c) c + 2(1 − λ + θλ) 2

(7)

It shows the optimal pricing strategy for the retailer without considering reference price effect. we can find that the retailer’s optimal presale price is related to the proportion of strategic customers, the spot selling price, unit cost, the anticipated availability of the product in spot sale season and the highest product value to consumers. And the optimal profit of the retailer can be indicated as: π1 (x∗1 ) = N

(x∗1 − c)[(1 − λ)(vm − x∗1 ) − θλ(x∗1 − p)] + (p − c)(x∗1 − p)θ (1 − λ)vm

(8)

Theorem 2. When the retailer takes the reference price effect into consideration, the only optimal presale price is expressed as: x∗2 =

λ(1 − λ)vm + λθ(λ + α)p + θ(p − c)[λ + λα + kα(1 − λ)] c + 2λ[1 − λ + θ(α + λ) 2

(9)

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75

It gives the optimal pricing strategy for the retailer when reference effect is considered and the consumers are assumed to be neutral to loss. And we can find that the optimal presale price in this scenario is specially affected by reference effect factor. And the optimal profit of the retailer is: π2 (x∗2 ) =

4.2

N (x∗2 − c)[(1 − λ)(vm − x∗2 ) − θ(λ + α)(x∗2 − p)] (1 − λ)vm ∗ N θ(p − c)(x2 − p)[λ + αλ + kα(1 − λ)] + λ(1 − λ)vm

(10)

Price and Advertising Dual-Driven Presale Strategy

Theorem 3. When the retailer adopts price and advertising dual-driven presale strategy considering the reference price effect, the only optimal presale price is: x∗3 =

λ(1 − λvm + λθ(λ + α) + θ(p − c)[λ + αλ + kα(1 − λ)] c + 2λ[1 − λ + θ(α + λ)] 2

(11)

And we find that Eq. (11) and Eq. (9) are exactly the same. Thus, we can infer: 2

2

2 Inference 1 x∗2 = x∗3 and DA = DA ; ΔDs = DS − DS2 = N θαβμ/λvm > 0

After optimizing the presale strategy by advertising, the optimal price of dual-driven strategy and single-driven strategy (price-driven) are the same considering the reference price effect. But the demand in the spot sale season increases while that in the presale period stays unchanged. As a result, the total demand of the retailer increases. This is because when the retailer adopts price and advertising dual-driven strategy, the advertising can enhance the reference price in customers’ mind which increase the transaction utility of both presale period and spot sale period. But the increase in two periods can just counteract with each other. Thus, strategic customers’ purchasing behaviors remain unchanged and the pricing strategies are same. Meanwhile advertising enhances the purchasing utility in the spot sale season, which stimulates some strategic customers with low WTP choose to buy in the spot sale season instead of leaving. In other words, advertising exploit the market of customers with low WTP and generate more demand which is profitable for the retailer. And the optimal profit of the retailer is: (1 − λ)(vm − x∗3 ) − θ(x∗3 − p)(λ + α) (12) (1 − λ)vm (x∗ − p)[λ + λα + kα(1 − λ)] + α(1 − λ)βμ μ2 − +N θ(p − c) 3 λ(1 − λ)vm 2

π3 (x∗3 ) =N (x∗3 − c)

In order to study the influence of advertising investment level on profit optimization, we use Δπ to indicates the deviation of the profits of two strategies. Δπ = π3 (x∗3 ) − π2 (x∗2 ) = −0.5μ2 + N θαβμ(p − c)/(λvm )

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Theorem 4. (a) When μ ∈ [0, 2μ∗ ], then π3 (x∗3 ) ≥ π2 (x∗2 ), for μ∗ = N θαβμ(p− c)/(λvm ). (b) When μ = μ∗ , the retailer can get the optimal profit adopting price and advertising dual-driven strategy. It suggests that if the retail’s advertising investment level is under the threshold, it can get higher profit than single-driven strategy. But if the investment level exceeds the threshold, the retailer’s profit will be damaged. And the optimal advertising investment level is related to several factors such as the spot sale price, unit cost, the proportion of strategic customers, anticipated availability of the product in second period and highest product value to the consumers, especially the potential market size. So, the retailer should investigate the potential demand for the product before advertising.

5 5.1

Numerical Analysis The Effect of Consumers’ Price-Reference Behavior

To numerically quantify the influence of consumers’ price-reference behavior on the decision of the retailer, we assign some values: N = 100, θ = 0.5, vm = 100, c = 40, p = 60, λ = 0.8 and k = 0.5 while the reference effect factor α ranges from 0 to 15. And Fig. 2 shows the change of optimal presale price, total demand and retailer’s maximum profit respectively. Proposition 1. (1) x∗2 ≤ x∗1 , D2 ≥ D1 ; (2) If α is low, π2 (x∗2 ) < π1 (x∗1 ), if α is relatively high, π2 (x∗2 ) > π1 (x∗1 ); (3) Δx = x∗1 − x∗2 and ΔD = D2 − D1 increase with α , and Δπ21 = π2 (x∗2 ) − π1 (x∗1 ) increases with α when α is high. Figure 2(a) indicates that the optimal presale price considering pricereference behavior is much lower than that without reference effect, and the deviation increases with the reference effect. This is because considering the reference price effect, the strategic customers’ purchasing utility in the presale period decreases. Then the retailer will lower the presale price to induce those strategic customers with high WTP to purchase in advance instead of waiting. Figure 2(b) shows when the consumers are more sensitive to the difference between the reference price and the presale price (or the spot sale price), the reference price will have more impact on the total demand. This is because more strategic customers will buy the product in the spot sale period. With the reference effect, strategic customers partially transfer from the presale period to the spot sale period. Meanwhile the market of low WTP customers in the spot sale period are fully exploited, which means they may choose to buy the product instead of leaving the market. And Fig. 2(c) shows the profit of retailers is deeply affected by the reference price effect. If the reference effect is relatively low, considering price-reference behavior leads to loss of profit for retailers. In contrast, the retailers benefit a lot from high level of reference effect.

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Fig. 2. (a) Change of optimal price, (b) Change of total demand, (c) Change of retailer’s profit.

5.2

The Effect of Consumers’ Structure

In this part, we assign α = 1, β = 0.8, μ = μ∗ = 20 θ and make θ range from 0 to 1 gradually. Figure 3 shows the results. Strategy S and Strategy D represents dual-driven strategy and single-driven strategy respectively. Proposition 2. When there are sufficient strategic customers, the retailer can get higher profit adopting price and advertising dual-driven strategy. Figure 3(a) and (b) shows that the optimal pricing decisions under two strategies are the same. But rising the reference price can increase the total demand because more consumers with low WTP choose to buy the product in the spot sale period instead of leaving. Figure 3(c) shows that the dual-driven strategy can create more profit with the number of strategic customers increasing, comparing with single-driven strategy. And when the customers are fully strategic, Δπ reaches the maximum. Figure 3(d) indicates that the retailer can turn the consumers’ strategic waiting behavior into an advantage of driving profit by implementing the dual-driven strategy. The profit of retailer increases rapidly with the number of strategic consumers if it is relatively sufficient.

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Fig. 3. (a) Change of optimal presale price, (b) Change of total demand, (c) Optimization of profit, (d) Change of retailer’s profit.

6

Conclusion

This paper studied the premium presale strategy of short-life-cycle products considering limited-rational behavior of consumers (price-reference behavior and strategic waiting behavior). we analyze the impact of the limited-rational behavior on the supply chain and optimize the presale scheme through advertising. Some conclusions are as followed. On one hand, the retailer ignoring the reference behavior of consumers when making decisions will lead to excessive presale price, low demand. Considering the reference price effect which is relatively weak to make the decision leads to loss of profit for the retailer. But if the reference price effect is much more significant, the retailer can get more revenue by taking the reference price effect into consideration. On the other, the optimization scheme of dual-driven of price and advertising brings many benefits to retailers. Firstly, the optimization scheme expands the demand for the spot sale period by exploiting the strategic consumer market with low WTP, which increases the profit of the retailer. Secondly, the optimization scheme can turn the strategic behavior of consumers into a favorable factor of driving the profit. In addition, the optimization scheme also has limitations. It is unprofitable if the retailer invests too much on advertising.

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Acknowledgements. The funding supports from the National Natural Fund Project (71871150); the Innovation Spark Project Library of Sichuan University (2018hhs35); the Project of Science and Technology Department of Sichuan Province (2019JDR0148).

References 1. Chenavaz, R., Paraschiv, C.: Dynamic pricing for inventories with reference price effects. Econ. Open Access Open Assess. E-J. 12(2018–64), 1–16 (2018) 2. Cheng, Y., Li, H., et al.: Advance selling with double marketing efforts in a newsvendor framework. Comput. Ind. Eng. 118, 352–365 (2018) 3. Duan, Y.R., Yu, B.F.: Capacity planning in advance selling in the presence of regret behavior. Ind. Eng. Manage. 23(1), 1–9 (2018) 4. Greenleaf, E.A.: The impact of reference price effects on the profitability of price promotions. Mark. Sci. 14(1), 82–104 (1995) 5. Gu, Y.H., Luo, X.X.: Advance selling strategies of new products and old products considering capacity constraints. Chin. J. Manage. Sci. 27, 130–139 (2019) 6. Helson, R.: Adaptation Level Theory. Harper and Row, New York (1994) 7. Huang, K.L., Kuo, C.W., et al.: Advance selling with freebies and limited production capacity. Omega 73, 18–28 (2017) 8. Li, C., Zhang, F.: Advance demand information, price discrimination, and preorder strategies. Manuf. Serv. Oper. Manage. 15(1), 57–71 (2013) 9. Li, R., Teng, J.T.: Pricing and lot-sizing decisions for perishable goods when demand depends on selling price, reference price, product freshness, and displayed stocks. Eur. J. Oper. Res. 270(3), 1099–1108 (2018) 10. Li, Y., Xu, L., et al.: Optimal advance-selling strategy for fashionable products with opportunistic consumers returns. IEEE Trans. Syst. Man Cybern. Syst. 44(7), 938–952 (2013) 11. Lu, L., Gou, Q., et al.: Joint pricing and advertising strategy with reference price effect. Int. J. Prod. Res. 54(17), 5250–5270 (2016) 12. Mei, W., Du, L., et al.: The effects of an undisclosed regular price and a positive leadtime in a presale mechanism. Eur. J. Oper. Res. 250(3), 1013–1025 (2016) 13. Nasiry, J., Popescu, I.: Dynamic pricing with loss-averse consumers and peak-end anchoring. Oper. Res. 59(6), 1361–1368 (2011) 14. Popescu, I., Wu, Y.: Dynamic pricing strategies with reference effects. Oper. Res. 55(3), 413–429 (2007) 15. Thaler, R.: Mental accounting and consumer choice. Mark. Sci. 4(3), 199–214 (1985) 16. Wang, X.H., Zeng, C.: A model of advance selling with consumer heterogeneity and limited capacity. J. Econ. 117(2), 137–165 (2016) 17. Xie, J., Shugan, S.M.: Electronic tickets, smart cards, and online prepayments: when and how to advance sell. Mark. Sci. 20(3), 219–243 (2001) 18. Xu, J., Liu, N.: Research on closed loop supply chain with reference price effect. J. Intell. Manuf. 28(1), 51–64 (2017) 19. Xu, X., Li, X., et al.: Advance selling in the presence of product diffusion effect. J. Syst. Sci. Syst. Eng. 26(1), 77–99 (2017) 20. Yang, H., Zhang, D., et al.: The influence of reference effect on pricing strategies in revenue management settings. Int. Trans. Oper. Res. 24(4), 907–924 (2017) 21. Zhang, J., Chiang, W.K.: Durable goods pricing with reference price effects. Omega (2018)

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22. Zhang, J., Gou, Q., et al.: Supply chain coordination through cooperative advertising with reference price effect. Omega 41(2), 345–353 (2013) 23. Zhang, J., Chiang, W.K., et al.: Strategic pricing with reference effects in a competitive supply chain. Omega 44, 126–135 (2014) 24. Zhou, E.F., Zhang, Y.L., et al.: Reference price effect and commitment in competition. Chin. J. Manage. Sci. 26(8), 75–85 (2016)

Supply Chain Design Optimization Considering Consumers’ Low-Carbon Awareness Under Carbon Tax Regulation Zhimiao Tao(B) Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, People’s Republic of China [email protected]

Abstract. The optimization problem for a two-stage supply chain consisting of a manufacturer and a retailer under the carbon tax regulation is investigated in this paper. Consumers’ low-carbon awareness level is considered in the decision models. Optimal decision policies, corresponding emissions, and profits are calculated for the decentralized decision-making mode. Under the decentralized mode, the two-stage supply-chain optimization problem is formulated as a Stackelberg game model, where the manufacturer and retailer were the leader and follower, respectively. The manufacturer decides the emission-reduction levels per product unit and the retailer decides the retail price per unit product. The optimal decisions are derived using the reverse-solution method. The influence of the regulation parameters and consumers’ low-carbon awareness level on the optimal decision policies, the corresponding emissions, and profits is discussed in detail. Finally, numerical experiments confirmed the analytical results. Keywords: Two-stage supply-chain optimization · Carbon tax regulation · Low-carbon awareness · Stackelberg game

1

Introduction

Climate change caused by increasing carbon emissions (emissions from greenhouse gases) has become a global issue due to their serious consequences. According to the report of Intergovernmental Panel on Climate Change (IPCC), industrial carbon dioxide emissions in 2050 must be 75% to 90% lower than those in 2010 to achieve the goal of controlling the rise of temperature within 1.5 ◦ C. To achieve the 1.5 ◦ C temperature control target, global climate action urgently needs to be accelerated. Faced with the grim situation, governments have to formulate various regulations to control emissions. As an potential policy instrument, carbon tax regulation attracts the attention from researchers [2,5,9]. The Intergovernmental Panel on Climate Change (IPCC) suggests that severe climate change can be prevented if we charge a carbon tax at $80 per-metric ton of CO2 on large carbon emitters [15]. Due to various environmental policies, c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 81–92, 2021. https://doi.org/10.1007/978-3-030-49889-4_8

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people gradually accept the idea of levying tax to abate carbon emission, and more companies are voluntary to report the carbon footprint of their prod- ucts and services, and starting to make a costly effort to curb their carbon emissions [10]. For example, Wal-Mart has committed to reduce 20 million metric tons of greenhouse gases emissions by 2015 [3]. Further, simulation results from Lu et al. [8] show car- bon tax proves to be an effective policy tool to abate emissions along with little negative effect on economic growth. As a result, imposing carbon tax turns out to be a significant step toward less carbon emission. As important sources of carbon emissions, firms must act in response to government emission regulations; otherwise, they are severely punished. Firms can achieve emission reduction in two aspects, technology upgrades and operation optimization. On the aspect of technology, firms can use more energy-efficient equipment and facilities, cleaner energy, and more environmentally friendly raw materials. Firms can also dispose of carbon emissions by postprocessing, such as Carbon Capture and Sequestration (CSS) technologies [11]. By March 2012, the Global CCS Institute had identified 75 large-scale integrated projects globally1 . All these emission-reduction technologies need extra investment. Apart from the aspect of technology, it is possible for firms to reduce emissions through individually optimizing operations [1]. For example, a logistics firm can change its carbon emissions by adjusting transport routes, the location of distribution centers, and delivering frequency. It should be noted that the effect of self-interested emission-reduction action of a firm is limited since a firm is part of a supply chain. Under carbon-emission regulation, customers’ low-carbon awareness (more generally, environmental awareness) has significant influence on supply-chain operations. The influence is from changes in consumer purchasing behavior. Some papers confirmed that consumers are willing to pay higher prices for environmentally friendly products [7,12,14,16]. To meet consumers’ willingness, the Ministry of Environmental Protection of China has organized and formulated the development plan of Environmental Certification Center Carries out Low Carbon Product Certification2 . Conrad [4] used a spatial duopoly model to determine how environmental concerns affect prices, product characteristics, and market shares of competing firms. Ji et al. [6] developed a detailed model for emissionreduction behaviors of chain members in retail- and dual-channel cases, which incorporates both cap-and-trade regulations and consumers’ low-carbon preference. Taking into account consumers’ low-carbon preferences and stochastic market demand, Wang et al. [13] derived a revenue model of retailer and manufacturer in decentralized and centralized supply chains when the supply chain reduces emissions or is not under stochastic market demand. From this background, the decision makers in supply chains must take emission regulations and consumers’ low-carbon awareness into account. This study establishes two-stage supply-chain optimization models involving cap-andtrade regulation and consumers’ low-carbon awareness. Specifically, the following issues are investigated: (1) What are the optimal decisions for decision maker(s) 1 2

http://www.ccsassociation.org/why-ccs/industry-experience/. http://www.mee.gov.cn/.

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under different modes? (2) How are optimal decisions, profits, and emissions influenced by regulation parameters and low-carbon awareness level? In this paper, consumers’ demand is set as an endogenous variable that depends on emission levels and consumers’ low-carbon awareness. Optimal decisions were derived from mathematical models under different modes. On this basis, this study analyzes the influence of regulation parameters and low-carbon awareness level on profits and emissions. The remainder of this paper is organized as follows: Sect. 2 proposes necessary assumptions and notations in preparation for mathematical model formulation. Mathematical models and analytical results are presented in Sect. 3. Section 4 presents a series of numerical experiments to confirm the analytical results. Conclusions and future research are provided in Sect. 5.

2

Related Notations and Assumptions

This study focuses on a simple two-stage supply chain with single-item product. This supply chain comprises three members, the manufacturer, the retailer, and the customer. The manufacturer and retailer are decision makers regulated by a cap-and-trade mechanism. The manufacturer generates carbon emissions during the production process, while the retailer’s carbon emissions originate from logistics. Under the carbon tax regulation, the regulator sets carbon tax rate to firms. They have to pay taxes on their carbon emissions. In this context, consumers’ low-carbon awareness can influence demand. In order to formulate the mathematical models, some key assumptions are presented as follows. Assumption 1. Retailer orders from manufacturer according to demand. No consideration is given to inventory. Assumption 2. Potential maximum market demand is fixed. Assumption 3. Both production emissions and logistics emissions linearly Table 1. Notations Parameters a

Potential maximum market demand

t

Carbon tax rate

eM Initial per unit-product emission by manufacturer; eR

Initial per unit-product emission by retailer;

pM Price per unit product paid by retailer to manufacturer according to contract h

Consumers’ low-carbon awareness level (LCAL)

k

Cost coefficient for emission reduction

Decision variable L

Reduction level of emissions per unit product (0 ≤ L ≤ 1)

pR

Retail price per unit product

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decrease in quantity. Assumption 4. Only manufacturer has the ability and opportunity to reduce emissions. Assumption 5. Lower production emissions can increase demand. Moreover, notations that are used in the models are summarized in Table 1.

3

Model Analysis

Under the decentralized mode, the retailer and manufacturer are independent decision makers. The decision-making process follows the Stackelberg game rule. In this study, the manufacturer is considered as the leader, while the retailer is the follower. In fact, retailer-leading supply chains are widespread, e.g., the Apple Inc.-based supply chain. The retailer determines their selling price to optimize their profit, while the manufacturer supplies them with the product at agreed price pM . The manufacturer determines carbon-emission reduction level L, which can influence demand since the customer is low-carbon-sensitive. The demand for the product at price pR and emission-reduction level L for the customer with LCAL h is (1) a − pR + hL. Unit cost paid on emission reduction with L is kL2 [7]. Here, the quadratic means that, as L grows, the cost increases faster. In other words, investment in emission reduction has a declining marginal effect. Hence, the optimization problem confronted by the manufacturer is formulated as: max πM = (pM − cM )(a − pR + hL) − eM (a − pR + hL)(1 − L)r − k(a − pR + hL)L2 ,

L ∈ [0,1]

(2)

where pR is optimal solution for the following model: max πR = (a − pR + hL)(pR − pM ) − eR (a − pR + hL)r pR

(3)

The second items in Eqs. (2) and (3) are taxes levied on the manufacturer and retailer, respectively. Proposition 1 proposes the optimal decisions under the decentralized decision-making mode. Proposition 1. Let Δ = (k (pM − a + eR r) + eM hr)2 − 3hk (reM (h + pM − a + eR r) + h (cM − pM )) , √ k(pM − a + eR r) + eM hr − Δ L1 = , 3hk √ k(pM − a + eR r) + eM hr + Δ . L2 = 3hk

If Δ > 0, the optimal L, denoted by L∗ , is shown in Table 2,

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Table 2. Values of L∗ when Δ > 0. L2 − L1 ≥ 1 1 ≤ L1

L∗ = 0

0 ≤ L1 < 1

L∗ = 0, if πM (L = 0) > πM (L = 1) L∗ = 1, otherwise

L1 < 0 < 1 ≤ L2 L∗ = 1 0 < L2 < 1

L∗ = L2

L2 ≤ 0

L∗ = 0

L2 − L1 < 1 1 ≤ L1 L∗ = 0 0 ≤ L1 < 1 < L2 L∗ = 0, if πM (L = 0) > πM (L = 1) L∗ = 1, otherwise 0 < L2 ≤ 1

L∗ = L2

and optimal pR , denoted by p∗R , is 1 (a + pM + hL∗ + reR ). 2 Otherwise, i.e., Δ ≤ 0, the optimal solution is   1 ∗ ∗ (L , pR ) = 0, (a + pM + reR ) . 2 p∗R =

(4)

(5)

Proof. The reverse-solution method for the Stackelberg game was used to solve the problem. For a fixed L determined by the manufacturer, let the first-order derivative of πR with respect to pR be zero, i.e., a + pM + hL + reR − 2pR = 0, which leads to pR =

1 (a + pM + hL + reR ). 2

(6)

(7)

Plugging 12 (a + pM + hL + reR ) in the place of pR in Eq. (2) and the first-order derivative of πM in L was calculated as ∂πM 3hk 2 ∂L = − 2 L + (k(pM − a + eR r) + eM hr) L 1 − 2 (h(cM − pM ) + eM r(pM − a + eR r + h))

(8)

which is a quadratic function of L with discriminant Δ. M If Δ > 0, the two real roots of ∂π ∂L = 0 are denoted as L1 and L2 , respectively. There are two cases based on a comparison of intervals [L1 , L2 ] and [0, 1].

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Case 1. L2 − L1 ≥ 1. In this case, there are five subcases according to the comparison between [L1 , L2 ] and [0, 1]. ∗ M Case 1.1 1 ≤ L1 . ∂π ∂L ≤ 0 for any L ∈ [0, 1], which indicates that L = 0. Case 1.2 0 ≤ L1 < 1. In order to determine the optimal L, it is necessary to compare πM (L = 0) with πM (L = 1). If πM (L = 0) is greater than πM (L = 1), πM takes the maximum at L = 0; otherwise, πM takes the maximum at L = 1. Case 1.3 L1 < 0 < 1 ≤ L2 . πM increases in L in interval [L1 , L2 ]; hence, πM takes the maximum at L = 1. Case 1.4 0 < L2 < 1. πM increases in [0, L2 ] and decreases in [L2 , 1], so πM takes the maximum at L = L2 . Case 1.5 L2 ≤ 0. πM decreases in [0, 1], so πM takes the maximum at L = 0. Case 2. L2 − L1 < 1. In this case, there are three subcases according to the comparison between [L1 , L2 ] and [0, 1]. Case 2.1 1 ≤ L1 . Similar to Case 2.1, πM takes the maximum at L = 0. Case 2.2 0 ≤ L1 < 1 < L2 . If πM (L = 0) is greater than πM (L = 1), πM maximizes at L = 0; otherwise, πM maximizes at L = 1. Case 2.3 L1 < 0 ≤ L2 ≤ 1. πM increases in [0, L2 ] and decreases in [L2 , 1], so πM takes the maximum at L = L2 . M If Δ ≤ 0, ∂π ∂L ≤ 0 for any L ∈ [0, 1], which implies that πM decreases in L. Thus, πM takes the maximum at L = 0. Plugging L∗ in the expression of pR , p∗R is obtained. Thus, this proof is completed. The influence of tax rate r and LCAL h on the manufacturer’s and retailer’ profits are characterized by Proposition 2 and Proposition respectively. The values of πM with different L∗ are 1 (a − pM − eR r)(pM − cM − eM r), 2 1 πM (L = 1) = (a + h − pM − reR )(pM − cM − k), 2 πM (L = 0) =

πM (L = L2 ) =

(9) (10)

  1 (a + hL2 − pM − reR ) (pM − cM ) − eM (1 − L2 )r − kL22 . 2 (11)

Proposition 2. (1) If the manufacturer has no chance to reduce emissions, i.e., L∗ = 0, the profit πM (L∗ = 0) is decreasing in r; Meanwhile, πM (L∗ = 0) is independent of LCAL h. (2) If the manufacturer has chance to reduce all emissions, i.e., L∗ = 1, the profit πM (L∗ = 1) is decreasing in r if pM − cM − k ≥ 0, otherwise πM (L∗ = 1) is increasing in r; Meanwhile, the profit πM (L∗ = 1) is decreasing in h if pM − cM − k ≤ 0, otherwise πM (L∗ = 1) is increasing in r. Proof. The results are derived from the first-order derivatives of πM (L∗ = 0) and πM (L∗ = 1) in r and h as following: 1 ∂πM (L∗ = 0) = − (eR (pM − cM ) + eM (a − pM ) + 2eM eR r)) , ∂r 2

(12)

Supply Chain Design Optimization

1 ∂πM (L∗ = 1) = − eR (pM − cM − k). ∂r 2 ∗ ∂πM (L = 1) 1 = eR (pM − cM − k). ∂h 2

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Since first-order derivative of πM (L∗ = L2 ) with respect r is too complex, we omit it. Proposition 2 indicates that the effect of the carbon tax on the manufacturers’ profit is negative when L = 0, but it is not true when L = 1. For the retailer’s optimal profits, we have the following proposition. M Proposition 3. (1) πR (L∗ = 0) is decreeing in r when r ≤ a−p eR , otherwise, ∗ ∗ πR (L = 0) is increasing in r. Meanwhile, πR (L = 0) is independent of h. M , otherwise, πR (L∗ = 1) is (2) πR (L∗ = 1) is decreeing in r when r ≤ a+h−p eR ∗ increasing in r. Meanwhile, πR (L = 0) is decreasing in h when h ≥ pM +eR r−a, otherwise, πR (L∗ = 1) is decreasing in h.

Proof. The profits of the retailer when L∗ = 0 and L∗ = 1 are πR (L∗ = 0) =

1 (a − pM − eR r)2 , 4

(15)

1 (a + h − pM − eR r)2 . (16) 4 The results are derived from the first-order derivatives of πR (L∗ = 0) and πR (L∗ = 1) in r and h as following: πR (L∗ = 1) =

1 ∂πR (L∗ = 0) = − (a − pM − eR r)eR , ∂r 2

(17)

∂πR (L∗ = 1) 1 = − (a + h − pM − eR r)eR , ∂r 2

(18)

∂πR (L∗ = 1) 1 = (a + h − pM − eR r), ∂h 2

(19)

As emissions are considered, emission amounts from manufacturer and retailer are 1 (a − pM − eR r)eM , 2 1 ER (L∗ = 0) = (a − pM − eR r)eR , 2 EM (L∗ = 1) = 0,

EM (L∗ = 0) =

ER (L∗ = 1) =

1 (a + h − pM − eR r)eR . 2

Proposition 4. (1) When L∗ = 0 and L∗ = 1, the increasing tax rate inhibits the emissions of both the manufacturer and retailer. (2) When the L∗ = 1, the retailer’s emission volume is increasing in h.

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Proof. From the expressions of EM (L∗ = 0), ER (L∗ = 0), EM (L∗ = 1), ER (L∗ = 1), the proof is trival. The first conclusion of Proposition 4 is intuitive. The second conclusion of Proposition 4 the emissions will not decrease with the increase of consumers’ lowcarbon awareness. This is because the increasing LCAL stimulated sales. This is a paradox, higher LCAL with higher emissions.

4

Numerical Experiments

In this section, a series of numerical examples are presented to illustrate the theoretical results proposed in this study. As shown in Proposition 1, there are several L∗D values under different scenarios. Only some specific scenarios are illustrated in this section, while others can be similarly implemented. Example 1. (The influence of r on profits) Let k = 1, a = 600, pM = 5, cM = 2 2, eM = eR = 1, h = 0.5. Under this setting, Δ = 3r4 − 3573r + 1416109 > 0 4 4 for any positive r, where Δ is defined in Proposition 1. In addition, assume that r lies in the [0.1, 1.2] interval. Thus L1 and L2 , defined in Proposition 1, satisfy 0 < L2 < 1, so L∗ = L2 . Based on the parameter setting, the influences of r 850

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on πM and πR are shown in Fig. 1 and Fig. 2 respectively. As shown in Fig. 1 and Fig. 2, both the manufacturer’s and the retailer’s profits are decreasing in the tax rate r. Example 2. (The influence of h on profits) Let k = 1, a = 600, pM = 5, cM = 2 1189h 2, eM = eR = 1, r = 0.5. Under this setting, Δ = 31h + 1413721 Assume 4 + 4 4 that h lies in [0, 1] interval. Thus L1 and L2 , defined in Proposition 1, satisfy 0 < L2 < 1, so L∗ = L2 . Based on the parameter setting, the influences of r on πM and πR are shown in Fig. 3 and Fig. 4 respectively. With the increase of h, the manufacturer’s profit increases first and then decreases (Fig. 3), while the retailer’s profit is growing (Fig. 4). 770 760 750 740 730 720 710 700 690 680

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Example 3. (The influence of r on emissions) Let k = 1, a = 600, pM = 5, cM = 2, eM = eR = 1, h = 1 and r ∈ [0.1, 1.2]. As indicated in Example 1, L∗ = L2 . Based on the parameter setting, the influences of r on EM and ER are shown Fig. 5 and Fig. 6 respectively. Figure 5 and Fig. 6 indicate that the increase in tax rates can curb emissions, regardless of the manufacturer or the retailer.

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Example 4. (The influence of h on emissions) Let k = 1, a = 600, pM = 5, cM = 2, eM = eR = 1, r = 0.5 and h ∈ [0, 1]. As indicated in Example 2, L∗ = L2 . Based on the parameter setting, the influences of h on EM and ER are shown Figs. 7 and 8 respectively. The two figures show that the growth of h suppresses the emission of manufacturers but promotes the emission of retailers.

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Conclusions and Future Research

This study focus on two-stage supply-chain optimization with carbon-emission consideration. The carbon tax regulations and customers’ LCAL are integrated into this problem. Under the decentralized decision-making mode, the optimal decisions, the corresponding profits and emissions for the manufacturer and retailer are derived from the mathematical models. Some propositions and numerical examples are presented to illustrate the influence of the tax rate and LCAL level on he optimal decisions, the corresponding profits and emissions. Future research can extend this study in the following four aspects. First, there can be more members in the supply chain, rather than only the two in this study. When there are more than one manufacturer or retailer, models are more complex (the Stackelberg–Nash model), and the solution method must be accordingly updated. Second, the study focused on a single-item productsupply chain. How heterogeneous products influence supply-chain operations can be considered in the future. Third, more a precise demand function should be formulated. The demand function affected by LCAL was simplified. The real demand function of LCAL should be derived through statistical techniques, e.g., regression. Fourth, future work should consider the influence of other regulations, such as the carbon cap and trade regulation. Future research expanding from these aspects can help researchers develop more reality-approaching models and provide more managerial insights for regulators and firms. Acknowledgements. This research was funded by the National Natural Science Foundation of China (grant No. 71401114), the Fundamental Research Funds for the Central Universities (Sichuan University, Grant No. skqy201524; Business School of Sichuan University, Grant No. B03).

References 1. Benjaafar, S., Li, Y., Daskin, M.: Carbon footprint and the management of supply chains: insights from simple models. IEEE Trans. Autom. Sci. Eng. 10(1), 99–116 (2012)

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2. Carattini, S., Kallbekken, S., Orlov, A.: How to win public support for a global carbon tax. Nature 565, 289–291 (2019) 3. Caro, F., Corbett, C.J., Tan, T., Zuidwijk, R.: Carbon-Optimal and Carbonneutral Supply Chains. Available at SSRN 1947343 (2011) 4. Conrad, K.: Price competition and product differentiation when consumers care for the environment. Environ. Resour. Econ. 31(1), 1–19 (2005) 5. Hoel, M.: Should a carbon tax be differentiated across sectors? J. Public Econ. 59(1), 17–32 (1996) 6. Ji, J., Zhang, Z., Yang, L.: Carbon emission reduction decisions in the retail-/dualchannel supply chain with consumers’ preference. J. Cleaner Prod. 141, 852–867 (2017) 7. Liu, Z.L., Anderson, T.D., Cruz, J.M.: Consumer environmental awareness and competition in two-stage supply chains. Eur. J. Oper. Res. 218(3), 602–613 (2012) 8. Lu, C., Tong, Q., Liu, X.: The impacts of carbon tax and complementary policies on Chinese economy. Energy Policy 38(11), 7278–7285 (2010) 9. Metcalf, G.E.: Designing a carbon tax to reduce us greenhouse gas emissions. Rev. Environ. Econ. Policy 3(1), 63–83 (2009) 10. Park, S.J., Cachon, G.P., Lai, G., Seshadri, S.: Supply chain design and carbon penalty: monopoly vs. monopolistic competition. Prod. Oper. Manage. 24(9), 1494–1508 (2015) 11. Riahi, K., Rubin, E.S., Taylor, M.R., Schrattenholzer, L., Hounshell, D.: Technological learning for carbon capture and sequestration technologies. Energy Econ. 26(4), 539–564 (2004) 12. Shuai, C.M., Ding, L.P., Zhang, Y.K., Guo, Q., Shuai, J.: How consumers are willing to pay for low-carbon products?-results from a carbon-labeling scenario experiment in China. J. Cleaner Prod. 83, 366–373 (2014) 13. Wang, L., Xu, T., Qin, L.: A study on supply chain emission reduction level based on carbon tax and consumer’s low-carbon preferences under stochastic demand. Math. Probl. Eng. 2019, 1621395 (2019) 14. Xia, L., Hao, W., Qin, J., Ji, F., Yue, X.: Carbon emission reduction and promotion policies considering social preferences and consumers’ low-carbon awareness in the cap-and-trade system. J. Cleaner Prod. 195, 1105–1124 (2018) 15. Yang, H., Chen, W.: Retailer-driven carbon emission abatement with consumer environmental awareness and carbon tax: revenue-sharing versus cost-sharing. Omega 78, 179–191 (2018) 16. Zhao, R., Geng, Y., Liu, Y., Tao, X., Xue, B.: Consumer’s perception, purchase intention, and willingness to pay for carbon-labeled products: a case study of Chengdu in China. J. Cleaner Prod. 171, 1664–1671 (2018)

Optimal Pricing of the Dual-Channel Closed-Loop Supply Chain in Advance Selling Mode Xinyuan Cui, Jiayi Wang, Yuyu Geng, and Chunxiang Guo(B) Business School, Sichuan University, Chengdu 610064, People’s Republic of China [email protected]

Abstract. Nowadays, advance selling has become increasingly popular as one of the essential sales strategies. Due to the continuous development of e-commerce and remanufactured products, it is urgent for merchants to decide how to price the product properly. This paper establishes a two-stage pricing model for the dual-channel closed-loop supply chain in advance selling mode and analyzes the impact of market competition and consumers’ purchasing behavior on pricing strategies. Then we found that (1) The retailer’s optimal price is lower when the market competition is relatively significant. (2) When the recovery rate rises, the optimal price remains steady, but the profits of the retailer and the manufacturer both increase. (3) The advance selling price is generally higher than the regular selling price. However, the emergence of remanufactured products hugely increases the regular selling price.

Keywords: Advance selling strategy

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· Remanufactured products · Pricing

Introduction

Advance selling is a selling method that allows consumers to submit preorder before the release of a new product [8,9,11,22,23]. It enables sellers to reduce cash flow pressure and decreases demand uncertainty. With the remarkable development of Internet and information technology, advance selling has become prevalent in the online retailing industry [17]. For example, the largest Chinese online retailing platform, Taobao.com, has launched Double Eleven (11th November) advance selling since 2009 [2]. In 2019, the revenue of the Double Eleven promotions exceeded 250 billion yuan. This advance selling strategy in both offline and online channels not only benefits sellers but also gives consumers more information about the product. When deciding whether to buy in advance, strategic consumers will predict and evaluate the future price, then make the most desirable option [16]. Therefore, the prices in advance selling and regular selling stages exert a significant influence on consumers’ choices. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 93–105, 2021. https://doi.org/10.1007/978-3-030-49889-4_9

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Meanwhile, with the initiatives for a recycling economy and sustainable development, more and more manufacturers such as Apple, Canon, and Panasonic begin to recycle and remanufacture waste products [15,24]. These companies take old products as roughcast and remanufacture them with unique processes and technologies. Then remanufactured products are put into commodity sales together with new products [15]. The whole process saves resources and reduces the damage to the environment [5,6,13,20]. The remanufactured product is not inferior to a new product in terms of performance and quality but has the advantage of the lower price. When the quality differentiation between the two types of products is not obvious, customers will buy the one with higher utility [3]. Therefore, when deciding how to price the products, sellers should consider not only the competition between new products in the market but also the impact of remanufactured products in different channels [21]. Based on the Stackeberg game, this paper researches the optimal pricing strategies of both retailers and manufacturers. We establish optimal pricing strategies with only new products in the first cycle, and the impact of remanufactured products has been considered in the second cycle. It not only could further enrich the existing research field of pricing but also provide useful suggestions for supply chain members, which helps improve enterprise efficiency and market share.

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Literature Review

Recent studies on the pricing in advance selling mode mainly focus on consumers’ refunds, product quality, market demand, and other aspects. Based on existing research, Xie et al. [19] studied the pattern of advance selling in a variety of situations such as limited capacity, second-period arrivals, refunds, and so on. Nasiry and Popescu [14] characterized the effect of anticipated regret on consumer decisions, firm profits, and policies in an advance selling context. Xiao et al. [18] investigated a seller’s equilibrium pricing strategies under two classic advance selling pricing schemes when the product quality was uncertain. Lin et al. [10] analyzed the effect of advance selling discount and quantity, and found that the amount was affected by market demand. Then, Moe and Fader [12] demonstrated the ability to forecast new album sales based only on the pattern of advance orders. The above literature provides a basis for sellers’ product pricing decisions in the advance selling mode. However, they only focus on the price in advance selling, and there is no combination of the two stages. Few studies have considered the impact of the price in advance selling on that in regular selling. With the development of e-commerce, advance selling achieves a high growth in online shopping, and many studies [2,7,16] on advance selling also take it as the study background by default. Cheng et al. [2] looked into a joint optimization problem of multiple and dynamic marketing decisions when advance selling is applied. Wang et al. [16] developed a pricing model for perishable goods in the context of online advance selling.

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Existing studies on remanufactured product pricing mainly focus on the risk preference of supply chain members, product recovery rate, and product recovery cost. Based on the experiment, Abbey et al. [1] demonstrated that consumer has a high sensitivity to price discounts and strong preferences for new productsa lwith an accompanying aversion to remanufactured products. Then, Gao et al. [4] studied an original equipment manufacturer, which made new products and re-products simultaneously. They concluded that in the variable market, as the market growth rate increased, the profit and the proportion of re-products increased simultaneously. Yan et al. [21] studied the pricing problem of a firm that sells both new and remanufactured products over a finite planning horizon from multiple perspectives, which means there is a mutual relationship between the two pricing. Therefore, remanufactured products are also an essential factor to be considered in the pricing model. The above studies have done some researches on advance selling, online and offline dual channels, and remanufactured products. However, the real situation is very complicated, and it needs to consider all these factors to develop a more reasonable pricing strategy. Therefore, the following research aims to analyze the dual-channel closed-loop supply chain in advance selling mode and establish an appropriate model, which provides new perspectives and useful research conclusions for the price strategies of supply chain members. Moreover, it further enriches and refines the existing research field of pricing.

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Model

In the dual-channel closed-loop supply chain, the sales process is considered as two cycles (see Fig. 1). In the first cycle, traditional retailers and e-retailers stock new products from manufacturers at a price of w1 , and sell them to consumers at the price of p1r and p1e respectively. At the end of the first cycle, traditional retailers recycle secondhand products from consumers at the price of A with a recovery rate of τ . In the second cycle, manufacturers produce new products and remanufacture secondhand products (which are bought from traditional retailers at a price of br ) at the same time (the unit cost for new product and remanufactured product is cm and cn , cm > cn ). Then they wholesale new products and remanufactured products to retailers at the price of w2 and δw2 respectively. Among them, β part of remanufactured products are sold to traditional retailers, and the rest part are sold to e-retailers. δ is the unit wholesale discount coefficient of remanufactured products which determined by the quality of the remanufactured product, the safety factor, and the bargaining power of the retailer and the manufacturer, δ ∈ (0, 1]. At this cycle, consumers can gather a variety of information about products (such as price, quality, and functionality, etc.) to compare the cost performance of new and remanufactured products comprehensively. After information collection and comprehensive evaluation, consumers will have a preference λ ∈ (0, 1) for remanufactured products. Therefore, in the regular selling, the price of the new product is p2i , and that of the remanufactured product is λp2i , i ∈ (r, e).

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In addition, according to the practical situation, selling can occur either in the advance selling stage or the regular selling stage. In the two stages, the price is the main factor that influences consumers to purchase products. The parameters used in the paper are described in Table 1. The following assumptions are made in the development of the model: (1) The manufacturer can conform to the market standard of remanufacturing. Meanwhile, the cost savings from remanufacturing is Δ(Δ = cm −cn ), which is higher than the traditional retailers’ transfer price, that is Δ > br . (2) In the whole supply chain, the manufacturer is the leader of the Stackelberg model, and the retailer is the follower, which means the optimal price of retailers is decided according to that of manufacturers. (3) Consumers that e-retailers lose do not buy products in other ways, and all consumers can buy only one unit of products. (4) In the advance selling mode, the time pressure will have a positive effect on strategic consumers’ purchasing intention. (5) All of the retailers sell new products at the same price during the advance selling stage. (6) Price is the main factor affecting the market demand. Based on the competitive environment of the market, demand functions are assumed as follows: qr = q0 − apr + bpe ; qe = q0 − ape + bpr ; qx = q0 − ax + bx In market competition between traditional retailers and e-retailers, their own prices have a greater impact on their own demand, thus a > b.

Fig. 1. Two-cycle sales flow chart

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Table 1. Model parameters and descriptions Notation Definition x

The price of new products in advance selling

w

The unit wholesale price of new products

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The price of new products in traditional retailers at regular selling

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The price of new product in e-retailers at regular selling

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The primary demand (when the selling price is 0)

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The positive price sensitivity coefficient (the influence coefficient of one’s price on demand in market competition)

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The reverse price sensitivity coefficient (the influence coefficient of competitor’s price on demand in market competition)

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The unit manufacturing cost of new products for manufacturers

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The unit manufacturing cost of remanufactured products for manufacturers

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The degree of consumersa´ r preference for remanufactured products

δ

The unit wholesale discount coefficient of remanufactured product

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The proportion of remanufactured products sold by traditional retailers

τ

The proportion of products recycled in the market

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The unit transfer price

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The unit retrieve price

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The fixed cost of investment in recycled products

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The profit function of supply chain members

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Pricing Strategy of New Products in the First Cycle

In the first cycle, the profit function of traditional retailers, e-retailers and manufacturers are as follows: π1r = (x1 − w1 )(q0 − ax1 + bx1 ) + (p1r − w1 )(q0 − ap1r + bp1e ) π1e = (x1 − w1 )(q0 − ax1 + bx1 ) + (p1e − w1 )(q0 − ap1e + bp1r )

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π1m = (w1 − cm )[2(q0 − ax1 + bx1 ) + (q0 − ap1r + bp1e ) + (q0 − ap1e + bp1r )]

In the Stackelberg model, the manufacturer is the leader and retailers are the followers. Therefore, manufactures determine the wholesale price w firstly. Then retailers determine the selling price p or x according to w. Using backward induction, we can get: ∂π1r = bp1e − 2ap1r + q0 + aw1 = 0 ∂p1r ∂π1e = bp1r − 2ap1e + q0 + aw1 = 0 ∂p1e ∂π1r = −(a − b)x + q0 + (b − a)(x − w1 ) = 0 ∂x

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By solving the equation above, the prices are: p1r =

q0 + aw1 2a − b

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With the definition of p1r , p1e and x, and Eq. (1), the derivative of the profit function of the manufacture with respect to the wholesale price w can be calculated by the following Eq. (5): ∂π1m (4a − b)[(a − b)cm + q0 − 2(a − b)w1 ] = ∂w1 2a − b 3.2

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Pricing Strategy of New Products in the Second Cycle

At the end of the first cycle, traditional retailers recycle used products at a proportion of τ with a varied cost of A and a fixed cost of I. Besides, the quantity of the used products can be described as S. S = 2(q0 − ax1 + bx1 ) + (q0 − ap1r + bp1e ) + (q0 − ap1e + bp1r ) =

(4a − b)[q0 − (a − b)cm ] 4a − 2b

In the second cycle, manufactures recycle τ S used products from traditional retailers at a price of br , then wholesale βτ S and (1 − β)τ S part of remanufactured products to traditional retailers and e-retailers respectively. As for new products, retailers buy them at a price of w2 and sell at a price of p2 . For remanufactured products, retailers buy them at a price of δw2 and sell at a price of λp2 . Similar to the first cycle, the profit function can be counted as follows: π2r = (x2 − w2 )[q0 − (a − b)x2 ] + (p2r − w2 )(q0 − ap2r + bp2e ) + (λp2r − δw2 )βτ S + (br − A)τ S − I π2e = (x2 − w2 )[q0 − (a − b)x2 ] + (p2e − w2 )(q0 − ap2e + bp2r ) + (λp2e − δw2 )(1 − β)τ S π2m = (w2 − cm )[2q0 − 2(a − b)x2 + q2r + q2e ] + (δw2 − br − cn )τ S

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Result Pricing Strategy of New Products in the First Cycle

Theorem 1. The optimal prices of two stages in the first cycle are as follows: (a − b)cm + q0 2(a − b)

(6)

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(a − b)acm + [2(a − b) + a]q0 2(2a − b)(a − b)

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(a − b)acm + [2(a − b) + a]q0 2(2a − b)(a − b)

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(a − b)cm + 3q0 4(a − b)

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x∗1 =

Noted that the prices p∗1r , p∗1e and x∗1 are associated with the optimal wholesale price w which can be calculated by letting Eq. (5) equal to zero. And with the definition of, and Eqs. (2), (3) and (4), the optimal prices in two stages come out. 4.2

Pricing Strategy of New Products in the Second Cycle

Theorem 2. The optimal prices of two stages in the second cycle are as follows: w2∗ =

(4a2 − 5ab + b2 )cm + (4a − b)q0 − (a − b)Sλτ 2(4a2 − 5ab + b2 )

(10)

a(2a + b)[(4a2 − 5ab + b2 )cm + (4a − b)q0 − (a − b)Sλτ ] 2(4a2 − 5ab + b2 )(4a2 − b2 ) 2(4a2 − 5ab + b2 )[S(bλτ + 2aβλτ − bβλτ + (2a + b)q0 ] + 2(4a2 − 5ab + b2 )(4a2 − b2 )

(11)

a(2a + b)[(4a2 − 5ab + b2 )cm + (4a − b)q0 − (a − b)Sλτ ] 2(4a2 − 5ab + b2 )(4a2 − b2 ) 2(4a2 − 5ab + b2 )[S(2aλτ − 2aβλτ + bβλτ + (2a + b)q0 ] + 2(4a2 − 5ab + b2 )(4a2 − b2 )

(12)

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(4a2 − 5ab + b2 )cm + 3(4a − b)q0 − (a − b)Sλτ 4(4a2 − 5ab + b2 )

(13)

Noted that the optimal prices are also calculated by the price of manufactures which is the leader of the supply chain. And all the prices can be defined by the known parameters.

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Numerical Analysis

To better understand the impact of some factors on the optimal price and profit of manufacturers and retailers, a numerical analysis is carried out for the system model. 5.1

The Impact of Market Competitiveness

In this cycle, (a − b) is the only target variable, which means the gap of retailers’ market competitiveness. The larger (a−b) is, the more competitive the market is. The other fixed values of irrelevant parameters are q0 = 7000, δ = 0.4, β = 0.4, cm = 6000. When (a − b) changes within [0,1], the trends of the optimal pricing are shown in Fig. 2. Therefore, the following conclusions can be obtained. Conclusion 1. When the gap of retailers’ market competitiveness increases, the optimal wholesale prices of all the supply chain members will decrease during the first cycle.

Fig. 2. The impact of (a − b) on pricing

As for the variation of (a−b) from 0 to 0.5, there are dramatic downward trends in all of the optimal pricing. Meanwhile, the optimal price of retailers (the optimal prices of the traditional retailers and e-retailers are the same, and the function curve completely overlaps) in advance selling is higher than that in regular selling. The price difference reduces as the value of (a − b) increases, showing a negative correlation. Moreover, the optimal pricing of each member in the supply chain declines marginally, and the tends gradually to be the same when (a−b) belongs to [0.5, 1]. The retailer’s optimal price p1 in regular selling is slightly higher than the manufacturer’s optimal wholesale price w1 . Hence, it can be concluded that when the gap of retailers’ market competitiveness increases, the retailers will occupy a

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dominant position in the market, and the retailers with the competitive advantage will perform strongly in the whole supply chain. Meanwhile, the bargaining power of manufacturers is weakened. And the manufacturer’s optimal wholesale price w1 is forced to be declined continuously. The more prominent the gap of market competitiveness is, the lower the optimal wholesale price is. 5.2

The Impact of the Recovery Rate

In this cycle, the recovery rate τ is the only target variable and other fixed values of irrelevant parameters are λ = 0.8, br = 1200, A = 1000, I = 100, 000, δ = 0.5, β = 0.4, cn = 2500. The impacts of the variation of τ on the optimal pricing and profit are shown in Fig. 3 and Fig. 4, respectively.

Fig. 3. The impact of τ on pricing

Fig. 4. The impact of τ on optimal profit in the second cycle

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Conclusion 2. Whatever the recovery rate τ changes, the optimal pricing of manufacturers and retailers remains steady during the second cycle selling. After the first cycle, the remanufactured products are produced. As the advance selling stage does not contain remanufactured products, we only need to analyze the optimal pricing of new products in the two selling stages. Figure 3 shows that the change of recovery rate τ has a slight impact on the optimal pricing. Conclusion 3. The profits experience growth with the rise of recovery rate τ . As shown in Fig. 4, compared with the traditional retailers, e-retailers grow faster. When π2e is equal to π2r , the recovery rate is τ ∗ . When the recovery rate τ belongs to [0, τ ∗ ], the traditional retailer’s profit is higher than e-retailer’s. When the recovery rate τ belongs to [τ ∗ , 1], the result is the opposite. The growth rate of manufacturers’ profits is relatively slow. On the other hand, it is remarkable that the profits of manufacturers are higher than that of retailers when the recycling rate is low. However, the profits of e-retailers and traditional retailers would exceed these of manufacturers if τ > τ1 , τ > τ2 , respectively. Therefore, to increase the total supply chain profit, a corresponding incentive mechanism could be developed to stimulate traditional retailers for product recycling and improve manufacturers’ remanufacturing enthusiasm. τ ∗ , τ1 , and τ2 are shown in the Appendix. 5.3

The Impact of Remanufactured Products

Conclusion 4. The advance selling price is higher than the regular selling price, while when the remanufactured products entered the market, the regular selling price is higher. As shown in Fig. 2 and Fig. 3, the advance selling price x1 is higher than the regular selling price p1 in the first cycle. After remanufactured products entering the market in the second cycle, the optimal advance selling price x2 marginally lower than the regular selling price p2 . In contrast, the optimal advance selling price of traditional retailers p2r is slightly lower than that of e-retailers p2e . Due to remanufactured products with the advantage of low prices, some pricesensitive consumers would give up buying new products. On this occasion, the unit profit of new products is higher than that of remanufactured products. Meanwhile, the increasing pressure of market competition forces retailers to set lower prices of new products in the advance selling to occupy more market shares. After the advance selling, the market is mainly for consumers who are not price-sensitive. At this time, increasing the regular price p2 can improve the profit of the unit product, thus improving the profit of the retailers effectively.

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Conclusion

This paper establishes a two-stage pricing model to analyze the dual-channel closed-loop supply chain in advance selling mode. Notably, the impact of remanufactured products on the price of new products is considered. In this way,

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we propound the following suggestions, through which the participants in the closed-loop supply chain can realize the optimal pricing strategy. (1) When retailers play a leading role in the market, manufacturers should sign long-term cooperation agreements with them to avoid the loss of their profits. (2) The improvement of the recovery rate can improve the benefit of the whole closed-loop supply chain, in which the e-retailer with the most massive profit should give some incentives to traditional retailers and manufacturers to achieve a win-win result. (3) Due to the price advantage of remanufactured products, the advance selling price should be lower than the regular selling price, which has reference significance for the pricing strategy in reality. For future research, one possible direction is to consider the effect of product supply restriction on optimal pricing under the advance selling mode. Another trend is to study the impact of substitutes for consumer behavior. When an enterprise expands from a single product to multiple products, considering the market encroachment between two similar products is the focus of future research. Acknowledgements. This study is supported by National natural fund project (71871150), Innovation spark project library of Sichuan university (2018hhs–35), and Project of science and technology department of Sichuan province (2019JDR0148).

Appendix Derivation of τ ∗ τ∗ =

−I + ap2e − ap2r − pe q0 + pr q0 − (a + b)pe w2 + (a + b)pr w2 . S(A − br + λpe − βλpr − λpr − δw2 + 2δβw2 )

Derivation of τ1 τ1 = {−ap22e + (a − 2b)p2r w2 − 6q0 w2 + p2e [bp2r + q0 + (2a − b)w2 ] + q0 x2 + 3(a − b)w2 x2 − (a − b)x22 + cm [(−a + b)(p2e + p2r + 4q0 − (a − b)2x2 )]}/ {S[br + cn − (1 − β)λp2e − βδw2 ]}

Derivation of τ2 τ2 = {−I − ap22r + p2r q0 + (2a − b)p2r w2 − 6q0 w2 + p2e [bp2r + (2a − b)w2 ] + q0 x2 + (3a − b)w2 x2 − (a − b)x22 + cm [(−a + b)(p2e + p2r ) + 4q0 − (a − b)2x2 ]}/ {S[A + cn − βλp2r − (1 − β)δw2 ]}

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References 1. Abbey, J.D., Blackburn, J.D., Guide Jr., V.D.R.: Optimal pricing for new and remanufactured products. J. Oper. Manage. 36, 130–146 (2015) 2. Cheng, Y., Li, H., Thorstenson, A.: Advance selling with double marketing efforts in a newsvendor framework. Comput. Ind. Eng. 118, 352–365 (2018) 3. S ¸ eref, M.M.H., S ¸ eref, O., et al.: Advance selling to strategic consumers. Comput. Manage. Sci. 13(4), 597–626 (2016) 4. Gao, P., Wang, X., et al.: Differentiated pricing policy for new, remanufactured and refurbished products. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 229(11), 2063–2075 (2015) 5. Guide, V.D.R., Harrison, T.P., Van Wassenhove, L.N.: The challenge of closed-loop supply chains. Interfaces 33(6), 3–6 (2003) 6. Gutowski, T.G., Sahni, S., et al.: Remanufacturing and energy savings. Environ. Sci. Technol. 45(10), 4540–4547 (2011) 7. Huang, K.L., Kuo, C.W., Shih, H.J.: Advance selling with freebies and limited production capacity. Omega 73, 18–28 (2017) 8. Kim, K.H., Lee, H.T., Seo, H.J.: The mechanism of the influence of advanced selling on consumer choice. J. Distrib. Sci. 14, 81–87 (2016) 9. Lim, W.S., Tang, C.S.: Advance selling in the presence of speculators and forwardlooking consumers. Prod. Oper. Manage. 22(3), 571–587 (2013) 10. Lin, Z., Zhou, Z., Wu, S.: Advance selling in the presence of strategic consumers and network externality. Ind. Eng. J. 18(2), 66–72 (2015) 11. Ma, S., Li, G., et al.: Advance selling in the presence of market power and riskaverse consumers. Decis. Sci. 50(1), 142–169 (2019) 12. Moe, W., Fader, P.: Using advance purchase orders to forecast new product sales. Mark. Sci. 22(1), 146–146 (2003) 13. Mok, H.S., Jeon, C.S., et al.: Development methods of remanufacturing industry for resources recycle. Trans. Korean Soc. Autom. Eng. 17(1), 120–129 (2009) 14. Nasiry, J., Popescu, I.: Advance selling when consumers regret. Manage. Sci. 58(6), 1160–1177 (2012) 15. Shu, T., Xu, J., et al.: Remanufacturing decisions with WTP discrepancy and uncertain quality of product returns. Sustainability 10, 2123 (2018) 16. Wang, X., Wen, H., et al.: Pricing for perishable goods in advance selling strategy. In: 2016 International Conference on Logistics, Informatics and Service Sciences (LISS), pp. 1–4. IEEE (2016) 17. Wei, M.M., Zhang, F.: Advance selling to strategic consumers: preorder contingent production strategy with advance selling target. Prod. Oper. Manage. 27(7), 1221– 1235 (2018) 18. Xiao, L., Xu, M., et al.: Optimal pricing for advance selling with uncertain product quality and consumer fitness. J. Oper. Res. Soc. 70(9), 1457–1474 (2019) 19. Xie, J., Shugan, S.M.: Electronic tickets, smart cards, and online prepayments: when and how to advance sell. Mark. Sci. 20(3), 219–243 (2001) 20. Bs, X.: Chinese characteristic remanufacturing industry and its innovation development. Electr. Welding Mach. 42(5), 1–5 (2012) 21. Yan, X., Chao, X., et al.: Optimal policies for selling new and remanufactured products. Prod. Oper. Manage. 26(9), 1746–1759 (2017) 22. Yu, M., Kapuscinski, R., Ahn, H.S.: Advance selling: effects of interdependent consumer valuations and seller’s capacity. Manage. Sci. 61(9), 2100–2117 (2015)

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23. Zeng, C.: Optimal advance selling strategy under price commitment. Pac. Econ. Rev. 18(2), 233–258 (2013) 24. Zhang, W., He, Y.: Optimal policies for new and green remanufactured shortlife-cycle products considering consumer behavior. J. Cleaner Prod. 214, 483–505 (2019)

When Barriers Need Attention: Adoption of Knowledge Management in Sustainable Supply Chain Muhammad Nazam1 , Muhammad Hashim2(B) , Waseem Ahmad1 , and Sajjad Ahmad Baig2 1 Institute of Business Management Sciences, University of Agriculture, Faisalabad, Pakistan 2 Department of Management Sciences, National Textile University, Faisalabad, Pakistan [email protected]

Abstract. In recent years, disseminating the knowledge among customers and stakeholders regarding production and distribution of items is grabbing more attention in the global supply chain system. The manufacturing industry is very important in delivering healthy products for life saving of the society. In this perspective, the present work focuses on prioritization of key barriers in the food sector in a developing economy scenario like Pakistan. The core objective of the existing research is to concentrate on prioritizing the essential factors based on fuzzy AHP methods in the perspectives of sustainable supply chain. Therefore, a quantitative analytical tool is employed for the selection and ranking of these barriers and primary data were collected through well-structured questionnaire and experts interviews. The study makes certain contributions to the literature by identifying and prioritizing the barriers. Furthermore, the results of this research suggest that decision makers should identify the barriers first then enhance the organizational performance and sustainability. Finally, the prioritization of (KM) barriers is expected to facilitate the food sector to design the knowledge management practices in a sustainable way. Keywords: Sustainable supply chain Knowledge management

1

· Barriers · Prioritization ·

Introduction

In the emerging supply chain environment, the concept of knowledge management has gain more attention for the success of any business. Knowledge management has been considered as major factor for businesses to gain competitive advantage in the domestic as well as international markets. The market positioning based on the organizations knowledge management implementation strategies [4,14,15,30]. Knowledge acts as a fuel to a firm through generating contribution to its people, products and processes; whereas knowledge management c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 106–118, 2021. https://doi.org/10.1007/978-3-030-49889-4_10

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is a transformation process which converts data and information of intellectual assets into sustainable values by adopting suitable knowledge for management actions [11,18,20,22]. Knowledge management is a process which facilitates the organizational knowledge to create value and enhance completive edge over competitor. Nowadays, in the organizations, knowledge management is considered one of the important tools for gaining competitive edge. Therefore, the needs to develop knowledge management model and strategies have been gaining attention for the academia and industry that bridge the gap to effective knowledge sharing between supply chain partners. The adoption of knowledge management in a supply chain strengthens a joint collaborative environment that facilitates the chain partners to be more efficient and responsive to achieve strategic position in the market. The exchange of knowledge among supply chain partners is a platform to get access in the external knowledge and eventually improve the competitiveness of the holistic supply chain. In addition, managing smooth flow of knowledge within the supply chain can help firms to utilize the resources efficiently and effectively by adopting the principles of lean, agile, resilient and green supply chain. From the last few years, knowledge management and supply chain are acting as two major streams for research and have significantly gained the attention of academician, practitioners and consultants. Although, knowledge management is a life blood of an organization and plays a vital role to achieve the goal of supply chain performance and competitive edge. Despite the importance of all these factors, why only a few supply chains are benefiting from the knowledge management? The major reason is knowledge sharing and transformation between dissimilar groups with dissimilar purposes. One of another major reason is incomplete understanding about knowledge management adoption and identification of barriers in supply chain timely. The prioritization and eradication of barriers in supply chain management is a multi-criteria decision making problem. It is very difficult for the experts to give opinions in exact numerical values or subjectively due to uncertain environment. In this case, fuzzy logic is important tool for tackling issues encountered by incomplete information and vague values. This study develops fuzzy analytical hierarchy process (AHP) to prioritize the solutions of knowledge management adoption in supply chain [27]. This research paper utilizes fuzzy AHP technique to compute weights intensity of the identified barriers. Finally, a case is given to show the applicability of the proposed framework [2,3,23,25]. This research deals with an important issue regarding identification of barriers in knowledge management adoption within supply chain. As knowledge management and supply chain have taken much attention over the last few decades to facilitate the profitability and performance level of the businesses [6,16,36]. Adoption of knowledge management effectively based on some previous studies of barriers identification in a supply chain but this study bridge the gap to identify the barriers in a Pakistani context. Like other disciplines, supply chain field faces some challenges to strengthen the role of knowledge management as it is not well integrated into business dynamics. As the organizations have not sufficient funds for adoption of knowledge management in supply chain [32,33]. The involvement of top level management in making strategies for adoption of knowledge management is necessary to make a good relationship with buyer and supplier [31].

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If the lack of information visibility prevails between the supply chain partners then it will put the organization into delays and poor responsiveness [35,40]. There is a need to develop knowledge-based supply chain models/frameworks for smooth flow of information visibly in the overall supply chain i.e from buyer demands to order fulfillment. This approach is very helpful for supply chain member to make decision on a timely basis and gain competitive advantage. For implication of the knowledge-based models the major hurdle is from the traditional mindsets as they believe that on investing knowledge transformation in costly. The well-established organizational structure enhances the upward and downward flow of communication more easy and effective by knowledge sharing [10]. The organizational attitude of the employees towards the innovation and transformation of latest knowledge is one of the potential barriers. This mindset of the employees is a constraint for developing of a knowledge-creation in the firm. Due to diversified workforce, the problem of knowledge sharing in such a situation is more complex [9,28]. The lack of managerial planning and empowerment of the decision makers are the most significant variable of knowledge management adoption in supply chain [5]. The concept of knowledge management is still not conceived in the organizations in a well manner. A common perception prevails that adoption of knowledge management requires more capital intensive investment and availability of huge labor force with a better infrastructure. There is need to sensitize the organization to be well aware about the significance of the knowledge management practices, but still employer of the manufacturing sectors consider it secondary matter [12]. The adoption of knowledge management should start from the strategic level rather than production and operation level [1,21,34]. To support the information sharing strategies technological infrastructure has direct effects on performance of firms. A strategic level of tact makes the knowledge sharing within and outside the boundary of the organization very crucial task. A hot issue with managing knowledge transfer to partners centrally is that communication barriers that may arise between inter-organizational knowledge sharing and other concerned departments [1,39]. In recent years, mostly Pakistani organizations realize that knowledge plays a vital role in the success of any business enterprise and adoption of knowledge management in a supply chain is the core process [7,13]. Few Pakistani manufacturing organizations have implemented knowledge management strategies through linkage with supply chain [8,17,19,29,38]. But the ratio of success very low due to certain barriers. Based on the above studies, the essence of barriers of knowledge management in supply chain can scrutinized through review of literature and experts opinions. The identification of the barriers in adoption of knowledge management is significant but not easy to tackle all the barriers at one time. The definition of barrier is different from industry to industry and it may be differently important for other organization due to different priorities, purposes, policies, resources and capacities. Therefore, it can be observed that in order to eradicate all the barriers in knowledge management adoption, a concrete and feasible ranking solution must be proposed and developed in stepwise way. The purpose of this research

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study is to identifies the list of barriers of knowledge management adoption in a supply chain and prioritize the solutions to tackle these barriers/hurdles. The identification and further ranking is important to prioritize the barriers in descending order I so that stakeholders’ may develop strategies on priority basis and sustain competitive edge. The overall objective of this study is to identify and rank the barriers in implementing KM in sustainable supply chain management of food industry. The specific objectives are: • To identify the key and potential barriers in (KM) implementation in the food sector; • To rank potential barriers for successful implementation of (KM); • To present its managerial implications to stakeholders of industry.

To eradicate essential barriers for implementation of KM

Managerial (M)

Organizational (O)

Technological (T)

M1

O1

T1

M2

O2

T2

O3

T3

M3 M4 M5

Social (S)

Individual (I)

I1 S1 I2 S2

O4

T4 I3

O5

S3

O6

I4

Prioritization of essential barriers for KM Implementation

Fig. 1. Decision hierarchy for prioritizing barriers of KM adoption in SSC

Therefore, to overcome on these barriers a knowledge-based framework has been developed to rank the potential barriers in a stepwise manner. The proposed problem is classified into four hierarchical levels and same is given in Fig. 1. These four levels are discussed as; Level 1) The overall goal of the selected problem, Level 2) this level explains the major criterion/barriers in adoption of knowledge management, Level 3) this phase of the decision hierarchy includes the sub-criterion/barriers and Level 4) priorities of potential barriers are ranked by using fuzzy AHP method.

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Proposed Methodology

This section proposes a methodology for prioritizing the barriers of KM adoption in sustainable supply chain to tackle its barriers in the food sector. In recent years, industries in Pakistan are realizing the importance of knowledge for the success of business. However, the adoption of knowledge management in sustainable supply chain is a core issue which needs to be addressed prior developing business strategies. Some of the multi-national industries are implementing knowledge management practices but most of the typical organizations are encountering challenges in adoption. In this perspective, an experts group was formulated from the food industries. Initially 15 experts were selected for pre-testing the variables. Afterwards, 3 most experienced experts were chosen to give opinions regarding intensity level of barriers which are prevailing in their industries. 2.1

Fuzzy AHP

The fuzzy AHP technique extends Saaty’s AHP by integrating it with fuzzy logic and theory. In this method, fuzzy rating scales are employed to determine the intensity of the variable in the identified attributes. Hence, a fuzzy pairwise comparison matrix based on expert’s judgment can be formulated. The resultant values of alternate options are also shown by triangular fuzzy numbers [37]. The optimum value of the alternates is got by rating the triangular fuzzy numbers using arithmetic symbols. This technique combined all the elements in terms of triangular fuzzy numbers [26]. The fuzzy numbers are used to compute the intensity level of the one criterion over other criteria. After this, a fuzzy judgment matrix is then generated for every criterion [24,26]. These matrixes are used to formulate the fuzzy pairwise comparison matrix for computation of each major criterion weight and then sub-criterion weight. In the Fig. 2, graphical representation of the fuzzy membership function for linguistic expressions for criteria and sub-criteria are shown categorically. Decision makers are requested to provide their suitable inputs in the form of linguistics values which were then transformed and analyzed to get the final or global weights.

M

(x)

1.0

Equally Moderately Strongly ˜ ˜ 5˜ 3 1

Very Strongly Absolutely 7˜ 9˜

0.5

0.0

1

2

3

4

5

6

7

8

9

10

11

Fig. 2. Fuzzy membership function for linguistic expression for criteria and sub-criteria

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The proposed technique comprises of three major phases as given in Fig. 3. In the first step, identification of barriers requires by the firm which come up with a comprehensive hierarchy of all the criteria which may affect the firm. This is done by reviewing the literature and consultation with the experts in the chain by identifying potential loopholes. Identifying the Barriers in Adoption of KM through Literature Review and Experts

Formation of Experts Panel

Concluding Remarks and Policy Implications

Listing of Barriers through Experts Input using Fuzzy Logic

Data Analysis 1. Prioritizing of Barriers 2. Results Analysis

Data Collection from IndustrialDD Experts

D

Fig. 3. Proposed research framework

The second step is the process for calculating weights of the barriers of KM adoption in sustainable supply chain by using fuzzy AHP methodology. The fuzzy AHP technique is employed for this problem and decision maker’s views are considered to take inputs in terms of linguistic variables. The third step involves determining the scores of different criteria by analyzing them under five different criteria; namely managerial, organizational, technological, social, and individual. In the fourth step, fuzzy global weights obtained through fuzzy AHP approach are used to rank the barriers. Finally, graphically comparative results of criterion weights with respect to adoption of knowledge management and managerial implications with a concluding remark have been explained.

3

Results and Discussion

The expert panel comprised of industrial decision makers including senior managers, IT specialists, and senior executive of supply chains. This research study identified 22 barriers (sub-criteria) of knowledge management implementation in supply chain. The results of the proposed problems deal with four levels/stages in hierarchical structure. The overall purpose of multi-attribute decision process is to rank the barriers of KM adoption in SSC which is considered as the first stage of hierarchy. The major barriers category exist on the second stage, the sub barriers at third stage and prioritization in the fourth stage of hierarchy. After structuring the decision hierarchy the group was requested to provide inputs using triangular fuzzy numbers from the Table 1. The pair-wise comparison matrix of five major barriers and 22 sub-barriers was constructed. The arithmetic mean of these values are computed to obtained the pairwise comparison

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matrixes of criteria and sub-criteria. The results obtained from the calculations based on pairwise comparison matrixes. The consistency ratio (CR) of the entire matrix is less than 0.1, which shows that matrices are consistent. The barrier M1 was ranked at the highest level in adoption of KM in sustainable supply chain. The values of consistency ratio less than 0.1 shows that the responses taken from experts were highly consistent. Therefore, this data can be used for further analysis which has been given in Tables 4, 5, 6, 7, 8, 9. The final weights of criterion are given in Table 10. Furthermore, it is easier to conclude that managerial barrier have greater effect on decision-making process in food sector. The managerial barriers are followed by technological barrier, social barriers, which are followed by organizational barrier, and finally individual barriers have the least influence on the decision-making (Table 2 and 3). Table 1. Scale for relative importance used in the pairwise comparison matrix Intensity of importance

Fuzzy number

Linguistic variables

Triangular Reciprocal of fuzzy numbers TFNs (TFNs)

1

1

Equally important

(1, 1, 3)

(0.33, 1.00, 1.00)

3

3

Weekly important

(1, 3, 5)

(0.20, 0.33, 1.00)

5

5

Strongly important

(3, 5, 7)

(0.14, 0.20, 0.33)

7

7

Very strongly important

(5, 7, 9)

(0.11, 0.14, 0.20)

9

9

Extremely more important

(7, 9, 11)

(0.09, 0.11, 0.14)

Table 2. The random consistency index Size (n) 1 2 3 RI

4

5

6

7

8

0 0 0.52 0.89 1.11 1.25 1.35 1.4

Table 3. Fuzzy evaluation scores for alternative Linguistic variables Corresponding TFNs Very poor (VP)

(1, 1, 3)

Poor (P)

(1, 3, 5)

Medium (M)

(3, 5, 7)

Good (G)

(5, 7, 9)

Very good (VG)

(7, 9, 11)

When Barriers Need Attention Table 4. Pairwise comparison matrix of the major criterion C1 C1 1

C2 C3

C4

C5

7

3

9

5

C2 0.14 1 C3 0.2

0.33 0.33 5

3

1

C4 0.33 3

3

7

0.33 1

9

C5 0.11 0.2 0.14 0.11 1 Table 5. Pairwise comparison matrix of the managerial criteria M1

M2

M3 M4

M5

3

5

3

9

M2 0.33 1

5

3

3

M3 0.2

1

0.33 0.33

M1 1

0.2

M4 0.33 0.33 3

1

3

M5 0.11 0.33 3

0.33 1

Table 6. Pairwise comparison matrix of the organizational criteria O1 O1 1

O2

O3 O4

O5

O6

3

7

3

7

5

3

5

O2 0.33 1

5

3

O3 0.14 0.2

1

0.33 0.33 0.33

O4 0.33 0.33 3

1

3

3

O5 0.14 0.33 3

0.33 1

3

O6 0.2

0.33 0.33 1

0.2

3

Table 7. Pairwise comparison matrix of the technological criteria T1 T1 1

T2 T3 T4 3

7

0.33

T2 0.33 1

5

0.33

T3 0.14 0.2 1

0.11

T4 3

1

3

9

Table 8. Pairwise comparison matrix of the social criteria S1 S1 1

S2

S3

3

5

S2 0.33 1

3

S3 0.2

0.33 1

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I2 I3

I4

9

3

I2 0.11 1 I3 0.2

5

0.33 0.33

3

1

0.33

I4 0.33 3

3

1

Table 10. Weights of criteria and sub-criteria for implementation of KM initiatives Major criterion

Major criterion weight

Managerial

0.5154

Organizational

0.0783

Sub-criteria

Consistency ratio (CR)

M1

0.0901

Social

0.2174

0.1625

0.4826

0.2487

1

0.1284

2

M3

0.049

0.0252

11

M4

0.1447

0.0746

5

M5

0.0747

0.0385

8

O1

0.4308

0.0337

9

0.2448

0.0192

12

O3

0.0378

0.003

21

O4

0.1429

0.0112

15

O5

0.0858

0.0067

17

O6

0.058

0.0045

19

T1

0.0944

0.2838

0.0617

6

T2

0.1503

0.0327

10

T3

0.0412

0.009

16

T4

0.5247

0.1141

3

0.6378

0.1036

4

0.2577

0.0419

7

0.1045

0.017

13

0.596

0.0158

14

I2

0.0578

0.0015

22

I3

0.1166

0.0031

20

I4

0.2295

0.0061

18

S1

0.0749

0.0288

S3 0.0265

Ranking

0.2491

S2 Individual

Final weight

M2

O2

Technological

Ratio weight

I1

0.0562

Where CR ≤ 0.1

4

Policy Implications

This research study can be helpful for experts, stakeholders, Government officials, technocrats, and industry managers to identify the potential barriers they may encounter in implementing KM aspects in their SSC. In briefly speaking followings are the implications developed through this study as;

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i. Developing Strategic Plan in adoption of KM initiatives: It is very important for the organization to have a strategic plan devise the strategy in implementation of KM aspects in a SSC. Further, management solely not responsible to remove the organizational hurdles in KM initiatives but nonmanagerial staff should also understand the benefits of KM adoption in their organization for long time period. ii. Involving Government to Support Essence of KM adoption activities: From the perspective of sustainability, Governmental policies and incentives in terms of monetary as well as morally assistance can be very helpful for food businesses organizations to perform knowledge-sharing activities in the food industries. iii. Understanding of market dynamics and potential buyers: Several types of market factors and consumer dynamics are crucial in solving the problematic issues related to the markets scenarios and shareholders’ behaviors. This understanding will definitely facilitate organizations to adjust threshold for sustainable supply chain developments in food industry. iv. Analyzing the sense of coordination among SSC members: A lot of exogenous factors like market competition, vendors’ behavior and customer attitudes may exist with regard to KM initiatives in business. This study helpful for managers to evaluate barriers related to coordination with SSC partners’ efforts for successful accomplishment of KM aspects in a SSC. v. Awareness of employees and business-community for KM acceptance: This work also reveals significant scope to educate employees and the businesscommunity to accept KM initiatives in an industrial SSC. vi. Launching seminars and campaigns for KM implementation: This work may also assists managers to launch seminars and conduct campaigns’ to enhance KM implementation capabilities in an organization’s in line with sustainability. The present work provides guideline to enhance awareness level among employees for the adoption of KM aspects in business.

5

Concluding Remarks

Adoption of knowledge management in supply chain to overcome its barriers is very difficult process. The finding of the results revealed that the success ratio of knowledge management adoption in supply chain is low due to potential barriers. This study addressed the scrutinized barriers through scientific process by providing valuable suggestion in terms of ranks. After ranking the barriers, the next step is to eradicate the barriers one by one but it’s very difficult to overcome due to certain constraints in the organizations. This research study, focused to develop a scientific model to rank the barriers of KM adoption in supply chain by using a multi-attribute approach which is fuzzy AHP method. Experts’ opinions are always uncertain and vague in conducting the evaluations of criterion. That’s why fuzzy AHP technique is adopted to perform in fuzzy environment. The weights were utilized to form pairwise comparison matrices and rank the computation for prioritized barriers. The results of the research

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shows the feasibility of the proposed model in food sector. The result shows that development of managerial planning regarding knowledge management adoption in sustainable supply chain is the highest rank barriers. These ratings facilitates industries to make decisions regarding eradication of barriers one by one. Similar type of research study can be applied to the rest of industries of Pakistan namely textile, fiber, clothing, medicine, fertilizer, leather, sugar, seed and plastic etc. A comparative analysis between two or more industries can be conducted to assess the level of sustainable supply chain practices in Pakistan. This study was limited to few variables but in the future studies more variable sustainable supplier selection criteria, pollution and environmental, production and operational performance can be added. Some popular techniques like Decision Making Trial and Evaluation Laboratory (DEMATEL), Structural Equation Modeling (SEM), Analytic Network Process (ANP), fuzzy PROMETHEE, fuzzy TOPSIS, fuzzy ELECTRE, and fuzzy VIKOR can also be applied to check the robustness of proposed approach.

References 1. Attia, A., Essam Eldin, I.: Organizational learning, knowledge management capability and supply chain management practices in the Saudi food industry. J. Knowl. Manag. 22(6), 1217–1242 (2018) 2. Aydogan, E.K.: Performance measurement model for Turkish aviation firms using the rough-AHP and topsis methods under fuzzy environment. Expert Syst. Appl. 38(4), 3992–3998 (2011) 3. Aziz, N., Sparrow, J.: Patterns of gaining and sharing of knowledge about customers: a study of an express parcel delivery company. Knowl. Manag. Res. Pract. 9(1), 29–47 (2011) 4. Batista, L., Dora, M., et al.: Knowledge management for food supply chain synergies-a maturity level analysis of SME companies. Prod. Plann. Control 30(10– 12), 995–1004 (2019) 5. Ceptureanu, S.I., Ceptureanu, E.G., et al.: An exploratory study on knowledge management process barriers in the oil industry. Energies 11(8), 1977 (2018) 6. Cheung, C.F., Cheung, C., Kwok, S.: A knowledge-based customization system for supply chain integration. Expert Syst. Appl. 39(4), 3906–3924 (2012) 7. Dolgui, A., Tiwari, M.K., et al.: Optimising integrated inventory policy for perishable items in a multi-stage supply chain. Int. J. Prod. Res. 56(1–2), 902–925 (2018) 8. Dubey, R., Gunasekaran, A., Papadopoulos, T.: Green supply chain management: theoretical framework and further research directions. Benchmarking Int. J. 24(1), 184–218 (2017) 9. Emamisaleh, K., Rahmani, K.: Sustainable supply chain in food industries: drivers and strategic sustainability orientation. Cogent Bus. Manag. 4(1), (2017). Article Id 1345296 10. Gloet, M., Samson, D.: Knowledge management to support supply chain sustainability and collaboration practices. In: Proceedings of the 52nd Hawaii International Conference on System Sciences (2019) 11. Gunjal, B.: Knowledge management: why do we need it for corporates. Malaysian J. Libr. Inf. Sci. (2019). ISSN 1394-6234

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12. Hashim, M., Nazam, M., et al.: Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment. J. Ind. Eng. Manag. 10(2), 188–212 (2017) 13. Hassan, S., Al-Hakim, L.A.Y.: The relationships among critical success factors of knowledge management, innovation and organizational performance: a conceptual framework. In: International Conference on Management and Artificial Intelligence, vol. 6, pp. 94–103 (2011) 14. He, Q., Ghobadian, A., Gallear, D.: Knowledge acquisition in supply chain partnerships: the role of power. Int. J. Prod. Econ. 141(2), 605–618 (2013) 15. Huang, C.C., Lin, S.H.: Sharing knowledge in a supply chain using the semantic web. Expert Syst. Appl. 37(4), 3145–3161 (2010) 16. Hutzschenreuter, T., Horstkotte, J.: Knowledge transfer to partners: a firm level perspective. J. Knowl. Manag. 14(3), 428–448 (2010) 17. Ji, G., Gunasekaran, A., Yang, G.: Constructing sustainable supply chain under double environmental medium regulations. Int. J. Prod. Econ. 147, 211–219 (2014) 18. Kasper, H., M¨ uhlbacher, J., M¨ uller, B.: Intra-organizational knowledge sharing in MNCs depending on the degree of decentralization and communities of practice. J. Glob. Bus. Technol. 4(1), 59–68 (2008) 19. Kumar, V., Holt, D., et al.: Developing green supply chain management taxonomybased decision support system. Int. J. Prod. Res. 53(21), 6372–6389 (2015) 20. Li, X., Hu, J.: Business impact analysis based on supply chain’s knowledge sharing ability. Procedia Environ. Sci. 12, 1302–1307 (2012) 21. Lim, M.K., Tseng, M.L., et al.: Knowledge management in sustainable supply chain management: improving performance through an interpretive structural modelling approach. J. Clean. Prod. 162, 806–816 (2017) 22. Marra, M., Ho, W., Edwards, J.S.: Supply chain knowledge management: a literature review. Expert Syst. Appl. 39(5), 6103–6110 (2012) 23. N¨ atti, S., Ojasalo, J.: Loose coupling as an inhibitor of internal customer knowledge transfer: findings from an empirical study in B-to-B professional services. J. Bus. Ind. Mark. 23(3), 213–223 (2008) 24. Nazam, M., Xu, J., et al.: Risk evaluation of warehouse operations by using fmea and combined AHP-topsis approaches under fuzzy environment. Int. J. Dev. Res 5(4), 4328–4339 (2015) 25. Niemi, P., Huiskonen, J., Karkkainen, H.: Supply chain development as a knowledge development task. Int. J. Networking Virtual Organ. 7(2–3), 132–149 (2010) 26. Patil, S.K., Kant, R.: A fuzzy AHP-topsis framework for ranking the solutions of knowledge management adoption in supply chain to overcome its barriers. Expert Syst. Appl. 41(2), 679–693 (2014) 27. Saaty, T.L.: Analytic Hierarchy Process. McGraw Hill, New York (1980) 28. Saeed, M.A., Kersten, W.: Drivers of sustainable supply chain management: identification and classification. Sustainability 11(4), 1137 (2019) 29. Sambasivan, M., Loke, S.P., Abidin-Mohamed, Z.: Impact of knowledge management in supply chain management: a study in Malaysian manufacturing companies. Knowl. Process Manag. 16(3), 111–123 (2009) 30. Shujahat, M., Sousa, M.J., et al.: Translating the impact of knowledge management processes into knowledge-based innovation: the neglected and mediating role of knowledge-worker productivity. J. Bus. Res. 94, 442–450 (2019) 31. Winkler, H.: Closed-loop production systemsa la sustainable supply chain approach. CIRP J. Manuf. Sci. Technol. 4(3), 243–246 (2011)

118

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32. Wong, W.P., Wong, K.Y.: Supply chain management, knowledge management capability, and their linkages towards firm performance. Bus. Process Manag. J. 17(6), 940–964 (2011) 33. Wu, D.J.: Software agents for knowledge management: coordination in multi-agent supply chains and auctions. Expert Syst. Appl. 20(1), 51–64 (2001) 34. Yan, X.H., Ma, J.: Development of sustainable food supply chain. Int. J. Eng. Technol. 4(2), 166 (2012) 35. Yang, Z., Jiang, R.: Artificial neural network and its application in the performance evaluation enterprise knowledge management research. Guangxi Soc. Sci. 126, 58– 61 (2005). (in Chinese) 36. Yeo, R.K., Svensson, G., et al.: Knowledge sharing through inter-organizational knowledge networks. Eur. Bus. Rev. 22(2), 153–174 (2010) 37. Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965) 38. Zailani, S., Jeyaraman, K., et al.: Sustainable supply chain management (SSCM) in Malaysia: a survey. Int. J. Prod. Econ. 140(1), 330–340 (2012) 39. Zanoni, S., Zavanella, L.: Chilled or frozen? Decision strategies for sustainable food supply chains. Int. J. Prod. Econ. 140(2), 731–736 (2012) 40. Zhao, J., de Pablos, P.O., Qi, Z.: Enterprise knowledge management model based on China’s practice and case study. Comput. Hum. Behav. 28(2), 324–330 (2012)

Smart Farming: Intelligent Management Approach for Crop Inspection and Evaluation Employing Unmanned Aerial Vehicles Carlos Quiterio G´ omez Mu˜ noz1 , Christian Paredes Alvarez1 , and Fausto Pedro Garcia Marquez2(B) 1

2

Universidad Europea de Madrid, Madrid, Spain Ingenium Research Group, Castilla-La Mancha University, Ciudad Real, Spain [email protected]

Abstract. This work presents an unmanned aerial vehicle management platform encompassed in the concept of smart farming. Automates inspections of different crops and monitors the status of the plantation is done by IoT, analyzing an area on an online map that provides air and weather restrictions. Intelligent route management algorithms are employed to generate the optimal inspection route and waypoints, maximizing the multispectral images capture. These multispectral images can be subsequently processed according to algorithms based on phytosanitary index formulas and regressions obtained with artificial neural networks. Reports are generated with analysis of the results by this approach, for example: optimal collection time, water stress, maturity index, etc. Keywords: Smart farming · Non-destructive tests · Crop evaluation · Unmanned aerial vehicles · Route management · Multispectral images

1

Introduction

Agriculture is an essential sector for the economy, and it also affects the environment [3]. The sustainable economy is based mainly in sustainable agriculture [6]. The sector is moving towards specialization and an important technological development due to competitiveness at international level, the restrictions of water reserves, the needs of intensification of production and the adaptation to an increasingly restrictive environmental regulation. A sustainable economy model agriculture should consider new technologies that allow an efficient use of increasingly scarce resources to minimize the environmental cost, and at the same time to meet the needs of the population [1]. It requires to optimize the production while developing healthy ecosystems and supporting the sustainable management of land, water and natural resources, guaranteeing the satisfaction of the needs of both present and future generations. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 119–130, 2021. https://doi.org/10.1007/978-3-030-49889-4_11

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Within this context, precision agriculture is a fundamental part of sustainable agriculture and it is included in the called “Agriculture 4.0” [5,25]. It employs techniques for agri-food production that allow advantages of the available resources utilization, and avoid, or minimize, the production of toxic waste [14]. Precision agriculture allows to know where, how and when to apply the resources, and to obtain maximum benefits within a sustainable environment, knowing the current state of crops over the time. In this context, it is essential to have as much information as possible about crop parameters in order to obtain decisions that improve the quality and efficiency of production [9,19]. This data collection is usually done with ground level sensors, sensors attached to the plants or through the acquisition of multispectral aerial images of the crop field [11]. Aerial images are images obtained with special cameras sensitive to narrow bands of the electromagnetic spectrum. With this information is possible to perform an analysis to know the status of the crops and have a solid basis for decision making [10,15]. It is optimized the use of scarce resources, distribute the necessary products locally and, according to the needs at each point, to minimize waste by the appropriate preventive and corrective actions in each case [20]. In order to perform this aerial work, it is important to calculate an optimal route for the unmanned aerial vehicles (UAV) [4,13]. Due to the technological limitations of UAVs, such as battery capacity, maximum flight time, etc., it requires optimal routes to maximize the number of multispectral image capture with each UAV flight [8,23]. One of the main novelties of this paper regarding to other smart routes algorithms for UAVs is that it is specially designed for capturing multispectral images, which require to be captured in particular conditions to facilitate their subsequent processing [26]. The processing of these images, that usually have a low resolution, consists of joining them to generate a new larger image and facilitate the extraction of data from large regions. To perform these operations, it is necessary to set the same direction of the UAV in all waypoints. This direction will set the direction of the UAV advance and will generate a route composed of paths parallel to this direction. In addition, in order to facilitate its subsequent image processing, there will be an overlap of a certain percentage of common areas between captures of each waypoint.

2

Tessellation Algorithm of a Region and Calculation of the Optimal Route for the UAV

The flight mission encompasses all the procedures that are part of the calculation of the parameters that will be sent to the UAVs [12,21], therefore, it finds the points from which it will capture hyperspectral images that will subsequently be processed and analysed to find vegetation indices [17].

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It was defined two operations for the flight mission: (1) Flight height and distance between image capture points. (2) Calculation of spatial coordinates of image capture points. It is sought to tessellate any polygonal area by means of rectangles of fixed dimensions, which covers its surface and a part of the surrounding surfaces. These rectangles are suitable for tessellation, since they cover a plane when assembled one after the other, without overlapping or leading spaces between them. It is possible to use this algorithm with other geometric figures, such as regular hexagons. Given the n vertices of the closed and simply connected polygon that delimits the area to be explored, defined by its coordinates as the points Pi = (xi , yi ), where i = 1, 2, 3 . . . n. Then, it is chosen the maximum and minimum coordinates on each axis to obtain a quadrilateral that surrounds and contains the polygon by Eq. (1): xmin = min (xi ) ,

xmax = max (xi ) ,

ymin = min (yi ) , ymax = max (yi ) .

(1) Four points are defined that will be the vertices of the rectangle that will contain the original polygon, according to Eq. (2): P1r = (xmin , ymin ) P3r = (xmax , ymax )

P2r = (xmin , ymax ) . P4r = (xmax , ymin )

(2)

Figure 1 shows the dimensions of the rectangle formed by these four points given by Eq. (3): Lx = xmax − xmin ; Ly = ymax − ymin .

(3)

The dimensions on each axis of the polygon to test, and the distance between the barycenters of a polygon and the subsequent one in the tessellation, are defined. The dimensions of the rectangle are height a and base b, being the dimensions of the image to be captured by the camera. The vertical and horizontal distances between two centres of consecutive rectangles are a and b respectively. The minimum safety margins for image capture are expressed based on the dimensions of the rectangle where the tessellation is performed, according to Eq. (4): Mv = %mv · a , Mh = %mh · b

(4)

where the Mv and Mh are the vertical and horizontal overlapping margins. The rectangle that contains the area to study is enlarged with these overlapping margins. The new vertices are given by Eq. (5): P 1r = (xmin − Mh , ymin − Mv ) P 3r = (xmax + Mh , ymax + Mv )

 P 2r = (xmin − Mh , ymax + Mv ) . P 4r = (xmax + Mh , ymin − Mv )

(5)

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Fig. 1. Satellite image to tessellate an area: The area to explore (orange); the rectangle that contains the orange zone (blue)

The larger rectangle is divided into rectangles with the size of the image to bed captured, taking into account the overlapping margins by Eq. (6): V , a H n= , b

V = Ly + 2 · Mv ; m =

(6)

H = Lx + 2 · Mh ;

(7)

where n and m are integer values. It is obtained that the number of rectangles, i.e. images, necessary for tessellation, is n × m. To calculate the centre of each of them, the first point is defined by Eq. (8): Q1 = (Q1x ,

Q1y ) ,

(8)

where Qx1 = xmin − Mh + b,

(9)

Qy1 = ymin − Mv + b.

(10)

and

Equation (11) is employed to find the points matrix that determine the center of each of the rectangles that test the greater rectangle Fig. 2: Qm×n = (xmin + j.b,

ymin + k.h) ; Q = [Qm×n ] ,

being j = 0, 1, 2 . . . n and k = 0, 1, 2 . . . m.

(11)

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Fig. 2. Points and rectangles of the area to be analysed

A rectangle of size a is constructed from each of the generated points that will be the centers of each rectangles (Fig. 3). Its vertices are calculated by Eq. (12):     V1i = Qxi − 2b , Qyi − a2  , V2i = Qxi − 2b , Qyi + a2  (12) V3i = Qxi + 2b , Qyi + a2 , V4i = Qxi + 2b , Qyi − a2 and Vr = [V1 V2 V3 V4 ].

(13)

Fig. 3. Tessellated area. Red dots indicate the position where the UAV should be located to make the image capture

The rectangles that are totally or partially inside the polygon are checked to obtain the set of rectangles that make the tessellation of the original polygon. The approach verifies if at least one of the vertices is within the polygon and then, in this case, the rectangle belongs to the final tiling. The Ray Casting algorithm is used, which indicates that if an imaginary ray is thrown out of the point, and the number of intersections with the sides of the polygon is odd,

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the point is included in the polygon, otherwise it is outside the polygon [7]. In addition, this method was validated with the dominant point method [24]. When the rectangles are set as part of the tessellation, the Qt matrix is done considering the ordered central points. These points, size a × b, define where to place the camera to capture the image. The points are ordered to define an optimal route for the image capture by a UAV. An efficient route will be the set by minimizing the non-useful movement considering that the images captured by the UAV is maximised. A point sorting algorithm has been designed in this paper. The first point of the matrix Qt is chosen as the starting point, which is the southernmost and easternmost point of the Qt . All points that belong spatially to the first column of the Qt , i.e., all those that have the same x coordinate, are ordered in ascending ranking. Then, they are grouped in a vector, therefore, the UAV passes through all the column points consecutively from south to north. The points of the column to the right of the previous one are chosen and grouped in other vector, leading to the UAV moves all the points in an orderly way downwards, from north to south. Then, both vectors are concatenated, and the operation is repeated for the following columns alternately. That leads to the UAV passes through all the points of the matrix in an orderly manner and capturing images both back and forth. The non-useful flight time is that in which the UAV will pass from the last point of a column to the first point of the next column. This approach minimised the non-useful time, reducing the total flight time, and optimised the batteries. These ordered points will be in a list with the coordinates for waypoints, and it will be sent to the UAV. The units are necessary that will be the same to perform these calculations. However, the coordinates of the vertices of the area to be explored are usually given by a global positioning system (GPS), and the measurements of the images depend on the optical and geometric characteristics of the camera, i.e. in meters. This approach converts the meters into GPS coordinates employing the Haversine formula [2].

Fig. 4. Distance between two points of a sphere

The Haversine formula used in this approach allows to determine the shortest distance between 2 points belonging to a perfect sphere orthodromically (Fig. 4) given its longitudes and latitudes in GPS coordinates, without approximating

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the curvature between them. Since the Earth is a spherical flat at the poles and bulky at the equator, but with a flattening ratio of 1/298, the approximation to a sphere is accurate (with a maximum error of 0.5%). The Haversine formula is the most appropriate for short distances, but there are other mathematical methods to find orthodromic distance. The Haversine formula is expressed by Eq. (14):   d = haversin (ϕ1 − ϕ2 ) + cos (ϕ1 ) cos(ϕ2) haversin (λ1 − λ2 ) , haversin R (14) where: d: distance between points (in meters). R: radius of the sphere, i.e. the terrestrial sphere (in meters). ϕi : latitude of point i. λi : point length i. And the function of Haversine is defined by Eq. (15): α haversine (α) = sen2 . 2

(15)

Equation (16) is employed to calculate the distances between two points whose angle to the centre of the sphere is α: d = α · R.

(16)

Equations (17), (18) and (19) are employed to minimize the computational costs:     ϕ1 − ϕ 2 λ1 − λ2 a = sin2 + cos (ϕ1 ) cos (ϕ2 ) sin2 , (17) 2 2   2 (18) c = 2 · atan2 a2 , (1 − a) , d = R · c,

(19)

where R is the average radius of the earth, being in this case R= 6.371 × 106 m. The results show that when two pairs of points with a similar GPS coordinate differences are taken, but with different positions on the sphere, the distance between the points of each pair is not constant. In addition, neither vertical nor horizontal distances are proportional to each other, but also depend on the GPS coordinates of each pair of points. This is due to how GPS coordinates are defined, depending on the latitude and longitude at which the point is positioned on the sphere, see Fig. 5. The conversion factors of GPS coordinates to meters are not constant. They must be calculated from the particular position of the reference points, considering the difference between them. The Haversine’s formula is used horizontally

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Fig. 5. Latitude and longitude

and vertically to find the conversion factors of GPS coordinates to meters, calculating the correspondence between a degree and its distance in meters for the chosen point. For the x-axis, the conversion factor can be calculated from a reference point and other auxiliary point located at one degree horizontally. For the y-axis, it is calculated the conversion factor in a similar way, with one reference point and other located at one degree vertically. Therefore, for the horizontal and vertical distances between two points P1 and P2 , it is possible to use the Haversine formula, using two auxiliary points P2x and P2y , where: P1 = (ϕ1 , λ1 ), P2 = (ϕ2 , λ2 ), P2x = (ϕ2 , λ1 ), P2y = (ϕ1 , λ2 ). The Eqs. (20), (21) and (22) are obtained considering the previous points:   ϕ1 − ϕ 2 ax = sin2 , (20) 2   λ1 − λ2 , (21) ay = cos (ϕ1 ) cos (ϕ2 ) sin2 2   2 (22) ci = 2 · atan2 ai 2 , (1 − ai ) and the distances would be expressed by Eqs. (23) and (24): dx = cx · R,

(23)

dy = cy · R,

(24)

where dx is the horizontal distance between P1 and P2 and dy is the vertical distance between P1 and P2 . The conversion factors for the area over which the tessellation process is being carried out is calculated considering the as reference. With these factors, it is converted the dimensions of the rectangle to degrees by Eqs. (25) and (26): a , dy b b (GP S) = . dx a (GP S) =

(25) (26)

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Fig. 6. Perimeter of the polygon to be inspected. In red, the optimal route that the UAV will follow within the polygon to obtain multispectral images

3

Flight Cycle

The maximum distance the UAV can travel is considered to set the flight cycles when the optimal route of the UAV flight has been found (done according the approach showed in Sect. 2). The flight cycle is defined as the route taken by the UAV from an initial point, the points that are part of the route of the optimal route and the return to the initial point. The distance travelled must be less than the maximum distance that the UAV can flight. The points to visit in each cycle are a subset points where the route, which is not repeated in different cycles, has the same start and end points for all cycles, chosen arbitrarily due to their proximity to the control posts. It simplifies the work of a UAV operator. Therefore, the operator chooses a point for the landing of the UAV that is more appropriate for the change of batteries, etc. [16]. The maximum distance is found by the maximum flight time with the battery fully charged [22]. Although it is not an exact value, the result is close to the real value. The maximum distance must be more than the distance between points of the optimal route. Possible disturbances that affect the calculation of this value are generally environmental, e.g. wind speed and direction and ambient temperature, etc. [18]. Usually, the maximum flight time is reflected in the UAV specifications, which allows a first conservative approach that can be adjusted experimentally. The geolocation of the UAV through GPS coordinates has been considered to calculates flight cycles. These coordinates are not absolute but depend on the location of the area to be explored within the globe, and, because of maximum flight distance can be expressed in meters, the relation between the two coordinate systems is found. A heuristic approach that requires less processing cost has been chosen referring to an arbitrary point of origin, although the exact position in meters of each point could be calculated and placed in a position matrix. The maximum

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distance (given in meters) is converted to a GPS coordinate differential, using the conversion factor presented by the most unfavourable scenario, i.e. the maximum between both factors. This method reduces the accuracy of the procedure but generates less computational cost. The maximum distance between GPS coordinates will be employed in an algorithm to calculate the theoretical distance travelled by the UAV between the points of the optimal route. The distance to the first point of the route is calculated from the starting point. The accumulated distance is also calculated as it advances through the optimal route, and the instantaneous return distance and the total distance is compared with the maximum distance. The return distance is a distance that depends on the last point of the optimal route before returning to the base. In some cases, it is an important value, depending on the geometric shape of the area to be analysed and its size, or the size of the images to be captured. In addition, it is a variable value that depends on the last position. For this reason, the calculation of the distances and their verification is done at each of the points. For example, let Ps be the initial point and Pi the points within the optimal route, i = 1, 2, 3 . . . n. Initially, only with P1 (the first point) the outward distance (distance between Ps and P1 ), the distance between travelled points and the return distance (distance between P1 and Ps ) are calculated. If the total distance is less than or equal to the maximum distance, then it continues to the next point. In the next loop, the distance travelled will be the distance between points P1 and P2 , and the return distance will be the distance between P2 and Ps . In the third loop, the distance between points is the accumulated distance: distance between P1 and P2 plus the distance between P2 and P3 , and the return distance will be the distance between P3 and Ps . If the distance is less than the maximum distance, the points are saved in a vector that will define the cycle. If the distance is greater, the cycle is defined with the vector of accumulated points, the vector is stored in a matrix for later use, the cycle counter is increased, and the current position is saved as the start of the next cycle.

4

Conclusions

An algorithm has been developed to manage unmanned automatic vehicles (UAV) routes efficiently focused on multispectral imaging. The objective is to acquire multispectral images to be subsequently joined to create a larger image. This method ensures that the UAV travel the maximum distance, according to the parameters of the camera. The input data are the vertices of an irregular polygon that forms the area. A field of view and a specific height will be obtained regarding to the parameters of the camera and the desired ground distance sample. A solution has been developed for interruptions in the inspection of large areas due to the limitations of UAV batteries. An algorithm has been created that dynamically checks the maximum points it can travel based on the characteristics of the flight, battery, distance between points, etc. It allows as many

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autonomous missions as necessary to be generated independently. It has been designed in such a way that the UAV returns to the starting point between the different missions. It leads that the operator can change the batteries and continue with the next flight. This novel intelligent management approach for agricultural purposes leads to enhance precision agriculture, as well as minimize production costs and manage crops in an efficient manner. The approach considers the following restrictions for multispectral images: Have a common area (in %) in both x and y directions to join the images; Perform the least number of waypoints; Travel odd rows in one direction and even rows in another to optimize the flight, etc; Move in a straight line between the end of row points and start of the next to optimize the route. Acknowledgements. The work reported herewith has been financially by the Direcci´ on General de Universidades, Investigaci´ on e Innovaci´ on of Castilla-La Mancha, under Research Grant (Ref.: SBPLY/19/180501/000102).

References 1. Borlu, Y., Glenna, L.: Environmental concern in a capitalist economy: climate change perception among US specialty-crop producers. Organ. Environ., 1086026618897545 (2020) 2. Chopde, N.R., Nichat, M.K.: Landmark based shortest path detection by using A* and Haversine formula. Int. J. Innov. Res. Comput. Commun. Eng. 1(2), 298–302 (2013) 3. De Janvry, A., Sadoulet, E.: How experimental research in agriculture has gone from lab to field. World Dev. 127(104), 782 (2020) ´ 4. Herraiz, A.H., Marug´ an, A.P.: Remotely operated vehicle applications. In: Nondestructive Testing and Condition Monitoring Techniques for Renewable Energy Industrial Assets, pp. 119–132 (2015) 5. Klerkx, L., Rose, D.: Dealing with the game-changing technologies of agriculture 4.0: how do we manage diversity and responsibility in food system transition pathways? Glob. Food. Secur.-Agric. 24, 100–347 (2020) 6. Lee, S.: Role of social and solidarity economy in localizing the sustainable development goals. Int. J. Sustain. Devel. World Ecol. 27(1), 65–71 (2020) 7. Ma, T., Li, P., Ma, T.: A three-dimensional cartesian mesh generation algorithm based on the GPU parallel ray casting method. Appl. Sci. 10(1), 58 (2020) 8. M´ arquez, F.P.G.: An approach to remote condition monitoring systems management. In: IET International Conference on Railway Condition Monitoring (2006) 9. M´ arquez, F.P.G., Mu˜ noz, J.M.C.: A pattern recognition and data analysis method for maintenance management. Int. J. Syst. Sci. 43(6), 1014–1028 (2012) 10. M´ arquez, F.P.G., Pardo, I.P.G.: Principal component analysis applied to filtered signals for maintenance management. Qual. Reliab. Eng. Int. 26(6), 523–527 (2010) 11. M´ arquez, F.P.G., Pedregal, D.J.: Applied RCM 2 algorithms based on statistical methods. Int. J. Autom. Comput. 4(2), 109–116 (2007) 12. M´ arquez, F.P.G., Ram´ırez, I.S.: Condition monitoring system for solar power plants with radiometric and thermographic sensors embedded in unmanned aerial vehicles. Measurement 139, 152–162 (2019)

130

C. Q. G´ omez Mu˜ noz et al.

13. M´ arquez, F.P.G., Pardo, I.P.G., Nieto, M.R.M.: Competitiveness based on logistic management: a real case study. Ann. Oper. Res. 233(1), 157–169 (2015) 14. Marug´ an, A.P., M´ arquez, F.P.G.: Advanced analytics for detection and diagnosis of false alarms and faults: a real case study. Wind Energy 22(11), 1622–1635 (2019) 15. Marug´ an, A.P., M´ arquez, F.P.G., Lev, B.: Optimal decision-making via binary decision diagrams for investments under a risky environment. Int. J. Prod. Res. 55(18), 5271–5286 (2017) 16. Moraleda, V.B., Marug´ an, A.P., M´ arquez, F.P.G.: Acoustic maintenance management employing unmanned aerial vehicles in renewable energies. In: International Conference on Management Science and Engineering Management, pp 969–981. Springer (2018) 17. Mu˜ noz, C.Q.G., Gonzalo, A.P., et al.: Online fault detection in solar plants using a wireless radiometer in unmanned aerial vehicles. In: International Conference on Management Science and Engineering Management, pp. 1161–1174. Springer (2017) 18. Mu˜ noz, C.Q.G., Jim´enez, A.A., M´ arquez, F.P.G.: Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis. Renew. Energy 116, 42–54 (2018) 19. Pedregal, D.J., Garc´ıa, F.P., Roberts, C.: An algorithmic approach for maintenance management based on advanced state space systems and harmonic regressions. Ann. Oper. Res. 166(1), 109–124 (2009) 20. Pliego, A., M´ arquez, F.P.G.: Big data and web intelligence: improving the efficiency on decision making process via BDD. In: Big Data: Concepts, Methodologies, Tools, and Applications, pp. 229–246. IGI Global (2016) 21. Ram´ırez, I.S., Marug´ an, A.P., M´ arquez, F.P.G.: Remotely piloted aircraft system and engineering management: a real case study. In: International Conference on Management Science and Engineering Management, pp. 1173–1185. Springer (2018) 22. Ram´ırez, I.S., S´ anchez, P.J.B., et al.: Autonomous underwater vehicles inspection management: optimization of field of view and measurement process. In: 13th International Conference on Industrial Engineering and Industrial Management, Servicio de Publicaciones de la Universidad de Oviedo (2019) 23. Segovia, I., Pliego, A., et al.: Optimal management of marine inspection with autonomous underwater vehicles. In: International Conference on Management Science and Engineering Management, pp. 760–771. Springer (2019) 24. Wu, W.Y.: Dominant point detection using adaptive bending value. Image Vis. Comput. 21(6), 517–525 (2003) 25. Zaman, N., Seliaman, M.E., et al.: Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence. Information Science Reference, Pennsylvania (2015) 26. Zheng, C., Li, L., et al.: Evolutionary route planner for unmanned air vehicles. IEEE Trans. Rob. 21(4), 609–620 (2005)

Learning Resource Management from Investigating Intrinsic Motivation in Various Learning Environments Elena Railean1(B) , Victoria Trofimov2 , and Daiva Aktas3 1

2

American University of Moldova, Chi¸sin˘ au, Moldova [email protected] University of European Political and Economic Studies “Constantin Stere”, Chi¸sin˘ au, Moldova 3 Vilniaus Kolegija University of Applied Sciences, Vilnius, Lithuania

Abstract. The puzzle of whether psychological issues are improving or harming resource management has been plaguing researchers for decades. Derived from the metasystems learning design theory, this study argued that studying intrinsic motivation in the diversity of learning environments improves our understanding of the state-of-art in the frontier area of psychology and resource management. To test this hypothesis, first, it was generalized motivation theories; then, it highlighted the scope of the Metasystems Learning Design Theory and, finally, developed an online survey using Google Drive. Data were collected from 114 respondents physically located in various countries. Our results confirmed a strong scientific bridge between intrinsic motivation and lifelong learning within the scope of resource management. Thus, all our respondents live in the diversity of learning environments, and most of them identify themselves as explorers, researchers, and observers. Their main motivation to be in the diversity of learning environments is argued by visiting new places and exploring new cultures. The principal external source of motivation is to achieve higher status in a job, secure professional advancement, and stay abreast of competitors. Moreover, motivation is not only about the power to control some aspects of human work, but also about the motivation of employees to manage their life evaluated as successful adaptation of employees or/and organisation at environmental challenges. Most young people possess a visual learning style. Future works of our research group will develop the metasystems learning design theory of motivation to work in a challenging world using as the baseline the survey format presented in this article. Keywords: Resource management · Organisational psychology Motivation theories · Intrinsic motivation · Feedback · Learning environments

c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 131–142, 2021. https://doi.org/10.1007/978-3-030-49889-4_12

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Introduction

Currently, research in resource management highlights the importance of intrinsic motivation for understanding the motives to work of employees. The relatively little investigation of the employees’ motivation has explored only “the surface area” of the motivation theories and their use in the science of resource management. Historically, this scientific problem arose in the XIX century when psychological issues became important in project management. Thus, in 1832 in the book “On the Economy of Machinery and Manufacture” Charles Babbage noted that people are crucial to the success of an organization. In developing the principles of scientific management, Frederick Taylor wrote that employee satisfaction is the best way to increase productivity. This idea was argued by Lillian Moller Gilbreth in “Psychology in the Workplace”, where she considered the benefits of psychology in scientific management [25]. Gilbreth believed in increasing the efficiency of each employee, and the organization, as a whole as the main driver of increasing profit of organization and employee satisfaction. Today, there is much to admire in the Gilbreths’ works. “The ‘Mother of Industrial Engineering,’ industrial psychologist and engineer Lillian Moller Gilbreth combined the social sciences with the mathematical and physical sciences in the formative days of industrial engineering” [24]. Moreover, Gilbreth anticipated Maslow’s Need Hierarchy Theory [12]. Until now, the psychology of intrinsic motivation has been a loosely defined field, but with many white spots. Thus, as was noted by [10], the actions and the behavioral outcome within work are determined by the person’s effort (the motivation factor), cognition (the emotional factor) and the ability to perform tasks (the social factor), but in general, by the capacity of the person to understand the situation. Human capital is the most important factor in sustaining business success. This statement proves the Gilbreth’s theory of motivation. However, the most accepted theories in resource management are the “Expectancy-value Theory” [23] and “Hull’s Drive-Reduction Theory” [14]. The first theory states that there are expectations as well as values or beliefs that affect subsequent behavior. The second theory tried to explain behavior through drive reduction (i.e. the drive is an incentive form of a biological need). Moreover, there are many contradictions between these theories [6]. The first contradiction is in theoretical focus (i.e. the “expectancy-value theory is a developmental theory” [19], while the drive-reduction theory is “an external display of human desire to satisfy his physical deficiencies” [1]. Nevertheless, have been theories are cited in resource management. In higher educational settings, the specialists in resource management are less interested in the intrinsic motivation of actors in design of educational processes (especially professors and students). However, it is well known that experts and novices differ in how they are motivated to learn in the diversity of learning environments. Their ability to self-regulate learning illustrates two important features of resource management: motive and intrinsic motivation. Therefore, experts (that are professors) are motivated to learn in both formal and non-

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formal environments, while developing expertise requires understanding why to learn in a diversity of learning environments. It is important to investigate the state-of-art of intrinsic motivation theories in the diversity of learning environments to understand the actual role of psychology in resource management. At present, as was noted by [14], any consensus on a single unitary definition of the construct of motivation, derived from the Latin words movere and motivus, is lacking in the psychological community. Motivation is viewed as a process in which a bodily need is evident. According to the above-mentioned theories, motivation is an active movement of an individual initiated by a stimulus and, therefore, the activity of a drive will evoke motivation. This study investigates the affordability of the motivation theories from the perspectives of teachers and students physically located in various learning environments. Using a holistic approach, we try to address the constraints of the actual theories of motivation in educational settings and to evidence the actual impact of the psychology on resource management. It should be noted that differences between drive and motivation in actual motivational theories are deeper than in the time of Hull’s Theory. In sum, the article aims to answer the research question: What are the elements of the scientific bridge between organisational and resource management?

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Theoretical Background

This study uses motivation theories (MT) as on operational framework to develop the metasystems learning design theory of motivation (MLDTM). The MT pattern supports the classical resource management approach on the connection between drive theory and theoretical investigations of intrinsic motivation and explains the ability of experts and novices to work and learn continuum in a diversity of learning environments. The novelty of MLDTM consists of the affordability of the concept “metasystem”, which is more than a system of systems. 2.1

Delimiting the Motivation Theories Used in Educational Organisations

A motive is what prompts a person to act in a certain way. There are various theories of motivation applied to resource management of educational organisations. There are four most used theories: • • • •

Maslow’s need hierarchy Theory; Herzberg’s motivation-hygiene theory; McClelland’s need theory; Leib’s theory of six sources of motivation for adult learning.

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One of the most cited is Maslow’s deed hierarchy theory, which states that people have five types of needs and that these are activated hierarchically. “According to Maslow, you need to know where a person is on the hierarchical pyramid to motivate him/her” [13]. Critics of Maslow have argued that neither people nor situations in which they live and work are not alike. According to [26], motivation is an important part of human resource management, a baseline of employees’ enthusiasm and creativity, and a key link to the organization of organizational goals. Instead of Maslow, Herzberg’s motivation-hygiene theory focuses on factors that caused positive and negative job attitudes. In this opinion, the motivation factors leading to job satisfaction and job dissatisfaction. Thus, the job satisfaction is “as an outgrowth of achievement, recognition (verbal), the work itself (challenging), responsibility, and advancement (promotion)” [17]. Thus, one could observe that the basic needs to work effectively relate to intrinsic motivation (e.g. personal growth and self-actualization). In contrast, job dissatisfaction results from other factors (e.g. job security, salary, physically working conditions, interpersonal relations, etc.). Removing job dissatisfaction factors cannot be relied upon to generate a high level of performance. McClelland’s Need Theory states that every person has its own drivers for motivation. For example, “when a need is strong in a person, its effect is to motivate the person to use behavior which leads to satisfaction of the need” [18]. Motivation gives direction and intensity to human behavior. In McGregor’s participation Theory, this statement lines the main idea of the book “The Human Side of Enterprise”. According to McGregor [2], people’s intrinsic motivation to work relies on three needs: achievement, power, and affiliation. Thus, achievement represents the drive to excel, to achieve with a set of standards, to strive and succeed; the drive of power is concerned with making an impact on others, the desire to influence others, the urge to change people, and the desire to make a difference in life. The drive of affiliation, similar to Maslow’s concept of self-actualization, is a desire to establish and maintain friendly and warm relations with other people. However, there are multiple sources of motivation: personal motivation, personal ability, social motivation, responsability and social ability, structural motivation, and structural ability [3]. The above mentioned and many other theories of motivation can be applied to the organizational setting to explain the motivational aspects of employees’ performance (i.e., autonomy, wellbeing, feedback, and responsibility). The motivational aspects of employees’ performance are best described in the Leib’s theory of six sources of motivation for adult learning. 2.2

Toward a Metasystems Learning Design Theory of Motivation to Work in Challenging World

The metasystems learning design theory states that intrinsic motivation depends on the abilities of adaptive critical thinking related to changing situations, working in the challenging environment of multitasking and effectively apply the

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metacognitive strategies [21]. The intrinsic motivation of the employees drives work into an open learning environment, where is periodically an emergence of new artifacts that could influence the state of social equilibrium. Thus, intrinsic motivation correlates with the dynamic equilibrium between external and internal factors and their impact on mind and behavior. Openness, as the main driver of actual educational systems, implies selfdirected working and development of professional competencies in a diversity of learning environments. To prove the idea it was decided to model a situation in which respondents who are located will share their opinions regarding the issues and affordability of the intrinsic motivation for employees.

3 3.1

Methodology and Data Collection Problem Statement

The focus of our research is on the humanistic theories of intrinsic motivation. The special focus is Leib’s theory of six sources of motivation for adult learning [15]. This theory states that there are six external sources of motivation: a) social relationships, b) external expectations, c) social welfare, d) personal advancement, e) escape/stimulation, and j) cognitive interest. We choose this theory because of its suitability to the world of lifelong learning, which is open, complex and multidimensional. We also, allow our respondents to choose one from five types of behavior: a) observer, b) researcher, c) interpreter, d) explorer and e) transformer. It is important to investigate the scope of self-regulated learning concerning intrinsic motivation and the impact of learning style on intrinsic motivation. Moreover, in this work, we have tried to check whether a methodology based on the Google Form online questionnaire is sufficient to achieve an understanding of how employees perceived intrinsic motivation in diversity of learning environments. The objectives of this research were: • Objective 1: Design and develop an online questionnaire based on understanding the specific features of intrinsic motivation derived from the metasystems learning design theory for respondents physically located in various learning environments. • Objective 2: Collect, analyse, interpret data, and make relevant conclusions. Based on the proposed objectives the following hypothesis has been formulated: studying intrinsic motivation in a diversity of learning environments will improve our understanding of the frontier area between psychology and management. 3.2

Modeling and Solution

The modeling approach is based on the metasystems learning design [22]. The cross-sectional survey design method was adopted for the study of intrinsic motivation in a diversity of learning environments. This design enables a large amount

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of data to be gathered at one time and provides an opportunity for eliciting a greater understanding of the phenomenon under study, which in this case are the opinions of respondents who are physically located in various learning environments, regarding the affordability of motivation theory in resource management. In this study, the respondents’ experience of intrinsic motivation is the dependent variable, manipulated by us to understand future trends in motivation theory. The solution of online survey results from the answers of 114 respondents. The majority of respondents were from Lithuania (64.9%). Other respondents are from the Republic of Moldova (11.4%), Croatia (7.9%), Russian Federation (5.3%), and other countries. The age of respondents varied from less than 25 years old (73.7%) to 25–39 years old (9.6%), 40–59 years old (12.3%), and 60+ (4.4%). To understand the intrinsic motivation related to travel in diverse learning environments it was proposed the question: How often do you travel abroad in the last ten years? The answers show that all respondents have experience of traveled abroad. However, young people like to travel more. Most of the young people travel between “at least once a year” (26.3%) and “more than twice per year” (25.4%). Moreover, the most response (88.6%) agreed that an innovative model of resource management describes people who take on their responsibility to renounce traditional values, to educate and re-educate themselves to become an ambassador of peace.

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Case Study

We expect that the majority of respondents are global citizens. To prove the meaning of this term, we offer the possibility choosing one answer from understanding that a global citizen is: a) “aware of the wider world and has a sense of their role as a world citizen” [9]; b) “able to learn, live and function in an increasingly interconnected world” [16]; c) competent in understanding, communicating with, relating to, and working with people from different ethnic, political, socio-economic and religious backgrounds in a highly interdependent world; d) the citizen who has respects for other cultures and values, are tolerant for ambiguity and cultural self-awareness, etc. The majority of respondents chose the last option. Our first remark is that users of intrinsic motivation to be a global citizen are so broad that they need to be further investigated. This remark is based on the following data: a) 9.6%; b) 19.3%; c) 21.9% and d) 49.1%. One could observe that half of the respondents (50%) considered that it is very important to learn in the diversity of learning environments. 4.1

Motivation to Self-regulate Learning in a Diversity of Learning Environments

To investigate the intrinsic motivation to learn in the diversity of learning environment it was proposed the following question: What type of Social Media

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tools do you frequently use to socialize? The Results show that most of the respondents use Facebook (Fig. 1).

Fig. 1. Rating of Social Media tools to socialize in the diversity of learning environments

4.2

Motivation to Live and Learn in a Multi-dimensional World

The world is multi-dimensional, sensuous, and spatially complex [11]. Living in a multidimensional world involves the adoption of one priority state of mind and behavior. Let us observe that social psychology describes the following types of behavior: observer; researcher; interpreter; explorer and transformer. An observer is a person who “tends toward thinking, caution, circumspection, reticence, and figuring things out” [7]; the researcher is someone who conducts research; the interpreter is someone to interpret the beauty of the world (e.g. painter, singer, etc.); and the explorer – the someone who travels to places where no one has ever been to find out what is there. The most “innovative” type of behavior is the transformer. The meaning of the transformer can be extracted from cultural resource management “transformers are believed to be spirit-beings capable of transforming themselves into stone” [4]. This result validates the following statement “each of us lives in a constantly changing private world, which he called the experiential field. Everyone exists at the center of their experiential field, and that field can only be fully understood from the perspective of the individual” [19]. The results are provided in Fig. 2. We mention that most of the respondents (46.5%) were explorers. The next question was on motivation to explore the beauty of the world, as described in [21]. The structure of the question is: “In your opinion why it is important to be in diversity of learning environments (e.g, e-learning, virtual learning, digital learning, non-formal learning, etc.)”. Our participants validated the idea that intrinsic motivation is a drive of extrinsic motivation that allows them, first of all, to visit new places and to explore new cultures. The results of our respondents are provided in Fig. 3.

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Fig. 2. Perception of those living in a variety of learning environments

Fig. 3. Motivation to be in a diversity of learning environments

4.3

External Sources of Motivation

According to Leib (1991) [27], there are six sources of motivation for adult learning. Our question is: What is, in your opinion, the highest source of motivation? The respondents select one response: • Social relationships: to make new friends, to meet the need for associations and friendships. • External expectations: to comply with instructions from someone else; to fulfill the expectations or recommendations of someone with formal authority. • Social welfare: to improve the ability to serve mankind, prepare for service to the community and improve the ability to participate in community work. • Personal advancement: to achieve higher status in a job, secure professional advancement, and stay abreast of competitors. • Escape/Stimulation: to relieve boredom, provide a break in the routine of home or work, and provide a contrast to other exacting details of life. • Cognitive interest: to learn for the sake of learning, seek knowledge for its own sake, and to satisfy an inquiring mind [5]. As can be seen in Fig. 4 the personal advancement is the best choice (31.6%).

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Fig. 4. Personal advancement in intrinsic motivation

4.4

Impact of Intrinsic Motivation to Self-regulated Learning

According to Rogers’s study, when learners have control the nature, timing, and direction of the learning processes, the enter experience is facilitated [20]. This idea could be associated with the structure of self-regulated learning. If so, the respondents need to choose one of the four ideas, as presented in Fig. 5.

Fig. 5. Three components of self-regulated learning

This result allows us to note that motivation in resource management is not only about the power to control some aspects of human work, but also about the motivation of employees to manage life evaluated as the successful adaptation of employees or/and organisation at environmental challenges. With this result captured, we next turn to think of how learning style influences the intrinsic motivation. The last question aimed to ascertain what preferred respondents physically located in a diversity of learning environments in the matter of learning style.

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The Impact of Learning Style on Intrinsic Motivation

According to Russell’s study, most of us develop a preference for the learning style that was developed in childhood and, therefore, the learning style can be considered as the “childhood learning patterns” [8]. We asked our respondents to choose one of the most studied learning styles. Results of the study are presented in Fig. 6.

Fig. 6. Scope of learning styles

There are three types of learning styles (i.e., visual, auditory, and kinesthetic). The data proved that most respondents are visual (55.3%). This is indicative of acceptance of the digital learning environment since childhood and, therefore, most of our respondents are young people (i.e., 82.3%, as is reported in an online survey). Thus, the possessors of visual learning style prefer using images, pictures, colours, and maps to organise information and communicate with others.

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Conclusions and Future Directions

This article has demonstrated a metasystems approach for understanding the impact of intrinsic motivation on resource management. Beginning with the summarization of motivation theories and continuing through modeling an online questionnaire using Google Forms, the authors evidence a strong correlation between intrinsic motivation and resource management. Our investigation allows us to receive the first data and to make relevant conclusions. The project will continue along two pathways. We will continue to investigate the scope of motivation theories and the hierarchy of core concepts. We will also advance our understanding of intrinsic motivation from the perspective of the Metasystems Design Theory. Acknowledgments. Thanks to all professors and students from around the world who helped us complete the online questionnaire and receive valuable data.

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References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

11.

12.

13. 14. 15. 16. 17. 18.

19.

20. 21. 22. 23.

24.

Drive-reduction theory (2020) McClelland’s need theory (2020) Six sources of influence: structural motivation and ability (2020) The Xaxli’p transformer rock: transforming the way we approach cultural resource management (2020) Allen, C.: The balance of personality. Creative commons attribution-non commercial-share alike 4.0 international license (2020) Atkinson, J.W.: An Introduction to Motivation (1964) Berezin, R.M.: Are you a participant or are you an observer? (2014) Bradley, R.H., Pennar, A.L., et al.: Changes in the organization of paternal behavior during early and middle childhood. Parenting, 1–27 (2020) Brigham, M.: Creating a global citizen and assessing outcomes. J. Glob. Citizensh. Equity Educ. 1(1), 15–43 (2011) Carrim, N.M.H.: Entering a new world: the identity work of older South African Indian male entrepreneurs in the digital era. In: Disruptive Technology: Concepts, Methodologies, Tools, and Applications, pp. 125–147. IGI Global (2020) Harris, T.M.: Multidimensional mapping and spatial communication through the virtual umwelt. In: Handbook of the Changing World Language Map, pp. 3703– 3718 (2020) Kalitanyi, V., Goldman, G.A.: Human capital management in the fourth industrial revolution. In: Human Capital Formation for the Fourth Industrial Revolution, pp. 100–126. IGI Global (2020) Kaur, A.: Maslow’s need hierarchy theory: applications and criticisms. Glob. J. Manag. Bus. Stud. 3(10), 1061–1064 (2013) Kirsch, M.: On the abilities of unconscious freudian motivational drives to evoke conscious emotions. Front. Psychol. 10, 470 (2019) Lieb, S., Goodlad, J.: Principles of adult learning (2005) Luo, W.A.: Enhancing global education in China-a global citizen language program (2017) Miner, J.B.: Organizational Behavior: Essential Theories of Motivation and Leadership, vol. 1. ME Sharpe, New York (2005) Pardee, R.L.: Motivation theories of Maslow, Herzberg, McGregor & McClelland. A literature review of selected theories dealing with job satisfaction and motivation (1990) Petersen, J., Hyde, J.S.: Gender-related academic and occupational interests and goals. In: Advances in Child Development and Behavior, vol. 47, pp. 43–76. Elsevier (2014) Pindur, W., Rogers, S.E., Kim, P.S.: The history of management: a global perspective. J. Manag. History (1995) Railean, E.: Metasystems Learning Design of Open Textbooks: Emerging Research and Opportunities: Emerging Research and Opportunities. IGI Global (2018) Railean, E.A.: Impacts of digital revolution on learning. In: User Interface Design of Digital Textbooks, pp. 1–22. Springer (2017) Schnettler, T., Bobe, J., Scheunemann, A., et al.: Is it still worth it? Applying expectancy-value theory to investigate the intraindividual motivational process of forming intentions to drop out from university. Motiv. Emotion, 1–17 (2020) Tietjen, J.S.: Lillian Moller Gilbreth: an industrial engineering pioneer. In: Women in Industrial and Systems Engineering, pp. 3–23. Springer (2020)

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25. Witzel, M.: Fifty Key Figures in Management. Routledge (2003) 26. Yu, M.: On the application of incentive mechanism in human resource management. Reg.-Educ. Res. Rev. 1(2), 1–5 (2020) 27. Lieb, S.: Principles of adult learning. Phoenix, AZ: Vision-South Mountain Community College (1991)

Risk Management - Performing Instrument in The Development of Economic Expertise Gheorghe Avornic1 and Cristina Copˇ aceanu2(B) 1

University of European Political and Economic Studies, “Constantin Stere”, Chisinau, Republic of Moldova 2 Faculty of Economics and Ecology, University of European Political and Economic Studies, “Constantin Stere”, Moscow, Russia copaceanu [email protected] Abstract. The article represents the results of the risk management research in the process of carrying out the judicial and extrajudicial economic expertise. The actuality of the research derives from the current needs of information and study in the field of economic expertise, which requires a modern approach, so the authors decided to approach the economic expertise from the perspective of risk management. The scientific methods used by the authors: analysis and synthesis, induction and deduction, comparison, reasoning, as well as the table method. The results obtained from the research carried out by the authors consist of the need to implement the internal management control, with emphasis on risk management, elaboration of a methodology on risk management, as well as the implementation of the risk management cycle in the activity performed by the experts. In conclusion, the authors mention about the need to raise awareness of the importance of risks by all the actors involved in the process of conducting economic expertise. Keywords: Judicial and extrajudicial economic expertise management · The risk register

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Introduction

The research of the risk management in the process of carrying out the economic expertise, derives from the following causes: currently, economic crises are developing extremely rapidly and aggressively, a process that is becoming increasingly difficult to control in all national and international economic systems, having a direct impact on global economic sustainability; the courts do not deal with the large number of cases; the processes in the economic-financial field are complex and lasting; alternative dispute resolution between the parties; adapting litigation to economic crises; the judicial economic expertise carried out is delayed for a long period, due to the lack of specialists in the field; alternative dispute resolution between the parties; adapting litigation to economic crises; economic and c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 143–153, 2021. https://doi.org/10.1007/978-3-030-49889-4_13

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financial crises directly affect the process of carrying out the economic and first of all the judicial expertise; the importance of risk management in the context of risk mitigation in the process of carrying out economic expertise: judicial and extrajudicial. Currently, the issues of economic judicial expertise, financial audit and accounting are the subject of in-depth research at the level of accountants and auditors, theorists and practitioners, as well as the regulatory bodies in the field, which are obliged to provide prompt solutions to the company’s demands. The current needs for information and study in the field of economic expertise are gaining new dimensions, and this in turn implies a modern approach, in the context of the connection with risk management, both within the judicial and extrajudicial processes [14]. In this context, the authors decided to approach the economic expertise from the perspective of risk management, in order to highlight the vulnerabilities, their size, the significance and the tightness of the risk control, in a global view of the risk factors.

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Literature Review

Therefore, the expertise is different from audit, control, review, inspection or verification because it contains the idea of free expression of the expert’s point of view on the objectives or facts submitted to the research, being warned for knowingly presenting false conclusions, the expert takes responsibility according to with art.312 of the Penal Code [11]. According to the specialized literature expertise is a personal and critical work that includes not only the result of examining the facts from the point of view of the formal and material accuracy, but also the expert’s opinion on the causes and effects in relation to the object under his research [2]. The researchers Avornic Gheorghe and Avornic Ana, considered that the term expertise has the meaning of probative means coming from a specialist in the reference field, in a given controversial, litigious and non-litigious situation. Expertise in general is a means of probing, finding, evaluating, clarifying or proving on the basis of scientific research the objective truth regarding a certain fact, circumstance, problem, situation, cause or dispute. The authors consider that the judicial economic expertise represents missions carried out by the economical experts in accordance with the requirements of the legislation in force and they include in themselves several types of expertise that must necessarily have a scientific methodology developed for their party [4]. In the vision of Professor Avornic Gheorghe and Avornic Ana, the judicial economic expertise can be divided into the following categories: a) b) c) d)

accounting; economic-financial; fiscal; other types of expertise adjoining to the economic ones (energy, analyticalfinancial).

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Expert Ghimp Ina, considers that economic expertise can be regarded as a distinct group of expertise. Currently, this group can be assigned: accounting, economic and financial - banking expertise. Since they are part of the same expert group, they are interdependent, the object of research of which is often common However, they differ by the objectives submitted for solution, the methods, techniques and procedures applied in the research carried out, as well as by the specialized knowledge required to solve the objectives advanced [6]. In the context of the above, the authors also make a clear distinction between economic judicial expertise and extrajudicial economic expertise, which in the literature is often confused (Fig. 1).

Fig. 1. The distinction between judicial and extrajudicial economic expertise (Source: elaborated by authors)

The approach of the notions of judicial and extrajudicial economic expertise, allowed the authors to focus on risk research. Good practices inform us that all systems and areas, including judicial and extrajudicial economic expertise, must be based on risk management analysis. Because, the risk is in a permanent change, it evolves in complexity, in addition to the traditional hazard exposures, adding operational, financial, strategic, market, country, legislative, human, fraud risks and the complex nature of the risk can be attributed to several factors that in the specialized literature are grouped into named macroeconomic and external and microeconomic factors named and internal [9].

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In Fact, What Is the Risk?

In its historical dimension, risk is a young concept and at the same time one of the few business terms with direct origins in the commercial and financial

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environment and not derived from military, psychological or scientific vocabulary. While in the 70s’ “risk ” was a notion associated in particular with the sciences of nature and less with the financial and insurance theory, in recent years, the concept of risk has gained importance among business decision-makers. In this context, American economists Harry M. Markovitz and James Tobin, Nobel laureates, have been pioneers. Their work focused on the concepts of efficient portfolios (the portfolio that provides the highest profit for a given level of risk or, equivalently, the lowest level of risk for an expected profit). Most would answer that the risk is the possibility of being hurt or causing various damages. This idea also exists in most dictionaries, for example Shorter Oxford Dictionary of the English Language defines risk as: “danger; the possibility of loss or injury”, respectively the danger; the possibility of losing or suffering damage [13]. According to the economic and financial dictionary, risk involves: a measure of the mismatch between different possible outcomes, more or less favorable or unfavorable, in a future action. In the field of commercial law, risk is a danger that glides on any contractual relationship and, in general, on any commercial operation whose execution is prolonged in time, which may fortuitously generate certain disadvantages regarding the fulfillment by the debtor of the contractual obligations assumed in front of the creditor and whose appearance inevitably causes certain losses for the contractor whose benefit cannot be executed [1]. From the point of view of the insurance field, risk is defined as a product between the possible loss and the probability of its occurrence. In the field of project management, the risk measures the probability and the effect of not meeting the objectives of a certain project. In the field of environmental sciences, risk represents the possibility of negative effects on the components of the environment as a result of harmful agents or of natural phenomena with disastrous effects. In the field of human health and safety, risk is defined as the probability of changing health as a result of exposure to one or more risk factors. In the field of entrepreneurship, the risk represents a totality of activities of some subjects of the entrepreneurial activity aimed at overcoming the uncertainty in conditions of evaluation and selection of the most advantageous variant to achieve the desired results or of the minimum deviations from those planned for each selected variant [8]. The word “risk ” derives from the Italian word “risk”, which means “to dare”. In this sense, risk is a choice, not a fate. The actions we dare to take, actions that depend on the degree of freedom we hold or assume, all help to define what it means to be a human person. From this definition it turns out that we are indeed at risk in our daily lives, but we have control in their coordination, because we can change many, if we have the time and inclination to do so We can say that there is risk in everything we do, like this: a simple action, to cross the street, to drive, to swim, to knock on the door of an unknown person can end in misfortune or disaster. There are risks in every activity we carry out. They manifest themselves in one way or another, even if we do not want to acknowledge them. But the wisest thing is to understand the risks and try to manage them, maybe for our own benefit [7].

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Application/Case Study

The mentioned ones, determined us to investigate the risk factor in the process of carrying out the economic expertise. Also, the benefits of risk management was a second condition that motivated us to investigate this topic. As is well known, risk can be understood as a complex of challenges, which will probably arise in any activity, in our case in the process of carrying out the expertise and will have an impact on reaching the set objectives. So, the risks must be identified at any stage of the economic expertise, where it is noticed that there are consequences on reaching the objectives and measures can be taken to solve the problems, raised by the respective risks. Effective risk management implies that risk identification is a permanent process, which allows the connection to the change/adaptation process. Basic rules associated with risk identification [12]: 1. The risk is linked to doubts and has an associated probability of materialization. Risk is not a sure thing and does not refer to a difficult problem that has already materialized. Example: the expert’s use of incorrect data from a criminal case. 2. Difficult problems that have already materialized should not be ignored: these may be potential risks in the future if the expert acts in the same circumstances. 3. There are no risks to those situations/problems that cannot arise (so-called fiction). Focusing the attention of fictional expert¸a`rs means wasting resources. Example: the concomitant illness of all the experts for unknown reasons, under the conditions of periodic health checks. 4. Those problems that will definitely materialize should not be identified as risks. These are not risks but certainties. Certainty must be managed and usually involve resource allocation, modification of assumed goals, changes of strategy. Example: loss of expertise held by certified experts as a result of steep contractual reductions. 5. The risks are not defined by their impact on the objectives. Impact is not a risk but a measure of how a risk materialization affects those objectives. Example: it is not identified as risk the delay in the service of an expert, but it is identified as risk not to timely fulfill some contractual provisions under the responsibility of the late one. 6. The risks are not defined by denying the objectives. Example: Objective: Problems that will definitely materialize should not be identified as risks providing expert services - Risk: failure to provide expert services. 7. There are no identified risks that do not affect the objectives: there are only risks correlated with the objectives. When identifying risks, avoid establishing an indirect causation because there is a danger of seeing risks everywhere.

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Example: The risk of irregularities in reception is not related to the objective of maintaining the reputation of the service. Risks have a cause and an effect: There is a cause for each risk and an effect if the risk Materializes. The cause - a context favorable to the occurrence of the risk. Effect - the impact of risk materialization. Example: The lack of the described processes regarding the carrying out of the expertise is a situation that favors the occurrence of the risk of nonqualitative activities, a risk that has an adverse effect on reaching the objective of maintaining the expert’s reputation. The distinction between inherent risk and residual risk must be distinguished. The inherent risk is the specific risk, which is related to the achievement of the objective, without taking measures to mitigate the risks, while the residual risk is that risk that remains after the internal control measures have been taken (what remained of the inherent risk after implementation of internal/managerial control measures). Residual risk is the expression that inherent risks cannot be fully controlled. Whatever steps were taken, uncertainty cannot be eliminated. Thus, the residual risk must be within the risk tolerance. Example: Objective: to ensure the purchase of computers for all experts by the end of the year. Inherent risk: (for which no control activities were applied): delay in placing the ad. Residual risk: although control activities have been undertaken such as: elaboration of the action plan/periodic verification of the execution of the plan/information on the course of the activities/elaboration of the announcement placement chart/delegation of the responsibilities for monitoring the execution of the acquisitions, however the risk of non-fulfillment of the activity, being caused by the human factor. Risk identification is not a strictly objective process, but it is highly dependent on the perception of those involved. It does not operate with the risks themselves, but with perceptions about the risks. The identified risks must be grouped. Risk grouping is done according to the perception and needs of the entity/experts.

In order to determine possible risks in economic expertise, it is important to draw attention to the characteristics of the risk, namely [5]: • the risk is uncertain, it is never known exactly whether it will manifest (the emergence of the risk); • the consequences and their level in the event of manifestation cannot be accurately quantified; • risk is measured in terms of impact and probability; • the exact date of the manifestation is not known. Thus, from the mentioned characteristics it derives the fact that a risk is always found in a chain of three components, namely: the cause, the risk and the effect, presented in Fig. 2.

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Fig. 2. The cause-risk-impact relationship (Source: Processed and adapted after Prioritising Project Risks [5])

Therefore, the cause is an event or set of circumstances currently in existence, which creates one or more risks. The risk is an uncertain event or circumstances, which may occur in the future, and if it does, it will directly affect the entity’s objectives. And the impact assumes the main effects of the occurrence of the risk, as well as a future event. Example 1. (Risk formulation). Cause

Risk

Due to the lack of qualified Non-qualitative and experts in certain fields (taxation, unprofessional banking, accounting) expertise can be performed

The impact Which may lead to the drafting of an Expert Report of poor quality

In this context, we draw attention to the fact that the researcher Petrisor N. [10], Found that unfortunately, in the administration of the court document, judges, lawyers and legal advisors tend to investigate the case only from a normative perspective, entering into conflict with arguments with accounting experts and with the litigating parties, which mainly consider economic issues. Often the judicial expertise becomes supreme evidence and convinces the judge not by their content, but by the formal authority enjoyed by any scientific evidence. But it becomes a useful evidence to the case only if the judge is able to ask the expert the question that provokes a relevant answer. Otherwise, the magistrate becomes the captive of a proof that he cannot properly value, which he cannot fight or corroborate with other probatives. Therefore, we mention that essentially risk management from the perspective of judicial and extrajudicial economic expertise, is a dynamic and continuous process that includes several successive stages in a single cycle, reflected in Fig. 3.

5

The Risk Management Cycle

The risk management cycle is an interactive process that allows to identify risks, assess their impact and prioritize risks, identify control actions, as well as

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undertake risk reduction measures. The steps to be taken in the implementation and development of risk management consist of: 1) setting the objectives is the basis of the risk management activity, these being a precondition of this process, which begins with the planning of the operational and strategic activities of the experts; 2) risk identification is a process that starts from an analysis, with the purpose of determining the internal and external factors, which influence the achievement of the operational and strategic objectives; 3) establishing the risk appetite, represents the amount of risk that the experts are willing to accept in carrying out the activities, in order to reach an expected level of growth or to meet the set objectives; 4) risk assessment involves evaluating the likelihood of materialization of risks and the impact on the objectives, if this materializes; 5) establishing the risk management measures takes place based on the results of the risk assessment and the established tolerance level, the types of risk response (tolerance, monitoring, avoidance, risk transfer and treatment) will be selected.

Fig. 3. The risk management cycle to be completed by experts (Source: elaborated on the basis [3])

Therefore, risk should be considered as normal, because it is a stimulator for experts in the field of expertise, it is a factor that allows more precaution, opportunities for development, improvement of decisions, therefore it cannot be ignored, it must also be identified and managed the risks associated with the objectives of the experts. Based on the methodology of conducting judicial economic expertise, we will exemplify possible risks that could arise at each stage, set out in Table 1.

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Table 1. Possible risks that could arise at each stage of judicial economic expertise (Source: compiled by authors) Expertise stage

Possible risks

Preparation and

• Lack of analysis of the need for economic expertise

disposition of

• The materials to be examined have not been determined and selected

economic expertise • The objectives to be addressed have not been formulated • The questions submitted for solution are not clear and accurate • Selecting the institution/expert who will perform the expertise based on certain interests • Lack of the act of carrying out the expertise • Delaying the sending of the documents, objects and materials of the case to the institution or the expert who will carry out the expertise • The institution/expert designated to carry out the expertise makes assessments related to the legal classification and the form of guilt • The institution/expert solves tasks that fall within the competence of the criminal prosecution body, the prosecutor, the judge Scheduling of • Initiating the expertise until receiving the act of disposition of the economic expertise judicial expertise works • Lack of a work program regarding the elaboration of economic expertise • Expert’s work does not specify the time budget required to perform the economic expertise • The working stages and the operations necessary for the elaboration of the economic expertise are not found in the expert work program Documentation of work on economic expertise

• Lack of supporting documents when preparing the expert report • The expert report is prepared on the assumptions, statements of the parties or witnesses • The accumulation of information on the production and development of economic and social phenomena • The economic-financial operations were not analyzed analytically • The degree of correspondence of the economic operations, was not opposed to the regulations, instructions and normative acts • Lack of control of the accuracy, continuity and completion • Of the economic operations related to the expert economic process

Writing the expert • The form, content and procedure for producing and administering report the expert report do not correspond to the regulations in force • The expert report contains only conclusions and answers to the questions set by the commissione • The expert report has no probative value

As benefits in identifying and managing risks in judicial and extrajudicial economic expertise, we mention: • support at all stages of carrying out the expertise, especially in their planning; • support in the use, effective planning of resources (human, financial, technical, etc.);

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• • • • •

rapid beneficiaries of new opportunities; fewer shocks and unknown situations (challenges); rapid beneficiaries of new opportunities; expert support throughout the process of conducting the expertise; insurance of the body that disposed/ordered the expertise (judicial) and the beneficiary (extrajudicial); • compliance with legislative and normative requirements; • permanently informed (the expert providing the expert service).

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Conclusions and Suggestions

The exercise of the profession of expert already implies the taking of major risks and a great responsibility. The responsibility for identifying, evaluating, mitigating and monitoring the risks rests exclusively with the experts appointed to perform the judiciary economic expertise. At the same time, it is necessary to mention that the process of expertise itself is a risky activity, with a major impact on all the actors involved in this process (expert, judge, beneficiary, etc.). The authors consider that in the context of the economic-financial crisis, RISk becomes an inevitable element in the process of carrying out judicial economic expertise. In the context of the above, we point out that the risk in the judicial economic expertise is directly related to the subsequent decisions by the courts, which implies a deep knowledge of the risk assumed, respectively the knowledge of the likelihood of the risk occurring. Therefore, if the risk is not taken into account by the economic experts, there is a likelihood that the courts will make decisions/decisions under risk conditions, thus decisions/decisions will be taken in conditions of uncertainty. In the context of the above, the authors propose: • implementation and development of the internal managerial control system in the process of carrying out the judicial/extrajudicial economic expertise, with emphasis on performance and risk management, including process description; • elaboration of a methodology on risk management, specific to judicial economic/extrajudicial expertise; • the implementation of the risk management in the activity carried out by the experts, with emphasis on the elaboration of the risk register and the description of the processes. In conclusion, the authors concluded that only when we become aware and accept that we live in a world of risk, we will have a priority/opportunity for development of the professionals who carry out the expertise as well as the authorizing officers, beneficiaries of expertise, as well as the whole companies.

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References 1. BankNews: Dictionary financial-banking (2002). https://www.banknews.ro/ dictionar financiar-bancar/ 2. CECCAR Publishing House: Accounting Expertise - Application Guide, 6th edn. Professional standard no. 35, p. 9 (2014). (revised and updated) 3. Chartered Institute of Management Accountants: Fraud risk management. A guide to good practice, pp. 19–22 (2009) 4. Gheorghe, A., Ana, A.: Economic expertise - introductory notions. In: Judicial Accounting Expertise. The 37th Congress of the American Romanian Academy of Arts and Sciences (ARA) (2013) 5. Hopkinson, M., Close, P., et al.: Prioritising Project Risks–a Short Guide to Useful Techniques, p. 59. Association of Project Management Ingmar Folkmans (2008) 6. Ina, G.: Methodology for conducting economic expertise. J. Info-Med., 125–131 (2017) 7. Marcel, G., Fl, B., et al.: Corporate governance and internal audit, pp. 99–100 (2010) 8. Maria, G.: Risk - an inevitable component of entrepreneurship. J. “Exact Econ. Sci.”, 114 (2014) 9. Mˇ adˇ alina, D.R.: The importance and role of risk management in auditing, pp. 484–489 (2010). http://mastermrufeaa.ucoz.com/s5/Dreve Raluca.pdf 10. Nelea, P.: Certainty, uncertainty and risk in the economy. Legal consequences. The need for alternative settlement of financial-banking disputes, p. 16 (2017) 11. Parliament of the Republic of Moldova: Criminal procedure code no.122 of 14.03.2003. Article 88, paragraph 4 (2003) 12. Project selected within the Operational Program Administrative Capacity cofinanced by the European Union, from the European Social Fund. Risk management methodology, p. 99 (2018) 13. University Stefan Cel Mare: Risk management, p. 58 (2019). http://silvic.usv.ro/ cursuri/managementul riscului.pdf 14. Vasile, G.: Tasks, objectives and research methods applied in carrying out the accounting expertise, pp. 19–24 (2019)

Review on the Development of Enterprise Risk Management Yanfei Deng1 , Huichao Liu1 , Xulian Xie1 , and Lei Xu2(B) 1

School of Management, Southwest Minzu University, Chengdu 610041, People’s Republic of China 2 School of Economics, Xihua University, Chengdu 610039, People’s Republic of China [email protected]

Abstract. The word, risk, has a long history, but the emergence of risk management in the real sense is not more than a hundred years. The risk always exists, as an important part of the market economy, so enterprises bear a variety of risks in the operation process. How to do a good job of risk management is a problem that every enterprise must face. In this paper, risk definition and risk management changes are sorted out in chronological order, and risk management procedures are summarized to find out the future development direction of enterprise risk management and provide references for risk management of small and medium-sized enterprises. Keywords: Enterprise risk

1

· Risk management · Review

Introduction

Risk is everywhere, how to deal with risk is what people have been doing, but people may not understand risk correctly. This paper first collates the change of risk meaning, hoping to arouse people’s thinking about risk. Secondly, we sort out the changes of risk management, and different enterprises can learn from it when they carry out risk management. Thirdly, in the process of combing, we find that the final link of risk management is lack of relevant theoretical research at present, that is, in the future research of risk management, the evaluation of the effect of risk management should be paid attention to, so that the study of risk management is more perfect. The full text is as follows: Firstly, sort out the changes in the meaning of risk. Secondly, combing the change of the meaning of risk management and the method of each link of risk management procedure. Finally, we introduce the latest content of risk management and draw conclusions.

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Enterprise Risk Definition

Before a comprehensive review of the development of enterprise risk management, it is necessary to have a clear mind of the definition of risk. Different c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 154–166, 2021. https://doi.org/10.1007/978-3-030-49889-4_14

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scholars have different definitions of risk in different eras. The definition of risk usually involves uncertainty, probability, loss and other meanings. As early as the 19th century, the western classical economic school proposed the concept of risk, thinking that the risk is the by-product of business activities, and the income of operators was the reward for taking risks in business activities. In the 20th century, one of the definitions of risk was the possibility of damage or loss [16,22]. The classic definition of risk was given by Frank Knight [23], an American economist in the book, Risk, Uncertainty and Profit (1921). Knight pointed out that the risk is measurable uncertainty that corresponding to risk, while Knight defined unmeasurable uncertainty as uncertainty. In the middle and late 20th century, the risk was generally defined as uncertainty of loss [19]. Another view was that it is self-contradictory to define risk as uncertainty. Risk is an objective state but uncertainty is a psychological state. Risk is a collection of dangerous states, determined by probability [31]. On the basis of this point of view, the concepts of risk and loss are further distinguished: risk is an antecedent concept, and loss is an ex post concept. Risk is a possible state of loss or profit result. Once the loss or profit occurs and the event is in a certain state, the risk will not exist. Yates and Stone (1992) [41] made a more thorough analysis of the connotation of risk and made a clearer distinction between risk and uncertainty. Whose three-factor model of risk reflects the basic connotation of risk in essence, that is the basic conceptual framework of modern risk theory. In the late 20th century, scholars more explored the connotation of risk from the perspective of probability theory, one of which defined risk as the difference between the possible outcomes in a given situation and in a given time [40]. Another view was that the risk was a function of the probability of an adverse event or loss and its consequences. In addition, there is another view that the risk and opportunity coexist. The risk can be loss but may also bring benefits, and the risk and uncertainty are often the opportunities for enterprise development [7,35]. With the continuous enrichment and improvement of risk management theory and practice, the concept of risk becomes more and more clear. Since the beginning of the 21st century, most of the organizations or institutions with international influence have constantly revised the definition of risk. Generally speaking, people’s cognition of risk is no longer limited to loss, which has changed the development of risk management theory to some extent. The revision of risk definition by some international organizations or institutions is presented in the form of a table (Table 1). Carding the definition of risk in time order it is not difficult to see the risk from the original the possibility of loss or damage gradually evolve into the uncertainty of coexistence of losses and gains reflecting enterprise or an organization of risk from the aversion to the use of a process change. This change also can prove its own complexity. Risk awareness promotes the development of the theory of risk management (Table 2).

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Time

Representative

Instructions

The end of the Risk is the 19th century – possibility of the end of the loss 20th century

Haynes (1895) [22], Kenneth J. Arrow (1974) [16]

This view does not quantify risk and only limits it to losses

1921

Risk is measurable uncertainty

Frank knight

The theory holds that risk is measurable and for the first time points to uncertainty as a source of profit

1956

Risk cannot simply be defined as uncertainty

Irving Pfeffer

The theory distinguishes between risk and uncertainty, opening up a new perspective on the definition of risk, but risk is still limited to losses

Late 20th century

A clearer distinction is made between risk and uncertainty

Williams C. A. (1993) [40] Yates, Stone (1992) [41]

The research in this stage summarizes the essence of previous theories and further distinguishes between risk and uncertainty

Late 20th century to present

Risk can be a loss or a gain

William F. Sharpe (1995) [41], Clarke, Varma, (1999) [7]

This understanding has promoted the development of comprehensive risk management and enriched the connotation of risk

3 3.1

Awareness of risk

Enterprise Risk Management Development of Enterprise Risk Management Theory

Risk management is initially considered as the integration of the concepts of risk and management, so risk management is essentially a generic term for management activities for various risks. As risk management is applied to the enterprise management, in order to better manage risk, the enterprise should have a fulltime risk manager. The authority shall be to further expand, not only can make it through the insurance risk can also pass on part of risk management, and actively advance but insurance is only part of the risk management tools rather than one of the only [14]. A sign that risk management has entered the stage of systematic research is the publication of Risk Management and Insurance (1964) by

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Table 2. Sort out the definition of risk in some international organizations in chronological order Time Awareness of risk

Organization or institution

Instructions

2004 Risk is the likelihood of Standards board of events occurring and Australia, Standards their impact on board of New Zealand objectives

This definition emphasizes that impact is divided into positive and negative, and considers risk to be neutral to some extent

2004 The negative impact of American COSO uncertainty on the committee, Risk target is called risk management – an integrated framework

This definition recognizes uncertainty as neutral, but treats risk as negative

2004 Risk refers to the Basel committee uncertainty of expected returns due to possible losses

This definition follows the concept of uncertainty of loss without in-depth study of risk

2006 Enterprise risk is the impact of future uncertainty on the realization of an enterprise’s business objectives

China state-owned assets supervision and administration commission

This definition determines that risk is neutral, which is a great improvement over the previous definition of risk

2009 Risk is the effect of uncertainty on the target

International standards committee, ISO/FDIS31000 risk management standard

This definition is similar to SASAC’s definition of risk, but more succinct

2017 The risk is the likelihood that events will occur and affect the realization of strategic and business objectives

American COSO committee

In this time, the revision of risk definition emphasizes the neutral connotation of risk more

Williams C. A. At this time, risk management focuses on reducing losses caused by risks by various management methods. Methodology of building enterprise risk management has been proposed, then analysis the risk management point of view question got more clearly defined: risk management, there are two different perspective about risk management. The first is based on the financial policy perspective of chief financial officer, and the second is based on officer position of risk and insurance perspective. From the middle and late 20th century, risk management theory began to be integrated with other theories and research fields, such as the combination of risk management and complex system models

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in management. Since then, the development of risk management discipline has had a more mainstream theoretical source [8]. Furthermore, the theory of risk management absorbs the analytical methods of modern economics to determine the optimal strategy of risk management, which is integrated with the theory of financial markets and becomes an important field of finance [9]. At the end of the 20th century, the concept of integrated risk management was proposed [21]. The application of risk management is not limited to enterprises, and risk management should be carried out in all fields of society [3]. Compared with individual risk management, integrated risk management could not only reduce the possibility of loss but also create profit opportunities for enterprises [15,34,36]. With the rapid development of Internet technology, the security and complexity of network information are factors that cannot be ignored in enterprise risk integration management [17]. It is worth noting that integrated risk management is not a model suitable for all enterprises to follow. Each enterprise must integrate its own resources according to its own actual situation to design its own risk integration framework [20,42]. The definition of enterprise risk management by the American COCO council (2004) emphasizes more on the integrity of risk management and that risk management is a process involving all employees rather than just a collection of methods. The new COSO-ERM (2017) emphasizes the importance of integrating risk management into all organizations and activities of the enterprise, as well as corporate culture, under the premise of the old version (Table 3). From the understanding of scholars and experts in different ages on risk management, it can be seen that before 1990s, the academic circle generally believed that risk management was a management activity to reduce business risks. Since then, as the connotation of risk has been enriched, risk management has also changed from the most basic loss reduction to the integration of all levels of the enterprise to achieve corporate goals. There are three main views on the division of the development stage of risk management theory: (1) according to different objects of risk management, the development of risk management is divided into three stages. In the first stage, the risk management objects were mainly pure risks from the 1950s to the 1970s. In the second stage, the risk management objects were mainly the volatility of business and financial results from the 1970s to the end of the 20th century. In the third stage, the risk management rose to the 21st century with multi-level and multi-angle integration. (2) Other scholars divided risk management theory into traditional risk management stage (before 1990s), modern risk management stage and comprehensive risk management stage (since the 21st century). (3) According to Cao Yuankun (2011) [6], the logical relationship between traditional risk management and modern risk management should be post-modern and ultra-modern, and this classification would cause confusion to the current research on risk management. Based on this view, risk management theory could be roughly divided into the risk management stage at the insurance and financial levels (from 1931 to the late 1980s and early 1990s) and the risk management stage at the overall level (from the early 1990s to the present). Through sorting

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Table 3. Sort out changes in the concept of risk management in chronological order Time

Awareness of risk

Organization Instructions or institution

1960

Insurance is only one of Russell B. the tools of risk Gallagher management

Initially he enriched the connotation of risk management, and began to explore the enterprise risk management

1964

Risk management is a series of management methods

Risk management has entered the stage of systematic research, which focuses on risk management methods

1976

Risk management is David integrated into the Cummins theory of financial market and becomes an important field of finance

Risk management theory has been gradually integrated with other fields, which has laid a foundation for comprehensive risk management theory

The end of the 20th century

The concept of integrated risk management was proposed

Miller, D. Kent (1992) [21] Peter L. Bernstein (1996) [3]

The research level of risk management theory is broader, and the application of risk management is not limited to enterprises

Since 2004

Risk management is a process, not just a method

The COSO committee

The connotation of risk management changes from method to process, and the importance of corporate culture becomes more prominent

Williams C. A

out, the author believes that the development of risk management theory is more concise and accurate in dividing risk management stage based on insurance and financial level and risk management stage based on the overall level. 3.2

Basic Procedures for Risk Management

The Japanese scholar riming Kamei Ming (1984) divided the main process of risk management into three parts: risk identification, risk measurement and risk treatment. Gleason J. T. (1999), an American risk management scientist, summarized the contents of risk management into the following three aspects: (1) make accurate and timely measurement of all risks faced by the enterprise. (2) establish a process to evaluate various risks within the business scope of production and operation. (3) establish a special risk management department within the enterprise to control enterprise risks and deal with losses caused by enterprise

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risks [27]. Some scholars regarded risk identification, analysis, evaluation and control as the main process of enterprise risk management [11,33]. Tuo Guozhu (2011) [38] regarded the basic procedure of risk management could be divided into risk identification, risk measurement, risk control and risk management effect evaluation, and the program was a cyclical process. By comparing the above scholars research on risk management procedures, the author thinks that the division of Tuo Guozhu is more comprehensive, in the following analysis, this article takes the application as a basic framework for further expounds the content of risk management. (1) Risk identification Risk identification is the first part of the risk management process, which involves the classification of risks first, then the judgment and identification of risks, and the classification of risks is the premise of enterprise risk management [9]. The different understanding of the nature of risk, the risk research from the point of view of the different of industry and enterprise would affect the classification of the risk. The risk classification of diversified, the characteristics of high overlaps and the classification of risk have or should not have uniform standard, just as the definition of risk in a constantly changing. The angle of risk classification will also change with the development of related disciplines, the change of social economy and other factors changed by, and the risk is not invariable. Therefore, the risk of enterprise work needs to have been identified. Crisis is a perception, and one of the best ways to overcome it is not to allow it to happen in the first place [37]. Enterprise environment is different, and the size of the different work in risk identification is different, so each recognition method has its applicable type and advantages and disadvantages of enterprise. The enterprise should be combined with their own actual situation and needs to choose, these methods not only can be used alone, also can supplement their shortcomings comprehensive use. Combined with the research on risk identification methods by domestic and foreign scholars, the commonly used risk identification methods are presented in the form of tables (Table 4). (2) Risk measurement Risk measurement refers to the use of probability theory and mathematical statistics to analyze a large number of detailed loss data collected on the basis of risk identification, to estimate and predict the probability (frequency) and loss range of risk occurrence. Risk measurement is an indispensable core link in risk management. Its importance lies not only in establishing risk management on the scientific basis, but also in quantifying risk analysis and providing a more reliable basis for choosing risk management technology and means [1]. The discrete probability distribution can be used to predict the potential loss scale in the future. However, in the risk estimation, some new events are often not sufficiently understood, and the variable distribution representing the risk cannot be deduced from the probability theory, and it is impossible to conduct sufficient experiments (technically impossible or too costly). At this point, we can refer to the subjective probability estimation made by relevant professionals

The calculation is simple, involving more financial indicators can be more comprehensive reflection of the financial situation of the enterprise

The Z-score model (Edward Altman, 1968 [1]) is a widely used method of financial crisis early warning

First draw the flow chart of the enterprise, find out the key points, as the center to find the risk

Z value test

Flowchart analysis

Surveyors do not make any judgments about the respondents, so the survey results are relatively objective Because this method requires multiple feedbacks, the final results are more stable and accurate

Standardized Questions raised by survey professionals or method institutions in surveys are applicable to all enterprises

Delphi method

Its essence is an anonymous correspondence method, used to predict the likely outcome

It can only reflect individual risks that can be reflected in financial indicators, so it needs to be used in conjunction with other identification methods

Disadvantages

Time-consuming and costly, it is not suitable for some unexpected risks

Because the investigation pattern is relatively fixed, the specific risk of the enterprise may not be identified

It can expose the Professional rendering potential risks of is required, and the enterprises and play an effect of the analysis early warning role method is limited by the level of the painter

Advantages

Risk Instructions identification methods

It is suitable for all kinds of enterprises, but more suitable for enterprises that make long-term strategies and decisions

All kinds of enterprises are applicable. However, the high cost of this method may be difficult for small enterprises to afford

Some businesses with simple business processes do not need to use this approach

Suitable for all kinds of enterprises, especially small enterprises

Application

Table 4. Common risk identification methods, advantages and disadvantages, application scope

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on the risk. Although the subjective probability has some shortcomings, practice has proved that the estimation made by experienced experts is often reasonable. Compared with other industries, the practice of financial industry in risk assessment is of great significance, especially investment banking enterprises, which can learn from the basic practice of risk estimation of investment Banks, consulting institutions and successful enterprises according to the actual situation [24,32]. The risk assessment methods commonly used by investment Banks are briefly introduced. (3) Risk control After risk is correctly identified and estimated, the third link of risk management is risk control, which means the process of using various risk management tools and optimizing the implementation based on the results of risk measurement and on the premise of achieving the risk management objectives. Under the premise that risk management enters into comprehensive risk management, systematic approaches are used to model enterprise risk control. In the framework of this model, enterprise risk control and various elements of enterprise operation were related [26], or this model can intuitively reflect the meaning of comprehensive risk management. From the perspective of financial management in a broad sense, enterprise risk management could start from assets, liabilities, equity and other aspects, which was applicable to all kinds of enterprises to A certain extent [12]. Comprehensive risk management’s proactive attitude to risk and demand orientation to create value enrich the means of risk control, which needs to seek new technical methods. On the one hand, risk management activities not only include transfer, elimination, reduction and control, but also take development, utilization and operation risks as important measures of risk management [13, 29]. In combination with the new revised ERM framework of COSO committee in 2017, the definition of risk tends to be neutral, and enterprise risk control should also step out of risk diversification, risk hedging, risk transfer and risk aversion and take advantage of the possibility that speculative risk can bring profits to elevate risk control to the height of enterprise strategy (Table 5). Strategic change, organizational ability and corporate culture are three important factors for an enterprise in the face of crisis, among which corporate culture plays a central role [10]. An enterprise with sustainable development often has efficient communication channels, clear goals and common values, which are exactly what inspires the enterprise to burst out cohesion [5]. It is difficult for enterprises to achieve sustainable improvement of enterprise risk management capability by unilaterally pursuing the perfection of risk management system and the adoption of advanced risk management technology, while ignoring the cultivation of internal risk management culture [30]. From the perspective of corporate culture, comprehensive risk prevention and control is a new construction mode, which is to transform constraint behavior into conscious behavior. The construction of corporate culture can permeate the implementation of comprehensive risk management into all aspects of the enterprise [18]. Positive corporate culture plays a positive role in corporate crisis management, and vice versa [2].

On the basis of probability theory, the language and method of mathematical statistics are used to quantify and measure the risks of investment Banks (Enterprises)

The foreseeable future loss caused by risk is converted into current cost, and the current return is adjusted to measure the adjusted return

VaR

RAROC

Pressure test Risk factors are defined method to assess the risk to investment Banks (firms) in extreme market conditions

Evaluation principle

Risk assessment method

VaR can only assess the risk of normal market operation, while stress test can fill the gap of risk assessment in extreme cases

It is beneficial for decision makers to consider the risk by including both risk and return into the scope of risk estimation

It can be used to measure different risks in different markets and express them numerically, which has wide applicability

Advantages

It requires a huge amount of computation, so risk cannot be measured alone and must be matched with VaR

The calculation of related elements such as economic capital is not easy to get an accurate value, which makes RAROC’s accuracy greatly reduced

Risk may be overestimated. Lack of anticipation and control over the occurrence of some extreme events

Disadvantages

Luciano, Elisa (2003) [24]

Bingwu Liu, Z. Li (2009) [4]

Philippe Jorion (1997) [32]

Sample

Table 5. Common risk assessment methods and advantages and disadvantages of investment banks

Development of Enterprise Risk Management 163

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To sum up, although corporate culture construction cannot be the only means of enterprise risk control, the combination of corporate culture construction and other risk control means can greatly improve the effectiveness of enterprise risk management and reduce the cost of enterprise risk management. (4) Evaluation of risk management effect As the last step of the risk management procedure, the evaluation of risk management effect refers to the analysis, inspection, correction and evaluation of the profitability brought by the implementation of risk management tools. Risks are constantly changing, and people’s understanding of risks and risk management techniques are in the process of continuous improvement. Therefore, risk identification, estimation, evaluation and strategy selection need to be regularly checked and revised to ensure the optimal use of risk management tools [38]. For now, our country enterprise risk management effect evaluation is still lack of systematic research. The article puts forward some scholars think that the enterprise risk management departments shall, in combination of monthly department report risk and performance monitoring and measuring key link to realize to contribute to the business objectives, in order to achieve the correct strategy to implement some of the problems. Enterprise risk effect evaluation is often replaced by enterprise management performance, which has not been well implemented in China, and the introduction of BSC is not universal. It can be seen that the construction of enterprise comprehensive risk management is still a long way to go.

4

Conclusion

To sum up, the complexity of risk determines that the connotation of risk will be constantly updated and changed, which means that the concept and method of risk management will also keep pace with the times and develop in the integration with various disciplines. In recent years, some scholars have conducted interdisciplinary studies on risk management, such as integrating the immune theory with the risk management theory, aiming at building the enterprise risk immune system by combining the immune mechanism and improving the alertness of enterprises to risk prevention and control [28]. Other scholars combined the theory of resilient with risk management and proposed the resilient risk management theory of keeping the bottom line and expanding the space [25,39]. These crossstudy cases also prove that risk management theory has a strong vitality. Faced with the uncertainty of the current market development, the enterprise shall refer to the institutions of the risk management framework to design suitable for the development of the enterprise the risk management framework, rather than copying the rigidity of risk management become a mere formality. It’s important to note that risk management is every enterprise need, rather than just listed companies only need, size small weak ability to resist risk of small and medium-sized enterprises should pay attention to risk management, grasp the opportunity to create value by risk management. Now, of course, the risk management research is not comprehensive, the study of risk assessment is more of a theoretical and a lot of operational model for the

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present are currently not operational. Moreover, as previously mentioned risk management effectiveness evaluation of the risk management program is also a lack of research, but as the last part of the risk management process, this process is indispensable. In general, the study of risk management is far more than this, and the evaluation of risk management effect should also be connected with the overall risk management work of enterprises and differentiated from the evaluation of enterprise performance. Acknowledgements. The work was supported by the Program of the Fundamental Research Funds for the Central Universities, Southwest University for Nationalities No. [2016NZYQN13]. The authors are indebted to the editors and reviewers for their valuable comments and suggestions.

References 1. Altman, E.I.: Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J. Finance 23(4), 589–609 (1968) 2. Amah, E., Nwuche, C., Chukwuigwe, N.: Effective reward and incentive scheme for effective organizations. Res. J. Finance Account. 4(13), 73–79 (2013) 3. Bernstein, P.: Against the Gods: The Remarkable Story of Risk. Wiley, New York (1996) 4. Bingwu, L., Li, Z.: The study of commercial bank loan risk pricing based on RAROC model. In: 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, vol. 2, pp. 541–543. IEEE (2009) 5. Camerer, C., Vepsalainen, A.: The economic efficiency of corporate culture. Strateg. Manag. J. 9(S1), 115–126 (1988) 6. Cao, Y., Wang, G.: Business risk management development course and new understandings of the research trends. Contemp. Finance Econ. 1, 85–92 (2011). (in Chinese) 7. Clarke, C.J., Varma, S.: Strategic risk management: the new competitive edge. Long Range Plann. 32(4), 414–424 (1999) 8. Close, D.B.: An organization behavior approach to risk management. J. Risk Insur. 41(3), 435 (1974) 9. Cummins, J.D.: Risk management and the theory of the firm. J. Risk Insur. 43(4), 587–609 (1976) 10. Deverell, E., Olsson, E.K.: Organizational culture effects on strategy and adaptability in crisis management. Risk Manag. 12(2), 116–134 (2010) 11. Jerry, M., Samir, S.: Enterprise risk management: an analytical approach. SSRN Electron. J. 2000, 1–12 (2007) 12. Doherty, N.A.: Integrated risk management: techniques and strategies for reducing risk (2000) 13. Drzik, J.: New directions in risk management. J. Financ. Econ. 3(1), 26–36 (2005) 14. Gallagher, R.B.: A practical approach to risk management 3(2), 78–86 (1960) 15. Gordon, L.A., Loeb, M.P., Tseng, C.Y.: Enterprise risk management and firm performance: a contingency perspective. J. Account. Public Policy 28(4), 301–327 (2009) 16. Hakansson, N.H., Arrow, K.J.: Essays in the theory of risk-bearing. J. Polit. Econ. 27(5), 1193 (1972)

166

Y. Deng et al.

17. Hernandez, L.R.: Integrated risk management in the internet age. Risk Manag. 47(6), 29–29 (2000) 18. Hu, Q., Dinev, T., Hart, P., Cooke, D.: Managing employee compliance with information security policies: the critical role of top management and organizational culture. Decis. Sci. 43(4), 615–660 (2012) 19. Jerry, S.R.: A case study in risk management. J. Risk Insur. (40) (1973) 20. Notingham, L.: Integrated risk management Canadian business review. Contemp. Finance Econ. 23(2), 26–28 (2002) 21. Miller, D.K.: A framework for integrated risk management in international business. J. Int. Bus. Stud. 23(2), 311–331 (1992) 22. John, H.: Risk as an economic factor. Q. J. Econ. (1895) 23. Knight, F.: Risk, uncertainty and profit. Soc. Sci. Electron. Publ. 4, 682–690 (1921) 24. Luciano, E., Peccati, L., Cifarelli, D.M.: VaR as a risk measure for multiperiod static inventory models. Int. J. Prod. Econ. 81, 375–384 (2003) 25. Lv, W.D., Wei, Y., Zhao, Y.: Resilient risk managementa lorganizational management techniques for dealing with uncertain situations. Manag. World 9(35), 116– 132 (2019). (in Chinese) 26. Li, T.G.: Research on enterprise risk management and control model. J. Financ. Econ. 1, 89–93 (2004). (in Chinese) 27. Ming, Z.S.: Modern Risk Management. China Textile Press, Beijing (2003). (in Chinese) 28. Nan, W.: Research on the relationship between the elements of enterprise risk management and risk management performance in view of immunology. PhD thesis, Ji Lin University, Jilin (2015). (in Chinese) 29. Nocco, B.W., Stulz, R.M.: Enterprise risk management: theory and practice. J. Appl. Corp. Finance 18(4), 8–20 (2006) 30. Donald, P.: Creating an operational risk culture 109 (2006) 31. Pfeffer, I.: Insurance and economic theory. Rev. Insur. Stud. 3(3), 135–136 (1956) 32. Philippe, J.: Value at risk: the new benchmark for cona ltrolling derivatives risk 63 (1997) 33. Schneier, R., Miccolis, J.: Risk: enterprise management. Strat. Leadersh. 26(2), 10–16 (1998) 34. Scordis, N.A.: Integrated risk management: techniques and strategies for reducing risk. J. Risk Insur. 67(4), 667–667 (2000) 35. Sharpe, W.F.: Capital asset prices: a theory of market equilibrium under conditions of risk. J. Finance 19(3), 425–442 (1964) 36. Shimpi, P.: Integrating risk management and capital management. J. Appl. Corp. Finance 14(4), 27–40 (2002) 37. Snoeijers, E.M., Poels, K.: Factors that influence organisational crisis perception from an internal stakeholder’s point of view. Public Relat. Rev. 44(1), 65–74 (2018) 38. Tuo, G.Z.: Insurance. Capital Economic and Trade University Press, Beijing (2011). (in Chinese) 39. Van, D., Vegt, G.S., Essens, P., et al.: Managing risk and resilience. Acad. Manag. J. 58(4), 971–980 (2015) 40. Williams, C.A., Smith, M.L., Young, P.C.: Risk Management and Insurance. McGraw-Hill Book Company (1993) 41. Yates, J.: Risk-Taking Behavior. Wiley, Hoboken (1992) 42. Zolkos, R.: Integrated risk management calls for common approach. Bus. Insur. 32(42), 3–4 (1998)

Does Commercial Housing Have Better Access to Public Service Than Affordable Housing? – An Empirical Study for Accessibility to Public Service of Different Housings in Chengdu Chao Huang(B) and Jiaqi Fan School of Public Administration, Sichuan University, Chengdu 610065, People’s Republic of China [email protected]

Abstract. Affordable housing is a kind of social security housing provided by the government for low-income families. Unlike the commercial house is sold and rent entirely according to the market price, affordable housing orients to a particular group at a standard rate or rent. Studies indicate that Many affordable houses are built in urban fringe areas and do not have adequate public services, such as hospitals, schools or shopping malls, which raised a question, “is there any quantitated evidence supporting that commercial housing has better access to public service than affordable housing?” In this paper, we proposed to use the accessibility to measure public service level of different housings. Within the central urban area of Chengdu, we selected 20 affordable communities and 20 commercial communities (near the median price of the secondhand house in Chengdu) randomly. After a brief overview of the theoretical foundation of accessibility, we proposed a mixed movement model to measure accessibility with Gaode Map API. The tool is arranged in such a way that it can easily calculate the travel time from the communities to 5 types of public service facilities through public transportation (schools, culture/sports facilities, commercial facilities, hospitals and public parks) separately. The independent sample t-test reveals that the commercial communities have significantly better access to all the public services than the affordable ones. The results could provide the decision-makers with supporting the allocation of affordable housing and observing the public service from a different perspective.

Keywords: Affordable housing Public service

· Commercial housing · Accessibility ·

c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 167–178, 2021. https://doi.org/10.1007/978-3-030-49889-4_15

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Introduction

To solve the housing problem of low-income families, China has built many affordable houses in the past twenty years. Affordable housing is a kind of social security housing with standards of construction and price, which is uniformly planned by the government. While the price of land close to the city center is far higher than that of the fringe area, local governments tend to build affordable housing in the urban fringe [15] without necessarily consulting with stakeholders [9]. Early in 1980, scholars [17] found that access to public service is uneven in many cities. It is not surprising that studies are indicating that the public service opportunities of affordable housing residents are poor [21]. While the affordable house doesn’t have to catch up with the commercial house in all aspects, they should be equal on the public service, like medical service, education and other public facilities. The poor access to public service of affordable housing might lead to more social problems, for instance, poverty concentration, worsening living environment and high crime rate. [1,7]. Unlike the affordable house, the commercial house is sold or rent entirely according to the market price, which makes the two housing not comparable in many aspects. However, it does not mean they should be regarded different for public services. This paper raised such a question, “does the commercial housing have better access to public service than affordable housing”? To answer this question, we selected Chengdu, who was rated as the happiest city in China in 2018 as an example. In 2017, the General Office of the Chengdu Municipal People’s Government promulgated the Five-Year Plan for Housing Security in Chengdu (2017–2021). The plan proposed that 5.76 million square meters of affordable housing should be built before 2021; meanwhile, it requires optimizing the location of affordable housing, implementing public service facilities and improving the living environment. The aforementioned question consists of three following questions. 1) What are the measurements for the access to public service; 2) How to measure it; 3) are there significant differences between affordable houses and commercial ones. In this paper, we proposed to use the accessibility, a concept widely used in transport planning, urban planning, geography, and policy-making and other scientific fields [18] to measure public service level of different houses. By comparing the accessibility of public service, this paper tries to reveal the unbalance of public services with quantitated evidence. This empirical study could also provide the decision-makers with supporting the affordable housing allocation and assuring the welfare for low-income people. This paper is organized as follows. After a brief overview for the theoretical foundation of accessibility and analysis of different measures of accessibility, we developed a mixed movement model to simulate the daily use of public transportation better. Not only the temporal and spatial dimensions are integrated,

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but also the path planning is included in this model. We then turned to the sampling method, by which 20 affordable communities and 20 commercial communities were selected. The measuring of accessibility to different types of public service facilities and independent sample t-test reveals the uneven accessibility of public service between affordable house and commercial ones. Policies suggestions on allocation of affordable house and public service were provided at the end of this paper.

2

Literature Review

For different scholars, the definitions for accessibility are different but with common characteristics. Hansen [11] first proposed the concept of accessibility and defined it as ‘the potential of opportunities for interaction’. Bertolini [4] considered accessibility to be ‘the amount and diversity of places that can be reached within a given travel time and/or cost’. Leonardi [14] defined accessibility as ‘the consumer surplus, or net benefit that people achieve from using the transport and land-use system’. Burns [5] defined accessibility as ‘the freedom of individuals to decide whether or not to participate in different activities’. El-Geneidy and Levinson [12] argued that accessibility is ‘a measure or indicator of the performance of transportation systems in serving individuals living in a community’. Over the past years, scholars have proposed different models to measure accessibility. Malekzadeh [16] categorized accessibility measurement methods into six types: Distance Measurements, Cumulative Opportunity Measures, Gravity-based Measures, Utility-based Measures, Space-Time Measure and Place Rank Measure. Distance Measure is simply merging the distance from a given origin to destinations [10], while Cumulative Opportunity Measurement, also known as isochronal, describes the accessibility of a given source as the number of opportunities accessible within a fixed travel time, distance or cost, or the time or cost required to calculate the number of opportunities to reach a fixed number [8]. Gravity-based Measures proposed a weight to opportunities for representing their attraction and considered an impedance value (decay function) to reflect their distance from origins [16]. Ben Akiva and Lerman proposed Utilitybased Measures based on the random utility theory, in which the probability of an individual choosing a scheme depends on the utility of all the schemes [2]. Space-Time Measure originated from the concept of space-time prism, in which giving the moving speed, the time to reachable destinations is calculated according to the chosen path [13]. Place Rank Measure ranks different places based on opportunities one person could get within the specific area [16]. The cumulative opportunity measurement is more suitable for the comparative study of traffic facilities and land use change under different time and space conditions [6]. This measurement can be used to compare the number of parks,

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shopping mall, hospital and other opportunities that residents in different locations can reach in certain travel time, so as to understand the configuration of public facilities in different areas in the same period. Using the open data of Gaode Map can make the isochronal drawn in the use of cumulative opportunity measurement more accurate, so this study chooses to use the cumulative opportunity method. However, some important components of public transport accessibility, such as the walking time between the departure, destination and transfer stations, and the waiting time for transfer, are usually not explicitly considered when calculating the total travel time [3]. Recent studies have shown that it is necessary to include actual traffic conditions related to time composition (i.e. traffic congestion, speed restrictions, waiting time, turning restrictions and one-way roads) [19,20].

3

Methodologies

The key issue of accessibility is to include actual traffic conditions in the measurements. In the context of affordable housing and public service, we assumed public transport is prioritised in travelling. After selecting affordable and commercial communities randomly, we get the coordinates of the sample points as the start points. To compare the accessibility of affordable and commercial houses to public services, we proposed a mixed movement model including walking, bus and metro to calculate the travel time. The path design strategy of the mixed movement model is ‘Fastest Mode’, which means the least time to reach one specific destination with public transportation and necessary walk. Three categories of travel time as 30 min, 30–60 min and more than 60 min were set, and isochronous circles were generated inverse distance weight method. The isochronous circles reflect how far you can reach within the given time from the start points. By counting and weighted sum-up of POI (points of interest) in different isochronous circles, we could obtain the accessibility to public service. The POI was defined as 5 types of public service facilities, which are public schools, public hospitals, culture/sports facilities, commercial facilities and public parks. The weights of isochronous circles are 3 for points for within 30 min circle, 2 for the 30–60 min circle, and finally, 1 for circle of beyond 60 min. We then calculated the accessibility for each type of public service through weighted sums. The independent sample t-test was employed to verify our hypothesis in the end. The technique flows of the methodology could be found as follows (Fig. 1), (a) Random sampling of affordable and commercial communities; (b) Request coordinates in maps to obtain the start points; (c) With Gaode Map API and API Application, set travel mode and travel strategy to obtain travel time from start points;

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(d) Use ArcGIS and inverse distance weight method to generate isochronous circle; (e) Count the number of accessible facilities in different time periods; (f) Calculate the accessibility score of each type of facilities and conduct independent sample t-test.

Fig. 1. Technique flows of the methodology

4

Data Collection and Analysis

The data of communities and facilities are limited in the central urban area of Chengdu, which includes Wuhou District, Jinjiang District, Qingyang District, Jinniu District and Chenghua District - the five regions with the highest GDP in 2018 in the central region of Chengdu defined in the report “Chengdu Urban Master Plan (2016–2035)” (Fig. 2).

Fig. 2. Study area

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The data of affordable housing were collected from the list of affordable housing published by Chengdu Housing and Urban-Rural Construction Bureau (http://cdzj.ch-engdu.gov.cn/cdscjw/index.shtml) in May 2019. Totally there are 56 affordable communities, 20 of which are selected randomly as samples. The data of commercial communities comes from China’s second-hand housing trading website (https://cd.lianjia.com). With a small interval around the median price of second-hand housing (14,959.13 CNY), 100 communities are extracted, and again, we selected 20 of them randomly (Fig. 3).

Fig. 3. Samples of affordable and commercial communities

The data of public service facilities are collected from open data sources, as shown in Table 1 and Fig. 4. And the weighted sums are calculated in Appendix Tables 2 and 3. The independent sample t-test results (Appendix Tables 4 and 5) show that the assumed equal variance of each type of facilities is significant, and there is a significant difference in the accessibility of public service facilities between the sample commercial housing and the affordable housing. There are a large number of high-quality hospitals, high-quality primary and secondary schools, comprehensive shopping malls, parks and other high-quality resources in the central area of Chengdu. Due to the suburbanization of affordable housing construction, there is a big gap with the ability of commercial housing residents to access public service facilities. Besides, the uneven spatial distribution of public resources is also one of the problems faced by the public transport of affordable housing residents.

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Table 1. Data sources for public service facilities Data

Data sources

Sports facilities

Public sports facilities inquiry system on the official website of Chengdu Sports Bureau. (http://cdsport.chengdu.gov.cn)

Public primary and secondary schools

Official website of Chengdu Education Bureau. (http://edu. chengdu.gov.cn)

Medical facilities

Information disclosure section of Chengdu Health Committee’s official website. (http://cdwjw.chengdu.gov.cn)

Cultural facilities

Catalogue of libraries and cultural libraries published on the official website of the Chengdu Municipal People’s Government. (http://www.chengdu.gov.cn)

Park

“Chengdu City Park Basic Data Statistics Information” from Chengdu Public Data Open Platform. (http://www.cddata.gov. cn)

Commercial facilities Chengdu ranks the top 45 shopping malls in terms of popularity on China review website. (https://www.dianping.com)

Fig. 4. Distribution of public service facilities in study area

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Conclusions

Although the mixed movement mode could accurately calculate the time required for walking and transfer in the process of public transport, which is challenging to do by traditional methods, there are still some limitations for this approach. The study didn’t include the different needs or preferences of residents, but it’s very likely that different people have different demands for public services. For instance, some people living in affordable might not care much about public sports facilities but concern the education or medical facilities a lot. An additional survey regarding the needs of public service would help assign weights to different types of public service. But still, we can see from the analysis results that Chengdu affordable housing residents do have poor access to public service facilities. Although other variables may affect decisions about the use of public services or facilities, such as personal capabilities and personal choices, accessibility is still an essential enabling factor for the poor to have proper access to urban public services and facilities. Just providing afford houses is by far sufficient for social equality, the accessible public service should also be taken into consideration. Given the above findings, we propose the following suggestions for policymakers. Firstly, the government should enhance public participation and include the demands of residents in affordable houses in urban planning and construction. It should be realized that the level of public service is also essential for affordable housing and budgeting should not be the excuse of it. Actually, the new construction of facilities is not necessarily the only option. Providing public service at the community level is an alternative approach. Secondly, improving public transport and strength the connections within the area is efficient to improve the accessibility. Related actions are but not limited to, adding new stations, increase the shifts and lines of bus or metro. Last but not least, the allocation of affordable houses and public services should be improved based on the needs of vulnerable groups. The improper distribution of facilities could also lower the accessibility to public services. Acknowledgements. This paper is financially supported by Sichuan Social Science Planning Project, “Research on the theory and method of statistical measurement of provincial resilience in China” (SC18TJ017), together with Research Center Project for social development and social risk control, Sichuan philosophy and Social Sciences Key Research Base, “Research on dynamic assessment method of urban resilience” (SR17A05).

Appendix

Sample Affordable Housing Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10 Sample 11 Sample 12 Sample 13 Sample 14 Sample 15 Sample 16 Sample 17 Sample 18 Sample 19 Sample 20

14

21

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6

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Educational Facilities Less Between Over 60 Score than 30 30 and minutes minutes 60 minutes

21

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51 68

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2 0

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77

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64

83

45

63

61

48

69

30

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15

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27

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11

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19

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17

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81

71

73

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64

66

68

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70 73

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82

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7

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Commercial Facilities Between Over 60 Score Less than 30 30 and minutes minutes 60 minutes

65

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39

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1

39

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18

23

8

12

2

28

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41

3

23

36

6 19

15

27

0

0

0

0

0

0

1

0

0

0

0

0

0

0

0

Cultural and Physical Facilities Less Between Over 60 Score than 30 30 and minutes minutes 60 minutes

1

1

0

0

0

0

0

0

0

0

0

0

1

0

3

0

0

0

0

1

12

10

8

13

7

7

4

8

8

1

3

1

13

9

10

1

9

9

2

13

18

20

23

18

24

24

27

23

23

30

28

30

17

22

18

30

22

22

29

17

45

43

39

44

38

38

35

39

39

32

34

32

46

40

47

32

40

40

33

46

Medical Facilities Less Between Over 60 Score than 30 30 and minutes minutes 60 minutes

5

3

0

3

0

0

0

1

0

1

0

1

3

0

4

0

1

29

25

18

31

15

19

12

13

17

9

13

5

27

20

36

2

17

23

16

0 1

31

2

46

52

62

46

65

61

66

66

63

70

67

74

50

60

40

78

62

56

64

57

119

111

98

117

95

99

90

95

97

91

93

87

113

100

124

82

99

105

96

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Park Facilities Between Over 60 Score Less than 30 30 and minutes minutes 60 minutes

Table 2. Count and score of various facilities accessible to sample affordable housing

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Sample Commercial Housing Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10 Sample 11 Sample 12 Sample 13 Sample 14 Sample 15 Sample 16 Sample 17 Sample 18 Sample 19 Sample 20

10

7

11

15

11

12

11

1

8

5

4

6

1

48

16

17

12

18

18

0

2

4

3

1

7

5

10

7

10

12

3 35

10 9

33

0 32 31 36 29

8

4

4

50

46

9

3

3

9

3

25

79

87

89

76

75

76

95

93

3

27

78

77

82

81

82

87

86

83

79

1

47

83 78

7

9

9

3

6

6

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4

77

33

30

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38

33

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1

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31

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1

9

Cultural and Physical Facilities Less Between Over 60 Score than 30 30 and minutes minutes 60 minutes

Educational Facilities Less Between Over 60 Score than 30 30 and minutes minutes 60 minutes

1

8

5

5

2

2

13

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3

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1

1

2

2

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1

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1

35

30

32

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21

25

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34

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41

32

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30

28

36

30

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9

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82

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12 33

70

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22

7

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83 85

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Commercial Facilities Between Over 60 Score Less than 30 30 and minutes minutes 60 minutes

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0

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18

17

19

21

17

17

17

18

18

18

16

17

17

18

18

13 8

19

19

18

12

10

2 0

12

1

45

48

46

46

43

41

50

51

46

44

44

44

46

48

48

49

44

43

45

45

Medical Facilities Less Between Over 60 Score than 30 30 and minutes minutes 60 minutes

6

4

4

2

1

0

6

7

2

2

0

0

24

17

30

29

28

19

33

34

30

33

31

38

31

30

2 3

38

29

1

7

32

28

2

27

2

27

7

4

50

59

46

49

51

61

41

39

48

45

49

42

46

48

41

44

46

50

46

49

116

105

118

113

110

99

125

128

114

117

111

118

117

114

120

123

116

112

121

115

Park Facilities Between Over 60 Score Less than 30 30 and minutes minutes 60 minutes

Table 3. Count and score of various facilities accessible to sample commercial housing

176 C. Huang and J. Fan

Does Commercial Housing Have Better Access to Public Service

177

Table 4. Group statistics

Educational facilities

Community type

N Mean

Affordable housing

20

Commercial housing 20 Cultural and sports facilities Affordable housing

20

Commercial housing 20 Commercial facilities

Affordable housing

20

Commercial housing 20 Medical facilities

Affordable housing

Park facilities

Std. deviation Std. error mean

38.7

6.86026

1.534

46.45

3.95335

0.884

63.1

11.33184

2.53388

82.15

5.75166

1.28611

68.1

8.54

1.91

86.65

8.293

1.854

20

39.1

4.962

1.11

Commercial housing 20

45.8

2.546

0.569

20 101.8

12.365

2.765

Commercial housing 20 115.6

6.597

1.475

Affordable housing

Table 5. Independent sample t-test results Levene’s Test for Equality of Variances

Educational Facilities Cultural and Sports Facilities Commercial Facilities Medical Facilities Park Facilities

Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed

t-test Equality of Means

F

Sig.

t

df

Sig. (2tailed)

5.427

0.25

-4.337

38

0

-7.75

1.77048

-11.33415

-4.16585

-4.337

30.366

0

-7.75

1.77048

-11.36398

-4.13602

-6.704

38

0

-19.05

2.84158

-24.80249

-13.29751

-6.704

28.18

0

-19.05

2.84158

-24.86904

-13.23096

-6.969

38

0

-18.55

2.662

-23.939

-13.161

-6.969

37.967

0

-18.55

2.662

-23.939

-13.161

-5.372

38

0

-6.7

1.247

-9.225

-4.175

-5.372

28.359

0

-6.7

1.247

-9.253

-4.147

-4.404

38

0

-13.8

3.134

-20.144

-7.456

-4.404

29.004

0

-13.8

3.134

-20.209

-7.391

7.158

0.6

6.754

9.036

0.011

0.809

0.013

0.05

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper

References 1. Apparicio, P., S´eguin, A.M.: Measuring the accessibility of services and facilities for residents of public housing in Montreal. Urban Stud. 43(1), 187–211 (2006) 2. Ben-Akiva, M.E., Lerman, S.R., Lerman, S.R.: Discrete Choice Analysis: Theory and Application to Travel Demand, vol. 9. MIT Press, Cambridge (1985) 3. Benenson, I., Ben-Elia, E., et al.: Estimation of urban transport accessibility at the spatial resolution of an individual traveler. In: Seeing Cities Through Big Data, pp. 383–404. Springer (2017) 4. Bertolini, L., et al.: Sustainable urban mobility, an evolutionary approach. Eur. Spatial Res. Policy 12(1), 109 (2005) 5. Burns, L.D.: Transportation, temporal, and spatial components of accessibility (1980) 6. Chen, J., Lu, F., Cheng, C.: Advance in accessibility evaluation approaches and applications. Progr. Geogr. 26(5), 100–110 (2007) 7. Crook, T., Bibby, P., et al.: New housing association development and its potential to reduce concentrations of deprivation: an english case study. Urban Stud. 53(16), 3388–3404 (2016)

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8. Envall, P.: Accessibility planning: a chimera? Ph.D. thesis, University of Leeds (2007) 9. Fu, Q., Lin, N.: Local state marketism: an institutional analysis of China’s urban housing and land market. Chin. Soc. Rev. 46(1), 3–24 (2013) 10. Geurs, K.T., Van Wee, B.: Accessibility evaluation of land-use and transport strategies: review and research directions. J. Transp. Geogr. 12(2), 127–140 (2004) 11. Hansen, W.G.: How accessibility shapes land use. J. Am. Inst. Planners 25(2), 73–76 (1959) 12. Krizek, K.J., Iacono, M., et al.: Access to destinations: application of accessibility measures for non-auto travel modes (2006) 13. Kwan, M.P., Weber, J.: Scale and accessibility: implications for the analysis of land use-travel interaction. Appl. Geogr. 28(2), 110–123 (2008) 14. Leonardi, G.: Optimum facility location by accessibility maximizing. Environ. Plann. A 10(11), 1287–1305 (1978) 15. Ma, Z., Li, C., Zhang, J.: Affordable housing brings about socio-spatial exclusion in Changchun, China: explanation in various economic motivations of local governments. Habitat Int. 76, 40–47 (2018) 16. Malekzadeh, A.: Measurement of transit network accessibility based on access stop choice behaviour. Ph.D. thesis, Queensland University of Technology (2015) 17. Preteceille, E., Pincon-Charlot, M., Rendu, P.: S´egr´egation urbaine. classes sociales ´ et ´equipements collectifs en r´egion parisienne. Editions Anthropos Preteceille, Edmond and Viet-Depaule, N(forthcoming)‘Dynamiques politiques locales et tendances nationales’, Espaces et Soci´et´es Paris (1986) 18. Zhang, S., Zhang, Y.: Analysis of network accessibility. In: Proceedings of the 4th International Conference on Computer Engineering and Networks, vol. 355. Springer (2015) 19. Van Wee, B.: Accessible accessibility research challenges. J. Transp. Geogr. 51, 9–16 (2016) 20. Widener, M.J., Farber, S., et al.: Spatiotemporal accessibility to supermarkets using public transit: an interaction potential approach in Cincinnati, Ohio. J. Transp. Geogr. 42, 72–83 (2015) 21. Zeng, W., Rees, P., Xiang, L.: Do residents of affordable housing communities in China suffer from relative accessibility deprivation? A case study of Nanjing. Cities 90, 141–156 (2019)

The Identification of Toxic Substances in Some Cosmetic Products Sold in Republic of Moldova Valentina Calmˆ a¸s(B) , Svetlana Fedorciucova, Ghenadie S ¸ pac, and Olga Tabunscic The Academy of Economic Studies of Moldova, 61, Mitropolit Gavriil Bˇ anulescu-Bodoni, 2005 Chisinau, Republic of Moldova [email protected] Abstract. Lipstick is a fat-based makeup product and it is used not only to colour lips, but also to protect them from external influences. The decorative cosmetics market includes a huge range of products. The purpose of this research is to determine the quality and harmlessness of some assortments of lipsticks which are sold in the Republic of Moldova. The research objects are: 8 types of lipsticks (AVON and ORIFLAME). Lipsticks were subjected to organoleptic and physical and chemical research. At the same time, was verified, the correctness of the presented information on the label. The organoleptic indices analysed were: the external appearance and the colour, the homogeneity, the odour, the capacity to cover and the physical-chemical indices IC presence of vitamins A and E, the presence of substances with toxic effect: phenol substances, glycerine and some heavy metals (Cr, Pb, Cu, Fe, Al). The research was carried out using the following methods: empirical research, expertise. Conclusions: of these 8 samples which were analyzed organoleptically, physical-chemical and the correctness of the information prescribed on the label IC none fully corresponds to the prescribed requirements. The closest to being suitable is the product from the Luxe Shape Sensation range, AVON; The One colour lipstick Unlimited, and Giordani gold iconic lipstick (ORIFLAME) contain heavy metals (Cu, Fe). Lux and Lucios Mark Shine Burst lipsticks, AVON do not contain vitamins E and A. Lux lipstick, AVON - contains phenol substances.

Keywords: Lipsticks metals

1

· Quality · Harmlessness · Vitamins · Heavy

Introduction

According to the Sanitary Regulation of the Republic of Moldova about the cosmetic products [3,8], a cosmetic product is any preparation or product intended for application to various parts of the human body (skin, hair, nails, lips) in order to cleanse them, give them a pleasant smell, change their appearance, c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 179–188, 2021. https://doi.org/10.1007/978-3-030-49889-4_16

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protect and keep them in good condition. This document establishes rules and norms for placing on the market of cosmetic products, in order to guarantee the functioning of the internal market and to ensure the protection of human health. Lipstick in this document is determined as a cosmetic product which is applied on the lips [3,8]. The commodity science describes lipstick as a cosmetic product that provides protection and allows lips to be highlighted. Because there are no sebaceous glands in the lip area, they are drier than the rest of the skin. Excessive cold, wind or heat can make them to crack. The saliva does not moisturize the lips, but evaporates from their surface, drying them out even more. These phenomena explain the need of using the lipstick. On the worldwide market for decorative cosmetics, lipstick is one of the most popular products. Currently, in the Republic of Moldova, the cosmetics market is growing rapidly and is represented over 900 items, including lipsticks, produced in 25 countries such as: France, Germany, USA, Poland, Turkey, Russia, Ukraine, Belarus, Baltic States, Asian countries and others. The cosmetic market includes a huge range of lipsticks. There are hygienic, matte and glossy lipsticks, persistent, moisturizing, nourishing, glazed, increasing the volume and others. From the history of lipstick, it is known that even in antiquity, women used the so-called paint or lip colour to highlight them. At the same time, the roman doctor and philosopher Claudius Galen was an ardent opponent of lip coloration due to the addition of toxic pigments [2]. Modern doctors have not put lipstick on the list of prohibited products yet, but even today, choosing this cosmetic product can turn into unpleasant consequences - from lip discomfort to allergies [9]. According to the data from the specialized literature and the normative acts, a qualitative lipstick must meet the following requirements [1,4]:  must not give the feeling of constraint (contracting) of the lips and weight on them;  must not leave traces, spots;  must smoothly lubricate the lips;  must give pleasant sensations on the lips;  the surface of the lipstick must be smooth;  consistency must be tough and durable;  not to melt under the action of the sun’s rays (like ice cream);  not to form agglomerations under the action of low temperatures (cocoons), and not to become “plasticine”;  the maximum term of validity of the lipstick is 3 years if it is kept in the refrigerator and applied with the brush. If applied directly from the product, the validity is 1 year.

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181

The general composition of a lipstick includes the following basic raw materials: – – – –

Castor oil - 65%; Beeswax - 15%; Other waxes - 10%; Lanolin - 5%; Dyes, scented base - 5%.

In addition to the basic ingredients, auxiliary ingredients are added in order to improve the lips skin, stability at retention, hardness and last but not least, for cheapening the product. These include vitamins A, E, C, folic acid, collagen, aloe vera plant extracts, tea tree, chamomile, etc. Capsaicin is also added in some lipsticks, a substance that comes from the hot pepper and is used to obtain a slight inflammation of the lips and increase their volume and/or eusin, a substance that increases the stability, intensifies and darkens the colour of the lipstick [2]. Lipsticks also contain substances that are suspected to be dangerous for human health. This group of substances includes: propylene glycol, mineral oils, parabens, some phenolic substances, heavy metals (Al, Cu, Pb, Mg, Cr and so on) [9]. The toxic effects of the substances that contain these metals are: cancer, reproductive dysfunction, neurological problems (loss of memory, nervousness), muscular and joints problems, cardiovascular disorders, problems with blood pressure, immune system, kidneys, headaches, diarrhea, contact dermatitis, hair loss, hormonal dysfunction [9]. For example, for some metals such as plumbum, the doses considered to be safe are not known. Along with this, petrolatum or glycerine, which is often “hidden” under the name of “mineral oil”, used as a conditioning agent, causes allergic reactions and increases the risk of cancer [9]. Phenols are used as antioxidant and antibacterial substances in many cosmetic products. These, along with parabens and phthalates, lead to many dermatological problems and the early onset of puberty among girls, whose mothers had used cosmetics with these ingredients. Among the natural products that have the property to naturally preserve some types of cosmetic products are: oregano, thyme, rosemary, gentian root, grapefruit seed extract, lavender oil and so on. All these cosmetics are bio and must be stored in the refrigerator. Toxic substances in cosmetics can be even more harmful than food. From the surface of the skin, the cosmetic ingredients reach directly into the blood and then into the whole body, without first passing through the liver and kidneys to be filtered, as happens with the potentially toxic substances found in food [9]. This problem is much better managed in Europe than in America. For example, European law is more restrictive regarding the toxicity of cosmetic ingredients and their dosage and thus better protects human health from the cumulative effects of harmful substances. In the United States, there are not required too many tests before a new cosmetic product is released.

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European legislation which regulates cosmetics products contains 1328 prohibited ingredients in cosmetics products sold in Europe (in the US, from this number of substances only 8 ingredients are prohibited). An extensive research organized by the American Medicines Agency has revealed that no less than 400 types of the most popular lipstick brands contain plumb. Between “contaminated” brands are L’Oreal, Revlon, Avon, Cover Girl, but also luxury brands such as Dior and M.A.C. A product is considered safe if it contains no plumbum at all. The more persistent a lipstick is and the lighter it is, the more plumbum it contains, with a toxic and neurotoxic effect. A UK study shows that women absorb annually, on average, 2.3 kg of toxic substances through the used cosmetic products [2]. Ladies who use lipstick twice a day are predisposed to ingest 24 mg of lipstick, including toxic substances. But there are women who use lipstick 10 times a day, being exposed to 87 mg of lipstick with toxic substances. Other substances found in lipsticks are As, Cd, Hg. These have been associated with lung cancer, liver cancer, diabetes, cardiovascular disease, gastrointestinal diseases, kidney dysfunctions, stomach tumors, memory loss, and allergies. Regarding the product safety, according to the Health Regulation of the Republic of Moldova about the cosmetic products, a cosmetic product placed on the market must be safe for human health when is used under normal or rationally foreseeable conditions of use, taking into account, in particular, the following elements:  presentation (shape, smell, colour, appearance, packaging), respecting the provisions of Law no. 422 on the general product safety [7];  labelling;  instructions for use;  the presence of composition certificates, laboratory test reports, etc. Taking into account the information presented above, the purpose of this research was to study the quality and harmlessness of some assortments of lipsticks sold in the Republic of Moldova. We believe that the results of our research can be useful for domestic consumers and not only. So, informed consumers will be able to be protected from the penetration into the body of harmful substances through cosmetic products. Also, consumers will be informed about the requirements regarding the quality of these products, the organoleptic and express methods of checking the conformity of the goods, as well as knowledge regarding the correct marking and labelling of the cosmetic products. The paper contains abstract, introduction, materials and research methods, results and discussions, conclusions and references. There are three tables in this work that contain the results of our research.

2

Materials and Research Method

As a subject of study have served 8 types of lipsticks, produced by two companies, namely:

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183

AVON (produced in Poland) • • • •

TRUE COLOUR PERFECTLY MATTE LUXE LUXE SHAPE SENSATION LUCIOS MARK SHINE BURST ORIFLAME (produced in Russia)

• • • •

GIORDANI GOLD ICONIC LIPSTICK GIORDANI GOLD ICONIC MATTE LIPSTICK THE ONE COLOUR UNLIMITED LIPSTICK THE ONE COLOUR STYLIST UNLIMITED LIPSTICK

In the Republic of Moldova the quality of decorative cosmetic products obtained on the basis of adipocere (which also includes lipsticks) is determined according to the requirements of the interstate standard GOST 31649-2012 [4]. The following countries participated in the process of elaboration of this standard: Armenia, Belarus, Kazakhstan, Kyrgyzstan, Republic of Moldova and Russia. The eight types of lipstick were examined according to the requirements of this standard, analyzing them organoleptically, some physico-chemical indices and the labelling correctness, which is one of the protection elements of the consumers’ rights and the safety of the products. We have determined the following organoleptic indications of the lipstick: the outer appearance and the colour, the homogeneity, the smell, the covering capacity. Between the physico-chemical indices, we have determinated the presence of beneficial substances in the composition of lipsticks (vitamins A and E), as well we determinated the presence of the substances with toxic effects for the body: phenolic substances, glycerine (petrolatum) and heavy metal cations (Cr, Pb, Cu, Fe, Al). The organoleptic examination of the investigated cosmetic products was achieved according to the requirements of the interstate standard GOST 29188.0-2014: Perfume and cosmetic products. Acceptance rules, sampling, methods of organoleptic testing. The presence of vitamins was determined using qualitative methods [1]:  determining the presence of vitamin A or carotene in lipstick - using concentrated acetic acid saturated with iron (II) sulphate and concentrated sulfuric acid;  determining the presence of vitamin E - using concentrated nitric acid;  the presence of phenolic substances was identified using iron chloride solution (FeCl3);  the presence of glycerine (propylene glycol) in the lipstick was identified using fresh solution of copper hydroxide [Cu(OH)2 ]. The heavy metals in the studied cosmetic products were identified, also, using qualitative methods. The essence of the method: heavy metals are used in the

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production of lipstick for colour stability. Sometimes they are in the form of residues in the dyes used to obtain cosmetics. In order to determine the presence of heavy metals we have used the following qualitative methods:  the presence of iron and copper cations determination - with solution of K4 [Fe(CN)6 ] and FeCl3 ;  determining the presence of Al3+ and Cr3+ ions, using CCl4 and NH4 OH;  the presence of Pb2+ ions was determined using the organic solvent CCl4 , solution of KM with a concentration of 1M. The research was carried out in the laboratories of the department “Trade, Tourism and Catering” of Academy of Economic studies of Moldova.

3

Results and Discussions

The obtained results after the organoleptic and laboratory investigations are presented in Tables 2 and 3, and the results of the labelling verification of AVON and ORIFLAME products are presented in Table 1. According to the requirements of the normative acts, the labelling elements must contain the following information on the product label [5]: Analyzing the content of Table 1, we have found some non-conformity. All 4 AVON products do not require information about the security rules and conditions of storage; bar code; specific information. At 2 lipstick samples (TRUE PERFECT COLOR AND LUCIOS MARK SHINE SHST) is missing the information about the product composition and validity term. The analysis of the labelling of the ORIFLAME products denotes the lack of information in all four samples regarding: security rules and storage conditions; date of manufacture; bar code; indicative of the normative document; specific information. Thus, out of eight products analyzed, none fully corresponds to the requirements of the information presented on their labels. We consider that it is a violation of consumer rights, art. 24 Consumer rights regarding the information and art. 25 Obligations of economic agents regarding the consumer information according to the Law nr.105 on consumer protection [6] and a violation of the Law about the general product safety [7], art. 6/2 Other of producers and distributors. Obligations. According to the requirements of the current normative acts, the organoleptic examination of the lipsticks is represented by: the external appearance and the colour; homogeneity; the smell; coverage capacity. All 8 lipstick samples were tested. The obtained data from the researches is presented in Table 2. The information presented in Table 2 shows that AVON and ORIFLAME products fully comply with the requirements of the normative acts. All the products have a smooth, homogeneous surface, evenly colored. The smell is specific to the product, without the presence of non-specific foreign nuances. The coating is smooth and uniform. Thus, the real organoleptic indices correspond to those prescribed. In addition to the organoleptic determinations, lipsticks were also

The Identification of Toxic Substances

185

Table 1. The results after analyzing the labelling of AVON and ORIFLAME lipstick Product name TRUE LUXE COLOUR PERFECTLY MATTE

LUXE SHAPE SENSATION

LUCIOS MARK SHINE BURST

AVON Name of the producing country

GIORDANI GOLD ICONIC LIPSTICK

GIORDANI GOLD ICONIC MATTE LIPSTICK

THE ONE COLOUR UNLIMITED LIPSTICK

THE ONE COLOUR

STYLIST UNLIMITED LIPSTICK

ORIFLAME +*

+

+

+

+

+

+

+

Name of + manufacturer, importer and exporter, address, telephone

+

+

+

+

+

+

+

The main or + functional destination/scope of the product

+

+

+

+

+

+

+

Security rules and storage conditions

−*

−

−

−

−

−

−

−

Consumption properties

+

+

+

+

+

+

+

+

Certification information

+

+

+

+

+

+

+

+

Net weight

−

−

−

−

+

+

+

+

Product composition

−

+

+

−

+

+

+

+

Product brand +

+

+

+

+

+

+

+

Manufacturing + date

+

+

+

−

−

−

−

−

+

+

−

+

+

+

+

The normative + document/ compliance/ safety mark

+

+

+

−

−

−

−

−

−

−

−

−

−

−

−

Specific − − information +* - The presence of information −* - The absence of information

−

−

−

−

−

−

Term of validity

Bar code

submitted to physico-chemical determinations in order to identify vitamins A and E, phenolic substances, glycerine and toxic metals (copper and iron cations, chromium, aluminium and plumb ions). The research results are presented in Table 3. According to the data presented Table 3, it can be mentioned that not all investigated lipsticks contain vitamins A and E - beneficial substances which increase the consumption properties of these products. Thus, the presence of vitamin A was registered only in 3 products out of 8 (LUXE SHAPE SENSATION, THE ONE COLOR UNLIMITED LIPSTICK, THE ONE COLOR

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Table 2. The results of organoleptic verification of AVON and ORIFLAME lipsticks Indicator name

Exterior appearance and colour

Product homogeneity

The real characteristic

The prescribed characteristic

Smell

Coverage capacity

Smooth, homogeneous surface, uniformly colored

Homogeneous without agglomerations and particles

Specific to the given product

The coating is smooth and uniform

TRUE COLOUR Ointment consistency, PERFECTLY bright pink, with a MATTE smooth surface to the touch

Homogeneous without agglomerations and particles

Specific to the given product

Smooth and homogeneous

LUXE

Ointment consistency, nude colour, with a smooth surface to the touch

Homogeneous without agglomerations

Specific to the given product

Smooth and homogeneous

LUXE SHAPE SENSATION

Ointment form, deep red, with a smooth surface to the touch

Homogeneous without agglomerations and particles

Specific to the given product

Smooth and homogeneous

LUCIOS MARK Ointment structure, Homogeneous SHINE BURST light pink, with bright without particles, with a smooth agglomerations surface to the touch

Specific to the given product

Smooth and homogeneous

GIORDANI GOLD ICONIC LIPSTICK

Ointment structure, nude colour, with bright particles, with a smooth surface to the touch

Homogeneous without agglomerations and particles

Specific to the given product

Smooth and homogeneous

GIORDANI GOLD ICONIC MATTE LIPSTICK

Ointment form, pale pink, with bright particles, with a smooth surface to the touch

Homogeneous without agglomerations and particles

Specific to the given product

Smooth and homogeneous

THE ONE COLOUR UNLIMITED LIPSTICK

Ointment form, brown-red, with bright particles, with a smooth surface to the touch

Homogeneous without agglomerations and particles

Specific to the given product

Smooth and homogeneous

THE ONE COLOUR STYLIST UNLIMITED LIPSTICK

Ointment form, intense pink, with bright particles, with a smooth surface to the touch

Homogeneous without agglomerations and particles

Specific to the given product

Smooth and homogeneous

STYLIST UNLIMITED LIPSTICK), and vitamin E - in 5 products (TRUE COLOR PERFECTLY MATTE, LUXE SHAPE SENSATION, GIORDANI GOLD ICONIC LIPSTICK, GIORDANI GOLD ICONIC MATTE LIPSTICK, THE ONE COLOR UNLIMITED LIPSTICK). The presence of phenolic substances was registered in the LUXE product from AVON, and the presence of glycerin - in all the analyzed products except the LUCIOS MARK SHINE BURST lipstick from AVON. Analyzing the data about the presence of heavy metals, we identified their presence in only 2 products - THE ONE COLOR

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187

Table 3. The results after investigating the presence of different chemicals in AVON and ORIFLAME lipsticks Product name TRUE LUXE COLOUR PERFECTLY MATTE

LUXE SHAPE SENSATION

LUCIOS MARK SHINE BURST

AVON

GIORDANI GOLD ICONIC LIPSTICK

GIORDANI GOLD ICONIC MATTE LIPSTICK

THE ONE COLOUR UNLIMITED LIPSTICK

THE ONE COLOUR

STYLIST UNLIMITED LIPSTICK

ORIFLAME

The presence of vitamin A

-*

-

+

-

-

-

+

+

The presence of vitamin E

+*

-

+

-

+

+

+

-

The presence of phenolic substances

-

+

-

-

-

-

-

-

The presence of glycerine

+

+

+

-

+

+

+

+

The presence of cooper cations

-

-

-

-

-

-

+

-

The presence of iron cations

-

-

-

+

-

-

-

The presence of chromium cations

-

-

-

-

-

-

-

-

The presence of aluminium ions

-

-

-

-

-

-

-

-

-

-

-

-

-

-

The presence of plumbum ions +* - The presence of information -* - The absence of information

UNLIMITED LIPSTICK from ORIFLAME in which was recorded the presence of copper cations and GIORDANI GOLD ICONIC LIPSTICK from ORIFLAME in which was identified the presence of iron cations.

4

Conclusions

(1) 8 types of AVON and ORIFLAME lipsticks sold on the Republic of Moldova market, have been subjected to research. (2) In all 8 lipstick samples there were identified non-conformities regarding the presentation of the information on their label. (3) Organoleptically, all the investigated lipsticks correspond to the requirements of the current normative acts. (4) In the chemical composition of 6 products out of 8, was registered the presence of vitamins A and E, which characterizes them having a positive impact, because these substances are antioxidants that block the fat oxidative processes in the composition of the lipsticks. Lux and Lucios Mark Shine Burst lipsticks, AVON do not contain vitamins A and E.

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V. Calmˆ a¸s et al.

(5) Most of the analyzed products (7 out of 8) contain glycerine (it is a substance with a negative effect) with the exception of LUCIOS MARK SHINE BURST from AVON. (6) The presence of phenolic substances was identified only in one product LUXE from AVON. The presence of these substances is not desired. (7) The investigated products did not record the presence of heavy metals in the form of chromium, aluminium and plumbum ions. (8) The presence of copper and iron cations was identified in the products GIORDANI GOLD ICONIC LIPSTICK and THE ONE COLOR UNLIMITED LIPSTICK from ORIFLAME. As a final conclusion, we can mention that, of the 8 samples examined from the organoleptic, physico-chemical point of view and the correctness of the information prescribed on the label, none of these products fully corresponds to the requirements prescribed by the current normative documents. The closest to being suitable to these requirements is the product from the Luxe Shape Sensation range, AVON.

References 1. Calmˆ a¸s, V., Damaschin, M.: Verificarea conformitˆ a¸tii produselor cosmetic decorative pe bazˆ a de adipocearˆ a ˆın scopul asigurˇ arii calitˆ a¸tii produselor cosmetic ¸si protect¸iei consumatorilor ˆımpotriva produselor contrafˆ acute, ˆIndrumar metodic pentru lucrˆ ari practice ¸si de laborator la disciplina Identificarea falsific˘ arii m˘ arfurilor ¸si protect¸ia consumatorilor. RM, Chi¸sinˆ au, ASEM, pp. 47–60 (2017) 2. Cele mai nicive substant¸e care se g˘ asesc ˆın rujuri. http://suntfericita.manager. no/cele-mai-nocive-substant¸e-care-se-regasesc ˆın rujuri 3. Decision of the Government of the Republic of Moldova No. 1207 of 02-11-2016 for the approval of the Sanitary Regulation on cosmetic products. Published: 11-11-2016 in OFFICIAL MONITOR, No. 388-398. https://www.legis.md/cautare/getResults? doc id=96079&lang=ro 4. GOST 31649-2012 Interstate Standard. Decorative cosmetic products on fatty and waxy basis. General specifications. https://internet-law.ru/gosts/gost/53310/ 5. GOST 28303-89 Perfumery and cosmetics. Packing, marking, transportation and storage. http://docs.cntd.ru/document/gost-28303 6. LAW of the Republic of Moldova No. 105 of 2003-03-13 on consumer protection. Posted: 2003-06-27 in OFFICIAL MONITOR No. 126-131. https://www.legis.md/ cautare/getResults?doc id=110237&lang=ro 7. LAW of the Republic of Moldova No. 422 of 2006-12-22 on the general product safety. Posted: 2007-03-16 in OFFICIAL MONITOR No. 36-38. https://www.legis. md/cautare/getResults?doc id=106998&lang=ro 8. Regulation(EC) No 1223/2009 of the European parliament and of the conuncil of 30 November 2009 on cosmetic products 9. Top-25-cele-mai-d?unatoare-ingrediente. http://www.clict.no/utile/sanatate/ substante periculoase rujuri inimafericita. no 2015/01/21/top-25-cele-maid˘ aunatoare-ingrediente

Renewable Energy Consumption-Economic Growth Nexus: Empirical Evidence from Morocco Mounir El-Karimi and Ahmed EI Ghini(B) LEAM, Faculty of Law, Economics and Social Sciences-Souissi, Mohammed V University, Rabat, Morocco [email protected], [email protected]

Abstract. This paper investigates the causal nexus between renewable energy consumption and economic growth in Morocco by incorporating capital and labour as main factors of production function. This study applies Toda and Yamamoto (1995) causality test on annual data covering the period 1980–2016. On one hand, the results gained from the causality analysis reveal that capital significantly affects the economic growth while labour has not important impact on growth. On the other hand, the findings display that there is no significant causality relationship between renewable energy consumption and economic growth. Our conclusion shows evidence of the neutrality hypothesis within the energy consumption-economic growth literature. This could probably be explained by the uneven and insufficient exploitation of renewable energy sources in Morocco.

Keywords: Renewable energy consumption Granger causality

1

· Economic growth ·

Introduction

The development processes in all countries are extremely dependent on the energy sector, and the global demand for energy is rising along time. Traditional sources of energy such as oil, coal, and natural gas are viewed to be the most effective factors of economic growth [1,10]. Economic and Social developments in the last decades have sharply raised the demand for primary energy [6]. However, the global dependence on primary energy sources has raised many global issues. Nowadays, security of energy supply, energy price shocks, large dependency on foreign energy sources, non-renewable characteristic of each of oil, coal, and natural gas as energy sources and global warming constitute heavy global issues [25]. These issues prompted many countries to look for alternative energy sources, namely renewable and clean energy sources [2,9]. In this framework, the generation and technologies of renewable energy have become the focus c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 189–199, 2021. https://doi.org/10.1007/978-3-030-49889-4_17

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of the energy policy. According to the International Energy Agency (IEA), the global electricity production from renewable sources is expected to increase at a rate of 39% by 2050. Many countries, such as Morocco, are now investing more in their renewable energy sectors and supporting them with diverse national policies. The later covers subsidies, discounts for installing renewable energy mechanisms, tax reduction for renewable energy supply, and creating markets for renewable energy certificates to diversify the energy mix [4,10,26]. The increasing trend in the global energy sector has raised the concern about the relationship between renewable energy consumption (REC) and economic growth. Domac et al. [13] argue that bio-energy should help increase the economic efficiency through the creation of employment and a number of economic gains. Awerbuch and Sauter [7] state that REC positively affects the economic growth through providing energy supply security and then reducing the negative effects of higher oil price volatility. The investigation of the REC-economic growth relationship has been the subject of several studies that investigate diverse countries and regions. The first group of studies finds a bidirectional causal link between REC and Gross domestic Product (GDP) growth. This kind of relationship represents the feedback hypothesis, which means that the REC and economic growth are jointly determined and affect each other. The second group of studies concludes that there is one way causal effect from REC to GDP growth. This nature of relationship represents the growth hypothesis, which expresses that energy conservation policies on energy consumption affect the economic growth level. The third group of studies identifies a one way causal impact from GDP growth to REC. The relationship is named the conservation hypothesis. This reflects that energy conservation policies could exert a weak or no effect on the economic growth. The forth group of studies finds no causal nexus between REC and GDP growth. This type of relationship is called the neutrality hypothesis, which explains that energy conservation policies do not significantly affect the economic growth. Table 3 in Appendix provides some studies that investigated the growth-renewable energy relationship in different countries and regions. This paper aims to examine which of the four aforementioned hypotheses is apparently confirmed, based on the considered data, in the case of Morocco. The remainder of the paper is organized as follows. In Sect. 2, we present an overview of the renewable energy in Morocco. Section 3 introduces Toda and Yamamoto (1995) test for Granger causality. Section 4 describes the data and discusses the empirical results. Finally, Sect. 5 concludes our findings.

2

Overview of the Renewable Energy in Morocco

Electricity demand in Morocco has experienced substantial increase last years. According to IEA (2014) [16], energy consumption has grown annually at an average rate of 6.5% over the period 2002–2014 due to the economic growth, population growth, and rise in energy consumption per capita. This rise in energy consumption was also owed to considerable investments carried out in a number

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of electrification projects. The later allowed the country to achieve a rate of 99.5% of electricity access in 2015, which is a great development given that the rural electrification level was amounted only at 18% in 1995 [11] (Table 1). Table 1. Renewable energy potential in North Africa Type of resource

Morocco

Tunisia

Algeria

Egypt

Libya

Solar radiation 1800–2550 (kWh/m2 /year)

1500–1900

1700–2600

2000–3000

2590–2960

Wind (m/s)

4.7–10.4

7–10

>4

6–11

6–11

Hydro

2500 MW. Good Good potential for Low potential potential for small small and medium and mini-hydro projects in three sites

Big potential only Not discovered for large hydro

Geothermal

Substantial potential in the Northeast

Potential for Not discovered development of geothermal energy along Gulf of Suez and Red Sea

Biomass

3M tons per year from urban domestic wastes

Limited to direct utilization

Confirmed capacity >700 MW

>30M tons per 3.7M of TOE a 63M tons per year year from organic from forests, and from agriculture 1.33M of TOE per and urban wastes wastes year from agriculture and urban wastes

2 TWh/year from biomass. Inadequate for large scale power generation

a

Tons of oil-equivalent Note: Source: Hawila et al. [15]

The development of electricity generation from renewable sources has experienced a number of successive steps. As early as 1994, Decree Law No. 294-503 allowed the development of independent electricity generation above 10 megawatts (MW) under contract with the National Electricity Agency (ONE), fostering the emergence of the country’s first wind farms. In 2008, Law 1608 increased the self-production threshold from 10 MW to 50 MW. In 2012, electricity generation from renewable sources was 2359 gigawatt-hours (GWh), representing 8.6% of total generation after being 10.8% in 2011. During the decade 2002–2012, the share of hydropower in domestic production was 7.6% on average. It decreased by 18.7% from 2011, down to 1 631 GWh in 2012, while wind power increased by 5.2%, up to 728 GWh. Other sources of renewable energy are still negligible. In 2009, the creation of the Moroccan Agency for Solar Energy (MASEN) and the transformation of the Centre for Renewable Energy Development into the National Agency for Renewable Energies and Energy Efficiency (ADEREE), provided renewed impetus. In parallel, Law 13-09 removed the power ceiling for renewable energy facilities which is previously limited to 50 MW. Fig. 2 in Appendix reports the share of renewable in electricity generation since 2000. According to the government estimates, the share of renewable energies in total installed electrical power would be amounted at 42% by 2020, where 20% from wind, 20% from solar, 12% from hydro (see Fig. 1). Reaching this goal is meant allow savings of 2.5 million tons of oil-equivalent (TOE) in fossil

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fuels and avoiding the emission of 9 million tons (Mt) of CO2 . Over the COP21 Conference in Parties, Morocco stated that the new objective is to rise the renewable energy capacity to 52% by 2030, where 20% from wind, 20% from solar, and 12% from hydro (see Fig. 1). Achieving this goal would allow Morocco to be the first African country that intends to achieve more than 50% electricity generation coming from renewable energy sources [12]. The announced goal is aimed because the country owns a high potential of solar and wind resources and plays an essential role in the Euro-Mediterranean energy hub, where the country is a member in many regional projects facilitating synergy as Project Med Grid [16].

Fig. 1. Moroccan energy mix aimed during 2020–2030 (Data source: High Commission for Planning (2016))

3

Methodology

A number of researchers have been focused on the analysis of the causality relationship that is defined by Granger [14]. It was to detect dependencies between two variables more precisely than those traditionally identified by the correlation. Indeed, if a variable causing another variable, both variables must necessarily be correlated but if two variables are correlated does not mean that one necessary causes other. Toda and Yamamoto [27] introduced an interesting yet simple procedure requiring the estimation of an augmented VAR model. Their approach allows overcoming the limitations related to the power and size properties of conventional unit root tests in testing for Granger-causality. In order to minimize the limitations that could be result from considering the series at first or second differences as perfect stationary process, the Toda and Yamamoto [27] procedure specifies a VAR model in levels. The correct lag order p in the VAR model is augmented by the maximum order of integration d of the variables.

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As a consequence, the test statistics for Granger-causality have the standard asymptotic distribution to draw valid inferences. Toda and Yamamoto (1995) procedure is used in a number of empirical studies [22,30,31]. 3.1

Toda and Yamamoto (1995) Test

Let (xt ), (yt ), (zt ), and (ut ) four time series which are not necessary stationary as it was considered in the conventional causality tests. Let p the lag length of VAR model for (xt , yt , zt , ut ) in level and d the maximum integration degree of (xt , yt , zt , ut ) . The Toda and Yamamoto (1995) test of causality from (yt ) to (xt ) conditionally to (zt ) and (ut ) is based on estimating the following augmented VAR(p + d) model for the time series vector (xt , yt , zt , ut ) in level: ⎤ ⎡ ⎤ ⎡ ⎤ ⎡ ⎤ μ1 ε1,t xt−i xt p+d ⎢ yt ⎥ ⎢ μ2 ⎥  ⎢ yt−i ⎥ ⎢ ε2,t ⎥ ⎥ ⎢ ⎥ ⎢ ⎥=⎢ ⎥+ Θi ⎢ ⎣ zt−i ⎦ + ⎣ ε3,t ⎦ , t = 1, ..., T , ⎣ zt ⎦ ⎣ μ3 ⎦ i=1 ut μ4 ut−i ε4,t ⎡

(1)

where μ1 , μ2 , μ3 , and μ4 are real parameters, Θi are 4 × 4 matrix of real parameters and the error vector (ε1,t , ε2,t , ε3,t , ε4,t )’ is i.i.d.N (0, ). The null hypothesis of no causality from (yt ) to (xt ) conditionally to (zt ) and (ut ) can be expressed as the coefficients of yt−1 , yt−2 ,..., yt−p in the equation of xt in Eq. (1) being equal to zero, ie. Θi,(1,2) = 0, i = 1, , p. Note that, according to Toda and Yamamoto [27], the d additional coefficients of yt−(p+1) ,..., yt−(p+d) are virtual and artificially included in the VAR model only to make the statistic for Granger-causality have the standard asymptotic distribution and draw valid inferences.   Let S1 = (1, 0, 0, 0) and S = Ip ⊗(0, 1, 0, 0) with Ip being the identity matrix of order p. According to Toda and Yamamoto [27], the following Wald statistic W has χ2 distribution with p degrees of freedom:



ˆ ∗ (S  ⊗ S  ) W = T (S 1 ⊗ S  )Θ 1

∧ 

−1 (S 1 ⊗ S  )

ˆ∗, (S 1 ⊗ S  )Θ

(2)

ˆ ∗ = vec(Θ) ˆ is a column vector obtained by stacking the rows of Θ ˆ matrix, where Θ ∧ ˆ is the ordinary least squares estimator of Θ = (Θ1 , .., Θp ), and is such as Θ 1 ˆ − Θ) . a consistent estimator of the asymptotic covariance matrix of T 2 vec(Θ In summary, two steps are involved with implementing the Toda and Yamamoto (1995) procedure. The first step includes the determination of the lag length p and the second one is the selection of the maximum order of integration d for the series (xt ), (yt ), (zt ), and (ut ). Measures such as the Akaike Information Criterion (AIC), Schwarz Information Criterion (SC), Final Prediction Error (FPE) and Hannan-Quinn (HQ) Information Criterion can be used to determine the appropriate lag order of VAR model.

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Econometric Model

The theoretical approach in this study lies with the economics of production. To represent a nexus between production inputs and output, a Cobb-Douglas production function including renewable energy consumption along with traditional inputs1 can be explained as follows [8,17]: Y = A.REC α .K β .Lγ ,

(3)

where Y is the output, REC is the renewable energy consumption, K is the capital input, L is the labour input, A is the total factor productivity, and α, β, and γ are real parameters. Several studies apply the log transformation to Eq. (3) [8,17], as each resulting coefficient in the transformed equation can be interpreted as elasticity. The obtained equation is developed as follows: Ln(Y ) = Ln(A) + αLn(REC) + βLn(K) + γLn(L),

(4)

In our econometric study, we firstly estimate a four-dimensional VAR model for the vector (GDPt , RECt , Kt , Lt ). In the subsequent, we examine the causality relationship between REC and GDP by implementing the Toda and Yamamoto (1995) test and focusing on the following autoregressive equations associated to GDPt and RECt : GDPt = a1 +

p+d 

θ11,k GDPt−k +

k=1

p+d 

θ12,k RECt−k +

k=1

p+d 

θ13,k Kt−k +

k=1

p+d 

θ14,k Lt−k + ε1,t ,

k=1

(5) RECt = a2 +

p+d  k=1

θ21,k GDPt−k +

p+d 

θ22,k RECt−k +

k=1

p+d  k=1

θ23,k Kt−k +

p+d 

θ24,k Lt−k + ε2,t ,

k=1

(6) where GDPt , RECt , Kt and Lt represent economic growth, renewable energy consumption, capital, and labour at t, respectively, in natural logarithms. The error vectors ε1,t and ε2,t are white noises with zero mean and positive definite covariance matrices, and a1 and a2 are reals. It is worth mentioning that the Granger causality running from each of K and L to GDP can be examined in a similar way.

4

Data and Empirical Results

In this paper, we use the Toda and Yamamoto (1995) [27] causality test to examine the causal relationship between renewable energy consumption and real 1

We do not consider other additional variables because our focus is to examine the effect of renewable energy input on the economic growth.

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Table 2. The results of the Granger causality analysis Toda and Yamamoto (1995) test with p = 1 and d = 2

Toda and Yamamoto (1995) test with p = 3 and d = 2

Null hypothesis Wald statistic p-value

Wald statistic p-value

REC  GDP

0.86

0.029

GFCF  GDP 4.400**

0.04

3.100*

0.08

LF  GDP

0.7

2.500

0.11

0.100 0.150

0.86

GDP  REC 0.150 0.7 0.001 0.97 Note: A  B indicates that A does not cause B. “**” and “*” indicate the significance at the 5% and 10% levels, respectively.

GDP within a multivariate framework by including measures for capital and labour. The study is based on annual data covering the period from 1980 to 2016. Renewable energy consumption (REC) data measured in billion kilowatt-hours (Bkwh) are obtained from the US Energy information administration (EIA). It represents energy consumption related to hydroelectric power, geothermal, solar, wind, and biomass. We use real GDP expressed in Moroccan dirham (MAD) and measured in base year 2010, as proxy for economic growth. The real GDP data are obtained from World Development Indicators database (WDI) of the World Bank. In addition, we employ labour force (LF )2 as proxy for labour, and real gross fixed capital formation (GFCF) as proxy for capital. LF and GFCF are expressed, respectively, in the number of person and constant MAD 2010. Both LF and GFCF data are obtained from WDI database of the World Bank. Because LF data are provided only for the period from 1990 to 2016, hence the data related to the period from 1980 to 1989 are collected from the Data Market repository (www.datamarket.com). The graphs of the aforementioned series are shown in Fig. 3 in Appendix. In our study, all series are taken in natural logarithms. In order to determine the maximum order of integration required by Toda and Yamamoto (1995) approach, ADF and KPSS tests are used. These later indicate that real GDP, real GFCF, and REC series are I(0), while LF series is I(2). As a result, Toda and Yamamoto (1995) test is implemented with the maximum order of integration d = 2. As for the lag order selection of the VAR model in level, SC criterion indicates p = 1 as the optimal lag length while other criterions show p = 3. To make the results robust to the choice of lag selection criterion, we implement the Toda and Yamamoto (1995) test within two augmented VAR(p + d) models: a first one is estimated with the lag order p = 1, and a second one is estimated with p = 3. The white noise assumptions are confirmed in both augmented VAR(p + d) by using the portmanteau tests and ARCH test. Table 2 reports the results obtained by implementing the Toda and Yamamoto (1995) test for both lags p = 1 and p = 3, respectively. The findings conclude that there is no significant Granger causality (GC) neither from REC to 2

The sum of persons in employment plus persons in unemployment.

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real GDP nor from the later to the former. In addition, the results indicate that GF CF significantly Granger-causes the real GDP while the Granger causality from LF to real GDP is shown no significant. As a consequence, on one hand, our econometric approach emphasizes that the economic growth in Morocco seems to be not empirically affected by the level of renewable energy consumption. Thus, our study shows evidence of the neutrality hypothesis within the energy consumption-economic growth literature. On the other hand, Morocco’s economic growth appears to be significantly influenced by capital level, while it is not substantially affected by labour.

5

Conclusion

This study uses Toda and Yamamoto (1995) causality test to perform the analysis of the causality relationship between renewable energy consumption and economic growth in Morocco during the period 1980–2016. The results do not confirm causality relationship between renewable energy consumption and GDP, suggesting evidence of the neutrality hypothesis. This finding could be partly explained by the uneven and insufficient exploitation of renewable energy sources in Morocco. Since 2013, considerable increase in renewable energy generation is observed in Morocco due to the recent rise of investments in renewable energy sector. However, the extent of renewable energy production does not meet the country’s challenges because many renewable energy projects are still under construction. The completion of the recent renewable energy projects in the near future will allow Morocco to benefit from its geographical advantages that favor a high production of green energy. In order to promote generation of energy from renewable sources, Morocco liberalized the local energy market and founded a number of organizations for managing the implementation, funding, and monitoring. In this context, Morocco has adopted a renewable energy development model founded on a public-private partnership in which the private sector brings its know-how to make projects operational and more efficient.

Appendix

Table 3. Summary of studies on GDP-renewable energy consumption relationship Source: compiled by the authors Author

Time period Country

Causality results

Menegaki and Ozturk [20] 1997–2009

MENA countries

GDP ⇒ REC

Tugcu et al. [29]

1980–2009

G-7 countries

GDP ⇔ REC

Apergis et al. [5]

1984–2007

Mixed countries

GDP ⇔ REC

Menegaki [19]

1997–2007

Europe

GDP  REC

Apergis and Payne [4]

1985–2006

Central America

GDP ⇔ REC

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Table 3. (continued) Author

Time period Country

Causality results

Apergis and Payne [3]

1992–2007

Eurasia

GDP ⇔ REC

Menyah and Rufael [21] 1960–2007

US

GDP ⇒ REC

Apergis and Payne [2]

1985–2005

OECD

GDP ⇔ REC

Sadorsky [25]

1994–2003

Emerging countries

GDP ⇔ REC

Payne [24]

1946–2006

US

GDP  REC

Tugcu and Topcu [28]

1980–2014

G7 countries

GDP  REC in the US, Japan, and UK. REC ⇒ GDP in Germany, Canada, France, and Italy

Adams et al. [1]

1980–2012

30 Sub-Saharan African countries

REC ⇒ GDP

Maji and Sulaiman [18] 1995–2014

West African countries

REC ⇒ GDP

Ozcan and Ozturk [23]

17 emerging countries

GDP  REC in 16 cases

1990–2016

38 top renewable REC ⇒ GDP in 57% of energy consuming the countries countries Note: “⇔” indicates a bi-directional causal relationship, “⇒” indicates a one way causal relationship, and “” indicates no causal relationship. Source: compiled by the authors. Bhattacharya et al. [8]

1991–2012

Fig. 2. Annual shares of renewable energy in total electricity generation in Morocco between 2000 and 2014 (Data source: International Energy Agency)

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Fig. 3. Annual data series for real GDP, REC, real GFCF, and LF in Morocco between 1980 and 2016

References 1. Adams, S., Klobodu, E.K.M., Apio, A.: Renewable and non-renewable energy, regime type and economic growth. Renew. Energy 125, 755–767 (2018) 2. Apergis, N., Payne, J.E.: Renewable energy consumption and economic growth: evidence from a panel of oecd countries. Energy Policy 38(1), 656–660 (2010) 3. Apergis, N., Payne, J.E.: Renewable energy consumption and growth in eurasia. Energy Econ. 32(6), 1392–1397 (2010) 4. Apergis, N., Payne, J.E.: The renewable energy consumption-growth nexus in central America. Appl. Energy 88(1), 343–347 (2011) 5. Apergis, N., Payne, J.E., Menyah, K., Wolde-Rufael, Y.: On the causal dynamics between emissions, nuclear energy, renewable energy, and economic growth. Ecol. Econ. 69(11), 2255–2260 (2010) 6. Aslan, A., Apergis, N., Yildirim, S.: Causality between energy consumption and gdp in the us: evidence from wavelet analysis. Front. Energy 8(1), 1–8 (2014) 7. Awerbuch, S., Sauter, R.: Exploiting the oil-gdp effect to support renewables deployment. Energy Policy 34(17), 2805–2819 (2006) 8. Bhattacharya, M., Paramati, S.R., Ozturk, I., Bhattacharya, S.: The effect of renewable energy consumption on economic growth: evidence from top 38 countries. Appl. Energy 162, 733–741 (2016) 9. Bilgili, F., Ozturk, I.: Biomass energy and economic growth nexus in G7 countries: evidence from dynamic panel data. Renew. Sustain. Energy Rev. 49, 132–138 (2015) 10. Bowden, N., Payne, J.E.: Sectoral analysis of the causal relationship between renewable and non-renewable energy consumption and real output in the us. Energy Sources Part B 5(4), 400–408 (2010)

Renewable Energy Consumption-Economic Growth Nexus

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11. Choukri, K., Naddami, A., Hayani, S.: Renewable energy in emergent countries: lessons from energy transition in Morocco. Energy Sustain. Soc. 7(1), 25 (2017) 12. Council, C.E.: Clean Energy Australia Report. Clean Energy Council, Melbourne (2015) 13. Domac, J., Richards, K., Risovic, S.: Socio-economic drivers in implementing bioenergy projects. Biomass Bioenergy 28(2), 97–106 (2005) 14. Granger, C.W.: Investigating causal relations by econometric models and crossspectral methods. Econom.: J. Econom. Soc. 37, 424–438 (1969) 15. Hawila, D., Mondal, M.A.H., Kennedy, S., Mezher, T.: Renewable energy readiness assessment for north african countries. Renew. Sustain. Energy Rev. 63, 128–140 (2014) 16. IEA: Energy policies beyond IEA countries: Morocco 2014. IEA (2014) 17. Inglesi-Lotz, R.: The impact of renewable energy consumption to economic growth: a panel data application. Energy Econ. 53, 58–63 (2016) 18. Maji, I.K., Sulaiman, C.: Renewable energy consumption and economic growth nexus: a fresh evidence from west africa. Energy Reports 5, 384–392 (2019) 19. Menegaki, A.N.: Growth and renewable energy in Europe: a random effect model with evidence for neutrality hypothesis. Energy Econ. 33(2), 257–263 (2011) 20. Menegaki, A.N., Ozturk, I.: Renewable energy, rents and gdp growth in mena countries. Energy Sources Part B 11(9), 824–829 (2016) 21. Menyah, K., Wolde-Rufael, Y.: CO2 emissions, nuclear energy, renewable energy and economic growth in the us. Energy Policy 38(6), 2911–2915 (2010) 22. Ocal, O., Aslan, A.: Renewable energy consumption-economic growth nexus in Turkey. Renew. Sustain. Energy Rev. 28, 494–499 (2013) 23. Ozcan, B., Ozturk, I.: Renewable energy consumption-economic growth nexus in emerging countries: a bootstrap panel causality test. Renew. Sustain. Energy Rev. 104, 30–37 (2019) 24. Payne, J.E.: On the dynamics of energy consumption and output in the us. Appl. Energy 86(4), 575–577 (2009) 25. Sadorsky, P.: Renewable energy consumption and income in emerging economies. Energy Policy 37(10), 4021–4028 (2009) 26. Salim, R.A., Hassan, K., Shafiei, S.: Renewable and non-renewable energy consumption and economic activities: further evidence from oecd countries. Energy Econ. 44, 350–360 (2014) 27. Toda, H.Y., Yamamoto, T.: Statistical inference in vector autoregressions with possibly integrated processes. J. Econom. 66(1–2), 225–250 (1995) 28. Tugcu, C.T., Topcu, M.: Total, renewable and non-renewable energy consumption and economic growth: revisiting the issue with an asymmetric point of view. Energy 152, 64–74 (2018) 29. Tugcu, C.T., Ozturk, I., Aslan, A.: Renewable and non-renewable energy consumption and economic growth relationship revisited: evidence from G7 countries. Energy Econ. 34(6), 1942–1950 (2012) 30. Wei, Y.: The informational role of commodity prices in formulating monetary policy: a reexamination under the frequency domain. Empirical Economics 49(2), 537–549 (2015) 31. Yamada, H.: A note on the causality between export and productivity: an empirical re-examination. Econ. Lett. 61(1), 111–114 (1998)

Construction of Evaluation Index System for the Ecological Civilization in Rural Tourism Destinations Hanmei Zheng, Qifeng Yin, Xiaoping Li, and Xiaowen Jie(B) Sichuan University, Chengdu 610065, People’s Republic of China [email protected] Abstract. The evaluation of ecological civilization construction is of great significance to promote the sustainable development of rural tourism destinations. Based on the research on sustainable development, ecological civilization construction and tourism evaluation at home and abroad, this paper sorts out 60 indicators to evaluate the ecological civilization construction of the rural tourism destinations. Try to build a six-dimensional comprehensive evaluation index system of rural characteristics, management system, ecological environment, ecological economy, infrastructure and public services, and rural civilization through AHP method, and evaluate the construction of ecological civilization in rural tourism destinations. Finally taking Jiuzhaigou county as the research object to carry on the empirical analysis, puting forward the corresponding improvement suggestions.

Keywords: Ecological civilization construction index · Rural tourist destination

1

· The evaluation

Introduction

Since the mid-1990s, with the continuous increase of China’s per capita disposable income, the number of leisure agriculture and rural tourism in China has been increasing year by year, and rural tourism has been developing vigorously, which has greatly promoted the development of rural tourism destinations. With the increasing intensity of social and economic activities in rural tourism destinations, a large number of tourists flood into the countryside, which not only promotes the development of local economy, but also brings many negative effects to the countryside. Driven by urbanization and commercialization, the original social culture of rural tourism destination is greatly impacted by foreign culture. The original production structure has changed, a series of ecological problems such as biodiversity reduction, resource decline, soil erosion and frequent natural disasters have become increasingly prominent. The problems of rural ecological environment caused by household pollution and the extensive management of township enterprises and agriculture are becoming more and more serious. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 200–214, 2021. https://doi.org/10.1007/978-3-030-49889-4_18

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The changes from environmental protection in the 1980s, sustainable development in the 1990s, and ecological civilization construction in the 21st century reflect China’s in-depth thinking and exploration of environmental issues. At the 18th national congress of the communist party of China (CPC), it was proposed to vigorously promote ecological progress and make comprehensive arrangements for it. The related institutional policies and theoretical studies of ecological civilization are also constantly being improved. Establishing the evaluation index of ecological civilization construction is an important content of ecological civilization construction, and it is also an important measure to ensure the soundness and sustainability of ecological civilization construction. Establishing a set of evaluation index system that can objectively evaluate the current status of ecological civilization construction in rural tourism destinations and having the value of promotion and application, which incorporating the resource consumption, environmental damage and ecological benefits into the evaluation system of economic and social development, will be helpful for rural tourism destinations to understand and grasp the deficiencies of current development, and to find realistic ways to improve the overall environmental quality of rural tourism destinations. The research purposes of this paper are as follows: (1) Construct an evaluation index system for the construction of an ecological civilization in rural tourism destinations by analytic hierarchy process (2) use a combination of qualitative and quantitative methods to evaluate the construction of an ecological civilization in rural tourism destinations. The general framework of this paper is as follows: first, the key problems and literature review in Sect. 2. Section 3 is the main part by introducing the index construction, weight determination and grade. Section 4, takes Jiuzhaigou as an example to make an empirical analysis, and puts forward suggestions on the construction of ecological civilization in Jiuzhaigou. Section 5 concludes with a summary.

2

Research on Ecological Civilization Construction Index System

The evaluation of rural tourism destination ecological civilization is a special evaluation type based on the evaluation of ecological civilization. At present, there are few systematic studies on the evaluation of ecological civilization construction in rural tourism destinations. However, there are still some researches that can be used for reference mainly includes the research on the evaluation of sustainable development and ecological civilization at home and abroad, the practical exploration made by the Chinese government on the evaluation of ecological civilization construction, and the related research on the evaluation of tourist destinations.

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Overseas Research on Sustainable Development

Based on the Pressure-State-Response model (PSR model) proposed by the OECD in 1996, CSD expanded to form a sustainable development driving forceState-Response model (DSR model). In the framework of four major, including economic, social, environmental, and institutional frameworks for sustainable development, 134 indicators were sorted out according to the content of Agenda 21, which covered four aspects-social indicators (41), economic indicators (23), environmental indicators (55), capacity building (15), basically summarized the possible characterization indicator system, and provided a most basic system basis for the sustainable development indicator system. The OECD [8] published the paper “Towards Green Growth: Monitoring Progress Paper prepared by the OECD” in 2011 to build a comprehensive measurement framework of production, consumption, policy and environment. The indicator system basically covered the main aspects of Green economic Growth and established an indicator system to monitor Green Growth. 2.2

Exploration on the Evaluation of Ecological Civilization Construction by Chinese Government

In 1996, the State Council of China agreed to a circular by the state planning commission and the state science and technology commission on further promoting the implementation of the (China Agenda 21) guidelines, which stated that “regions and departments with conditions may formulate an indicator system for sustainable development based on the actual situation and pilot it in their own regions and departments”. The publication of the guideline has greatly promoted the research and implementation of the sustainable development indicator system by Chinese government departments. To promote the construction of ecological civilization, the state administration of forestry and forestry has successively issued a number of documents and compiled several evaluation indicator systems for the construction of ecological civilization for multi-level administrative units [6,7]. In 2014, the policy document “National ecological civilization construction demonstration villages indicator (trial) (environment and development [2014] no. 12)” [4] combed for 18 indicators, and 21 indicators for assessment of villages and towns from production development, good ecology, rich life and rural civilization four aspects, providing a reference model to rural primary evaluation of the construction of ecological civilization. In 2019, the latest revision of the “National ecological civilization construction demonstration cities and counties indicators (ring ecology [2019] no. 76)” [5] combed the 40 indicators from the ecological system, ecological security and ecological space, ecological economy, ecological life, ecological culture to evaluate six aspects, providing the latest measure for the rural ecological civilization construction, and the basic reference for the rural tourism destination ecological civilization construction.

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Research on Rural Tourism Destination Evaluation

Rural tourism destination evaluation studies focus on rural tourism destination evaluation, rural tourism destination comprehensive evaluation, rural tourism comprehensive evaluation, rural tourism catering service quality evaluation. Brohman [1] discusses the environmental destruction, and rising cultural alienation that tourism brings to local areas. It is believed that the sustainable development of emerging third world tourism needs the guidance of national governments to establish institutional mechanisms in terms of tourism planning and encourage the community participation. Zheng [10] believes that the evaluation dimensions of rural tourism destinations include geographical environment, economic basis, landscape characteristics and rural atmosphere. Ma and Chen [3] believes that dimensions of comprehensive evaluation of rural tourism destinations include local characteristics, development environment, management level and growth ability. Liu [2] believes that the dimensions of the comprehensive evaluation of rural tourism include rural tourism development ability, rural tourism development management ability and rural tourism development environment quality. Yang and Ma [9] believes that the evaluation dimensions of tourism catering service quality in rural tourism destinations include service quality, health safety, rural flavor, food quality, entertainment experience and additional services. Such related researches on the evaluation of rural tourism destination provide theoretical support for the construction of the evaluation indicator system of rural tourism destination ecological civilization.

3 3.1

Construction of Indicator System Preliminary Design of Evaluation Indicator Framework

Through literature review, it is found that there is no unified standard for the construction of ecological civilization in rural tourism destinations at present, and the evaluation contents basically include such elements as politics, society, economy, environment and resources. Overall, the development of rural tourism destinations needs to take ecological, economic and social benefits into consideration. Based on the above the principle and train of thought of indicator construction, rural tourism destination set for ecological civilization construction of “local color”, “management system”, “ecological environment”, “ecological economy”, “infrastructure and public service”, “local custom civilization” six primary evaluation indicator, to build a “characteristics - the system - environment - economy - service - governance” six dimensions comprehensive evaluation indicator system framework. The second-level indicators are initially refined into 14 assessment levels, and the third-level indicators are divided into qualitative indicators and quantitative indicators, with a total of 73.

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Optimization of Evaluation Indicators

The evaluation of ecological civilization construction in rural tourism destinations is a systematic comprehensive evaluation, which involves tourism, ecology, economy, management and other aspects. In order to ensure the rationality and representativeness of the indicators, 40 experts were invited on the basis of the initial screening indicators to evaluate each indicator in terms of relevance, clarity and importance. The 40 experts came from the four fields of tourism, ecology, economy and management, with 10 experts in each field to jointly evaluate the ecological civilization construction of rural tourism destinations. Considering that the expert opinions of different majors may be different, when summarizing the expert opinions, giving priority to the advice of experts in the field where the indicators are in (Table 1). Table 1. Indicator evaluation description Item

Scale 4

3

Correlation Very good

5

Good

So so Bad

Very bad

Relevance

Good

So so Bad

Very bad

Very good

2

1

Importance Very important Important So so Not important Not very important Correlation: whether the indicator conforms to the definition and description of the assessment objective; Relevance: whether this indicator is easy to understand; Importance: whether this indicator captures the main points of the assessment is representative.

(1) Elimination of indicators The exclusion of indicators mainly considers the relevance and importance of indicators. According to the expert score, the indicators with relevance and importance lower than 3 points were considered and removed. To find out the reasons why the indicators were removed, communications were made with experts for further analysis, finding the following situations. In the first case, due to the lack of relevant statistical caliber, it is difficult to obtain effective values, so the score of relevance and importance is low, such as emission reduction of major pollutants. In the second case, there is a high correlation between indicators, which is likely to lead to repeated indicators. Therefore, experts give lower scores for the relevance and importance of such indicators, such as the number of tourist receptions and tourism income. The third kind of situation is the indicator correlation degree is low, such as tourism volunteer service belongs to this kind of situation. The fourth situation is the low importance of indicators, such as ecological parking lot, new energy car ownership, etc.

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(2) Consolidation of indicators According to the feedback of experts, on the ensurance of the scientific integrity of the indicator system, some indicators are combined. Indicator consolidation is mainly concentrated on the management system level. Due to the great differences in rural tourism destinations, in order to avoid repetition and redundancy, indicator consolidation is adopted to simplify. For example, the rural tourism environmental supervision mechanism, the rural tourism health and service supervision mechanism and the rural tourism integrated management mechanism are combined into the rural tourism quality supervision, for the rural tourism service quality supervision is more explicit, more comprehensive and more convincing. Tourism management talent incentive policy and tourism development incentive and subsidy policy are combined into the tourism development incentive system, for the tourism development incentive system is more consistent with the institutional guarantee, more representative and typical. (3) Modification of indicators According to the expert score, the indicators with less than 4 points in clarity were modified, such as “ecotourism income”, which scored higher than 4 points in importance and relevance. Therefore, ecotourism income was judged to be an indicator that could be used to evaluate ecotourism. Although “ecotourism income” is more compatible with “ecotourism”, there is a lack of statistical scope for ecotourism income. Experts suggest that “tourism income” should be used to measure the development of ecotourism in rural tourism destinations. (4) Determination of indicators Through indicator optimization, the basic framework of the evaluation indicator system for the construction of ecological civilization in rural tourism destinations remains unchanged, and the evaluation of the construction of ecological civilization in rural tourism destinations is carried out from six dimensions: rural characteristics, management system, ecological environment, ecological economy, infrastructure and public services, and rural civilization. Meanwhile, the middle layer of the evaluation indicator system for the construction of ecological civilization in rural tourism destinations remains unchanged. However, the elements of the evaluation indicator system for the construction of ecological civilization in rural tourism destinations are changed, either removed, modified or merged. Through indicator optimization, 60 three-level indicators were finally determined. 3.3

Determination of Indicator Weight

AHP method is a very classic comprehensive evaluation method which is suitable for processing a multi-objective, multi-level, many standards, qualitative indicators more complex issues of social system engineering, and is suitable for the

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construction of ecological civilization of the rural tourism destinations such comprehensive evaluation problem, so this article selected AHP method to determine the indicator weight. With the help of the 1–9 scale of Satty, the judgment matrix is constructed according to the way of expert scoring. Since the construction of ecological civilization involves many fields, the evaluation of ecological civilization construction of rural tourism destinations is a systematic comprehensive evaluation. In order to avoid the influence of subjective judgment on the result, this indicator weight is determined by group judgment. The importance of the same indicator is judged by experts from tourism, ecology, management and economy. The weights given vary according to the type of specialist, and make sure the sum of the weights is 1. The software yaahpa´ rs group decision panel is used to calculate the weighted indicator score given by experts to obtain the comprehensive indicator weight. The main steps are as follows: Table 2. Weight of indicators in the indicator system Grade I indicators

Grade II indicators

Grade III indicators

Property Weight

Rural characteristics (A1)

Rural landscape (B11)

The vernacular nature of rural landscape (C101 )

A

0.0493 0.1287 0.2465

The uniqueness of rural landscape (C102 )

A

0.0482

The coordination of rural landscape (C103 )

A

0.0312

The nativity of rural culture (C104 )

A

0.0339 0.0865

The diversity of rural culture (C105 )

A

0.0167

The inheritance of rural culture (C106 )

A

0.0122

Experientiality of rural culture (C107 )

A

0.0237

Authenticity of rural life (C108 )

A

0.0213 0.0313

The degree of civilization of rural life (C109 )

A

0.0101

Rural culture (B12)

Rural life (B13)

Management System (A2)

Institutional guarantee (B21)

Innovation demonstration (B22)

Rural tourism development A planning (C201 )

0.024

0.1106 0.1896

Rural tourism quality supervision system (C202 )

A

0.0356

Tourism security system (C203 )

A

0.0334

Tourism development incentive system (C204 )

A

0.0176

Smart tourism construction (C205 )

A

0.0354 0.079

Environmental protection innovation (C206 )

A

0.0199

Public service innovation (C207 )

A

0.0237 (continued)

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Table 2. (continued) Grade I indicators

Grade II indicators

Grade III indicators

Ecosystem (A3)

Environmental quality (B31)

Rural water quality (C301 ) B

0.0126 0.0898

Good air quality days (C302 )

B

0.017

Environmental noise (C303 )

B

0.0119

Forest and grass coverage (C304 )

B

0.0137

Ecological Economy (A4)

Property Weight

Biodiversity (C305 )

B

0.0119

Number of severe and mega environmental incidents (C307 )

B

0.0226

Ecological Alien species invasion protection (B32) (C308 )

B

0.0138 0.0837

Natural landscape protection (C309 )

B

0.0241

Ecological carrying capacity (C310 )

B

0.0202

Soil erosion control rate (C311 )

B

0.0117

Ecological and environmental protection investment (C312 )

B

0.014

Eco-tourism (B41)

Ecological agriculture (B42)

Green dining (C401 )

A

0.0277 0.1054

Green accommodation (C402 )

A

0.0152

Green entertainment (C403 )

A

0.0111

Green transportation (C404 )

A

0.0127

Green shopping (C405 )

A

0.0108

Tourism income (C406 )

B

0.0279

Proportion of organic/green/pollutionfree agricultural planting area (C407 )

B

0.0113 0.0508

Safety utilization rate of polluted farmland (C408 )

B

0.0047

Permanent basic farmland protection (C409 )

A

0.0128

Agricultural fertilizer application intensity (C410 )

B

0.0064

Comprehensive utilization of crop straw (C411 )

B

0.0045

Agricultural film recycling rate (C412 )

B

0.005

Comprehensive utilization rate of livestock manure (C413 )

B

0.0061

0.1735

0.1562

(continued)

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H. Zheng et al. Table 2. (continued)

Grade I indicators

Grade II indicators

Grade III indicators

Infrastructure and public services (A5)

Infrastructure (B51)

Road infrastructure (C501 ) A

0.0151 0.0793 0.1523

Rural tap water penetration rate (C502 )

B

0.0095

Rural sewage treatment rate (C503 )

B

0.0072

Rural sanitary toilet penetration rate (C504 )

B

0.0087

Rural clean energy use (C505 )

B

0.0057

Waste classification coverage (C506 )

B

0.0048

Harmless treatment rate of B domestic garbage(C507 )

0.0048

Comprehensive improvement of village environment (C306 )

A

0.0235

Tourist service center (C508 )

A

0.0153 0.073

Tourism identification system (C509 )

A

0.0351

Tourist service facilities (B52)

Tourist toilet (C510 ) Rural civilization (A6)

Property Weight

A

0.0226

Education (B61) Residents’ environmental protection education (C601 )

A

0.0064 0.0307 0.082

Environmental protection education for tourists (C602 )

A

0.0064

Percentage of residents receiving high school education or above (C603 )

B

0.0033

Public participation in ecological civilization (C604 )

B

0.0056

Public satisfaction with ecological civilization (C605 )

B

0.009

Village Regulations (C606 )

A

0.0083 0.0512

Implementation rate of open government affairs system (C607 )

B

0.0164

Residents’ participation in grassroots governance (C608 )

B

0.0113

Rural governance (B62)

Public satisfaction with B social order (C609 ) A stands for qualitative indicator, B stands for quantitative indicator.

0.0153

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(1) Select experts and set expert weights to ensure that the sum of the weights of the four types of experts is 1. Ten experts of tourism, ecology, economy and management were selected to give weight to the indicators in the evaluation indicator system of rural tourism destination ecological civilization construction. (2) Input the judgment matrix data of each expert. Import the judgment matrix data of several experts and conduct consistency check. Only 5 experts’ questionnaire assignments can pass the consistency test. (3) Group decision calculation. In the group decision panel, the expert scores are selected to be mathematically averaged to obtain the group decision results. According to the judgment and opinion of experts, the weight of each indicator in the indicator system of ecological civilization construction of rural tourism destination is obtained (Table 2). 3.4

Determination of Indicator Grades

In this paper, a comprehensive evaluation method of qualitative and quantitative tourism is used to comprehensively evaluate the ecological civilization construction of rural tourism destinations. Comprehensive evaluation of the construction of ecological civilization in rural tourism destinations is made by using expert scoring method and Fishbein-Rosenberg model. Among the 60 third-level indicators in the evaluation index system for the construction of ecological civilization in rural tourism destinations, there are both qualitative and quantitative indicators, of which 29 are qualitative indicators and 31 are quantitative indicators. Qualitative indicators are described in language, and quantitative indicators are in objective statistics. The Fishbein-Rosenberg model is a mathematical model that calculates scores by weights and scores. Its traditional formula is: E=

n 

Qi Pi .

i=1

Where E stands for comprehensive evaluation value; Qi is the weight value of the i factor; Pi is the score value of the i factor; n is the number of evaluation factors. As far as rural tourism destinations are concerned, the traditional FishbeinRosenberg model cannot reflect the particularity and diversity of evaluations of different types of experts. Therefore, based on the evaluation subjects of different types of experts, and giving corresponding weights according to the importance of the evaluation subjects, The Fishbein-Rosenberg model is optimized.

E=A

n  i=1

Qi Ri + B

n  i=1

Qi Si + C

n  i=1

Qi Ti + D

n  i=1

Qi Li .

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E represents the comprehensive and evaluation value of ecological civilization construction in rural tourism destinations, where A represents the weight of tourism experts, B represents the weight of ecological experts, C represents the weight of management experts, and D represents the weight of economic experts. Ri represents the score of tourism experts on the ith factor, Si represents the score of ecological experts on the ith factor, Ti represents the score of management experts on the ith factor, and Li represents the score of economic experts on the ith factor. Set a grading level every 20 points to divide the grading level of the evaluation index of ecological civilization construction in rural tourism destinations into five levels, and the grading ranges are 80 to 100, 60 to 80, 40 to 60, 20 to 40, 0 to 20. The qualitative indicators are divided into different grades according to the interpretation of the indicators, and different grades are assigned different intervals (Table 3). Table 3. Comprehensive evaluation level of ecological civilization construction Rating Score segment

4

Description

A

90≤ score 0.1). Based on Model 1, the variables of innovation network characteristics and absorptive capacity are added in Model 2 and Model 3, respectively. The values of R2 have been significantly improved, indicating that the addition of variables can better explain the impact of innovation network characteristics and absorptive capacity on relationship learning. From the regression results of Model 2, it can be concluded that, network size and network centrality have no significant impact on relationship learning (p > 0.1), while relationship strength and relationship quality have significantly positive impact on relationship learning (p < 0.01). Compared with relationship strength, relationship quality promotes more relationship learning (0.494 > 0.218). Therefore, H1a and H1b are invalid, and H1c and H1d are verified. That is, the size and position of an enterprise in the innovation network have no significant impact on the relationship learning among organizations. However, in the innovation network, the frequency of communication, the mutual commitment and trust between an enterprise and its partners have a significant effect on promoting the relationship learning between these two parties. From the regression results of Model 3, it can be concluded that, the absorptive capacity of an enterprise has a significantly positive impact on relationship learning (F = 84.448, p < 0.01), among which the knowledge digestion ability (β = 0.243, p < 0.01), the knowledge acquisition ability (β = 0.284, p < 0.01) and the knowledge application ability (β = 0.395, p < 0.01) promote the relationship learning in turn. Therefore, hypotheses H2a, H2b, and H2c are supported. Model 5 uses an enterprise’s absorptive capacity as the dependent variable. When the variables of innovation network characteristics are added on the basis of Model 4, the values of R2 significantly increase, indicating that the addition of these variables can better explain the impact of innovation network characteristics on the absorptive capacity of an enterprise. From the regression results of Model 5, it can be concluded that, except for the relationship strength (p > 0.1), the network size (β = 0.241, p < 0.01), the network centrality (β = 0.267, p < 0.01) and the relationship quality (β = 0.402, p < 0.01) have a significantly positive impact on the absorptive capacity of an enterprise, and the effects are sequentially increased. Therefore, H3c is invalid while H3a, H3b and H3d are valid. In other words, in an innovation network, the frequency of communication between an enterprise and its partners has no significant impact on the absorptive capacity, while an enterprise’s network size, position in the network and mutual commitment and trust between enterprises have significantly positive impacts on its absorptive capacity.

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X. Yang et al. Table 4. Results of regression analysis

Variables Relationship learning Model 1

Model 2

Absorptive capacity Model 3

Model 4

Model 5

Innovation network characteristics NS

0.106 (1.557)

0.241*** (3.936)

NC

0.121 (1.666)

0.267*** (4.112)

RS

0.218*** (2.826)

0.075 (1.090)

RQ

0.494*** (8.626)

0.402*** (7.853)

Absorptive capacity KAC

0.284*** (4.818)

KDI

0.243*** (3.411)

KAP

0.395*** (5.850)

Age

0.065 (0.804)

0.029 (0.624)

0.020 (0.444)

0.052 (0.652)

Size

0.174** (2.189)

0.015 (0.326)

0.001 (0.023)

0.215*** (2.725) 0.030 (0.730)

0.036 (0.873)

Industry (0.069) (−0.980) (0.023) (−0.584) (0.046) (−1.191) (0.034) (−0.493) (0.021) (−0.608) R2

0.046

0.708

0.719

0.059

0.766

Adj.R2

0.032

0.698

0.711

0.045

0.758

F 3.250** 68.281*** 84.448*** 4.221*** Note: *p < 0.1, **p < 0.05, ***p < 0.01; T value in parentheses.

4.2

92.319***

Mediating Effect

In order to further test the mediating effect of enterprise absorptive capacity between innovation network characteristics and relationship learning, three variables of absorptive capacity are added in order based on Model 2. The regression results are shown in Table 5. The R2 values of Model 6, Model 7 and Model 8 have been significantly improved on the basis of Model 2, which indicates that the addition of these variables can better explain the impact of innovation network characteristics and absorptive capacity on relationship learning. From the regression results of Model 6, it can be concluded that, after adding knowledge acquisition capability (β = 0.267, p < 0.01), although the regression coefficients of relationship strength (β = 0.141, p < 0.1) and relationship quality (β = 0.455, p < 0.01) are still significant, both of them have slightly decreased, which means that the impact of relationship strength and quality on relationship learning has weakened. In other words, the ability of knowledge acquisition has a partially mediating effect in the impact of relationship strength and relationship quality on relationship learning. Therefore, H4c and H4d are supported. Likewise, from the regression results of Model 7 and Model 8, it can be concluded that, after adding knowledge digestion ability (β = 0.333, p < 0.01) and knowledge application ability (β = 0.358, p < 0.01), respectively, the regression coefficients of relationship strength (β = 0.138, p < 0.01; β = 0.130, p < 0.01) and relationship quality (β = 0.359, p < 0.01; β = 0.290, p < 0.01) are still significant. But both of them have slightly decreased, that is, the knowledge digestion ability and the knowledge application ability have a partially mediating effect in the impact of relationship strength and relationship quality on relationship learning. Therefore, H5c, H5d, H6c and H6d are valid.

Impact of Enterprise Innovation Network Characteristics

699

Table 5. Test results of mediating effect Variables Relationship learning Model 2 Model 6

Model 7

Model 8

0.052 (0.801)

0.047 (0.730)

0.000 (−0.001)

0.051 (0.745)

Innovation network characteristics NS

0.106 (1.557)

0.020 (0.289)

NC

0.121 (1.666)

0.076 (1.071)

RS

0.218*** (2.826) 0.141* (1.829)

RQ

0.494*** (8.626) 0.455*** (8.093) 0.359*** (6.149) 0.290*** (4.560)

0.138*** (1.308) 0.130*** (1.220)

Absorptive capacity KAC

0.267*** (3.926)

KDI

0.333*** (5.610)

KAP

0.358*** (5.824)

Age

0.029 (0.624)

0.019 (0.418)

0.018 (0.410)

0.020 (0.460)

Size

0.015 (0.326)

0.006 (0.136)

0.003 (0.063)

0.018 (0.419)

Industry (0.023) (−0.584) (0.027) (−0.700) (0.020) (−0.557) (0.043) (−1.161) R2 Adj.R

2

0.708

0.729

0.749

0.751

0.698

0.718

0.738

0.741

F 68.281*** 66.043*** 72.923*** 73.970*** Note: *p < 0.1, **p < 0.05, ***p < 0.01; T value in parentheses.

4.3

Robustness Test

To avoid sample selectivity bias and endogenous variables, we also adopt two methods for the robustness test. First, the Bootstrap method is used for repeated sampling of 1,000 times and the 95% confidence interval is calculated. The results show that the above valid research hypotheses and their corresponding confidence intervals do not include 0. Hence, the results are robust. Second, the absorptive capacity generated by principal component analysis is used as the instrumental variable to replace three variables of absorptive capacity in Models 6–8, and the results are still robust.

5 5.1

Conclusion Research Conclusion

Based on the related research of enterprise innovation network and relationship learning, this study proposes research hypotheses concerning the impact of innovation network characteristics on relationship learning, and the intermediary role of enterprises’ absorptive capacity. In empirical research, enterprises in the innovation network are selected as research objects. Empirical tests are conducted based on the 205 valid samples to analyze the impact of four dimensions of

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enterprises’ innovation network characteristics and three dimensions of absorptive capacity on relationship learning. The following four research conclusions are made. First, the relationship characteristics (i.e., relationship strength and relationship quality) of enterprise innovation network have a positive impact on relationship learning. That is, from the strength of the relationship, the higher the frequency of communication between organizations is, the more beneficial it is to share information between organizations, develop a sense of reciprocity, enhance inter-organizational understanding and consensus, improve the learning efficiency of each participant, and then promote the relationship learning between organizations. From the quality of relationship, high trust and commitment can increase the speed and frequency of knowledge, and information exchange between organizations. Thus, both parties can understand and meet each other’s needs and expectations, maintain a stable cooperative relationship, and then promote the continuous updating of relationship memories between enterprises. This can further accelerate relationship learning. Second, absorptive capacity (i.e., knowledge acquisition ability, knowledge digestion ability and knowledge application ability) has a positive impact on relationship learning. That is, the ability of enterprises to obtain knowledge from the outside is conducive to promoting the transfer of knowledge between subjects and promoting information sharing between organizations. The knowledge digestion ability can effectively help enterprises to interpret, understand and handle tacit and complex knowledge from the outside, and strengthen the common understanding of exchanged information between organizations. The ability to apply knowledge is conducive to transforming new knowledge into product innovation and service innovation, thereby promoting the interaction between enterprises and the partners. By acquiring, digesting and applying the knowledge obtained from partners, a shared specific relationship memory is formed between organizations, which plays a positive role in promoting relationship learning. Third, the characteristics of enterprise innovation network (i.e., network size, network centrality and relationship quality) have a positive impact on absorptive capacity. That is, the larger the network size of an enterprise is, the more connections can be established across organizational boundaries. It is more likely to acquire the heterogeneous technologies or resources needed by the enterprise, facilitate the internalization of external knowledge, and then increase its absorptive capacity. The centrally located enterprises have more information channels and information sources, and can use the location advantages to obtain the required information resources, promote the digestion and utilization of knowledge through cooperation and communication with other members. Moreover, high relationship quality among members of the network can promote communications and cooperation between two parties, increase the level of trust and commitment between each other, reduce the difficulty of acquiring, absorbing and digesting external knowledge, and thus increase the absorptive capacity of enterprises.

Impact of Enterprise Innovation Network Characteristics

701

Forth, knowledge acquisition ability, knowledge digestion ability and knowledge application ability have a partially mediating effect in the impact of enterprise innovation network characteristics (i.e., relationship strength and relationship quality) on relationship learning. That is, the absorptive capacity of an enterprise acts as a connecting link that cannot be ignored in the mechanism of impact of enterprise innovation network relationship characteristics on relationship learning. 5.2

Theoretical Contribution and Practical Implication

This study offers several theoretical contributions. First, in the context of innovation network, four dimensions that reflect the characteristics of enterprise innovation network are selected. Through combining the absorptive capacity of enterprises, we explore its impact on relationship learning, enrich the research content of relationship learning, and further expand this research under the framework of network. Second, based on previous related research that focus on relationship strength and relationship quality, we improve the impact of network structure characteristics on relationship learning by considering the role of network size and network centrality on relationship learning. Third, during the process of exploring and discussing the impact mechanism of enterprises’ innovation network characteristics on relationship learning, we consider the mediating effect of corporate absorptive capacity, and carry out research simultaneously from two aspects, i.e., the impact of network characteristics on absorptive capacity, and the impact of absorptive capacity on relationship learning. This attempt breaks through the existing research approaches of relationship learning. The practical inspirations of this study lie in the following aspects. First, the innovation network contains a wealth of information and knowledge resources, providing an opportunity for enterprises to solve problems encountered in the production and operation process and realize enterprise innovation. Therefore, enterprises should strengthen the communication and cooperation with the subjects in the innovation network, use the characteristics of the innovation network to improve the efficiency of relationship learning, and achieve long-term development. Second, during the communication and cooperation with various subjects in the innovation network, an enterprise needs to enhance its knowledge acquisition ability, and realize the efficient transfer of knowledge from the outside to the inside through interaction with partners. Meanwhile, an enterprise also needs to enhance its knowledge digestion ability. Through interpreting, understanding, classifying and merging knowledge, the enterprise should systematically incorporate new knowledge into its knowledge base and further expand its knowledge base. Furthermore, an enterprise should also strengthen its knowledge application ability, apply new knowledge into products and services. By successfully transforming knowledge value gained through the innovation network into business value, the enterprise thus can improve its business performance. Third, relationship learning can help an enterprise improve its ability to integrate and restructure resources, improve product quality, accelerate the commercialization of new products, enhance the operational efficiency, and then obtain higher

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profits. Therefore, an enterprise should strengthen cooperation with partners in the innovation network. At the same time, it also should strengthen exchanges on market, customer, product, technology and strategy information, proactively share relevant information resources, and promote relationship learning between organizations, so as to provide guidance and reference for its decision-making in the future. 5.3

Research Limitations and Future Prospects

On the one hand, although the samples selected in this study cover a large geographical range and various industries, and there are also big differences in the nature and scale of business operations, there are big differences in sample sizes in different provinces and cities. Future research can extend the samples evenly to a wider area to verify the universality of our conclusions. On the other hand, the static research is adopted in this study, which takes several months from the design of the research to the recovery of questionnaire data. Future research can use a longitudinal research method to obtain the development of relationship learning over time, and to verify the relationship hypotheses established in the research at different time points. Acknowledgments. This work was supported by National Natural Science Foundation of China [grant number 71904137] and Ministry of Education of the People’s Republic of China [grant number 18YJC630227].

References 1. Chang, M.L., Cheng, C.F., Wu, W.Y.: How buyer-seller relationship quality influences adaptation and innovation by foreign MNCs’ subsidiaries. Ind. Mark. Manag. 41(7), 1047–1057 (2012) 2. Chesbrough, H.W.: Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business Press, Brighton (2003) 3. Cohen, W.M., Levinthal, D.A.: Absorptive capacity: a new perspective on learning and innovation. Adm. Sci. Q. 35(1), 128–152 (1990) 4. Dhanaraj, C., Lyles, M.A., et al.: Managing tacit and explicit knowledge transfer in IJVs: the role of relational embeddedness and the impact on performance. J. Int. Bus. Stud. 35(5), 428–442 (2004) 5. Dyer, J.H., Singh, H.: The relational view: cooperative strategy and sources of interorganizational competitive advantage. Acad. Manag. Rev. 23(4), 660–679 (1998) 6. Frazier, B.J., Huddleston, P.: The role of market embeddedness in market scanning and marketing competence. J. Small Bus. Entrep. 22(2), 165–180 (2009) 7. Hongbin, D., Zhengbin, W.: An empirical study on the network structure’s impact to the firm growth performance: the intermediary role of exploitative learning and explorative learning. Nankai Bus. Rev. 14(3), 15–25 (2011). (in Chinese) 8. Ibarra, H.: Network centrality, power, and innovation involvement: determinants of technical and administrative roles. Acad. Manag. J. 36(3), 471–501 (1993)

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9. Jansen, J.J., Van Den Bosch, F.A., Volberda, H.W.: Managing potential and realized absorptive capacity: how do organizational antecedents matter? Acad. Manag. J. 48(6), 999–1015 (2005) 10. Lai, C.S., Pai, D.C., et al.: The effects of market orientation on relationship learning and relationship performance in industrial marketing: the dyadic perspectives. Ind. Mark. Manag. 38(2), 166–172 (2009) 11. Lavie, D.: Alliance portfolios and firm performance: a study of value creation and appropriation in the US software industry. Strat. Manag. J. 28(12), 1187–1212 (2007) 12. Lenox, M., King, A.: Prospects for developing absorptive capacity through internal information provision. Strat. Manag. J. 25(4), 331–345 (2004) 13. Liu, C.L.: An investigation of relationship learning in cross-border buyer-supplier relationships: the role of trust. Int. Bus. Rev. 21(3), 311–327 (2012) 14. Lyles, M.A., Salk, J.E.: Knowledge acquisition from foreign parents in international joint ventures: an empirical examination in the Hungarian context. J. Int. Bus. Stud. 27(5), 877–903 (1996) 15. Madani, F., Daim, T., Weng, C.: ‘Smart building’ technology network analysis: applying core-periphery structure analysis. Int. J. Manag. Sci. Eng. Manag. 12(1), 1–11 (2017) 16. Nan, G., Wei, J., Hu, H.: Analysis of the multi-agent’s relationship in collaborative innovation network for science and technology SEMs based on evolutionary game theory. Int. J. Inf. Tchnology Manag. 18(1), 1–15 (2019) 17. Nasierowski, W., Arcelus, F.J.: Interrelationships among the elements of national innovation systems: a statistical evaluation. Eur. J. Oper. Res. 119(2), 235–253 (1999) 18. Rampersad, G., Quester, P., Troshani, I.: Developing and evaluating scales to assess innovation networks. Int. J. Technol. Intell. Plan. 5(4), 402–420 (2009) 19. Ren, S., Wu, J., Wang, L.W.: A study on network embeddedness and enterprise’s innovation performance: test of the moderating effect of network competence. R&D Manag. 23, 16–24 (2011). (in chinese) 20. Selnes, F., Sallis, J.: Promoting relationship learning. J. Mark. 67(3), 80–95 (2003) 21. Sun, Y., Wang, T., Gu, X.: A sustainable development perspective on cooperative culture, knowledge flow, and innovation network governance performance. Sustainability 11(21), 6126 (2019) 22. Uzzi, B.: Social structure and competition in interfirm networks: the paradox of embeddedness. Adm. Sci. Q. 42(1), 35–67 (1997) 23. Vera, D., Crossan, M.: Strategic leadership and organizational learning. Acad. Manag. Rev. 29(2), 222–240 (2004) 24. Wang, H., Zhao, Y., et al.: Network centrality and innovation performance: the role of formal and informal institutions in emerging economies. J. Bus. Ind. Mark. 34(6), 1388–1400 (2019) 25. Ye, Z., Zheng, J.: Network characteristics and corporate entrepreneurship of cluster enterprises: an empirical study based on entrepreneurial competence. Sci. Res. Manag. 35(1), 58–65 (2014). (in Chinese)

Application Research on the BIM and Internet of Things Technology in Construction Logistics Management in the Period of Big Data Ling Wan1(B) and Yue Bai2 1

Guangdong Ocean University Cunjin College, Zhanjiang 524000, Guangdong, People’s Republic of China [email protected] 2 Beibu Gulf Development Research Center, Zhanjiang 524000, Guangdong, People’s Republic of China Abstract. In recent years, with the advent of digital economy, big data has been widely used in all walks of life. Building logistics has become a new source of profit for the construction industry. In this context, the BIM (Building Information Modeling) technology and Internet of things technology will bring new application value to building logistics management. This paper uses comparative analysis and case analysis to analyze the BIM technology and Internet of things technology in the era of big data in the construction industry, The main contribution of this paper is to analyze the new characteristics of building logistics management based on the BIM technology and logistics technology in the era of big data, build the logistics collaborative management platform based on big data and the BIM Technology, and analyze the logistics collaborative management platform based on big data. Finally, through the case analysis, it is concluded that the BIM technology and Internet of things technology have great application value in all aspects of construction logistics management in the era of big data. Keywords: BIM (Building Information Modeling) Technology · Internet of things technology · Construction logistics management Application

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Introduction

Construction industry is one of the pillar industry of our country, occupy important position in the national economy in our country, in recent years, with the speeding up of economic globalization, information technology, Internet technology and the rapid development of Internet technology, accelerating the pace of China’s development and puts forward new requirements for the development of construction industry, due to the particularity of the construction industry, c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 704–716, 2021. https://doi.org/10.1007/978-3-030-49889-4_54

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it is different from general enterprise logistics management, There are many materials in the construction industry, The construction site links are complex and changeable, the space is limited, Construction logistics has always been the problem of low efficiency of logistics management. At the same time, with the speeding up of the global economic development and integration, puts forward new requirements to green development, China’s construction industry has been faced with low efficiency, low efficiency of resource utilization, serious environmental pollution and other problems, the promotion of green development of the construction industry largely depends on the link of construction logistics activities, Including the procurement, transportation, inventory, construction, operation and maintenance of construction materials and other links, currently, SCM, ERP, JIT and other management ideas have been applied to construction logistics, accelerating the improvement of logistics management level in the construction industry to some extent. However, there are still some problems in China’s construction logistics, For example, the level of informatization is limited, the logistics management system is not perfect, and the impact of construction logistics on project profit has not been paid much attention, and the large proportion of construction logistics costs restrict the development of the construction industry. The BIM (Building Information Modeling) is a major reform of the construction industry, is the effective utilization of digital technology to simulate the information model of construction project, At present, it has been vigorously promoted by the state and is considered as the driving force to promote the industrialization and informatization of the construction industry [3], Practice has proved that the BIM technology has become the basis for the informatization development of the construction industry. Meanwhile, the Internet of things technology can effectively adopt and transfer real data to the BIM model database. It can integrate virtual models with real situations, effectively realize the field operation and management behavior in the construction process, so as to ensure the improvement of the informatization level of the construction industry [7].

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The Characteristics and Application Status of the BIM and Internet of Things Technology in Construction Logistics Management in the Era of Big Data New Features of Building Logistics Management Based on BIM and Internet of Things Technology in the Era of Big Data

Construction logistics refers to the procurement, transportation, inventory, construction, operation and maintenance of materials, implementation equipment, construction components and other construction materials needed in the whole life cycle of construction projects, including the logistics, capital flow, information flow in the operation process [2], the ultimate goal of architectural logistics management activities is to make all aspects of logistics management orderly

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through effective technologies and methods, so as to maximize the benefits of logistics management and ensure the level of logistics services. In the era of big data, combined with the characteristics of the meaning of modern logistics management and logistics, construction logistics management is to use the advanced information technology and method of the era of large data, with the highest efficiency and lowest cost will be needed for the engineering materials, supplies, equipment, in accordance with the need to be delivered in a timely manner, to ensure the project smooth implementation of the management activities. In the era of big data, in addition to completing logistics services according to customer requirements, it is necessary to make full use of information technology and the Internet to realize the rapid, precise and intelligent logistics management, and improve the informatization level of construction logistics management and the efficiency of construction logistics management [9]. 2.2

Comparative Analysis of Construction Logistics Management and Traditional Construction Logistics Management Based on BIM Technology and Internet of Things Technology

The BIM technology is not only an information model of building digitization using some software, but also a management idea, which emphasizes the collaboration and interaction of information within the whole life cycle of construction projects, site management and post-operation and maintenance management. The BIM technology can realize simulation calculation, collision inspection, pipeline optimization, intelligent building and so on. The application of the BIM technology is a dynamic and continuous process, which runs through the whole life cycle of construction project management. In this process, continuous collection of various data, real-time analysis and processing of data, is a basic link to achieve building information [13]. The Internet of things provides support for the implementation of BIM, the Internet of things technology mainly uses sensors, intelligent terminals, the QR codes, the RFID tags and other facilities and devices to collect data and information in real time. Then the mobile network is used to feed back into the BIM model, so as to provide dynamic realtime data update for the static BIM model, the BIM model is combined with the actual data in the construction process of building engineering, realizing the combination of virtual model and real data and information. It can better realize the operation and management behavior of construction site and promote the informatization and intelligence level of construction logistics management. The comparison and analysis of traditional construction logistics management and construction logistics management based on the BIM technology and Internet of things technology are shown in Table 1: In view of the problems existing in the construction logistics management based on the BIM Technology and Internet of things technology, we need to solve them from the following aspects: first, we need to strengthen the construction enterprises’ cognition of the BIM Technology and Internet of things technology, and promote the use of BIM Technology and Internet of things technology in the construction logistics. At the same time, the government departments should also

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Table 1. Correlation table of the traditional construction logistics management and construction logistics management based on the BIM and Internet of things technology [4, 6, 10, 12] Nature

Type Feature

Advantage

Existing problem

Traditional construction logistics management

1. High inventory cost 2. Information lag 3. Slowness of material supply 4. Poor coordination of each logistics link

1. The traditional construction logistics management mode is mature 2. There are enough talents for traditional construction logistics management

1. Low level of informatization 2. The proportion of logistics costs is relatively large 3. The logistics supply relationship is not stable 4. Inefficient extensive logistics management 5. Material supply is not timely 6. Low degree of informatization

Construction logistics management based on BIM and Internet of things technology

1. Accuracy of calculation 2. Positioning accuracy 3. High level of informatization 4. Information sharing 5. Collaborative

1. Save construction logistics cost 2. Improve coordination efficiency and improve the refinement level of logistics management 3. Allocate resources reasonably and effectively to improve the efficiency of logistics management 4. Cooperate and complete projects better and faster 5. Improve asset management and daily maintenance

1. Limited understanding of construction enterprises and insufficient attention 2. The information management system is not perfect 3. Logistics informatization management mode is not mature enough 4. Lack of senior informatization logistics management talents

strengthen policy support and promote the new information technology based on big data Secondly, we should strengthen the development of logistics information technology, establish a more advanced and perfect logistics information management mode, make use of the characteristics of the big data era, constantly develop new logistics information management mode, integrate the latest information technology into the logistics information management system, so as to improve the efficiency of logistics management; finally, we should constantly pay attention to the cultivation of high-level logistics information management talents, pay attention to the training of logistics engineering composite talents, on the one hand, we need to deeply understand the thought of logistics management, on the other hand, we need to be familiar with the knowledge of logistics information technology in the era of big data. Only with high-quality composite logistics management talents, we can integrate the BIM technology and Internet of things technology into the construction logistics management and play its advantages.

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The Application of BIM Technology and Internet of Things Technology in the Construction Logistics Management of Construction Enterprises

With the rapid development of information technology and the era of digital economy, there are some problems in the modern construction logistics management of construction enterprises. Such as, they don’t pay much attention to all aspects of construction logistics, they don’t realize that logistics management is the “third-party profit source”, they don’t know enough about the application of information technology in the logistics management of construction enterprises The management information level is not high, the logistics cost proportion is large, the material supply relationship is not stable and so on. Many construction enterprises still use the traditional logistics management mode. The logistics management information level of China’s construction industry is low. In the era of big data, this obviously does not meet the development needs of the times. At present, the BIM technology and Internet of things technology are still developing in China It is the primary stage of popularizing and using. The development is not mature enough. There are not many the BIM Technology and Internet of things technology can be applied to the construction logistics management. The managers of construction enterprises seldom realize the value of the BIM Technology and Internet of things to the construction management. Because the informatization level of the construction industry logistics management is low, there is no perfect and efficient logistics management system, there are still some difficulties in applying the BIM Technology and Internet of things technology to building logistics management [1]. The application of the BIM Technology in the construction industry is the general trend. The national government is constantly encouraging the enterprises in the construction industry to adopt the BIM Technology. The application of the BIM Technology in the logistics management and control of the construction industry is the requirement of the sustainable development of the construction industry. However, the cost of using the BIM Technology is too large and the owners do not pay much attention to it. There are many obstacles in the application of the BIM technology. The purpose of this paper is to discusses the application value and practice of the BIM technology in building logistics management. The visualization of the BIM technology can greatly improve the value of building logistics management. Through the visualization, it can simulate the construction process and the storage, loading and unloading of materials. The BIM5D can carry out cost analysis, optimize the transportation route and determine the best purchase quantity. The BIM technology for building logistics management It has great application value. The BIM model provides the carrier of information transfer for building logistics management. It can store data and transfer information. There are many practical cases of material management based on it, but the BIM technology has not been used in the whole process of building logistics management. At present, the BIM Technology still stays in the stage of collision inspection and virtual construction simulation, such as If the real data of the construction site is not transferred to the BIM

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model, the application value of BIM technology in the logistics management is greatly weakened, which also results in the fact that the BIM technology only stays at the level of construction material engineering quantity statistics, unable to control the construction logistics link in depth and effectively. The Internet of things technology cannot analyze and process the collected information and data, but as long as the Internet of things technology and the BIM technology are integrated, the data and information can be transferred to the BIM model through the Internet of things technology. The Internet of things technology can locate, monitor, monitor and collect material information, which can better play the BIM technology and the Internet of things technology in the construction industry enterprise logistics Application value in management.

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Application of the BIM and Internet of Things Technology in Construction Logistics Management Based on the Big Data Build Logistics Collaborative Management Platform Based on BIM and Internet of Things Technology Based on the Big Data

The BIM and Internet of things technology can be integrated into building logistics management to establish a collaborative platform of logistics management, and the application of the BIM and Internet technology can be integrated into the whole process of building logistics management. It can establish a logistics cooperative management platform with logistics information system as the core, so as to maximize the benefits of construction logistics. The main purpose is to monitor the logistics, capital flow and information flow of materials, facilities and materials involved in the construction process from the beginning to the end of the project. Through the transmission and interaction of data and information between BIM model, Internet of things technology and inventory system, it can provide a basis for decision-making for realizing construction logistics management goals. Grasp the status of logistics, capital flow and information flow in the construction process in real time, and better control the implementation of construction projects. So as to better control all aspects of material procurement, transportation, inventory storage, construction and operation and maintenance in the construction process and maximize the efficiency of construction logistics management. Achieve the goal of efficient management and control of the whole process of construction logistics, achieve the goal of logistics management with the lowest logistics cost, and obtain the maximum social and economic benefits. In order to ensure the effective operation of this platform, certain organizational guarantee, system guarantee, and fund guarantee measures are also needed to achieve the objectives of construction logistics management (Fig. 1). Logistics information system is the core system of logistics collaborative management platform, which consists of the BIM model, Internet of things technology and inventory system [10]. The construction logistics information system is the center of the whole platform, it is responsible for commanding and controlling the functions of the platform. All the information transfer and data analysis

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Fig. 1. Framework diagram of logistics collaborative management platform

are carried out on this platform, it can integrate the logistics, information flow and capital flow during the implementation of construction projects. Through the analysis of information and data, it provides decision-making basis for the construction logistics management. Meanwhile, in this system, the transmission and information interaction between the BIM model and data collected through Internet of things technology can be realized to control the status of construction logistics in real time. In addition to data and information transfer and interactive functions, the BIM models and Internet of things technologies also integrate with each other. The information and data collected through the Internet of things can be transferred to the BIM model in time to realize the coordination of information and data. Data analysis and data processing are carried out on this platform, and basic data of building construction are put into the BIM model in real time through Internet of things technology. It can carry out data and processing of information, and make a series of decisions such as optimal fund use plan, procurement plan, transportation route, storage yard placement, construction site layout, etc. 3.2

Information Interaction of Logistics Collaborative Management Platform Based on the Big Data

The biggest feature of the collaborative platform of logistics management is to make use of the BIM technology and Internet of things technology to achieve collaborative sharing and connectivity of information. The BIM technology can realize the visualization, virtualization and simulation of building models, and more intuitively identify and control building construction. However, building information model is a static multi-dimensional model, and it is difficult to truly reflect the reality of the construction site. Internet of things technology has made up for these problems, the Internet of things technology can collect the learned information and data through the equipment end of the construction

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site in real time, it will Upload to the BIM model through wireless network, and Integrate and interact the collected information and data on the logistics information collaborative platform, finally, it will transfer in the form of a table or a document, So as to accurately control the implementation state of building materials and effectively control each class of building logistics management. The information interaction diagram of this platform is shown in Fig. 2:

Fig. 2. Information interaction diagram of logistics collaborative management platform

In the logistics collaborative management platform, the purchase demand is analyzed by the BIM model. At the same time, the QR code or RFID tag information in the Internet of things technology is used to correlate with the purchase demand. The collected data and information will be transferred to the logistics information system in time. The collection and transmission of these data and information run through the five links of the whole logistics management, it will make real-time data transmission of information and real-time monitoring of material arrival status related to procurement, production, transportation, inventory, construction and operation and maintenance. At the same time, the actual situation is compared and analyzed with the statistical data and information in the model based on the BIM model. In case of any discrepancy, timely correction and adjustment shall be made. The revised data is re-input into the logistics information system, Through the input and output of data and information of each logistics link, information collaboration and sharing among all participants in each logistics management link can be realized. In this logistics information collaborative platform, operational data of all stages of construction logistics activities are concentrated here. This platform shall be responsible for the collection, transmission and management of relevant information in all construction logistics links.

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Operation Process of Logistics Collaborative Management Platform Based on the Big Data

In the implementation of construction projects, the project construction phase of the construction of logistics part mainly includes the procurement, transportation, inventory, construction and operational management of the five links, BIM and Internet technology can be applied at each different logistics, the specific each link of logistics platform operation and application of the corresponding points, as shown in Fig. 3 [8]:

Fig. 3. Application value analysis of logistics collaborative management platform

As can be seen from Fig. 3, in the implementation of construction projects, different logistics links have different content of logistics collaborative management platform, and the corresponding application value is also different in the five-logistics links of procurement, transportation, inventory, construction and operation and maintenance.

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Collaborative Application of BIM Technology and Internet of Things Technology

In the implementation process of the project, the BIM Technology is fully used to connect the whole process of project design, construction, building logistics management, property management, etc. and truly realize the collaborative management of the whole process of the project. The specific implementation mode is shown in the Fig. 4 below:

Fig. 4. Implementation of BIM

The application of the BIM model can optimize the design. In the construction process of a construction project, a lot of building materials and facilities and equipment are used. Through the BIM model, the detailed information of materials, equipment, building components and accessories required in the process of project facilities can be accurate to the size and location of each construction. Through 3D model, the detailed display can be made, and each material can also be made the engineering quantity required by the equipment and the purchase quantity of materials are calculated accurately. The collision inspection can be carried out through the BIM technology to correct the conflicts in the scheme design in time and reduce rework, so as to more accurately measure the quantity of materials and components and parts. Through the logistics collaborative management platform, these data and information can be transmitted in real time, so as to ensure that all parties involved in the project can share these information and data in time, and update and correct them in time, so as to ensure the construction materials Through performance optimization analysis, the BIM model can analyze the light, sound, wind and green performance of materials and equipment in the BIM model, so as to determine the type selection of materials and equipment that meet the requirements, and finally determine the material supplier in combination with the requirements of the owner to ensure that the construction materials provided meet the requirements of construction engineering [11]. This project adopts prefabricated technology, and all components used in the project are transported to the project site for assembly after being processed in the factory, which requires high requirements for component design, processing

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and manufacturing, and customized implantation with the QR code or RFID tag. After scheme optimization through the BIM model, the BIM model is used to connect with material supplier in real time. Both parties extract and update data and information through the BIM model. Material supplier processes and manufactures according to the data provided by the BIM model. After production, two-dimensional code or RFID tag is used to write corresponding coding information, which is transmitted to the BIM model through Internet of things technology. In addition, the BIM model is used for material management to ensure the real-time data collection and input of construction materials in the later stage of transportation, construction and operation and maintenance [11]. In a word, the BIM technology and Internet of things technology play an irreplaceable role in the whole implementation process of the project, and they are indispensable in the design, construction, prefabricated components, production components, production, transportation inventory and other aspects of the project. During the implementation process of the project, the specific the BIM Technology and the application of Internet of things technology in various stages of building logistics are shown in Fig. 5:

Fig. 5. Implementation of BIM and Internet of things technology

3.5

The BIM Technology and Internet of Things Technology Application Value Analysis

During the implementation of the project, the BIM technology and Internet of things technology are integrated into the whole project process. In each link of the construction logistics management of the project, the BIM technology and logistics technology are used to control the whole logistics link and effectively locate and track the materials in each link. At the same time, the logistics management of each stage is seamlessly connected and effectively simulated in

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advance, which greatly improves the efficiency of logistics management, reduces the inventory cost and transportation cost, and greatly improves the efficiency of project management to a certain extent. From the actual implementation of the whole project, the overall comprehensive technical and economic benefits are greatly improved. In the process of project implementation, the construction link compared with the previous projects, the water consumption for maintenance, the use of formwork and the consumption of various materials in the project are greatly reduced [5]. At the same time, due to the improvement of relevant management efficiency, the project is also completed ahead of time. In the 5G era of rapid development of information technology, the BIM technology and Internet of things technology have greatly improved the informatization of project management, each project participant can query the information needed by all parties on the BIM model, realizing information collaboration and reducing communication cost For the whole project, the competitiveness has been greatly improved, and the collaborative management based on the BIM technology and Internet of things technology has been realized. As a prefabricated construction project, the project realizes the information-based collaborative management mode by using new technology, which greatly improves the value of the whole project. The whole management mode is worth thinking about by construction industry.

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Conclusion

In the era of big data, construction logistics management presents new features. Digital economy puts forward new requirements for construction logistics management. Through research, it is found that construction logistics management based on the BIM and Internet of things technology has many advantages compared with traditional building logistics management, such as accuracy of calculation, accuracy of positioning, high level of informatization, and information sharing and coordination, The integration of the BIM technology and Internet of things technology can effectively promote the improvement of construction logistics management level and meet the development requirements of informatization industrialization of the construction industry. Meanwhile, the specific application of the BIM technology and Internet of things technology in building logistics management can be realized by building a collaborative management platform of building logistics. Information interaction and collaboration can be realized on this platform, it will realize the intelligent construction logistics management. The application value of the BIM and Internet of things technology in each link is explained according to the five major links of construction logistics management, which may become a new idea for the development of construction logistics management in the era of big data. Acknowledgements. This research topic by Science and technology special project in Zhanjiang city subsidy (NO: 2019B01163); by Young innovative talents project of Department of education of Guangdong Province subsidy (NO: 2019KQNCX215), this

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paper was completed under the guidance of master tutor Yue Bai. His rigorous academic attitude and scientific research spirit have inspired me a lot. In addition, I would like to thank all the scholars in this field, which is the basis of this paper. Thank you for everyone’s contribution!

References 1. Chen, X., Ding, L.: Application research of building safety operation and maintenance management based on internet of things and bim-a case study of urban lifeline project. Constr. Econ. 11, 34–37 (2014). (in Chinese) 2. Costin, A., Pradhananga, N., Teizer, J.: Passive RFID and BIM for real-time visualization and location tracking. In: Construction Research Congress 2014: Construction in a Global Network, ASCE, pp. 169–178 (2014) 3. Davis, D.: BIM (Building Information Modeling) Update. American Institute of Architects, Washington, D.C. (2003) 4. Ilozor, B.D., Kelly, D.J.: Building information modeling and integrated project delivery in the commercial construction industry: a conceptual study. J. Eng. Proj. Prod. Manag. 2(1), 23–36 (2012) 5. Li, W.: Research on integrated application of BIM and RFID technology in construction logistics management. Beijing: Master’s Thesis of Beijing University of Architecture (2016). (in Chinese) 6. Montaser, A., Moselhi, O.: RFID indoor location identification for construction projects. Autom. Constr. 39, 167–179 (2014) 7. Sacks, R., Koskela, L., et al.: Interaction of lean and building information modeling in construction. J. Constr. Eng. Manag. 136(9), 968–980 (2010) 8. Truijens, M., Wang, X., et al.: Evaluating the performance of absolute RSSI positioning algorithm-based microzoning and RFID in construction materials tracking. Math. Probl. Eng. 2014 (2014) 9. Valero, E., Ad´ an, A.: Integration of RFID with other technologies in construction. Measurement 94, 614–620 (2016) 10. Wang, C.: Research on bim technology-based construction enterprise logistics management. Technol. Econ. Manag. 12, 55–58 (2014). (in Chinese) 11. Wang, L.C., Lin, Y.C., Lin, P.H.: Dynamic mobile RFID-based supply chain control and management system in construction. Adv. Eng. Inform. 21(4), 377–390 (2007) 12. Wang, Y.: Research on the application of BIM technology in the logistics management of construction enterprises. Logist. Technol. 5, 39–41 (2019). (in Chinese) 13. Zhao, X.: A scientometric review of global BIM research: analysis and visualization. Autom. Constr. 80, 37–47 (2017)

Evaluating the Trustworthiness in Sharing Economy: A Case Study of DiDi Users in Shanxi, China Guohao Zhao1 , Junaid Jahangir1 , Muhammad Waqas Akbar2 , Muhammad Hafeez3 , and Haseeb Ahmad4(B) 1

4

School of Business Administration, Shanxi University of Finance and Economics, Taiyuan 030012, Shanxi, People’s Republic of China 2 School of Finance, Shanxi University of Finance and Economics, Taiyuan 030012, Shanxi, People’s Republic of China 3 School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, People’s Republic of China Department of Computer Science, National Textile University, Faisalabad, Pakistan haseeb [email protected] Abstract. Sharing economy is emerging phenomena in commercial marketing and growing very fast in all over the world especially in China. This study tries to investigate the trust level of people on the online sharing economy platform and the factors behind that trustworthiness. Primary data has been collected from DiDi users in Shanxi, China through monkey survey. SPSS, statistical computational tool, is used to evaluate and analyze the primary data. Correlation matrix is used to identifying the inter-dependence and the relationship between trustworthiness and ability, integrity, benevolence, predictability and safety of the consumers respectively. Regression analysis has been conducted to unveil the impact of considered variable on trustworthiness. Moreover, cross tabulation and chi-square reveal that 58.3% users affirmed that the platform is able to offer trustworthy and good services to consumer. The “DiDi” platform is most appropriate and secure to travel. The “DiDi” users are satisfied and believe that it never cheats its customers along comfort. While, “DiDi” users do not have confident that vendors on the platform are honest and trustworthy. The “DiDi” platform needs to work on vendors to sustain its users. The sharing economy is beneficial for low income level and can also enhance the quality of life. Keywords: Trustworthiness · Sharing economy China · Consumer to consumer

1

· DiDi platform ·

Introduction

Tragedy of the commons was the stimulation of sharing economy to prefer to act exclusively only for own interest and deplete the mutual resources to fulfill c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 717–729, 2021. https://doi.org/10.1007/978-3-030-49889-4_55

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the need of quality life. In the era of Greet Recession, the term sharing economy is originated to appear around, the term sharing economy refers to the way of allocating goods and selling products to consumers that is totally different from the conventional way. Indeed, it refers to share people’s belongings with other individuals like their home, their cars, their personal goods, accommodation, education, ride sharing or ride hailing, bike sharing and food needs in a peer-to-peer fashion that is called sharing economy [5,12]. Consumer’s purchasing power is something which can triggers the commercial markets dynamics of an economy. Transportation is a pivotal need for all type of consumers whether they are students, business holders, whether they belong to services sectors, workers etc. but not all can afford their own cars or mean of transportation. As results, taxi services or public transport has been used. Sharing economy, one of the commercial methods, is emerged and influenced by consumers [3,7]. Furthermore, these taxi services provide a luxurious service on cheap price that is also called shared taxi service [3,7]. Many terminologies related to sharing economy have been found from the recent available literature such as “collaborative consumption”, “sharing”, “the mesh”, “commercial sharing systems”, in addition “co-production”, “co-creation”, “presumption”, “product-service systems” [3,4,7,9]. Through sharing economy, we can also save our natural environment by emitting less pollution regarding the sharing taxi service. It will bring a noticeable decrease in carbon emission from transportation. The sharing taxi services, and shared taxi is an everyday feature now a days in the world with different names. It traces an increasing trend across globe the world both developed and developing countries such as “Algeria, Argentina, Canada, Ethiopia, Ghana, Cameroon, Mali, Morocco, South Africa, Tanzania, Tunisia, China, Hong Kong, India, Indonesia, Iran, Israel, The Philippines, Thailand, Australasia, New Zealand, Cyprus, Turkey, Estonia, Greece, Lithuania, Netherlands, England, and United States. According to [8], institutional changes affect the environmental and social effects of the sharing economy because institution regulates activities on the platforms and as well as shape the future improvements. It is summarized from the literature that sharing economy will positively affect the environment, traffic and overcapacity problems development [13]. The risk aversion is another important factor which effects consumer satisfaction associated with online service platform [19]. The fastest growing sharing economy of China has the potential to create businesses in different sectors in future. Thus, in China only for sharing economy a research center has been established in January 2017 in State Information Center (SIC) [20,21]. According to a report, it is expected that china’s shared economy will maintain almost 40% annual growth in next 5 years, and according to officials it will grow over 20% by 2025 [20,21]. According to SIC, the sharing economy of China has generated revenues of up to RMB 4.9 trillion (around US$729 billion) in 2017. The categories of services in the sharing economy are knowledge and skill, lodging, transportation, life service, production facility, medical service, and social lending given below in the Table 1 [20,21].

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Table 1. Transaction value of sharing economy in China (CNY billion) Year

2015 2016 2017

Knowledge and skill

20

61

138

Lodging

11

24

15

Transportation

100

204

201

Life service

360

723 1321

Production facility

200

338

412

7

16

7

Medical service Social sending

1000 2086 2826

Total 1698 5452 4621 Source: Sharing Economy Research Center [20, 21]

The sharing economy is an umbrella enclosed by information and other computer technologies that supports to share products and services sharing online [12]. Today, an enormous number of online media are helping to share tools, clothes, or entertainment products in digital environments [1]. Didi (Chuxing) is a platform on which people can order taxis and rides, with worth of 56 billion USD. Didi is on the top in this field by commanding a share of 75% in ride-sharing business in China after inclusion of Uber China’s business in 2016 [22,23]. The aspiration of the study is to explore the role of online platforms play in the sharing economy. The current research work also interested to figure out the question; Are those platforms trustworthy enough for the people who use that and what are the factors behind that which force people to think that these platforms are trustworthy? This study evaluates that why people’s trust on online platform is important in sharing economy. Furthermore, Sect. 2 elaborates the conceptual background in the light of literature review. While, data collection and research methodology are discussed in Sect. 3. Section 4 states the data analysis and results discussion. Lastly, the concluding remarks are given in Sect. 5.

2

Theoretical Background and Literature Review

Sharing economy has been developed through peer-to-peer (P2P) commerce; this mainly involved the supply of services. P2P growing quickly day by day and this development is more prominent inn travel and tourism industry. In this kind of marketplaces consumer have direct interaction with seller, on the other hand a third party (other than seller and consumer) upheld the podium. Some markets like eBay worked as traditional traders of retail items [7]. Economic and societal concerns initiate the upward movement in the sharing economy in tourism, particularly in the accommodation market. In this industry most

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of the services are provided by natives, like taxi services (Uber), restaurant services (Eatwith), tour guide services (Vayable), and accommodation services (Airbnb) [3,4,7,9]. Direct interactions with locals help tourists to get lower rates for accommodation. This direct interaction, which includes online deals, includes the individuality between early P2P markets and new sharing economy markets. In early P2P markets sellers’ profile did not have enough information, but sharing economy market contain more personal information, such as seller’s personal photo. This photo of seller is very useful for identity verification and to build sense of personal contact [17]. The current phenomenon of the sharing economy has positive (increasing) effects on global economy. It provides opportunities for clients to turn into small scale businesspersons and because of the sharing economy market conventional differences between production, trade and consumption becoming extent. After pervasive concept of car sharing, the economic significance of sharing accommodation is increasing. The sharing economy is not only about sharing the cars and accommodation but also includes the sharing of the other goods in a well-managed way for example clothes, tools and digital means of entertainment etc. [1]. In this kind of sharing platform there is a dire need to attract a huge number of consumers, and sometimes it becomes much difficult to attract certain amount of customers. Therefor in order to convince more users, it is very crucial to address them in right way and explain the advantages (such as ecological sustainability, rapid and global access to products and low price) of the sharing economy. Advantages could be different for different products accordingly. The low price of sharing offers as compared to classical consumption offers is the strongest reason for customer. The term sharing economy is not clearly defined yet, but it has emerged as a game changing phenomenon of this century and the emergence of this phenomenon fueled by internet and mobile technology [19,20]. The term sharing economy often used as an umbrella term in information system (IS) for different types of P2P exchange and for combined consumption, accessbased consumption or commercial sharing systems [10,17,22–24]. There can be many reasons for participating in the sharing economy, but trust is the most important factor among all. In sharing economy trust is labeled as “currency” [12]. In a report, the authors argued that, in sharing economy trust is symbolized by a set of exclusive transaction features and there are four factors of differentiation 16. First, trio of relationship (peers, platform and underutilized products) must be there at least when transaction takes place. Second, not only online interactions but offline interactions must be a part of social connection. Third, no handover of ownership, i.e., transaction of product with the entrusting component of returning [17]. Fourth, except of exchanging pure goods, transactions may be related with personal characteristics of services. Hence, importance of trust in P2P sharing platforms has different value in comparison with other economic exchange such as established business-to-consumer (B2C) or (C2C) e-commerce. In the light of aforementioned discussion, this study proposes the conceptual framework of trustworthiness in Fig. 1 as following. It demonstrates that platforms Ability (AB) to give excellent services, transaction and life safety

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mechanism can make people think that platform is trustworthy, platforms Integrity (IT) is also be an important factor from consumer’s point of view as they think the platform can keep promises to meet user’s expectations. For DiDi platform to be trusted the predictability (PD) is also important factor because people can predict about the platform that what it will do and what to expect from the platform. Safety of the consumers (SC) also important as consumers can be sure if they got any trouble they will get help immediately from the platform and are confident that the platform will conduct adequate authentication and background checks to ensure the safety of consumers.

Fig. 1. Conceptual framework of Trustworthiness

3 3.1

Data Collection and Research Methodology Data Collection

This study is a descriptive come empirical in nature. The study aims to find that how trustworthy “Didi” online platform is, who provide taxi service in Shanxi, and what are the factors of that trust. The analysis is based on primary data collected from DiDi users. Survey Monkey (https://www.surveymonkey.com/) is an online platform to collect data set [24]. The new technology has eased the process of collecting responses, and thus in this article, we generated our own micro-data based trough online Survey. As pointed out by [24], the advantages of the online survey are to minimize the cost, time, realtime access and convenience for the respondent. The target population of our study is the group of respondents currently using DiDi service oftenly. The sampling frames used for this article are comprehensive. The questionnaire was designed based on the following studies; such as [10,17,18]. The study aims to find that how trustworthy “Didi” online platform is which provide taxi service in Shanxi, and what are the key features of that trust. For this purpose, a survey has been conducted

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to collect the data from Didi users in Shanxi province. The convenience sampling technique applied to collect the data relating to demographics, income and questions related to Trust on the platform, Ability of the platform to provide excellent services to its consumers, questions about the “Integrity”, questions related to “Predictability” and Safety of the consumers from 327 respondents. 3.2

Statistical Computational Tools

The statistical computational tools SPSS is used to evaluate and analyze the primary data. The participants were asked to answer the questions related to the demographics; like their gender, their education, their marital status, their income level, their age. The Correlation matrix is used to examine the data, identifying the inter-dependence and the relationship between Trustworthiness and other variables as Ability, Integrity, Benevolence, Predictability and Safety of the consumers. Regression analysis has been used to check the relationship and the impact of considered variable on trustworthiness.

4 4.1

Data Analysis and Results Discussion Demographic Attributes

For primary data analysis, we use the Statistics and Data (Stata) and Statistical Package for Social Sciences (SPSS) as mentioned above. A total of 327 users of DiDi service in the survey. Table 2 demonstrates the descriptive statistics of the participants. The Male participants (66) are more than Female participants, while the majority participants were bachelor’s degree holders 46%, master’s degree holders were 31% and above that 22%. Moreover, age wise most participants were young like between 18 and 25 (40%), while the participants within Table 2. Descriptive statistics of future intentions (N = 327) Variable Gender

Number

Female Male Age 18 to 25 26 to 30 31 to 40 Education Bachelor Master Doctor Income Less than 5,000 5,000–10,000 More than 10,000

Frequency Percentage 111 216 132 125 70 153 102 72 197 93 37

33.9 66.1 40.4 38.2 21.4 46.8 31.2 22 60.2 28.4 11.3

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the age group of 26´lC30 were 38% and 21% were above 31 of age. According to income we divided the sample into three categories less than 5,000, 5,000 to 10,000 and above 10,000 and most of the participants belongs to first category less than 5,000 (60%), 28% participants were with 5,000 to 10,000 income and only 11% were having more than 10,000 income. Table 3. Gender Mean comparison AB Male

IT

BN

PD

SC

2.37 2.51 2.35 2.26 2

Female 2

2.58 2.77 2

1

Figure 2 and Table 3 depict the mean comparison between male and female and concludes that there is a preferential difference between the answers of male and female. Some of the factors are important for male and others are considerable for females. It infers that Ability (AB) of DiDi platform is important for both the genders but it is more important for males as compare to females. Which means for male ability is an important factor which makes the platform trustworthy. Integrity (IT) is also an important factor according to both genders and both. For males Predictability (PD) is more preferable as compare to females because they think that platform is trustworthy as they know that the platform is predictable, and they are quite certain about what the platform will. Safety of the consumers (SC) is also important determinant for both male and female but as we can see from the results shown above female are more concern about the security of the consumers so they think security of the consumer is very important to trust on the platform as compare to male consumer although both the genders thinks that its an important factor.

Fig. 2. Gender Mean comparison

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Correlation Matrix

This study tries to investigate the trust level of people on the online sharing economy platform and the factors behind that trustworthiness. A user’s perception after using DiDi service provided the strongest prediction for whether online platform providing riding services is trustworthy or not. The matrix correlations in Table 4 reveal that there is a negative correlation between Trustworthiness and Ability to provide excellent service. It indicates that people who use this service are not saying that the platform is trustworthy because the platform can provide excellent service. Moreover, there is a positive correlation between Integrity, Benevolence, Predictability and Safety of the consumers and trustworthiness. Table 4. Matrix of correlations Variables TR

4.3

AB

IT

BN

PD

SC

TR

1

AB

−0.036 1

IT

0.272

0.317 1

BN

0.092

0.367 0.37

PD

0.391

0.302 0.299 0.225 1

SC

0.395

0.197 0.382 0.284 0.53 1

1

Regression Analysis

Reliability and validity tests were performed in the model. Convergent validity was examined by three tests, i.e., Factors loading, Composit reliability (CR) and Average variance extraction (AVE) the factor loadings value should be greater than 0.70 and our models Factor loading value is more than 0.70 with statistical significance; composite reliability (CR) should be larger than 0.80 as mentioned in the Table 4 its greater 0.80 and average variance extraction (AVE) should be higher than 0.50 our model this value is also according to the condition [11]. Table 5 indicates that all values of factor loading are greater than 0.70 in both organized & unorganized formats. In addition all items shows the higher level of composite reliability (CR) and Cronbach’s alpha values range from 0.91 to 0.98 in the model which is also fulfilling the conditions. AVE is also greater than benchmark value 0.50. Thus, it indicates the high and good level of convergent validity and reliability in the model. Table 6 shows the results of regression analysis and the results shows that there is a direct impact of all the under taken questions like questions related to the ability (AB), that platform has the ability to give excellent services, transaction and life safety mechanism on the platform is reliable and overall it worked very well technically so the generated variable shows that people think that platform is trustworthy because that’s fulfilling their requirements and they think that platform is able to give good services as its value is positive and

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Table 5. Reliability and Validity tests results Construct

Factor loadings Cronbach’s Alpha CR

Trustworthiness T1 T2 T3 T4

0.884 0.714 0.775 0.806

Ability A1 A2 A3 A4

0.944 0.853 0.828 0.802

Integrity I1 I2 I3

0.886 0.819 0.78

Benevolence B1 B2 B3

0.899 0.883 0.788

Predictability P1 P2 P3

AVE

0.879

0.895 0.631

0.908

0.918 0.737

0.861

0.869 0.689

0.885

0.893 0.736

0.898

0.863 0.68

0.935

0.923 0.707

0.74 0.901 0.825

Security of the consumers 0.8 S1 S2 0.74 S3 0.897 S4 0.865 S5 0.89

statistically significant. Integrity (IT) is also an important factor according to consumer’s point of view as they think the platform’s action is always consistent with his words, the platform can keep promises to meet user’s expectation and the platform doesn’t cheat users for its own good so the variable composed have a positive and statistically significant impact on trustworthiness as its p-value is less than 0.05. Questions asked in the predictability (PD) were based on my experience in the past, I know the platform is predictable, I am quite certain about what the platform will do and I am quite certain what to expect from the platform.

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Definition

Variable

B

Std. error Beta t

Sig.

People think that the internet sharing economy platform has the ability to offer excellent service to meet consumer’s needs

Ability (AB)

0.212 0.053

0.215 3.97 0

People think that Integrity (IT) the platform doesn’t cheat users for its own good

0.192 0.06

0.177 3.18 0.002

The platform won’t Benevolence (BN) do anything to harm the user’s interests

0.022 0.052

0.023 0.42 0.67

Based on my experience in the past, I know the platform is predictable

Predictable (PD)

0.28

0.056

0.291 4.97 0

I can get help immediately from the platform when I’m in danger

Consumers safety (SC) 0.178 0.048

0.222 3.72 0

And people think that as they can predict about the platform that’s why they have a trust on that platform as the result in the Table 5 shows the positive and statistically significant result. Safety of the consumers (SC) I can get help immediately from the platform when I am in danger, I am confident the platform conducted adequate authentication and background checks to ensure the safety of users, the platform has enough safeguards to make me feel comfortable using it, I feel assured that deposit and insurance mechanisms adequately protect me from trading problems and I believe the platform can provide reasonable compensation once I encounter losses the p-value of Safety of consumer is also less than 0.05 which indicated that people believe that the platform is trustworthy because it is too conscious about their customers safety.

5

Conclusion

According to SIC, The sharing economy in China generated revenues of up to RMB 4.9 trillion in a recent couple of years. The sharing economy is an emerging solutions for many problem such traffic, energies consumption and pollution control in our case “DiDi” platform.

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According to the results shown above customers trust on online platform of DiDi service is due to different aspects that customers think are very important according to them. As in the questioner different questions were asked from participants about the services that DiDi is providing like do they have the ability to provide services according to your demand, are the transaction and life safety mechanism on the platform is reliable and overall it worked very well technically. In the Integrity (IT) question like, the platform’s action is always consistent with his words, the platform can keep promises to meet user’s expection and the platform doesn’t cheat users for its own good were asked. Questions asked in the predictability (PD) were based on my experience in the past, I know the platform is predictable, I am quite certain about what the platform will do and I am quite certain what to expect from the platform and people believe that they can predict about the platform that’s why they have a trust on that platform. Safety of the consumers (SC) I can get help immediately from the platform when I am in danger, I am confident the platform conducted adequate authentication and background checks to ensure the safety of users, the platform has enough safeguards to make me feel comfortable using it, I feel assured that deposit and insurance mechanisms adequately protect me from trading problems and I believe the platform can provide reasonable compensation once I encounter losses and the results showed that people do have enough trust on the platform. So the present study concluded that the share of sharing economy has been increasing and investors are keen to invest in the sharing economy the reason behind that is that people trust the sharing economy platforms and they believe that these platforms will ensure their security, safety, comfort and never cheat them for their own benefit. The current research unfolds that sharing economy is beneficial for low income level and can also enhance the quality of life. It also found that “DiDi” users are satisfied and believe that it never cheat its customers along comfort. On the other hand, “DiDi” users do not have confident that vendors on the platform are honest and trust worthy. The study also explored that male users are more satisfied and trust on “DiDi” platform as compared to female while Single users have more trust on “DiDi” platform as compared to married The “DiDi” platform needs to work on vendors to sustain its users. So for sharing economy it is very important to take into account the quality and responsibility of good services provided on the online platforms. Acknowledgements. The authors would like to acknowledge the respected General Chair Jiuping Xu, The International Conference of Management Science and Engineering Management and anonymous reviewers for their valuable suggestions and comments, to improve manuscript quality.

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References 1. Balck, B., Cracau, D.: Empirical analysis of customer motives in the shareconomy. Technical report, working paper series, University of Magdeburg, Magdebur (2015) 2. Batista, C., Lacuesta, A., Vicente, P.C.: Testing the ‘brain gain’ hypothesis: micro evidence from cape verde. J. Dev. Econ. 97(1), 32–45 (2012) 3. Belk, R.: Sharing. J. Consum. Res. 36(5), 715–734 (2010) 4. Belk, R.: You are what you can access: sharing and collaborative consumption online. J. Bus. Res. 67(8), 1595–1600 (2014) 5. Benkler, Y.: Coase’s Penguin, or, Linux and “the nature of the firm”. Yale Law J., 369–446 (2002) 6. Boncea, I.: Turning brain drain into brain gain: evidence from romania’s medical sector. Procedia Econ. Financ. 20, 80–87 (2015) 7. Bostsman, R., Rogers, L.: What’s Mine is Yours. Harper Business, New York (2010) 8. Frenken, K.: Political economies and environmental futures for the sharing economy. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 375(2095), 20160,367 (2017) 9. Gansky, L.: The Mesh: Why the Future of Business is Sharing. Penguin, London (2010) 10. Group A.: The global product design benchmarking report (2005) 11. Hair, J.F., Ringle, C.M., Sarstedt, M.: PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 19(2), 139–152 (2011) 12. Hamari, J., Sj¨ oklint, M., Ukkonen, A.: The sharing economy: why people participate in collaborative consumption. J. Assoc. Inf. Sci. Technol. 67(9), 2047–2059 (2016a) 13. He, C., Zhang, J., Liu, H.: Sharing economy: literature review and future directions. Jingji Guanli 1 (2017). (in Chinese) 14. Hussain, S.M.: Reversing the brain drain: is it beneficial? World Dev. 67, 310–322 (2015) 15. Ifanti, A.A., Argyriou, A.A., et al.: Physicians’ brain drain in greece: a perspective on the reasons why and how to address it. Health Policy 117(2), 210–215 (2014) 16. Li, H., Ma, Y., et al.: Skill complementarities and returns to higher education: evidence from college enrollment expansion in China. China Econ. Rev. 46, 10–26 (2017) 17. Neely, A., Mills, J., Platts, K., Richards, H., Gregory, M., Bourne, M., Kennerley, M.: Performance measurement system design: developing and testing a processbased approach. Int. J. Oper. Prod. Manag. (2000) 18. Robert, S.: The balanced scorecard: measures that drive performance. Harv. Bus. Rev. 70(1), 71–79 (1992) 19. Santana, J., Parigi, P.: Risk aversion and engagement in the sharing economy. Games 6(4), 560–573 (2015) 20. Sharing Economy Research Center, State Information Center, and Sharing Economy Working Committee: Zhongguo Fenxiang Jingji Fazhan Baogao 2017 (Report on the Development of Sharing Economy in China) (2017). http://www.sic.gov. cn/News/568/7737.html. (in Chinse) 21. Sharing Economy Research Center, State Information Center, and Sharing Economy Working Committee: Zhongguo Gongxiang Jingji Fazhan Niandu Baogao 2018 (Annual Report on the Development of Sharing Economy in China) (2018). http:// www.sic.gov.cn/News/79/8860.htm. (in Chinese) 22. Tomoo, M.: Sharing economy in China and Japan. Jpn. Polit. Econ. 66 (2019). https://doi.org/10.1080/2329194X.2018.15556

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23. Xin, J.J., Xin, J.Y.: Nian Didi Chuxing Pingtai Jiuye Yanjiu Baogao. (New Economy, New Jobs: Research Report on the Jobs at Didi Chuxing Platform) (2017). Downloaded at http://www.199it.com/archives/646093.html. (in Chinese) 24. Yu, W.: To stay or to return? Return intentions and return migrations of Chinese students during the transition period in the united states. Pap. Appl. Geogr. 2(2), 201–215 (2016)

5W Mode Analysis of the Media Communication Strategies of Online Video-Produced Variety Shows Using the Chinese Variety Show U Can U BiBi as an Example Yuheng Chen1 and Xin Liu1,2(B) 1

2

College of Communication and Management, Sichuan University of Media and Communications, Chengdu 611745, People’s Republic of China [email protected] Business School of Sichuan University, Chengdu 610065, People’s Republic of China

Abstract. Watching online video network variety shows has become a popular entertainment mode as they have, rich content and allow for audience interaction. This paper explored the unique media communication elements and network modes of Chinese online variety shows based on the classical “5W” theory of media communication. Taking a Chinese variety show, U can U BiBi, as an example, the media communication content, channel, audience targeting, media communication effects, network survey data, media communication characteristics and commercial value are systematically analyzed. Effective media communication needs successfully positioned itself to meet the psychological needs of the target customers, allows the audience to interact and think about serious social issues through its entertaining format. Its future developments aim is to create great content, match precisely the theme using big data, and balance commercial and social benefits.

Keywords: Variety show communication mode

1

· U can U BiBi · 5W theory · Media

Introduction

Compared with TV variety shows, online video variety shows have developed rapidly since 2014, and have become increasingly popular and increasingly competitive. Consequently, there has been a rise in academic studies on online video shows over the past three years in an attempt to understand and explore their development and popularity. Recent studies have focused on the optimized operation system of internet streamed programs [5], the differences between online variety shows and traditional TV variety shows [8], the multiple business models c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 730–741, 2021. https://doi.org/10.1007/978-3-030-49889-4_56

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Table 1. Development of Chinese internet streamed programming Year

2014

2015

2016

2017

2018

Policy

Policy loosening

Policy tightening

Policy tightening

Policy tightening

Policy tightening

Capital

Capital calm Capital period input

100 million CNY Investments

Capital influx

Return to calm capital

Talents

Attract people from TV stations

Traditional TV Talents

Traditional TV Talents in bursts

Traditional and internet platforms progressing together

Continuous supplement for talents

Production Company

Initial development of internetbased programs

Fast development of internetbased programs

Synchronization of new and Traditional Companies

Advantages of the traditional programming outweighs internetbased programming

Stable production status

Platform

Start up

Internet platforms affect traditional channels

Internet platforms Attract youth to variety shows

Stable status and diversified revenue

Internetbased variety show quality improved

Example

U can U BiBi

Go Fridge

Mars Intelligencee Agency

The Rap of China

Produce 101

[9], analyses of the cultural hybridity presenting an important ways of synthesizing the study of cultural and communication in the context of globalization [4], analyses on online media industry’s innovation and challenges to the traditional media platforms [3], and youth subculture productions [14]. Therefore, to fully understand these internet-based variety shows, it is necessary to review the development of TV internet programming in China. The development process for internet based Chinese variety shows is shown in Table 1. In 2014, an internet-based online talk show called U can U BiBi was launched by iQIYI, an online video platform based in Beijing, China, that had a large production budget and well-known Chinese celebrities, which changed the impressions in China that online shows were crudely manufactured [6]. Over five seasons, the production has attracted 1.5 billion CNY and has resulted in a significant rise in other competing online video productions. Therefore, U can U BiBi was a turning point in China’s online video production industry. Because of its success, U can U BiBi has attracted significant academic media research attention. From 2014 to 2019, there were 334 papers that mentioned

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or discussed U can U BiBi on the National Knowledge Infrastructure (CNKI) website and foreign journals, the main research points from which are discussed in the following. Studies on U can U BiBi have discussed the host [13], the branding [10] and the online video advertising marketing strategies [12]. However, these studies were focused on a specific aspect of the programming rather than examining the reasons for the success of U can U BiBi. Therefore, this paper applied Lasswell’s 5 W classical media communication theory to systematically explore the media communication strategies of the online variety show U can U BiBi.

2

“5W” Media Communication Theory and Methodology

Harold Lasswell, an American scholar, proposed five basic elements for the media communication process and ranked them in structural order; who, what says what, through which channel, to whom, and with what effect [7]; which was the first time that media communication activities had been modeled as a process of five links and elements to understand its inherent characteristics. Using these five elements, this paper examines the media communication strategies of the online variety show U can U BiBi in terms of its media communication methods, the content, the channel, the audience and the effect. Three methods were used to examine these five elements of U can U BiBi. First, the relevant literature on CNKI; relevant publications, investigation reports from internet data survey agencies (CNKI, Ent Consulting or authoritative information websites) and media reports on network variety shows and U can U BiBi were extracted. Second, media communication theory was used to comprehensively explore the online video variety show U can U BiBi. Finally, a textual analysis was conducted on the media communication subjects, contents and U can U BiBi channel.

3 3.1

U Can U BiBi Media Communication Model An Analysis of Communication Subjects on U Can U BiBi

The recent increase in the number of online video variety shows has given rise to significant research into new media communications. Therefore, an analysis of the structure and relationships within these new media communication companies can reveal the specific characteristics and functions. Taking U can U BiBi as an example, the new media communication relationship structures are shown in Fig. 1, each element of which is discussed in the following. (1) Professional production team The success of U can U BiBi is inseparable from the efforts of the creative team. First, the U can U BiBi production team has wide program production experience. The chief producer, Di Mou, who is charge of the network variety show, previously worked at CCTV China Central Television and has had significant

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Fig. 1. Analysis of Media communication variety show U can U BiBi

experience in making shows for TV. Famous as being one of the youngest directors in the history of CCTV, she was the director of famous TV shows such as Joy Street, Happy China Travel, The First Lesson of School and Dream Chorus. As the audience orientation of U can U BiBi is young people born after 1990, the main creative team is staffed with young people with an average age of 24 to ensure that there is a better understanding of the likes and needs of this generation. Because there is a professionally trained production team, the show has very strict quality requirements in terms of the way the program is shot, the use of subtitles, and the expressions and symbols given prominence by the contestants. Two-thirds of the 30-member production team are female, with the four core directors all being women, as it is believed that they are more able to deal with the details and connect with the mostly female audience. The team leader, Dong Ma, gives the young team his full trust, which means that the team is free to develop each program in a relaxed and creative atmosphere. People in the entertainment industry have commented that the recording and production levels of U can U BiBi are equal to other first-class variety shows in China. (2) Creative program host The creative hosting is another characteristic of U can U BiBi. The variety show has brought together what is known as the “Ma Xiao Kang” combination; that is, the most talkative intellectuals in China named Xiaosong Gao, a well-known host of Taiwan’s most popular program Kangxi Come named Kangyong Cai, and Dong Ma, a humorous former CCTV host. In the fifth season of the show, Dan Li and Zhaofeng Xue were brought on board as creative mentors. Dan Li is very popular with young Chinese people because of his witty and humorous performances in another variety show called Roast, and Professor Xue, who is also known as “Professor Economics” because of his economics course that has attracted more than 250,000 subscribers on an Internet knowledge service platform. The participation of Professor Xue means that he can give opinions from an economic angle on the debate topics, which has aroused audience curiosity and made the program more appealing.

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(3) Star guests As U can U BiBi is an interactive debate program, to attract audiences, every show invites star guest, such as Shanshan Yuan, Yan Liu, Yang Lan, and Jun Lei, to join in the debates, who are decided on using big data judgements. When U can U BiBi invited Shanshan Yuan to two programs, even though she did not talk much during the show, the Baidu Index showed that her participation set a new demand rate. The program also uses big data to select the star guests, and the production team chooses topics that are related to these star guests. For example, a guest called Xiyuan Xu had once said that she attached great importance to love and would devote herself 100% to every relationship, but that if she found the relationship was not suitable, she would end the relationship decisively. Therefore, the program team specifically matched her with the topic “Would you get divorced if you met your true love after getting married?” In other examples, as Xidi Xu has been rumored to have had cosmetic surgery, the program specifically matched her appearance with the debate topic “Will cosmetic surgery help you become a winner of life?” and because Isabella Leong gave birth to three sons to Hong Kong businessman Zekai Li at the age of 19, after which they broke up, the program specifically matched her with “Would you tolerate your partner if they snuck behind your back?” This approach of matching the debate topics with the star guests has attracted significant audience interest as it allows the general public to hear real answers from their stars. (4) Diversified debaters U can U BiBi also ensures that it has diversified debaters when selecting contestants and focus on people who are authentic and good at expressing themselves. Quite a few contestants come from the professional debating world, such as Ming Chen, a journalism and media communication lecturer at Wuhan University, Weiwei Ma, a debate captain at Sun Yat-sen University, and Zhan Qingyun, a debate team captain at Harvard University, all of whom use their ideological knowledge to deepen the debate. However, it also includes people such as the rapper Future Start, who used his unique rap logic to persuade the audiences and Yulin Shen and Tiantian Fan, famous comic actors. The host of U can U BiBi, Dong Ma, told the Global People: “I think the greatest value of people today is to be different. Therefore, we should use Qiba to distinguish and find those who are different from the common people, people who have had different experiences, have different feelings, or have different talents. In short, people who have the power to make themselves stand out and be quickly recognized in the crowd” [15]. The program allows the diverse contestants to argue freely and openly, which results in magnetic viewing. 3.2

An Analysis of the Media Communication Content in U Can U BiBi

(1) Using big data to select the debate topics The debate topics used in each U can U BiBi programme are all topics the audiences may encounter in real life. To ensure the choice and design of the debate topics are acceptable to as many people as possible, in the early planning

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stages, the program team conducts extensive research on thousands of topics, selects some of them and then puts them on internet to let the audience vote. For example, in the fifth season, the 38 final topics covered emotions, professional life, and social life. While around 50% of the topics were related to love because of the young target audience’s interest in emotional topics, the professional life topics were also popular. (2) Audience sub-culture The values of the young people of the internet generation are quite different from those of the older generation. The majority of Chinese internet users are teenagers, young adults and the middle-aged, with the estimated value of these being estimated at 802 million internet users in June 2018. Of these, the 0–39 age group accounts for 70.8% of total internet users, 27.9% of which are users aged 20–29 [1], who are the main audience for U can U BiBi. As most internet users have grown up with the television and the internet, they have higher requirements and unique preferences for variety shows. Therefore, the unique style and content of the online variety show U can U BiBi satisfies the cyber generation’s rebel resistance and mocking of mainstream life, and its personalized approach makes U can U BiBi more attractive and acceptable to the audience. In addition to the content, the audience can use a bullet screen (a moviewatching model that was introduced into selected theaters in China in 2014 and widely used by video websites) to express their views and opinions on the program content in real time. Therefore, some viewers also like to watch the bullets to know what other viewers think of the program. Because bullet screen culture has spread rapidly among young people, the iQIYI platform has set up an official bullet screen for U can U BiBi that also includes a section that invite hosts and viewers to participate, which has further strengthened the program’s popularity. 3.3

An Analysis of the U Can U BiBi Media Communication Channel

(1) On-line multichannel media communication model The network variety show U can U BiBi has a multi-dimensional media campaign. At the beginning, the U can U BiBi creative team used big data to fully investigate other social platforms and visited the websites and platforms frequented by their target audience such as Douban, Weibo, WeChat, and Moments, on which they posted their popup advertisements for the video website. The program production team also registered a Wechat public number “Dongqimen” to report what goes on behind the scenes of U can U BiBi, and purchased hot topic micro-blogs for their advertising as well. In addition, iQIYi has also made full use of Baidu and its own iQIYi platform. If U can U BiBi is used as a key word in a Baidu search, it is given a prominent position on the home page with links directly to the relevant videos. The Baidu search engine has the highest user share in China, with an average of 6 billion search requests per day; therefore, many viewers tend to use Baidu as their priority choice when searching for video content.

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After acquiring PPS, iQIYI had a huge number of users. By December 2018, the iQiYi app was the first in the industry with a total usage of 4.36 billion hours per month, 17.53% higher than the second Tencent video platform (3.71 billion hours) [2]. U can U BiBi has several positions on the iQiYi platform, including the home page screen, which recommends variety shows. The prominent recommendations on the iQiYi platform attracts audiences for U can U BiBi and allows iQiYi users to watch its exclusive VIP program Qipa ICU to learn more about U can U BiBi in front of a./nd behind the scenes. In short, the programme’s creative team has sought to expand the influence of U can U BiBi on multiple channels and levels. (2) Offline face-to-face interactive media communication mode In addition to the online publicity, from the first season to the fifth season, the U can U BiBi production has held a number of fan meetings to promote the show. At the fan meetings, the popular debaters interact with the host, answer questions and play games with the fans, which encourages close fan contact and allows the debaters to thank their supporters, which further strengthens the connections with the show’s audiences. 3.4

Audience Analysis of U Can U BiBi

(1) U Can U BiBi audience A structural audience analysis is vital to the study of U can U BiBi, for which big data was used. A consulting company named Shenzhen TENTINET published a series of audience surveys, from which it was found that the main characteristics of the U can U BiBi audience were highly educated, mid 90s born young women [11].

Fig. 2. Age distribution of the U can U BiBi audience

As can be seen from Fig. 2, 60% of the U can U BiBi’s audience were between 18 and 30 years old, with a further 16.9% being under 18 years old, and around

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15% being 30 or older. Therefore, most of the audience are young people, as is the case for most online video programs in China. The U can U BiBi production team put trailer announcement that the program encourages tens of millions of post-90s and post-95s to discuss the debating topics on Baidu’s post bar, to further strengthen audience participation.

Fig. 3. U can U BiBi audience gender statistics

As can be seen in Fig. 3, the U can U BiBi audience is 69% female, possibly because of the emotional topics on the program. As can be seen in Fig. 4, 73% of the U can U BiBi audience has college, undergraduate or postgraduate degrees, probably because audiences that have a high level of knowledge and good cultural foundations can better understand the program content and the critical thinking required. (2) Psychological analysis of the U can U BiBi audience U can U BiBi has clear audience and program orientations. As post-90s born are the main target customers, all the U can U BiBi debate topics are closely related to “post-90s” concerns such as emotional confusion or current social problems, all of which resonate with the young urban target audiences and keeps them returning to the show. This internet generation likes to browse the internet and express their opinions freely through posting, commenting and leaving messages, with the assured anonymity allowing them to express their opinions more truthfully in the microblogs or screen bullets, which gives them psychological satisfaction. The U can U BiBi production team also strives to create a “content ecological chain” to attract users from the Qipa community. For example, audiences are able

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Fig. 4. U can U BiBi audience education level

to view videos from Season 1 to Season 5 U can U BiBi shows on the iQIYI platform and review the controversial topics, interesting debates and unusual contestants. After the success of U can U BiBi, Ma Dong’s team launched another free variety talk show The Temptation of Dinner and the derivative work Here They Come, which has attracted audience attention because of their ability to be involved in the selection of the contestants. Its latest developed paid program Let’s talk has also attracted many hardcore fans and now, some special snack items such as melon seeds, original French fries, and fresh ground beef have been developed for purchase on the official Wechat account “Dongqimen”. 3.5

Analysis of the Media Communication Effect of U Can U BiBi

(1) User satisfaction The U can U BiBi talk variety show has been able to attract audiences for five consecutive seasons because the programme content has been able to satisfy viewer interests through the careful selection of the debating topics by the programmers that encourage audience comments on the screen bullets, and allow them to compare their values with the debaters in the program. The consulting company TENTINET reported as Fig. 5 shown that nearly three-quarters of the U can U BiBi audience had positive emotions while watching the program, and only 12.62% had negative emotions, with most feeling optimistic after watching the show. As the U can U BiBi content is relaxed and pleasant and the debates humorous, people feel relaxed while watching the program. (2) Positive program dissemination energy In his book Positive Energy, Richard Wiseman, a professor of mass psychology media communication in Britain, pointed out that “Positive energy refers to all

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Fig. 5. U can U BiBi audience emotion analysis [11]

the motives and feelings that give people hope and motivate them to pursue a happy life”. In addition to its bold alternative active form, as U can U BiBi conveys positive ideological and cultural values, it offers educational and spiritual guidance to the audience. As entertainment is the top priority of all major variety shows, few variety shows consider entertainment that conveys mainstream values. As a talk show for young audiences, U can U BiBi not only makes the audience happy because of its alternative debate format, but also transmits positive energy on social responsibility. The U can U BiBi debate topics are generally topics that young people care or are curious about. The debates allow the contestants to express new and interesting views, which can arouse the young people’s thinking on these topics and the current society. For example, through the topic “will cosmetic surgery help you become a winner in life”, rather than being overly concerned about face value, young people can realize that their own quality is the key to success. In other examples, the topic “should couples peep at each other’s mobile phones?” reminded young people of the respect and understanding couples should have and “is it necessary to buy an apartment before getting married?” reminded young people that they should not regard buying a house as the only goal in life. In summary, the variety show U can U BiBi not only entertains people, but also actively promotes positive audience social values.

4

Conclusions

With the development of mass media and the development of diverse interests, entertainment program choices have become diversified. Therefore, an excellent

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variety show must constantly innovate its content to enhance audiences’ attention. The U can U BiBi variety show produced by iQIYI has attracted significant sponsor investments and super stars. Since its launch, its ratings have soared, it has been widely praised by media and arts experts, and has provided a powerful reference for the development of other comprehensive online video programs. Based on the “5W mode” of mass media communication proposed by the famous American scholar Lasswell, this paper analyzed the media communication, content, channel, audience and effects of the online video variety show U can U BiBi. To ensure effective media communication, U can U BiBi put together a young creative planning team, a dignified mentor lineup and diversified debaters, and used big data to select current debate topics for its target audience. The production team uses multiple online or offline channels to publicize and promote the show and has successfully positioned itself to meet the psychological needs of the target customers. Lastly, from the point of effect, U can U BiBi disseminates positive values and allows the audience to interact and think about serious social issues through its entertaining format. There has been a rapid development in the production of online video variety shows in China. However, future developments should aim to create great content, make full use big data, and balance commercial and social benefits. Only in this way, can a network variety show gain greater recognition and support from the audience.

References 1. CNNIC: The 42nd China statistical report on internet development (2018). (in Chinese) 2. CSND: iQIYI’S active users continued to grow in size in 2018 and ranked first in the online video industry steadily [EB/OL] (2018). (in Chinese) 3. Cunningham, S., Craig, D.: Online entertainment: a new wave of media globalization? Int. J. Commun. 10, 5409–5425 (2016) 4. Flew, T., Ryan, M., et al.: Culture, communication and hybridity: the case of The Rap of China. J. Multicult. Discourses 14(2), 93–106 (2019) 5. He, S.: The operation mode of network video websites-based on a case study of iQIYI. In: 2018 2nd International Conference on Management, Education and Social Science (ICMESS) (2018) 6. Johnson, D.: From Networks to Netflix: A Guide to Changing Channels. Routledge, New York (2018) 7. Lasswell, H.D.: The structure and function of communication in society. Commun. Ideas 37(1), 136–139 (1948) 8. Luo, Y.: The Role of the Target Audience and Their Preference for Programming in Increasing Subscribers to China’s Online Video Website iQiyi. Drexel University, Pennsylvania (2019) 9. Ou, S.H., Su, H.T.: Hybrid business model innovation: the cross-boundary mechanism for over-the-top organizations. Manag. Rev. 36(4), 1–15 (2017) 10. Rong, K., Xiao, F., et al.: Platform strategies and user stickiness in the online video industry. Technol. Forecast Soc. Change 143, 249–259 (2019)

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11. Tentinet: Internet audience investigation of U can U BiBi [EB/OL] (2018). https:// mp.weixin.qq.com/s?--biz (in Chinese) 12. Xu, J., Duan, Y.: Subscription price and advertising space decisions for online content firms with reference effect. Electron. Commer. Res. Appl. 30, 8–24 (2018) 13. Yang, Y.: An exploration of controlling ability of the host from the variety show U can U BiBi. Drama House 23, 243–244 (2016). (in Chinese) 14. Zhang, N.: Business logic and youth subculture production: critical discourse analysis of Netscape programs. Mod. Media Commun. (J. China Media Univ.) 41, 138–142 (2019). (in Chinese) 15. Zhao, X.: Madong: let’s the variety show U can U BiBi develop faster. Global People 3, 20 (2015)

Clusters as an Environment of Competitive Collaboration. A Case Study on the Emerging Apparel Economic Cluster in the Republic of Moldova Elina Benea-Popu¸soi(B) and Ecaterina Rusu Academy of Economic Studies of Moldova, Chi¸sin˘ au, Republic of Moldova [email protected], [email protected]

Abstract. The research aims to explore the drivers and barriers that influence the inter-firm competitive collaboration within clusters. In this view, a case study on the emerging apparel cluster in the Republic of Moldova was accomplished. It focused particularly on identifying the types of existing collaboration linkages between firms and evaluating the context-specific factors that inhibit or encourage these linkages. The results suggest that despite the relatively dense agglomeration of firms within the emerging cluster, this does not translate into extensive collaboration networks. Entrepreneurs manifest hesitation toward collaboration and the lack of relational capital, as a common feature of most post-socialist economies, remains a big issue in making the cluster work. This represents a missed opportunity for cluster performance, specifically as the social capital crucially matters for knowledge and innovation to be transferred more readily. Keywords: Clusters · Agglomeration · Proximity · Networking · Relational capital · Social capital · Competitive collaboration · Collaborative environment · Coopetition · Transition economies · Former centrally planned economies

1

Introduction

In the past decades, much attention has been paid to the industrial clusters, that are considered a significant source of competitiveness and innovativeness. Many empirical studies claim that clustered firms show a higher innovative capacity than isolated firms and experience stronger growth because of the geographical proximity that encourages knowledge externalities. However, more recently scholars brought into the light the non-spatial forms of proximity, highlighting that the processes of interaction and networking necessary for knowledge diffusion do not occur automatically in physical space and it is not equally spread within the cluster [7,8]. Thus, considering the overemphasized role of geographical proximity and underestimated role of networks, it was imperative to pay c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 742–754, 2021. https://doi.org/10.1007/978-3-030-49889-4_57

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more attention to the analysis of the culture of collaboration. Related to this, scholars started to integrate the social capital dimension in the theory of clusters and connect it with economic performance. As Porter highlights, the key determinants in clusters performance are the social embeddedness, the existence of facilitative social networks and institutional structures [28]. However, the studies operationalizing with the cluster concept in terms of networks and social capital are scarce and the relationship between social capital and degree of collaboration within clusters is still widely under-investigated [21,25]. Moreover, it is little known about the firm-level factors that stimulate creation, duration, and dissolution of collaboration networks and how they underpin the inter-firms’ knowledge diffusion within clusters. This paper aims to investigate the issues, based on a case study in apparel cluster in the Republic of Moldova. We seek to explore the patterns of collaborations in the cluster, by identifying what type of collaboration linkages exists between firms, and assessing whether these links contribute to learning and innovative capabilities of the cluster. The paper is also meant to contribute to the research of social capital within the transitions economies, specifically by examining how mentality and entrepreneurial behaviour inherited from the centrally-planned economic system may influence networking and the evolution of social ties. The case study is based on qualitative methodology, relying on interviews taken from different cluster actors. The consideration of qualitative methodology is essential when operating with networks and collaboration, as it helps to rigorously understand connectivity and explore assumptions about their implications [13]. The evidence of our research suggests scarce collaboration forms within the analysed emerging apparel cluster, also highlighting that despite the relatively dense spatial agglomeration of firms, they do not succeed to form a well-working cluster as defined by Enright [14]. This is primarily explained by the insufficient development of the institutional framework in terms of both formal and informal game rules. Accordingly, the problem can be traced back to the long period of being under a centrally planned economic system that resulted in a low stock of relational capital, lack of trust and too individualistic approach toward solving problems and operating businesses.

2 2.1

Literature Background Competitive Inter-firm Collaboration Within Clusters

Nowadays, strong competition at the local, regional and global level requires the firms to continuously upgrade their products and services. However, many firms do not have enough internal capacities to sustain and generate innovation for keeping competitive. Therefore, agglomeration economies become increasingly strategic solutions for companies to create a facilitative environment for resources, knowledge, and innovation transfer. The idea of positive effects of geographical concentration of firms belonging to the same industry could be traced back to the Marshall’s work who underlined that it creates positive externalities

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due to the access to local information and knowledge, supply inputs, and skilled local labour pool [23]. Lately, Porter developed and introduced the concept of cluster, that envisages a collaborative network that provides the necessary environment for firms to achieve higher performance due to advantages that arise from the interconnectedness of companies and institutions [27,28]. Thus, the competitive collaboration advantages associated to clusters refer to benefits that reside not within an individual firm, but rather, outside its boundaries, through the inter-firm connections. However, cluster concept does not infer that there is no competition within its members, but as regularly, cooperation resumes to specific activities that generate higher outputs if jointly produced, thus, the advantages prevail over the constraints. Therefore, cluster could transform the contradictory duality of cooperation and competition, also referred to as coopetition into a win-win situation profitable for all participants. Empirical evidence shows up that the frequent and multiple collaborative relationships among clustered firms are leading to higher competitiveness. As through inter-firm collaboration networks enterprises could: (i) complement their capabilities, that is a cost saving advantage that helps firms reach economy of scale, by helping each other with large orders, producing component-parts for one another, sharing the use of equipment, or engaging in joint marketing, etc. [11]; (ii) become more innovative, as diffusion of information takes places smoother, facilitating the transfer of tacit knowledge [19]. Moreover, the recent study of Boix, Galletto, and Sforzi introduced the idea of “the industrial district as an innovation machine”, revealing that industrial districts are characterised by greater innovative intensity than the national average [6]; (iii) internationalize more and grow in new markets as cluster helps companies to expand and improve their own capabilities and become more competitive [3]. 2.2

Proximity, Collaboration, and Relational Capital

There is a large body of literature that explains the differences in performances between regions by agglomeration economies as it offers firms the opportunity to benefit from localized knowledge. When referring to conditions for knowledge diffusion, it is obvious that geographical proximity does matter in the sense that the cost of establishing and maintaining these diffusional channels is sensitive to the distance between the generator and recipient of the knowledge. The informational exchange could take place smoother within the same area, due to the higher probability of establishing social bonds as a result of frequent face-to-face interactions. This namely explains the fact why innovative networks often do not extend beyond the regional boundaries and why they tend to keep stable once have been established. Another aspect that deserves to be emphasized when considering geographical proximity refers to the “tacitness” and “sticky” aspect of knowledge. The diffusion of valuable non-codifiable information requires repeated interaction and human contacts that can be realized just within close geographical proximity. Spatial proximity, thus, could offer

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a sustainable source of competitive advantages, therefore geographical clusters give more innovation opportunities than disperse locations [9]. Yet, the relation between spatial proximity and local economic growth is more complex and does not occur as simply as expressed in the Marshallian agglomeration model, but rather, is based on the behavioural dimension, sense of belonging and synergies within the cluster [20]. Boschma contributed to the literature in this sense, by pointing out that other types of proximity and namely cognitive, organizational, social and institutional one influence the degree of interactive learning effectiveness [7]. These relational dimensions of proximity determine the degree of firms’openess to connect and manage collaboration within and even outside the cluster. Therefore, the relational capabilities of the clusters influence their innovation performances, as more relational proximity exists between firms the more they are willing to interact, learn and innovate [3]. Therefore, the practical importance of studying the relational capital dimension derives from its role in the chain of innovation and knowledge diffusion within the industrial agglomeration. Thus, studies on clusters regularly integrate this dimension, as collaboration is a complex social process, locally embedded, that relies on mutual trusts, reciprocity and engagement that does not allow the knowledge to be locked-in, but ensure its diffusion and recombination by other actors. Hence, we could refer to the role of relational capital as creator of “value” within the cluster – “value potentially produced when people work together and trust one another” or “value potentially created on the basis of collaborative and distinctive exchanges” [2]. The two broad opportunities in which relational capital can translate into economic advantages for regional clustered businesses refer to (i) supporting innovation and (ii) diminishing transaction costs. (i) Relational capital facilitates the dissemination of intellectual capital. Organizations could have a high level of knowledge and competences, qualified staff, but this is not enough for achieving developmental objectives. It is also the mechanism of knowledge transfer that matters too, the typical example refers to the transfer of knowledge from research institutions, universities or public sector. Moreover, human capital could be a “dead capital” in the absence of proper networks that can ensure mobilization and application of skills and knowledge [1]. (ii) Relational capital as a way to diminish transaction cost. The higher propensity to cooperate as the result of established direct contacts among economic actors, trust-based networks, interpersonal meetings, less bureaucratic barriers translate into lower transaction cost. This is justified by the fact that the price of obtaining external knowledge from market-based transactions is very sensitive to the level actors know and interact with each other [5]. Relational capital can influence the way industrial agglomerations evolve and develop. The classification of clusters according to the state of development (working, latent, potential clusters) proposed by Enright serves a good way to show that the level of relational capital embeddedness varies in accordance to cluster development stage - more developed and well-functioning clusters have

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a more pronounced pattern of interactions [14]. Therefore, Enright attributes the most advanced state of developments to the working cluster, characterized by a dense presence of the critical mass of economic actors, expertise and information that form the agglomeration from which firms can take advantages of. Moreover, the most distinctive feature of this type of cluster refers to dense and high-involvement networks established between participants, allowing them to cooperate and thus, offering a competitive advantage in comparison to firms that do not belong to the cluster. On another side, latent clusters, are characterized as having a high number of firms in related industries but without a well-established level of interaction. Thus, the low cooperation and networks between them hinder the information flows, representing a missed opportunity in grasping the advantages of co-location. Potential clusters reveal promising perspectives, possessing some elements necessary for successful cluster development, but these elements need to be broadened to make possible the benefits of the agglomeration to be reached.

3

Methodology Framework

The development of cluster is a relatively new phenomenon for Moldova’s economy, being still in the emerging stage, a fact also confirmed by the Global Competitiveness Report that places Moldova on the last position (138) in the rank of state of cluster development [30]. However, acknowledging the importance of cluster for regional development and following the international experience, the government of Moldova initiated several cluster-related measures to foster their formation. As a result, at the end of 2017, an apparel cluster SORINTEX was formally created [26]. The cluster was joined by 20 manufacturing companies (specialized in garments production, supply of fabrics, accessories and machinery, embroidery services, printing) and has also as partners educational/research institutions and various public bodies. The companies and institutions formed the Apparel Cluster aiming to strengthen the collaboration among them and to increase cluster’s export competitiveness, improve quality and quantity of the labour force, and enhance cluster capacity to absorb and implement innovation. Based on a case study, our research has focused on analysing the nature and implication of collaboration between the members of SORINTEX Apparel Cluster, detailing drivers and barriers that influence them. Exploration of the relational/social capital is a versatile and complex topic as it implies understanding of institutional embeddedness of trust, structural and cognitive peculiarities of social interactions. Thus, the qualitative methodology was applied in investigating business relations and the face-to-face interviews helped to reveal personal perceptions, beliefs, and concerns of cluster representatives related to collaboration [16]. As there is no universal definition and uniformity regarding the indicators and approaches used to measure aspects of social capital [29], our analysis of social capital in the case-study cluster, mainly have focused on 3 dimensions:

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– overall perception of social capital in the society (in terms of legislation, public institutions etc.); – attitudes toward cooperation within the cluster (opportunities, barriers, drivers); – forms of cooperation within the cluster showing the existing level of relationships among competitors, customers, suppliers, universities and government institutions. Primary data collection implied 17 face-to-face interviews from the managers of the cluster’s companies, representatives of public authorities and universities. The interviews were semi-structured, allowing the flexibility to ask questions not specified in the topic guide and helping to probe in this way different assumptions. The thematically analysis method was used to process the information collected. It allowed the exploration of data’s implicit and explicit ideas, through the development of codes and themes (see Appendix A, Table 1).

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Case Study Findings and Results Interpretation

Geographical proximity assumes that it is a high probability of establishing social bonds within the cluster. Indeed, the interviewed managers reported that they know other firms’ representatives for a long time, due to the spatial proximity of the cluster that allows frequent face-to-face interactions. However, interaction takes forms of the conversations aiming to socialize instead of professionalizing. When referring to professional cooperation, most of the relationships among cluster’s firms are vertical, implying the supply of raw materials (fabrics, accessories) or services (mainly embroidery services). Thus, out of twelve firms interviewed, only four firms reported they have developed vertical collaboration within the cluster. In addition, it is worth mentioning that the rest of companies do not need to establish local supply relations because they are provided with all the necessary fabrics and accessories in the framework of the lohn agreements they have established with international firms. The horizontal relations are underdeveloped too. Some firms share the same operating space, using in common some equipment, technical materials and information. To ensure the necessary volume of products requested by contractors, they take major orders together. The joint production generates greater rents, allowing firms to take over major orders, to reduce their costs, and reduce competitive pressures. Another form of identified horizontal cooperation refers to co-investment in assets (for example joint acquisition of a soft necessary for design and respectively printing the sewing patterns). The use in common of the software contributes to the consolidation of relations between them, respectively allowing access to indirect benefits (flow of information, ideas on product design, improvement of the production process, and opening new market opportunities). The interviews with business agents have revealed reasons for the weak and underdeveloped forms of collaboration between the cluster’s members. Thus, the main identified reason refers to “self-sufficiency” mentality of the society

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expressed in the low trust and inability to work in teams. Moreover, respondents have mentioned that distrusting other entrepreneurs is a measure of protection of their business from outside competition. However, they agree this part of the “mentality” must be changed in the context of the actual business environment that requires cooperation to become internationally competitive. The scarce collaboration forms between firms and the fear to engage in collaboration expressed by many respondents make clear that the cluster is characterized by a narrow radius of trust. This results in negative externalities for firms that are not covered by this radius and acts as barriers for getting access to new ideas and information [17]. Furthermore, even some companies that are formally part of the cluster, do not identify themselves as such. For many companies, the attitude toward the cluster lacks common values as trust, beliefs, group identity. Moreover, some managers claimed that within the cluster there are companies that get more preferences and advantages than others. This is in line with the Olson view, stating that within association there are companies that seek to get a “larger slice of the social pie”, at the expense of the whole group benefits, that ultimately trigger the redistribution mechanism and creates inefficiencies [24]. Although, entrepreneurs are starting to understand that some of the problems they face could be resolved or mitigated via cooperation. The interviews reveal two main reasons why did companies become part of the cluster and why they would agree to collaborate. The first reason refers to the long-term development strategy. Thus, companies expect to obtain competitive advantages that would be impossible to achieve acting individually. They are mainly interested in cooperation focused in areas such as modernizing production process, employee training schemes, research, marketing and participation in trade fairs that will gradually give access and increase awareness on international markets. The second reason is the opportunistic one. The cluster, (since being conferred a juridical entity) started to get assistance and financial support through various international cluster development schemes. Additionally, different training for managers, working visits abroad, participation at international conferences, and other immediate benefits motivate firms to engage in the cluster at least formally.

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Further Discussion and Recommendations

The examined cluster proved a weak level of co-operation and networking among companies. Even though enterprises are closely located to each other, the study revealed scarce forms of collaboration between them. Following the typology on the state of cluster development proposed by Enright [14], this cluster could be classified as a latent one. Despite the dense geographical concentration of firms, they do not succeed too much in developing productive networks. Many scholars suggested that geographical proximity is a necessary condition for cluster development, as it increases the chances of establishing cooperation between members and facilitates interactive learning. However, this dimension is mostly imperative for the initial stage of cluster development, while when it

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comes to engage in more mature forms of cooperation the common location is no longer sufficient [9,22]. When referring to the analysed cluster, it appears that geographical proximity was not sufficient to develop collaborative networks. In fact, due to spatial proximity, some firms managed to engage in joint activities, as the common use of equipment, co-investment in fixed assets or joint production under big orders. Nevertheless, most of the firms proved to be atomistic in their behaviour, therefore ignoring the opportunity to engage in long-term collaboration. Also, this points out other forms of proximities are missing or being underdeveloped, that determine the low willingness to engage in collaboration. Thereby, the weak relational capital within the examined apparel cluster could be explained by the following. (i) The underdeveloped social capital dimension within the society as a whole. As the networks between firms are generally grounded in relations between persons, thus, the scarce relations among actors at the micro-level comes firstly from the distrust and competition between people [25]. Most companies have not yet developed a culture for the association, and even being formally in the cluster do not identify themselves as a part of it that leads to low social proximity. Additionally, as several firms within the cluster operate since the Soviet Union, this has left a deep imprint on their way of doing business. Thus, the restricted, heavily regulated relationships between different actors during the centrally planned economy, has further hindered the natural and spontaneous development of partnerships, with repercussions that are still felt nowadays [31]. (ii) The underdeveloped knowledge base and inequalities in absorptive capacities between firms justifies their weak willingness to establish new ties. The absorptive capacities of firms are crucial for creating dynamic capabilities and driving innovation process [4]. Companies that are more similar in their size, number of employees, technological endowment, and market specialization are more eager to engage in horizontal collaboration. As a result, carrying out joint projects allow firms to diminish transaction costs, by accessing complementary resources and generating higher relational rents than other cluster-based firms. The above-mentioned context limits the emergence of cohesion effect that requires stable and dense social structure to occur. Hence, the simple fact that enterprises are located close to each other, does not necessarily mean they are going to collaborate in any concrete sense or that this is the main source of regional dynamism. Many firms frequently manifest a lack of loyalty and reticence to long-term engagement. From the transaction cost perspective, firms’ behaviour reproduces mostly the peculiarities of the pure-agglomeration type of cluster as described by Iammarino and McCann [20]. It is difficult to change the way firms behave and treat each other, and the relational capital cannot be rapidly achieved, requiring a proper institutional and inter-organizational environment [12]. However, it is important to underline, that with the formalization of the cluster (attribution of a legal entity) the cluster starts to get a more

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explicit and identifiable image. It changes the way firms perceive collaboration, understanding that it could bring long-term benefits. The physical infrastructure of the cluster, its management body and wide range of activities as joint marketing, quality control, training of employees, progressively build the relational capital throughout the cluster. As Porter noted [28], it could take a long time for the full effects of the cluster to be felt. In the case of the Republic of Moldova’s apparel cluster, the formalization of the cluster has served as the first stage to make up for the lack of social capital and to start building the cognitive, organizational and social proximity to foster cross-firms’ relationships. Belonging to the same juridical entity of cluster leads companies to share common values and vision [15]. The cluster body that coordinates activities, organizes meetings, applies for development projects makes firms feel they belong to the cluster, creates synergies that were absent before. Furthermore, as firms interact in the same organizational environment, they tend to become more similar in their structure, behaviour, and strategic vision, that consequently facilitates the better coordination of their activities. However, many steps are still to be undertaken to drive the development of the cluster. Based on Enright cluster model [14] it can be inferred that knowing the stage of the cluster development is imperative for articulating cluster-oriented policies. For instance, the stage of a working cluster requires policies for enhancing further penetration into the export market, whereas a latent cluster needs support in developing inter-firms’ relations for ensuring the smooth flow of knowledge, ideas, and resources. Our research has identified that the investigated apparel cluster lacks the main aspects of relational capital in terms of trust, networks, and synergies. However, we conclude the trust could be restored and networks created via deliberate steps of efficient policy intervention. In this regard, the following recommendations are proposed: – improving the legal environment and the framework conditions that nowadays undermine the business collaboration, in particular referring to issues of property rights, protection of investments, and corruption incidence. Moreover, here should be mentioned the elimination of legislative bottlenecks that hinder the common research activities between firms and universities and restrictions on providing allocation of public resources for R&I funds to the business sector [10]; – the public intervention has an important role in supporting organizational innovation. In this regard, government should design and implement “sustainability initiatives” aiming to support clusters development. This could be driven through the funding schemes for cluster development targeting investment in knowledge and expertise of the firms’ managers. Furthermore, it should be stimulated the collaboration of managers with other actors for the cross-fertilization of knowledge necessary to generate radical innovations [18].

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Conclusion

Republic of Moldova quite recently has integrated the concept of clusters in its industrial policy, thus aiming to support the activity of small and medium enterprises and enhance their competitiveness. While the benefits of clusters are well known from the experience of other countries, our research has found several issues undermining the spread of these benefits in the case of the Republic of Moldova. We aimed to analyse the degree of firms’ engagement in competitive collaboration networks. Based on the case study of the apparel cluster, we have found the cluster is in the latent stage of its development, without a wellestablished level of interaction among cluster members. Our research has also focused on revealing the context-specific factors that influence the patterns of collaboration, particularly identifying the lack of social capital as the most significant barrier in this regard. Despite the relatively dense agglomeration of firms in the region, just a few of them have managed to engage in either horizontal or vertical collaboration. It was reported a low degree of trust and under-developed culture of collaboration, that in turn represents a missed opportunity in grasping the advantages of co-location. This is in line to the Boschma’s [7] findings underlying that physical proximity could generate cohesion effects within the cluster, but it is also the relational proximity that influences the degree of engaging in collaboration. Because interaction per se is a socially embedded process, it should not be isolated from the institutional and cultural context. Additionally, the reminiscences of the planned economy during the former soviet period have also left an imprint on today’s entrepreneurial behaviour, which is prone to an individualistic approach of conducting business. Our interviews confirmed that Moldovan firms keep at a distance one another, fearing their ideas, capitals or clients may be taken over by competitors. Overall, the collaboration within clusters is affected by the general atmosphere of mistrust also due to ineffective judiciary systems, low protection of property rights, and corruption incidence. Well-designed policies are necessary to change the current attitudes and perceptions that hinder collaboration within clusters. Such policies have to cover both general regulations on improving the macro-institutional environment and also be specifically targeted, initiating actions to encourage more systematic inter-firm collaboration and higher involvement of educational/research institutions in this process.

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Appendix

Table 1. The codebook (fragment) of the thematic analysis Organizing themes

Basic themes

Description

Examples

Inter-firms relations

Code 1.1 Legal framework

The weakness of the national legal framework, expressed in low protection of property rights, burden of government regulation, inefficient justice and poor investment protection, makes firms reticent to collaboration.

“Bureaucracy and difficult access to funding make our firms’ innovation capacities to lag behind countries with competing apparel industries”. “There are too many control bodies that only have the objective to amend the entrepreneurs but not to help them. They are more concerned to gather money for the state budget than to help entrepreneurs”.

Code 1.2 Perceptions

The perception toward collaboration splits actors in two categories, those who agree that it could help to achieve common goals and increase competitive advantages and other who are more skeptical.

“Limited production capacities do not allow us to take over major and long-term contracts. While taking a small order we cannot ensure sustainability. Thus, having a partner, we could engage in major orders that is much more profitable for us”. “The cluster is involved in different projects, receiving financial grants from external partners. However, not all companies get equal access to these benefits, some are more favored then others. This always will happen, so collaboration will not help everyone”.

Code 1.3 Barriers

The identified barriers toward cooperation in cluster refer to mentality of acting alone, being afraid of competition and of that their ideas will be stolen.

“Moldovans’ mentality differs from that of Europeans when referring to cooperation in clusters. Moldovan entrepreneurs are more individualistic, not many will agree to cooperate, people are afraid to risk”. “It’s risky to engage in collaboration with other firms, because we are competitors, our ideas or clients could be stolen”.

Code 1.4 Motivation

Entrepreneurs start to acknowledge that some of the problems they face can be solved through cooperation with other businesses and organizations or even with clusters from abroad.

“When our customers for whom we operate in “Lohn” now, will decide to leave Moldova for a cheaper labor force, for example, in Africa - will we be ready to quickly develop our own collections and successfully sell them? I think this requires a long-term preparation phase that needs joint efforts”.

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References 1. Adam, F., Ronˇcevi´c, B.: Social capital: recent debates and research trends. Soc. Sci. Inf. 42(2), 155–183 (2003) 2. Benea-Popu¸soi, E.: The transcendence of the human capital towards spirituality. In: International Scientific Conference “Classical and Innovative Approaches in Contemporary Economic Thought”, 2nd edn. pp. 105–112. ASEM, Chi¸sin˘ au (2016). http://irek.ase.md/xmlui/handle/123456789/294 3. Bettiol, M., Chiarvesio, M., et al.: Local or global? Does internationalization drive innovation in clusters? Eur. Plan. Stud. 27(10), 1995–2014 (2019) 4. Bittencourt, B.A., Galuk, M.B., et al.: Cluster innovation capability: a systematic review. Int. J. Innov.: IJI J. 7(1), 26–44 (2019) 5. Bjerke, L., Johansson, S., et al.: Innovation and firm collaboration: an exploration of survey data. Technical report, Centre for Excellence of Science and Innovation Studies Electronic Working Paper Series (2014) 6. Boix-Domenech, R., Galletto, V., et al.: Place-based innovation in industrial districts: the long-term evolution of the IMID effect in Spain (1991–2014). Eur. Plan. Stud. 27(10), 1940–1958 (2019) 7. Boschma, R.: Proximity and innovation: a critical assessment. Reg. Stud. 39(1), 61–74 (2005) 8. Capone, F., Lazzeretti, L.: The different roles of proximity in multiple informal network relationships: evidence from the cluster of high technology applied to cultural goods in Tuscany. Ind. Innov. 25(9), 897–917 (2018) 9. Crescenzi, R., Rodr´ıguez-Pose, A.: An ‘integrated’ framework for the comparative analysis of the territorial innovation dynamics of developed and emerging countries. J. Econ. Surv. 26(3), 517–533 (2012) 10. Crescenzi, R., Gagliardi, L., et al.: The bright side of social capital: how ‘Bridging’ makes Italian provinces more innovative. In: Geography, Institutions and Regional Economic Performance, pp. 143–164. Springer (2013) 11. Dadashian, F., Shakibfar, S., et al.: Strategic alliance for core competencies improvement in textile industries. Int. J. Manag. Sci. Eng. Manag. 2(2), 98–107 (2007) 12. Day, M., Fawcett, S.E., et al.: Trust and relational embeddedness: exploring a paradox of trust pattern development in key supplier relationships. Ind. Mark. Manag. 42(2), 152–165 (2013) ´ Enterprise clusters in developing countries: mecha13. Dijk, M.P.V., Sverrisson, A.: nisms of transition and stagnation. Entrep. Reg. Dev. 15(3), 183–206 (2003) 14. Enright, M.J.: The globalization of competition and the localization of competitive advantage: policies towards regional clustering. In: The Globalization of Multinational Enterprise Activity and Economic Development, pp. 303–331. Springer (2000) 15. Feldman, M.S.: Organizational routines as a source of continuous change. Organ. Sci. 11(6), 611–629 (2000) 16. Fujii, L.A.: Interviewing in social science research: a relational approach. Routledge Series on Interpretive Methods (2017) 17. Fukuyama, F.: Social capital, civil society and development. Third World Q. 22(1), 7–20 (2001) 18. Grashof, N., Hesse, K., et al.: Radical or not? The role of clusters in the emergence of radical innovations. Eur. Plan. Stud. 27(10), 1904–1923 (2019)

754

E. Benea-Popu¸soi and E. Rusu

19. Hervas-Oliver, J.L., Sempere-Ripoll, F., et al.: Agglomerations and firm performance: who benefits and how much? Reg. Stud. 52(3), 338–349 (2018) 20. Iammarino, S., McCann, P.: The structure and evolution of industrial clusters: transactions, technology and knowledge spillovers. Res. Policy 35(7), 1018–1036 (2006) 21. Lazzeretti, L., Capone, F., et al.: Rethinking clusters towards a new research agenda for cluster research. Eur. Plann. Stud. 27(10), 1879–1903 (2019) 22. Lis, A.M.: The significance of proximityin cluster initiatives. Compet. Rev.: Int. Bus. J. 29 (2019) 23. Marshall, A.: Principles of Economics. Cengage Learning (1920) 24. Olson, M.: The Rise and Decline of Nations: Economic Growth, Stagflation, and Social Rigidities. Yale University Press (1982) 25. Ooms, W., Werker, C., et al.: Personal and social proximity empowering collaborations: the glue of knowledge networks. Ind. Innov. 25(9), 833–840 (2018) 26. Platform ECC (2019). https://www.clustercollaboration.eu/cluster-organisations/ sorintex 27. Porter, M.E.: On Competition. Harvard Business Press (1998) 28. Porter, M.E.: Location, competition, and economic development: local clusters in a global economy. Econ. Dev. Q. 14(1), 15–34 (2000) 29. Sabatini, F.: The empirics of social capital and economic development: a critical perspective. In: Social Capital, Lifelong Learning and the Management of Place, pp. 92–110. Routledge (2007) 30. Schwab, K.: The Global Competitiveness Report 2017–2018. World Economic Forum (2017) 31. Teller, R., Validova, A.F.: Innovation management in the light of universityindustry collaboration in post-socialist countries. Procedia Econ. Finance 24, 691– 700 (2015)

Effect Mechanism of New Varieties and Technologies on Greening Development of Tartary Buckwheat Industry Jingwei Huang1,2 , Peng Wang2 , Liang Zou1,2 , Yan Wan1,3 , and Gang Zhao1,3(B) 1

Key Laboratory of Coarse Cereal Processing, Ministry of Agriculture and Rural Affairs, Chengdu, China 2 College of Medicine, Chengdu University, Chengdu 610000, People’s Republic of China 3 College of Pharmacy and Biological Engineering, Chengdu University, No. 2025, Chengluo Avenue, Chengdu 610106, People’s Republic of China [email protected]

Abstract. With reference to the project on tartary buckwheat by the Sichuan research team conducted in the previous decade and targets of modern green industry development, this article focuses on the mechanism of new varieties and technologies in the greening development of the tartary buckwheat industry. Based on the market changes and requirements of green industry development, our team proposed new requirements for the innovation chain of the tartary buckwheat industry. Further, we summarize five major problems in this industry, provide the corresponding solutions, and develop a technology innovation chain based on new varieties and technologies. We propose a core mechanism for the tartary buckwheat industry with new varieties and technologies by promoting the “technical innovation” and “industrial innovation” chains. Using mutual enhancement between “technical innovation chain” and “industrial innovation chain” can help to improve the “industrial value chain”, and thereby finally accomplish the industrial transformation and sustainable development. Keywords: New variety · Technological innovation buckwheat · Green industry · Dual innovation

1

· Tartary

Introduction

Tartary buckwheat is known as the “King of Grains” and primarily planted in remote mountains area in China. In recent years, the nutritional and medicinal value of tartary buckwheat has been widely recognized, and it has gradually become a new functional food. However, the cultivation technology for tartary buckwheat is still relatively extensive; the level of development and utilization is lagging, and quality control systems are sub-par. These factors severely restrict c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 755–762, 2021. https://doi.org/10.1007/978-3-030-49889-4_58

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the vigorous and rapid development of the tartary buckwheat industry. Therefore, what are the new market demands of supply in the modern green industry of tartary buckwheat? How should new varieties and technologies promote the development of the tartary buckwheat green industry? This article is based on a project conducted by a research team of the China agriculture research system and cereal processing ministry of agriculture and rural affairs in the previous decade. According to the requirements of the development of the modern green industry, this research studied the mechanism for the development of the tartary buckwheat green industry by combining new varieties and technologies. The current agriculture in China has been characterized by high-quality development, and the tartary buckwheat industry has gradually entered a stage of rapid development. However, it has encountered a bottleneck. As the data shown in the Fig. 1, the Food and Agriculture Organization of the United Nations (FAO) reported that the five primary producers of buckwheat in 2016 were Russia (683 thousand tons), China (623 thousand tons), Kazakhstan (255 thousand tons), Ukraine (145 thousand tons) and France (142 thousand tons). In 2018, the buckwheat planting area in China was 620,000 hectares, with an output of 850,000 tons. The tartary buckwheat planting area was approximately 543,000 hectares, with an output of nearly 490,000 tons. The total processing capacity of the producing company was approximately 600,000 tons, with an output value of nearly 6 billion CNY. Among the three primary producers of buckwheat, Russia and Ukraine have negative average annual agricultural labor productivity, and the agricultural labor productivity in China has numerous advantages. China is the only country in the world that grows tartary buckwheat on a large scale; however, the average yield is only 1200–1500 kg/hm2 , whereas the yield of the high-producing country worldwide is 2200 kg/hm2 [1]. The main factors for limiting the development of the tartary buckwheat industry is the low agricultural production levels in the majority of the tartary buckwheat, and the severe lack of the new varieties and technologies. 1.2% 1.4% 3.6% 3.9% 6.4%

1.2% 5.0%

31.0%

6.6% 11.6% 28.2%

Russia China Kazakhstan Ukraine France Poland the United States Japan Republic of Belarus Republic of Lithuania other countries

Fig. 1. The primary producers of buckwheat in 2016

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The fundamental approach to overcome this problem must include improvement of the structural reform of supply in agriculture, focus on enhancing quality and efficiency instead of increasing the planting area, and transform from quantitative growth to high-quality production. In underdeveloped states, tartary buckwheat is the primary crop for local residents. In mid-developed economies, tartary buckwheat is gradually receiving attention from the public. However, the high price of the tartary buckwheat lead to a small market size. In recent years, market demands for high-end buckwheat products have significantly increased. The current per capita annual consumption of buckwheat in worldwide and in China is 0.29 and 0.4 kg, thereby indicates the excellent market potential of tartary buckwheat [8].

2

Background: Features of Tartary Buckwheat Industry

Tartary buckwheat can be grown in barren soil and conducive to preventing soil erosion, therefore planting tartary buckwheat promotes environmental protection [5]. Local governments have taken advantage of the excellent ecological environment and promoted a recognized public branda lLiangshan Tartary Buckwheat-as a representative in the region, which has positively contributed to poverty alleviation [2]. High-quality ecological environment is the premise of tartary buckwheat green planting. Based on the physiological characteristics of tartary buckwheat, the tartary buckwheat production can easily meet green and organic standards and have a relatively low cost. Tartary buckwheat is rich in various active substances, such as amino acids, resistant starch and polyphenol flavone, which can improve the diet structure and conform to consumer demands for green products [4,9]. The management standards and the green production technology standard for the taratary buckwheat industry showed be formulated and refined. The lack of new high-quality professional farmers is a prevalent problem in the tartary buckwheat industry of China. The research team explored the cultivation model of “experts + enterprises + new management entities + farmers” in the major tartary buckwheat producing counties. They established tartary buckwheat demonstration bases as advanced representatives of science and technology combination in Yanyuan and Beichuan counties of Sichuan province. Real practice shows that the new type of tartary buckwheat business support based on technology could integrate scientific and technological features into production practice and promote the use of the scientific research achievements in the countryside. The development of science and technology industry chain ultimately promote the development of the modern green industry of tartary buckwheat. The tartary buckwheat industry chain with large enterprises as the core mainly consists of two parts: the sales chain focus on the social services enterprises and the agro-processing chain focus on the deep processing enterprise. Numerous leading companies have promoted the industrialization of tartary buckwheat based on the green industrial chain. Sichuan Huantai Industrial Corporation Limited works closely with scientific research teams to develop a

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complete buckwheat industry chain for the “selection of food ingredients, biological cultivation, purification, deep processing, and sales.”

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Results

There are five major concerns under the new demands of the modern tartary buckwheat green industry: (1) lack of specialized varieties; (2) low and uneven quality of large-scale production of seedlings; (3) lack of green standardized production technology; (4) less application of mechanized production; and (5) lack of intensive processing technology, as well as high-quality and diversified development. Moreover, we must restructure the technological innovation chain to produce more mid-to-high-end products of tartary buckwheat, and improve the technological innovation chain and core competitiveness of the modern green industry of tartary buckwheat. To reconstruct the green industry technology innovation chain for tartary buckwheat by using essential new technologies, we must focus on the following five aspects: The research team has successfully developed 13 new varieties of tartary buckwheat, including the first easy shelling variety-miqiao 1 and a high-yield and highflavone variety-Xiqiao 4. The average output of these varieties reached that of the high-producing countries worldwide and has effectively overcome the lack of high-quality special varieties in industrial development [3]. The research team helped the households providing training on high-yield cultivation techniques for tartary buckwheat and constructed a promotion method combining high-yield fields, high-yield creation model households, and high-yield creation demonstration films to ensure a large-scale balanced increase in the output. The output of high-yield tartary buckwheat increased by more than 18%, and the cumulative promotion area was 900,0000 ha, thereby increasing the output of tartary buckwheat to 270,000 tons, with an added output value of 1.1 billion CNY. Planting industry is the front industry of tartary buckwheat industry chain, the development of the tartary buckwheat production industry could effectively promotes the sustainable and healthy development of the green tartary buckwheat industry. The research team proposed to increase space and time efficiency through cultivation technologies that integrate sowing time and density, improve fertilizer efficiency by using balanced fertilization technology [7], decrease the lodging rate and increase the seed setting rate of tartary buckwheat through trace element supplement technology [6], and improve the emergence rate by using endophyte polysaccharide induction technology [10]. The research team innovatively integrated various cultivation techniques to enhance the yield and quality of tartary buckwheat. The research team cooperate with several companies to establish an original tartary buckwheat breeding base as “two nurseries a year.” At the same time, through research-Centerprise cooperation, organic bases in various regions, including Meigu and Puge, were developed with more than 898 acres of organic bases, forming an integration model of company + base + farmer, which enabled a good cycle of production and sales. The establishment of a fine-grained organic production base is crucial in maintaining the supply and quality of raw materials and in increasing the added value of raw materials for tartary buckwheat.

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The harvest of tartary buckwheat is still lack of mechanized production mode. The research team successfully designed and developed a small tartary buckwheat planter and a buckwheat multifunctional seeding and fertilizing machine suitable for hilly and mountainous region. This machine has a compact structure, with convenient disassembly and handling, and it can be powered using a micro-tiller. We can use machinery for tartary buckwheat harvest in hilly areas, which can significantly improve production efficiency and save production costs. The research team cooperated with numerous enterprises and realized the market transformation of the obtained results for the deep processing of tartary buckwheat. We integrated processing technologies, including biological enzymolysis and polysaccharide induction, to effectively increase the content of functional components, such as flavonoids, combined with biological germination technology and other methods to create tartary buckwheat tea products (e.g., tartary buckwheat germ tea and ultra-micro tea), thereby effectively promoting the development of the tartary buckwheat tea processing industry. The team used various methods, such as modern biological fermentation technology and ultrasonic-assisted extraction technology, to overcome the problem that loss of active ingredients in tartary buckwheat distilled wine and developed five types of tartary buckwheat wines, such as tartary buckwheat bud health wine and high-flavonoid tartary buckwheat products. We used various technologies, such as ultra-fine crushing technology and compounding technology, to successfully develop tartary buckwheat cakes, such as tartary buckwheat shaqima and tartary buckwheat crisp [10]. The marketization of refined and deep-processed products has been widely promoted. In the past 10 years, the cumulative output value has increased by 3.1 billion CNY, providing more than 1,800 jobs and training more than 600 technical personnel in the industry. This project has produced significant economic and social benefits.

4

Discussion

In this section, we discuss the interaction of technological innovation and industrial innovation for the industry of tartary buckwheat from the following four aspects: interaction mechanism, research team, operation system and the development of value chain. Based on the research in the previous decade, we summarize that the core mechanism for the development of the modern green industry of tartary buckwheat is the development and utilization of the new varieties and technologies. In accordance with the new market changes and industry requirements, the team reconstructed the technology innovation chain of the modern green tartary buckwheat industry. Base on the technology innovation chain and the industrial innovation chain, the “circulated effect chain” and promoted the sustainable development of the modern green industry for tartary buckwheat are successfully developed and realized.

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From the perspective of technical system engineering, although any new variety and technology have a certain impact to push technical innovation in theory, the development of technology innovation chain can really promote the development of industry. High-level industrial innovation chains inevitably require highlevel technological innovation chains. The effective interaction between technological and industrial innovation chains is crucial for promoting industrial transformation and upgradation. The tartary buckwheat technology innovation chain is the base of the development of the industrial innovation chain, and the industrial innovation chain is the conversion of the technology innovation chain. The development of an innovation chain and the technical incubation of the two chains in a cyclical and spiral manner is an interactive process. This incubation is a leap from technological innovation to industrial innovation and is the basis for improving the overall innovation efficiency. The construction of the tartary buckwheat technology innovation chain is the basic support for the “three-chain linkage transformation and upgradation” mechanism. The tartary buckwheat technology innovation chain restricts the energy level and potential of the industrial innovation chain, whereas the industrial innovation chain determines the value and benefit of other one. Therefore, we must systematically analyze the key technologies of the modern green industry of tartary buckwheat to understand the primary needs of industrial development. We promote the relevant research and development technology innovation chain system that supports the tartary buckwheat green industry innovation chain. We take the key technology as the breakthrough point, reconstructre technology research and development system with breakthrough innovation. In accordance with the “three-chain linkage” and based on market demands, we develop the tartary buckwheat technology innovation chain and the industrial innovation chain, in order to enhance the overall value and market competitiveness of the industry technology value chain. Extending the tartary buckwheat industry innovation chain is a decisive stage for realizing the value added by the tartary buckwheat technology innovation chain. The implementation effect at this stage determines the prevalence of the competition. The modern green industry of tartary buckwheat involves the construction and innovation of multiple industrial chains, and the development goals of each chain must be established in accordance to local conditions. In the process of constructing the industrial innovation chain, we must understand the limitations and the main contradictions that restrict the development of the industrial chain. We should overcome the technical bottleneck as the key link, and extend the modern green industry innovation chain of tartary buckwheat. The key to ensure the market competitiveness of the tartary buckwheat industry innovation chain is the increasing share of its leading innovative mid-to-high-end consumer products. The value-added effectiveness of the interaction between scientific and technological innovation and industrial innovation must be analyzed, and the interaction how to enhance the technology value chain. Can the tartary buckwheat technology value chain be modified and upgraded to a new industrial level? Can a new round of “three-chain linkage” be started? “Developing a tech-

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nological innovation chain-extending the industrial innovation chain-increasing the value chain of science and technology” is mechanism of the “three-chain linkage” transformation and upgrading. The mechanism is one of important rule that concluded from the transformation between the scientific and technological achievements of the development and practice of the tartary buckwheat industry. The mechanism is an important way to deepen supply-side reform in agricultural and the concrete manifestation of an innovation-driven strategy in promoting the development of the modern green industry of tartary buckwheat. The principle of “three chain linkage” reveals the inherent importance of new varieties and technologies in promoting the development of the modern green industry of tartary buckwheat. The strategy has universal applicability in the development of modern high-tech industries and is conducive to the rapid improvement in the core capabilities of enterprises, complementary sharing of production, teaching, and research resources, creation of synergistic innovation effects of industrial clusters, reduction of the risk and cost of enterprise innovation, increase in market response speed and in development opportunities, and promotion of industrial development in new directions. Acknowledgements. The work was supported by the China Agriculture Research System (CARS-08-02A), Potato Staple Food Strategy Research Center of Key Research Base of Humanities and Social Sciences of Sichuan Provincial Department of Education (MLS1804), and National Key Research and Development Program of China (2019YFD100130, 2019YFD1001303).

References 1. Fan, Y., Ding, M., et al.: Overview of buckwheat germplasm resources. J. Plant Genet. Resour. 20, 813–828 (2019). (in Chinese) 2. Li, H., Yu, S.: The ractice and thinking of the development of tartary buckwheat industry in Liangshan, Sichuan. China Agric. Inf. 12, 60–62 (2014). (in Chinese) 3. Song, C., Ma, C., Xiang, D.: Variations in accumulation of lignin and cellulose and metabolic changes in seed hull provide insight into dehulling characteristic of tartary buckwheat seeds. Int. J. Mol. Sci. 20(3), 524 (2019) 4. Wang, J., Xiao, J., et al.: Analysis of tartary buckwheat (fagopyrum tataricum) seed proteome using offline two-dimensional liquid chromatography and tandem mass spectrometry. J. Food Biochem. 43(7), e12863 (2019) 5. Wu, Q., Zhao, G., et al.: Characterization of the transcriptional profiles in common buckwheat (fagopyrum esculentum) under PEG-mediated drought stress. Electron. J. Biotechnol. 39, 42–51 (2019) 6. Xiang, D., Song, Y., et al.: Relationship between stem characteristics and lodging resistance of tartary buckwheat (fagopyrum tataricum). Plant Prod. Sci. 22(2), 202–210 (2019) 7. Xiang, D.B., Zhao, G., et al.: Effect of planting density on lodging-related morphology, lodging rate, and yield of tartary buckwheat (fagopyrum tataricum). Plant Prod. Sci. 19(4), 479–488 (2016) 8. Xu, X., Zhao, L., et al.: Cereal food intake and changes in Chinese residents. Food Nutr. China 23, 44–46 (2017). (in Chinese)

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9. Zhang, J., Wang, D., et al.: Lipid-polymer hybrid nanoparticles for oral delivery of tartary buckwheat flavonoids. J. Agric. Food Chem. 66(19), 4923–4932 (2018) 10. Zhao, J., Zou, L., et al.: Effects of polysaccharide elicitors from endophytic bionectria pityrodes fat6 on the growth and flavonoid production in tartary buckwheat sprout cultures. Cereal Res. Commun. 43(4), 661–671 (2015)

The Impact of Video Information and Publisher’s Characteristics in Tik Tok Platform on the Spreading Effect of Poverty Alleviation by E-Commerce Jinjiang Yan, Yunjie Zhang, Lingling Chen(B) , Lu Huang, and Yong Huang Business School of Sichuan University, Chengdu 610065, People’s Republic of China [email protected]

Abstract. With the characteristics of fragmentation, low threshold of creation and large user groups, Tik Tok has attracted more and more enterprises or individuals from poor areas to create videos on it for poverty alleviation. This article studies the main influencing factors of short video transmission of agricultural products for e-commerce poverty alleviation on Tik Tok platform and gives some strategies to promote the spread of Tik Tok video. Based on the theories of Internet information dissemination, this paper quantifies the evaluation index of dissemination effect, establishes a model of influencing factors of video distribution from two aspects of video information characteristics and video publisher characteristics, and validates the model by data from Tik Tok, so that we find which factors will affect the dissemination effect and how to influence it. Some suggestions are put forward for improving the spread of short videos about e-commerce poverty alleviation on Tik Tok.

Keywords: E-commerce

1

· Poverty alleviation · Tik Tok

Introduction

According to the statistical monitoring bulletins of the National Bureau of Statistics of 2014, China still has 70.17 million poor people under the current standard. In order to achieve the goal of building a well-off society in an all-round way by 2020, China must solve the problem of poverty alleviation in these poverty areas. At the Central Poverty Alleviation and Development Working Conference held in November 2015, it was particularly emphasized that we must adhere to targeted poverty alleviation and improve the effectiveness of poverty alleviation; we must find the right way and build a good institutional mechanism. In the “Guiding Opinions on Promoting the Rapid Development of Rural Electronic Commerce” issued by the General Office of the State Council in November 2015, it was stated that “rural e-commerce is an important means to transform agricultural c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 763–777, 2021. https://doi.org/10.1007/978-3-030-49889-4_59

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development methods and an important carrier for targeted poverty alleviation. We should rely on mass entrepreneurship and innovation and promote the role of market mechanisms to accelerate the development of rural e-commerce. “Since the National Poverty Alleviation Work Conference in late 2014 merged e-commerce into the national poverty alleviation policy system and work system for the first time, the e-commerce poverty alleviation has continued to spread and develop in poverty-stricken zone across the country. As “Internet +” rises to become a national strategy, “e-commerce” and “precision poverty alleviation” become closer and closer. With the development of network technology and the arrival of the social age, users keen on the content consumption of mobile short videos. Compared with text and long videos, short videos have the advantages of being intuitive, effective, and fragmented. Depending on their “short, flat, fast” characteristics, they are widely used in agricultural product sale that helps poor households selling their products and promotes the performance of poverty alleviation by e-commerce. As an original short video platform, as of June 12, 2018, Tik Toka´ rs daily active users exceeded 150 million and monthly active users exceeded 300 million. At the same time, because Tik Toka´ rs creative threshold is low and the operation is simple, a large number of ordinary people and organizations in poverty-stricken zone settle down, create agricultural video related to poverty alleviation, and attain great achievement. Therefore, it is of great significance to study the influencing factors of Tik Tok short video transmission of poverty alleviation by agricultural e-commerce. This paper mainly studies the influencing factors of video propagation related to e-commerce poverty alleviation and provides targeted strategies for promoting the propagation of videos on Tik Tok. Based on the theory of Internet information dissemination, this paper quantifies the evaluation index of dissemination effect, establishes a model of influencing factors of dissemination from both video information characteristics and video publisher characteristics, and crawl data related to short videos about agricultural products e-commerce poverty alleviation, thereby quantify the propagation evaluation indicators and influencing factor indicators. And in the paper, we use variance analysis and multiple linear regression analysis to determine the factors affecting video propagation, thereby providing effective suggestions for promoting spread of short videos related to e-commerce poverty alleviation. This paper tries to answer three questions as follows: 1. How to quantify the dissemination effect of these videos? 2. What factors will affect the spread of such short videos? 3. How do these factors affect short video propagation? By researching, we find that video about rural emotion is more popular. And the number of Aite, the number of topic challenges and the top setting has a positive impact on the dissemination effect. Simultaneously, the time of releasing short video, the number of fans, video introduction also has impact on the dissemination effect.

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Literature Review

At present, there are few studies on Tik Tok at abroad, and there are few studies on the influencing factors of video propagation on Tik Tok in China. It is concluded that the current domestic research on Tik Tok mainly focuses on the following three aspects: Firstly, the dissemination characteristics and development strategies of Tik Tok are elaborated, and the existing problems and solutions of Tik Tok are pointed out. Secondly, research on the development of Tik Toka´ rs business value, including the role of urban image dissemination, urban tourism, media guidance and government affairs. Thirdly, it briefly analyses the psychology and behavior of Tik Toka´ rs users by using mainly the theory of use and satisfaction, such as Meng Yuanyuan regards the short video platform and users as the research object to analyze the characteristics of the short video platform and the user’s usage habits with the use and satisfaction theory [14]. In the term of the relevant theories of information dissemination, some scholars do some researches. In 1971, H. Lassville (1971) [8], an American scholar, putted forward the traditional 5 W model of information dissemination. And from the perspective of communication, communicators and audiences are closely related and interact, which are two parts of the communication system that are difficult to separate. Therefore, the disseminator and the audience will be the participants of information dissemination, and they should be combined in the analysis [5]. Then Hsin Hsin Chang [3] discover that in the network environment, user behavior and attitude to information have an interactive relationship. After that, basing on the 5 W model of H. Lassville, Luo Hao [12] also propose the basic model of network communication shown in Fig. 1. Now, we will use the model for reference to carry out research. Some scholar also do researches about concepts related to the effect of network information dissemination. Generally, the dissemination effect is hierarchical, after the audience receives the information, there will be cognitive changes at

Fig. 1. Basic model of network communication

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the psychological level firstly, then accumulated to produce emotional responses, finally psychological changes will be translated into action changes [10]. In the network environment, the amount of clicks and forwards of information can directly measure the scope and impact of propagation and the response of audience to dissemination activities mainly includes the degree of attention (access, click, forwarding), the degree of motivation (download, search, comment), the attitude of the audience (praise), etc. [15]. In the term of influencing factors of network information dissemination effect, there are also interactions between communicators/audiences and information, which can be studied by using the two-path model. The model believes that information quality and source credibility have a great impact on user acceptance and dissemination of information [16]. And Hong [7] find that message characteristics affect website credibility and information adoption. Sundar [18] also propose that the credibility of information sources will affect the degree of information acceptance. In the term of information quality, When Rabjohn [17] built the information adoption model, he mentioned that the relevance, timeliness, completeness and accuracy of information will affect the audience’s behavior of information adoption. And basing on the empirical study, Arazy [1] believes that information quality can be judged from the following aspects: accuracy and objectivity, integrity and representativeness. Zhou [23] also finds that information quality can affect customer satisfaction by affecting customer perception. With the help of the heuristic-systematic model (HSM), Li Yonglin [9] think that what really has a significant impact on the communication effect is the content and quality of the video, such as shorter video descriptions, more prominent description words. Through the analysis of the research results, we will choose adequacy, scope, timeliness and usefulness as the dimensions of measuring information quality.

3 3.1

Modeling Data Selection and Acquisition

(1) Video publisher and video screening principle Firstly the area is poor. Judgment of poverty-stricken areas: judging whether it is located in the national poverty-stricken counties according to the specific location of the video; or when the proportion of the poor counties in the city where the publisher is located is more than 90%, the area where the publisher is located is identified as poverty-stricken areas. Secondly publishers use e-commerce to sell local superior resources, such as agricultural products, in the form of opening commodity windows, Taobao stores and so on. Based on the two principles, 10 poverty-stricken areas were randomly selected, and the video publishers related to e-commerce poverty alleviation in these areas were randomly selected. One video publisher was selected from each area, and 10 video publishers were finally obtained. And the selected videos are related to e-commerce poverty alleviation, including rural information, popular science exhibition of agricultural products, rural

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emotional, food, landscape and talent exhibition. According to this screening principle, 354 videos related to e-commerce poverty alleviation were randomly selected as the research objects. (2) Data acquisition In this paper, the Python crawler method is used to automatically capture the relevant information of the research object. Finally, 354 data sets are obtained, including the publisher’s name, the video duration, the number of Aite, the number of video participants, the number of challenges, whether to set the top, the length of the profile, the publication time, the frequency of uploaded works, the number of publishers’ fans, the number of points of praise, the number of comments and the amount of shares. 3.2

Basic Model

According to the relevant theories of information dissemination mentioned in Sect. 2 and the specific situation of the distribution of video related to ecommerce poverty alleviation on Tik Tok, the basic model of influencing factors of video dissemination is constructed, as shown in Fig. 2.

Fig. 2. Model of communication influencing factors

3.3

Selection of Influencing Factor Indicators

(1) Selection of video propagation effect index Propagation effect refers to the scope of dissemination and the intensity of the influence. Functional effect refers to the reaction of the audience on emotional, cognitive and behavioral, including the degree of attracting the attention of the audience, the degree of stimulating the acquisition of the audience, the degree of influencing the attitude of the audience, and the degree of influencing the behavior of the audience [22].

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Wu S and Hofman JM [20] believe that two-step dissemination is the simplest and most effective dissemination path for social networks. It is divided into friend path and retransmission path. During the dissemination process, users, topic content, and relationships between users are three important factors. Hong [6] uses reposting as a evaluation of favorite of information, and uses machine learning technology to predict the possibility of reposting. In this paper, the likes, comment and share of video are taken as the evaluation indicators of video communication effect: likes measures the emotional response of the audience; comment reflects the audience’s access to information, so it is used to measure the extent of stimulating the audience’s access; share is the premise of content dissemination, which is used to measure the potential range of video propagation. (2) Index Selection Based on Video Information Characteristics a. Video content type For short video dissemination, content is one of the most important influencing factors. Generally speaking, the richer the content, the lower the ambiguity of the information, so rich content has a positive impact on the efficiency of information propagation [4] Based on the research on the short video content of “agriculture, rural areas and farmers”, Zhang Cao [21] divides the contents of short video of “agriculture, countryside and farmers” into four categories: rural audiences, agricultural products and rural delicacies, rural emotions and agricultural technology knowledge. Zhang Cao’s research provides a reference for the content classification of the short videos of e-commerce poverty alleviation in this paper. Based on the actual investigation, the author classifies the short videos related to e-commerce poverty alleviation into five categories: rural audiences, rural emotions, popular science exhibition of agricultural products, food courses and other categories. b. Video presentation characteristics Video presentation characteristics refer to the characteristics of video presentation. In this paper, the length of video, the number of Aite, the number of video topic challenges, whether to set the top or not, and the length of the introduction are used as indicators to measure the characteristics of video presentation. c. Characteristics of video publishing time Tang Jia [19] thinks that the release time may have an impact on the dissemination effect and proves that the different release time will have an impact on the forward of official blog of tourism institutions by empirical research. Therefore, the characteristics of video publishing time are considered as a factor affecting the effect of short video propagation. d. Brief introduction of emotion Berger and Jonah [2] have studied the dissemination of network content and find that the more emotional network content, the easier it is to be forwarded and disseminated by the audience. The emotional analysis in this paper is an analysis of text-video profiles.

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This paper uses ROST CONTENT MINING, a tool developed by the virtual team of Wuhan University, to conduct emotional analysis of video profiles [13]. (3) Index selection based on video publisher characteristics Liu Jiqun [11] finds that the user’s personal characteristics such as gender, age, education level, geographical location, number of fans, and behavioral characteristics such as interaction rate, content publishing frequency will have a certain impact on the dissemination of social network information. In this paper, the number of publishers’ fans and the frequency of video upload are taken as the measurement indicators of the characteristics of video publishers. Among them, the frequency of uploaded works = the time of the latest video upload − the time of the first work upload)/the total number of works. Therefore, this section establishes and quantifies the influencing factors evaluation index and influencing factors index. Detailed data are shown in Table 1. Table 1. Indicators of influencing factors of video transmission for poverty alleviation in E-commerce First level index

Second level indexes

Information characteristics

Content type

Third level indexes

Remarks Rural information, rural emotions, popular science exhibition of agricultural products, food courses, and other five categories

Video duration, number of Aite, number of video challenge topics, top setting, length of profile

The number of Aite, the number of video challenge topics, the length of the introduction and the length of the video are continuous variables, and whether the top is a binary variable or not

Is it released for holidays?

Dichotomous variable

Presentation characteristics Release time characteristics

Video Publisher Characteristics

Brief introduction of emotion

It is a numerical value with positive and negative values, in which positive and negative emotional tendencies are distinguished, and the numerical value represents emotional intensity, which is a continuous variable

Number of fans, frequency of uploading works

As a continuous variable

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Data Analysis Data Preprocessing

Firstly we perform normality test, and find that the results do not conform to normal distribution, so the dependent variables are logarized to make it conform to normal distribution without changing the nature and correlation of the data. Then we perform multiple collinearity test by Durbin-Watson test. The D.W statistics of LN point preference, LN comment and LN share are 1.724, 1.675 and 1.733 respectively, which shows that there is no collinearity in the model. 4.2

Correlation Analysis

In this paper, Spearman correlation coefficient is used to analyze the correlation degree between each independent variable and LN point approval, LN comment and LN share. In terms of video information characteristics, there is no significant relationship between information adequacy and dissemination effect; Information scope and information usefulness have significant influence on dissemination effect; while the significant relationship between information time and three dependent variables is not the same, there is high correlation with LN point approval and LN comment, and low correlation with LN share. In terms of the characteristics of video publishers, the correlation coefficient between video upload frequency and dependent variables is low. The number of publishers’ fans has a high correlation with LN point approval and LN comment but has no significant correlation with LN share. 4.3

Multivariate Linear Regression Analysis

In this paper, the dependent variables are continuous variables, the independent variables are binary variables, continuous variables and multi-classified variables, and the multi-classified variables are treated as dumb variables, which can be used for multiple linear regression analysis. The dependent variables are likes, comment and share. (1) Conclusions When LN Point Plus is Dependent Variable Firstly, we perform multivariate linear regression analysis with LN Point Plus as dependent variable. In the summary of multivariate linear regression model with point preference as dependent variable, the adjusted R-square is 0.462, the sig value corresponding to F-value is 0.000, and the regression model is significant. Table 2 is the coefficient table of regression model. In terms of the adequacy of information, the length of the video and the length of the introduction have no significant effect on the point preference of the video. In terms of the scope of information, the number of Aite, the number of topic challenges, and the top setting all have significant positive effects on the amount of likes, while the type of video has significant effects on the amount of likes. In terms of the timeliness of information, the publication of

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holiday has a positive impact on the point approval. In terms of the usefulness of information, introducing emotions has a significant positive impact on likes, thus video introductions of positive emotions are more likely to be praised by audiences than video introductions of negative emotions, and the stronger the positive emotions of video introductions, the more points praised. The two indicators of video publisher’s characteristics have different effects on point acceptance. Among them, the number of publishers’ fans has a positive impact on the likes, while the frequency of video upload has no significant impact on the likes. Table 2. Multivariate linear regression analysis with LN point plus as dependent variable Model

Standardization coefficient Beta Sig.

(Constant)

0

Number of @

0.229

0

Number of topic challenges

0.335

0

Number of publishers’ fans

0.16

0.002

Emotional tendency of brief introduction −0.223

0

Introduction length

−0.062

0.178

Frequency of uploading works

−0.11

0.145

Topped

0.136

0.001

Released on holidays

0.159

0

Video duration

−0.323

0.089

N1 - agriculture products

−0.125

0.014

N2 - rural emotions

0.183

0

N3 - delicious food

−0.122

0.066

N4 - others

−0.28

0

(2) Conclusions When LN Commentary is Dependent Variable In the multivariate linear regression model with comment as dependent variable, the adjusted R-square is 0.491, and the sig value corresponding to F-value is 0.000. The regression model is significant. In terms of the adequacy of information, the video length and the introduction length have no significant impact on the video comments. In terms of the scope of information, the number of Aite, the number of topic challenges, and the top setting all have significant positive effects on the comment volume; Video types have significant effects on the comment volume. In terms of timeliness of information, publishing on holidays has a positive impact on the number of comments. In terms of the usefulness of information, video emotion has a significant negative impact on the amount of comments. The two indicators of video publisher’s characteristics have different effects on the comment volume. Among them, the number of publishers’ fans has a

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positive impact on the comment volume, while the frequency of video upload has no significant impact on the comment volume (Table 3). Table 3. Multivariate linear regression analysis with LN comments as dependent variables Model

Standardization coefficient Beta Sig.

(Constant)

0

Number of @

0.14

0.001

Number of topic challenges

0.184

0

Number of publishers’ fans

0.304

0

Emotional tendency of brief introduction 0.158

0

Introduction length

−0.093

0.069

Frequency of uploading works

−0.082

0.094

Topped

0.205

0

Rleased on holidays

0.147

0

Video duration

−0.27

0.078

N1 - agriculture products

−0.218

0

N2 - rural emotions

0.262

0

N3 - delicious food

−0.125

0.068

N4 - others

−0.308

0

(3) Multivariate linear regression analysis with LN sharing as dependent variable In the multivariate linear regression model with share as dependent variable, the adjusted R-square is 0.398, and the sig value corresponding to F-value is 0.000, which indicates that the regression model is significant. The specific regression model coefficients are shown in Table 4. In terms of the adequacy of information, the length of video and the length of introduction have no significant impact on the video sharing. In terms of the scope of information, the number of Aite, the number of topic challenges and the top setting all has significant positive effects on the amount of sharing; video types have significant effects on the amount of sharing. In terms of the timeliness of information, there is no significant difference in the amount of video sharing during the holidays. In terms of the usefulness of information, video emotion has a significant positive impact on the amount of sharing. The two indicators of video publisher characteristics have no significant impact on the amount of sharing. 4.4

Variance Analysis

The content types of independent variables are multi-classified variables. In the previous section, dummy variables have been transformed into dummy variables

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Table 4. Multivariate linear regression analysis with LN sharing as dependent variable

Model

Standardization coefficient Beta Sig.

(Constant)

0

Number of @

0.262

Number of topic challenges

0.275

0

Number of publishers’ fans

−0.021

0.71

Emotional tendency of brief introduction 0.243

0

0

Introduction length

−0.12

0.219

Frequency of uploading works

0.179

0.354

Topped

0.155

0

Released on holidays

−0.038

0

Video duration

−0.134

0.368

N1 - agriculture products

−0.147

0.063

N2 - rural emotions

−0.233

0.008

N3 - delicious food

0.197

0.006

N4 - others

−0.178

0

and multivariate linear regression has been made. In order to compare the differences of dependent variables under different content classifications, variance analysis has been used separately. With LN likes as dependent variable and content type as independent variable, it was found that for different content videos, the number of likes of rural emotional video is the highest, followed by food and rural audiences, followed by agricultural products display, and other categories of video is the lowest. When the dependent variable is LN comments, rural emotional videos are most likely to attract audiences’ comments. Food and rural audiences are closely behind. Agricultural products videos have fewer comments. But other categories video is the least likely to attract users to comment. When the dependent variable is LN sharing, rural emotional video still has the best dissemination effect and the highest sharing amount; while there is no significant difference among the three types of video: food, rural news and agricultural products display; the other types of video share the lowest amount. From this, we can know that different video content will make significant differences in video likes, comment and share.

5 5.1

Conclusion Conclusion Analysis

(1) Influences of information characteristics on propagation effect As far as information adequacy is concerned, video length and introduction

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length have no significant influence on the propagation effect of short video (likes, comment and share). On the one hand, because the Tik Tok platform has a rigid restriction on the length of short video and the length of introduction, there is no big difference in the length of video and the length of introduction; On the other hand, the short video mainly attracts users by content, while the length of video and the length of introduction are external forms, so the length of video and the length of introduction will not have a significant impact on the short propagation. In terms of information scope, the number of Aite, the number of topic challenges, and the top setting have a positive impact on the propagation effect. Among them, the number of Aite and the number of topic challenges can increase the chances of promoting the home page on the video and increase the exposure; while setting the top of the video on the personal page makes it easier to attract users’ attention and generate further propagation behavior. Video type is one of the important factors for video propagation. Emotional video is better in rural areas, followed by food and rural news, agricultural products and other types of video. The reason is that rural emotional videos are easy to arouse the emotional resonance of the audiences. Rural audiences and gourmet videos are interesting and practical; while agricultural products display videos are only simple and rough displays of agricultural products, which is not lively and interesting enough to promote the dissemination of audiences. In terms of information timeliness, the publication of short videos during holidays has a significant positive impact on the amount of likes and comments, but not on the amount of sharing. This is because audiences will praise or comment on a video when they express their support for it, but they will not necessarily share it. Only when the audiences’ emotions about the video are strong, will it be carried out. In terms of information usefulness, the emotions of video profiles have a positive impact on point approval and sharing, but a negative impact on comment. This is because positive videos and video profiles are easy to be pushed by the home page of the platform and exposed more; Moreover, they are more likely to be loved by the audience, who are also willing to share positive emotional profiles. The video profile of negative emotions is more infectious, and it is easy to stimulate the audience to encourage or tuck through comments. (2) The impact of video publisher’s characteristics on propagation effect Publisher upload frequency has no significant impact on the video propagation effect. The upload frequency is high, but the propagation effect is not necessarily good. The reason is that audience pay more attention to the content of video, not upload frequency, on the contrary, “screen brushing” may also cause audiences’ negative psychology. The number of publishers’ fans has a positive impact on the likes and comment of the video, but has no significant impact on the share. The reason is that it needs more accumulation of the audience’s cognitive and emotional so that transform into sharing behavior further.

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Suggestions on Promoting Short Video and Video Progagation for Poverty Alleviation in E-Commerce

(1) Make full use of Aite and Challenge Topics, Top-setting Function In the creation of video related to e-commerce poverty alleviation, we should pay attention to: Make full use of Aite and Challenge Topic function, improve interaction with other video publishers, especially the influential video publishers. For example, For example, the video related to e-commerce poverty alleviation can cooperate with local official accounts and leverage the popularity of official accounts to increase video exposure. At the same time, when choosing the topic of video creation, we should find out the most concerned topic of the audience with the help of the analysis of Tik Tok hot topic, and rub off the traffic of hot topic, and improve the video exposure rate. And we should choose the appropriate video to set the top. For e-commerce poverty alleviation videos, the following two types of videos can be selected: videos containing information about agricultural products or videos with good propagation effect. Setting the top of the video containing information about agricultural products can quickly promote the audience understanding the relevant information of agricultural products and promote consumption; while setting the top of the video with good propagation effect, which can leave a good impression on the audience through high-quality video, thereby stimulating the audience to watch other videos of the publisher. (2) Reasonable choice of video content Video content is one of the important factors affecting the effect of short video dissemination. Referring to the results of this study, some rural emotional videos can be released in an appropriate amount to arouse the emotional resonance of the audience, thereby promoting forwarding. Food videos and rural display videos are interesting and practical, and also a good choice for video creation. It should be noted that the display of agricultural products and other resources is indispensable in the short video of e-commerce poverty alleviation. The display of agricultural products can help audiences intuitively understanding the resources of agricultural products sold and stimulate the purchasing desire of audiences. However, simple and crude display of resources should be avoided, and a certain plot design or other shooting techniques should be supplemented to make the video more ornamental and avoided. Video is boring and homogeneous. In addition, when creating short video, we should pay attention to the needs of the audience, cater to the audience’s preferences, and make corresponding changes to the video content according to the popular topic trend of the Tik Tok at that time. (3) Reasonable choice of video publishing time point This study shows that releasing videos on holidays will bring better propagation effect. This is because that in holiday, audiences have more time to watch short videos. Therefore, videos can be released on holidays. (4) Brief introduction to emotional style Brief introduction of emotional style has a significant impact on propagation

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effect. Positive emotions can promote the praise and sharing of videos, while negative emotions can promote the comments of videos. Video publishers should reasonably measure their expectations of likes, sharing and comment, and pay attention to the grasp of emotions. Of course, while meeting their expectations, they should also avoid excessive negative emotions. They can use emotional introduction to inspire effectively the audience, and bring positive, happy and pleasant emotions to the audience. Acknowledgements. This research is funded by China National Social Science Fund Project (16BGL011).

References 1. Arazy, O., Nov, O., et al.: Information quality in Wikipedia: the effects of group composition and task conflict. J. Manag. Inf. Syst. 27(4), 71–98 (2011) 2. Berger, J., Milkman, K.L.: What makes online content viral? J. Mark. Res. 49(2), 192–205 (2012) 3. Chang, H.H., Wang, I.C.: An investigation of user communication behavior in computer mediated environments. Comput. Hum. Behav. 24(5), 2336–2356 (2008) 4. Chang, Y.S., Yang, C.: Why do we blog? From the perspectives of technology acceptance and media choice factors. Behav. Inf. Technol. 32(4), 371–386 (2013) 5. Guo, H.: A study of “mimetic environment” in the perspective of communication. Ph.D. thesis, Sichuan University, Chengdu (2006). (in Chinese) 6. Hong, L., Dan, O., Davison, B.D.: Predicting popular messages in Twitter. In: Proceedings of the 20th International Conference Companion on World Wide Web, pp. 57–58 (2011) 7. Hong, T.: The influence of structural and message features on web site credibility. J. Am. Soc. Inf. Sci. Technol. 57(1), 114–127 (2006) 8. Lasswell, H.D.: The structure and function of communication in society. Commun. Ideas 37(1), 136–139 (1948) 9. Li, Y., Wu, Y., et al.: Content is king: research on knowledge dissemination mechanism of social short video platform. Journal. Writ. 06, 23–32 (2019). (in Chinese) 10. Lin, Z., Guo, Q.: On the hierarchy of communication effect. J. Chengdu Univ. (Soc. Sci. Ed.) 4, 46–48 (2004). (in Chinese) 11. Liu, J.: Overseas social media impact research review - progress and enlightenment. Mod. Intell. 36(03):158–166+177 (2016). (in Chinese) 12. Luo, H.: Research on influencing factors of bullet screen video transmission on video website. Ph.D. thesis, Harbin University of Technology, Harbin (2017) 13. Ma, Z.: Video emotion recognition based on multi-feature fusion. Ph.D. thesis, Ludong University, Yantai (2018) 14. Meng, Y.: Usage and satisfaction of mobile short video platform usersa la la case study of quick hands app. China Ethnic Expo 01, 236–237 (2019). (in Chinese) 15. Peng, L.: Introduction to Internet Communication. Renmin University Press (2002). (in Chinese) 16. Petty, R.E., Cacioppo, J.T.: Communication and Persuasion: Central and Peripheral Routes to Attitude Change. Springer, Heidelberg (2012) 17. Rabjohn, N., Cheung, C.M., Lee, M.K.: Examining the perceived credibility of online opinions: information adoption in the online environment. In: Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008), p. 286. IEEE (2008)

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18. Sundar, S.S., Knobloch-Westerwick, S., Hastall, M.R.: News cues: information scent and cognitive heuristics. J. Am. Soc. Inf. Sci. Technol. 58(3), 366–378 (2007) 19. Tang, J., Li, J.: Study on influencing factors of official blog forwarding of tourism bureau based on multiple logistic regression. J. Tour. 30(01) (2015) 20. Wu, S., Hofman, J.M., et al.: Who says what to whom on Twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 705–714 (2011) 21. Zhang, C.: Can the traditional TV media from UGC to OGC grasp the “agriculture, countryside and farmers” type of short video outlet? News Commun. 13, 39–42 (2018). (in Chinese) 22. Zhong, Y.: Analysis of content factors affecting the international communication of Chinese in the social network environment. Ph.D. thesis, Jinan University, Jinan (2013) 23. Zhou, T.: Examining the critical success factors of mobile website adoption. Online Inf. Rev. 35, 636–652 (2011)

Perspectives on the Future of Higher Education Grigore Belostecinic1(B) , Igor Serotila2 , and Maria Duca3 1

The Academy of Economic Studies of Moldova, Chi¸sin˘ au, Republic of Moldova [email protected] 2 Moldova Young Researchers Academy, Chi¸sin˘ au, Republic of Moldova 3 State University “D.Cantemir” of Moldova, Chi¸sin˘ au, Moldova Abstract. Globalization and technological progress have transformed the world in all areas of human activity, including education. Although, it is certain that higher education will change in the near future, there is no clear or unanimously accepted vision. The article provides analysis and perspectives on the historical evolution and features of universities, best practices in tackling challenges related to globalization and technological progress. Moreover, it offers an insight into the arguments that fundament the need to rethink the way we perceive higher education, its mission and goals, as well as draft strategies aimed at ensuring the capacities of universities to be competitive in the ever-changing educational environment. Keywords: Globalization · Higher education · University Competitiveness · Socio-economic development

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Introduction

Globalization and technological progress have profoundly transformed economies and radically redistributed opportunities to participate and thrive. As a result, there is a need for new deliberate action across stakeholders-business, government and workers-to create greater shared prosperity. Economic inequality and social polarization are growing in many countries. All of this has come on top of the effects of globalization, which left many low-skilled workers in a precarious position by the time the Fourth Industrial Revolution began to unfold. Globalization and technological change affecting labor markets and skills demands is not a new phenomenon. However, the speed of the current transformation requires timely, responsive and bold policy to ensure that the benefits are widely distributed [23]. Whether large or small, strong or weak, all countries face similar odds when it comes to challenges of globalization. While examining these odds we take into account the legislative frameworks, administrative procedures, as well as tax, monetary, financial, commercial, environmental, judicial and even educational systems c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 778–790, 2021. https://doi.org/10.1007/978-3-030-49889-4_60

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of a state. According to Stryazhev, the differences between the developed and developing states depend on their economy in only one third, and the other two thirds relate to the discrepancies existing in the level and quality of education [21]. As Muravska and Berlin underline, in the last decade, there has been a major eastward shift in global economic power of unprecedented nature. The exact composition of the newly emerging global economic powers is not yet clear, but it is now fully acknowledged that the political and economic relevance of the West is being rescaled and even downscaled. The European Union (EU), as a trading bloc, since its inception in 1952, has expanded regularly both in scope and membership. Less than 20 years earlier, the EU was primarily seen as a regional integrational entity among a relatively small number of participating countries tearing down the wall that separated them and prevented their economic and political integration, the EU’s external policy being essentially a sub-product of this internal consolidation. With globalization, this internal integrating approach to the Single Market was losing its relevance and consequently the EU’s external policy acquired a new importance and dimensions, which needs to be taken into account in consolidating the fragmented character of the governance of the EU’s external policy, including its economic aspects. In the 21st century, societies with different and complex cultural identities and beliefs are forced to closely interact. In the EU Member States just as in any ENP country, discussion is taking place on what will be the political as well as methodological response to the challenges in the EU external relations and changing EU Neighbourhood Policy [12]. Globalization comprises several challenges, such as backwardness of economic growth of a number of countries, prevention of environmental pollution, ensuring an ecological balance, energy supply and raw materials etc. Moreover, the phenomenon has allowed the increase of the international financial organizations role and the emergence of various regional economic and political aggregates that have brought about the fear of the rise of supranational structures, losing elements of national sovereignty, as well as culture and national identity loss. It has already been estimated that nation states are becoming economically, socially and politically less relevant, as compared to corporate states and other virtual communities. For example, Microsoft could become more powerful than the US, and sports might be more influential than parliamentary elections in the near future [8]. Scientific knowledge transformed into new technological developments becomes a catalyst for economic growth at both microeconomic and macroeconomic levels. This statement is validated through the multifunctional role that classical science has in accomplishing its three main functions – socio-cultural (science as part of culture and society), educational (impact on the level of education) and the function of influencing the economy (economic growth and sustainability) [7]. Moreover, qualitative indicators of a nations development could comprise the expenses for science and education related to GDP, the number of registered

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patents and inventions, the number of scientific personnel, the production and marketing of high-tech competitive products, etc. In the economically developed states, the investments in knowledge, measured by the expenditures for R&D, higher education, and information technologies, are growing at a higher rate than the investments in the economy in general. It should be noted that globalization has had a significant transformative impact on national higher education systems, moreover, some researchers argue that globalization is actually one of the fundamental challenges that higher education has faced throughout its history [19]. A globalized society generates a global education. Thus, one can find terms and expressions in specialized scientific works related to this topic, concepts such as global market for educational services, global universities, transnational education, etc.

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Literature Review

While considering the future of higher education certain scholars refer to universities as ruins [15], or that in 30 years the great university campuses shall become relics, vestiges [6]. Although, it is certain that universities will change in the near future, there is no clear or unanimously accepted forecast. It is likely that the very idea of a university will be rethought and reconsidered. Robertson identifies the future of education as open, risky and uncertain. When education futures are claimed by economic actors seeking to expand capitalist markets, there are competing projects around whose future this is [18]. Rieckmann establishes that universities play an important role in shaping the future of the world society in terms of sustainable development by generating new knowledge as well as contributing to the development of appropriate competencies and raising sustainability awareness [17]. M´ arquez-Ramos and Mourelle argue that a quantum approach to time and change (QATC) helps to set out the future scenario where the current educational model will be called into question; it is also a key tool for studying the relationship between higher education and society. One of the advantages of the QATC for studying the future of higher education institutions is that it does not start with the assumption that organizational processes are predictable or consistent. By taking a QATC perspective, we see that there are always multiple paths to the future, and some are associated with pasts that did not occur but may characterize future situations better than the actual past. In this context, it not occurred in the 1980s that the future generations of students were born with continuous access to digital information. Thus, in the 80s and 90s, parents tended to worry about face-to-face dangers to their children, present mainly during the school day and with a small audience (for example, bullying). For children born in the 2000s, cyberbullying coexists with traditional bullying; children face an anonymous enemy and can be bullied not only at school, but also at home, all day and with a wider audience. This example illustrates how the environment of future generations of students has changed in relation to the previous ones [11]. In his research on the processes of internationalization of higher education in Uzbekistan, Uralov underlines that globalization and internationalization have

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entered history as critical influential processes of the century. Internationalization is changing the world of higher education, and globalization is changing the world of internationalization. Uralov establishes that for Uzbekistan internationalization has become the main strategy and dominant trend in the development of higher education, it is an important component for the development of the national economy as well as a mechanism for promoting cultural diversity and national identity [22]. In order to become and remain part of the world’s academic elite, institutions have to come up with a well thought out model, and count on visionary management and dedicated staff for flawless execution. In this respect, Noukakis, Ricci and Detterli establish that the academic world is more than ever a global war for talent, international mobility of students and faculty, diversification of funding, are a few of the main features of this changing environment faced by universities. International rankings are blooming and contribute - despite their obvious limitations - to globalization as well as competition. The aforementioned authors argue that innovation is a key driver for the economy and society, and universities play a crucial role at the very origin of the economic and industrial pipeline. Many institutions have therefore developed specific initiatives to support knowledge and technology transfer projects in their very early stages. Interdisciplinarity is a buzzword in all institutional visions and strategies, for beyond cutting-edge research within scientific domains, more and more discoveries occur at the interface between disciplines. Many institutions, including Imperial College, Yale University, KTH Stockholm, Duke University and MIT promote such interdisciplinarity beyond structural organizations, through dedicated centres and programmes [14]. Craciun underlines that higher education has always been international in scope. Nevertheless, against the backdrop of globalization and neoliberalism, nation-states’ and, by extension, universities’ have faced pressure to internationalize their practices at an increasing pace. As such, higher education internationalization is talked about as a strategic priority for governments and is considered to be at the forefront of policy agendas around the world. Since the beginning, the main goals of the Bologna Process - specifically the harmonization and mobility aspects - have underscored an interest in internationalizing national higher education systems in Europe. Despite this, there is little large-scale comparative research on the actual policies deployed by nation-states to internationalize their higher education systems. With some notable exceptions, country level studies on internationalization policy typically focus on in-depth case studies or small-n comparative research. Nevertheless, internationalization does not occur in a vacuum. It only occurs at the intersection of cooperation and competition between nation-states, institutions, and individuals. The author also highlights that large-scale comparative research of national higher education internationalization strategies can bring to light new aspects of the process that would otherwise be obscured in small-n in-depth case studies [4].

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De Wit and others sustain that the global higher education landscape and its international dimensions are constantly changing. The global competition for talent, the emergence of international branch campuses, growing complexity in cross-border activity and questions raised in the United States on the payment of agents to recruit students are just some of the issues that until recently were not at the forefront of higher education debates. However, these are now high priorities, not only for international educators, but also for university presidents, associations of universities, politicians and other key higher education players around the world. The emergence of a global higher education space has implications for our way of looking at internationalization. As the international dimensions of higher education have developed their own momentum and become a global topic of interest, the growing globalization of internationalization requires a more nuanced approach to its interpretation and delivery than has hitherto been the case. Western countries have tended to dominate research and discussions on internationalization, and the flow of students has been largely in their direction. However, as more countries attract inbound students and open up to internationalization, their experiences offer new perspectives and issues for consideration [5].

3

Analysis

The first European university was established in the 11th century. As a whole, medieval universities initially encompassed theology, medicine and law faculties and later added the arts. Their graduates represented scholars with a specific vision on their society and culture, rather than professionals. The idea of a classical university came into fruition in the 19th –20th centuries, in the form of several higher learning schools. These schools are known today as part of the liberal model of education (the British model or the Oxbridge model), based on close communication between students and teachers. Later, they were called the Chicago model, having as a core general knowledge university courses with a strong humanitarian content. Similar to the British model, the French model of grande ´ecoles represented caste universities with a special atmosphere focused on training the cultural and intellectual elite. The mission of the aforementioned models aimed, first and foremost, at the acquisition of cultural values, intellectual and spiritual development. The neoclassical or reformatory university model is linked to the Humboldt name. The later founded the Berlin University in 1810 (hence called Humboldtian Universities). The Humboldtian model of higher education contributed to the advancement of German science in the beginning of the 19th century, to the extent that research and study activities constituted inseparable components of university life and students had to get their scientific research skills through active involvement in the search for knowledge. The Humboldtian research-based university model spread throughout Europe, gaining significant popularity over the conservative French grand ´ecoles. Countries used this model in order to develop their own higher education systems. The neoclassical and classical university models imply the detachment

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from utilitarianism, based on the concept of institutionalization of research and separation from church, state and other interests [24]. The neoclassical university is the current most widespread model in the world, where science is the core content of the university, the main source of reputation and well-being, followed by teaching, learning, and education. Furthermore, the model of pragmatic, corporate, innovative, religious, and even political universities can be considered among the new emerging university models [3,20]. As the end of the 19th century saw the rise of the neoclassical university, the beginning of the 21st century is marked by the apparition of modern universities as complex institutions of higher education, which strive to become educational ecosystems. The universities of today are much more complex in construction, being also ubiquitous in the online environment. Basic human resources are supplemented with highly qualified specialists from various fields, who develop technological, linguistic, project writing skills as well as offer career counseling. Academic activity (teaching) is no longer the central objective, but one of the multiple objectives of the university. Many universities of this type are the equivalent of small or medium-sized cities, each with its own services, housing programs, food and health system, transport infrastructure and entertainment providers. Most own research institutes, technological incubators and related services. It is worthwhile to mention that the modern university inherited characteristic features pertaining to different models, each of them providing certain competences to the institution: The Humboldtian model - scientific research skills, the Oxbridge model - communication skills, as well as a new broad spectrum of socio-economic skills, etc.

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Discussion

Taking into account the considerable increase of the amount of information, methods of obtaining, storing and transmission of data, change in the way of socializing, as well as the increasing role of the social networks, modern universities have found themselves unsynchronized with current cultural realities. Information with an applicative added value is more demanded and appreciated. Although, states continue to govern the development and functioning of universities, the industry and business, through its support and linkage, including the financial one, is conditioning and shaping the activity of universities. While the paradigm of universities shifts as resources, including those obtained from non-public sources start to flow in, the need to rethink and resize the ideological foundations of the modern higher education begins to ascend. In order to synchronize, universities are increasingly shifting to a postmodernist organizational-structural and functional form. Globalization represents a determining factor in the decline of the traditional research-based university model, in which the university was perceived as a protector of national culture and claimed to create the values necessary for social integration of a

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nation as a state. For this very reason, education is perceived as a well-structured system, and those responsible for education hold well-defined positions as well as the right to decide what and how to learn. Given the role of globalization, the value of the nation-state is considerably reduced, and the university ceases to be means of national-cultural identification. The university can no longer be perceived solely from a utilitarian perspective, as a place where students acquire a profession under the guidance of teachers. The strictly professional training is devoid of perspective, considering the speed that the world changes, when the forecast of the labor market is obscured, at least within a generation. If universities want to be actively involved in the process of modernizing the society, as well as be an essential and successful component in this process, then they must exceed the role of educational services providers. They must evolve from a place of communication and learning, of transmission of traditions and knowledge and become a platform for new knowledge, which ultimately forms the chain of innovative processes. Universities must become the place where new social practices are formed and disseminated, such as the production of new philosophies, creation of new political and economic discourses to persuade the diverse social spectrum, conception of new directions of human action, which, aligned with the effort of graduates are transformed into new activities (market, financial, political, etc.). The university is increasingly seen as a social institution, which by launching new generations into the global and multicultural world creates and shapes this world. Thereto, while touching upon the social role of the university it is indispensable to prepare students that are citizens of an increasingly pluralistic and diverse world, where uncertainty and ambiguity dominate, where everybody is capable of making mistakes or worthy of the absolute trust of authorities. Universities as modern society knowledge centres must anchor their activity on fundamental and inalienable ideas and values, such as: freedom, honesty, truth, tolerance, cultural diversity, loyalty, democratic norms, etc. The direction towards postmodernism reinforces the importance of interpretative strategies, challenging modern university with special tasks, such as: training individuals capable of constantly interpreting changing realities, as well as acting accordingly and adjusting their own interpretations to the interpretations of those around. Furthermore, universities must contribute to the expansion of social horizons as well as changing practices, while creating the opportunity to connect their local, national interests to global issues. The idea of education needs an update. It is necessary to go beyond the limits of education as means of disseminating research results and interpretations. Moreover, it is necessary to develop new methods and models of teachinglearning, which will encourage students to formulate problems, face and argue situations, hold debates and deal with controversies. Thus, education has to cause fermentation in the students’ minds [10]. Such an education process requires constant communication with students, encouraging and strengthening self-confidence, analyzing and raising awareness of their own achievements

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and successes. It is constructive to mention that in such circumstances, teaching activity could become overly laborious and some scholars would prefer to focus on research activities. Internationalization of universities arises in response to globalization. Under the later, internationalization takes on new shapes which open many promising opportunities for higher education institutions and systems. At the same time, the real risks and challenges are inherent in such a complex environment, so that aspects of competitiveness and relevance regarding the international dimension require new actions and types of strategic thinking for all forms of higher education. Guri-Rosenblit argues that internationalization of higher education requires a significant shift in the operation of higher education systems, as well as of individual higher education institutions. Operating in a most complex world, policy makers at the national level of higher education, as well as leaders of universities and other higher education institutions have to handle concurrently contrasting trends, and define their missions and operational strategies accordingly. The increased focus on international collaborative ventures, the growing link between internationalization, research and employability require the rethinking of the roles and responsibilities of higher education institutions within national borders and beyond [9]. Another important source of transformation in higher education systems is the development of technology. On one hand, the digital revolution has fundamentally changed and is still changing every aspect of human activity, such as economy, innovation, education, health, etc. While forecasted to end Moore’s law by 2025, the pace of this digital revolution is constantly increasing. Digital technologies such as the internet, mobile phones as well as any other tools that collect, store and distribute information are spreading rapidly throughout the world, both in economically developed and developing countries. Furthermore, the online environment has become a key platform for new resources. On the other hand, books, articles and other types of knowledge products are published and spread at a much greater speed than our ability to understand and assimilate them. With the increasing access to information, the academic society is deprived of its previously held right to have exclusive control and access over sources of knowledge. These are the very reasons behind the fact that technology transforms the nature of university activities: creation, maintenance, integration and knowledge transfer. From a historic perspective, university education was focused on the teaching process (i.e. the transfer of knowledge) and not that of learning. Hence, the task of the modern university lies in teaching its students how to operate with new information flows, not trying to replace them in the spirit of the previous models. In this regard, the need for new teacher qualities arises. The modern university teacher should be a designer of the teaching process and its environment. On the backdrop of lucrativeness discussions, the omnipresent task to amass resources for activities is also shaping the future of higher education. Thus, the entrepreneurial university is shifting from traditional objectives of education,

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research and service to society to the focus on what is economically profitable (i.e. short-term professional training, which does not necessarily have to take place on university premises). Meanwhile, the increasing number of clients and beneficiaries of the provided services, as well as its expanding offer, could lead to the circumstances where professional training of students becomes economically less attractive for some universities. An outcome of this experience would materialize in a university with no students. Reddy argues that with the emergence of new science-based technologies such as electronics, bio-, and nanotechnologies, university research has come to play a greater role in industrial innovation. Added to it, the perceived notion of knowledge economy made the policymakers to think that university research and innovation are indispensable for industrialization and economic development. Consequently, governments have started fine-tuning their policies to promote university-industry interaction. Stemming from the industrialized world, particularly Europe, this idea is fast spreading to developing countries. Universities, today, are not only collaborating with the industry through technology transfer, but are also undertaking entrepreneurial activities themselves. This has generated a heated debate on the pros and cons of university’s direct participation in industrial innovation and its potential impact on knowledge generation and welfare. Some critics suggest that financial rewards that accrue from research results may bias and distort the judgments and actions of academicians with respect to problem choice and research direction and in the long run may draw scientists away from basic research [16]. It is important to underline that universities should obtain a broader autonomy, as well as independence from social and political actors, in order to become platforms for new forms of views. However, in light of the aforementioned, higher education autonomy must be put in accord with institutional mechanisms of university accountability to society. In conditions of globalization, an important tool for sustainable development and competitiveness of countries as well as for the development of a knowledgebased economy is the efficient integration of science, education and business. This integration can be achieved by creating associations with representatives of professional and business environments. Research geared towards solving specific challenges faced by the real sector of an economy and involvement of business in the research process will inevitably lead to the strengthening of the knowledge triangle - education, research, innovation, represented by universities, research institutes and companies, and, it will boost economic growth. In this regard, research results have to also be analyzed in terms of their impact on society. Business opts to be actively involved in adjusting the fields of study, give recommendations regarding students’ knowledge and skills necessary to increase the chances of further employment, design teaching materials, adjust university curricula, assign university professors to activities and offer internships for students. The partnership and cooperation among universities and businesses should be used to assess the level of acquired knowledge, skills and capabilities

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that are sufficient to allow graduates to be hired or to set up their own businesses, thus facilitating the process of correlating the educational offer with the labor market requirements. While the university variety is high, we can identify certain basic characteristics that position them as a core element in a society geared towards lifelong learning: the transition from teacher-oriented to student-oriented educational institutions; accessibility for all, regardless of financial resources; tendency towards lifelong learning; lack of space and time restrictions in the learning process; interactive learning; democratization of higher education; accessibility, including disadvantaged/vulnerable people; transition from knowledge teachinglearning to training students’ ability to independently perceive new knowledge and to successfully adapt to the new demands of society; transition from formal education (a certain period/number of years) to the idea of lifelong learning, etc. Universities need to be aware that the 21st century student is different from previous generations. The student requires partnerships with teachers, interactive training methods and online student-teacher communication systems. They must train the ability to understand and accept cultural differences, think critically, tackle problems from a global perspective, work in cooperation, be able to change their lifestyle and consumption habits so as to ensure the protection of the environment, etc. Universities must also be aware of the fact that education has lost the limitation of borders. This has enabled a very competitive environment. In Europe, it is referred to as the European Higher Education Area, with a considerable increase in academic mobility and greater opportunities for those young people who opt for a European university. The aforementioned challenges require radical changes and refinements in higher education systems, as well as economic systems. The drafting of the strategies geared towards training abilities and capacities of being competitive under new requirements of the educational environment is required. In line with these strategy, each university must aim to achieve performance in accordance with its goals and strategic priorities. Considering the plenitude of challenges that higher education is facing it is intricate to estimate whether universities will become mainstream or will dwindle and focus on the intellectual elite. It is very likely that there will be both elite and mass universities, where select applicants or everyone will be entitled to get a degree. At the same time, their differentiation becomes more evident. Since education is essential, universities will have to maintain a duality of providing access to all those who have the necessary knowledge and desire to learn and put in effort to discover young talents across all social backgrounds. The world we live in has become extremely complicated and complex, furthermore, the terms that best characterize it are: uncertainty, instability, unpredictability, hesitation, fragility, and insecurity [1]. This is a state of the modern world, where life training is part of the challenges which university has to face, thus, education has to be geared towards training students a comfortable life under these circumstances.

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Furthermore, as a result of globalization, one of the key challenges of higher education has been defined as brain drain. The emigration of highly trained or qualified people from East to West has had an overwhelming impact on higher education. This is particularly valid for Moldova. In the last 10 years the number of students has decreased by approx. 50%. If in 2008 in higher education institutions there were 115 000 young people, in 2018 this number has diminished to 60 000 [13].

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Conclusions

Globalization, alongside many other challenges have a significant transformative impact on higher education, requiring a greater role and implication of universities within society. Universities are called to radical internal changes and refinements, including drafting of strategies oriented towards ensuring the necessary capacities to be competitive under new circumstances and conditions of the educational environment. With certainty we can state that there are no universal recipes to boost competitiveness of universities. Each university must work at achieving performance in accordance with its mission and strategic priorities. While the political and economic centrality of universities has increased dramatically and has fostered more autonomy for universities in stark contrast with a tradition of often coercive state steering, it has also created overly optimistic expectations on the university system, and a search for quick fixes in the form of a simplified emulation of a US-styled governance model. This does not necessarily fit very well with existing institutional structures or with the socioeconomic conditions surrounding universities; it might instead create islands of excellence with global connections but limited interaction with broader social and economic interests [2]. Furthermore, it is natural that, only in the case of a true university autonomy, supplemented by sufficient funding, an increase of reciprocal responsibility of both universities and public authorities, complemented by a more active involvement of scholars in the research process, international staff and researcher mobility, along with the internationalization of higher education institutions will contribute to the increase in the capacity to train highly qualified and competitive labor market personnel, as well as to develop knowledge-based economies, where the collaborations among universities, research institutions and business will make headway and provide added value. Higher education is crucial in development, stimulation and maintenance of economic growth in the ever-changing landscape of the world.

References 1. Barnett, R.: Realizing the University. McGraw-Hill Education, New York (1999) 2. Benner, M.: In search of excellence? An international perspective on governance of university research. In: Universities in Transition, pp. 11–24. Springer (2011)

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3. Carrie, G.: Cultural models of universities. Alma Mater 3, 14–30 (1996). (in Moldova) 4. Cr˘ aciun, D.: National policies for higher education internationalization: a global comparative perspective. In: European Higher Education Area: The Impact of Past and Future Policies, pp. 95–106. Springer (2018) 5. De Wit, H., Deca, L., Hunter, F.: Internationalization of higher education—what can research add to the policy debate? (overview paper). In: The European Higher Education Area, pp. 3–12. Springer, Cham (2015) 6. Drucker, P.F.: The age of social transformation. Atlantic Monthly 274, 53–80 (1995) 7. Duca, G., Hajiyev, A., Serotila, I.: Evolving science management paradigm for the benefit of socio-economic development. In: International Conference on Management Science and Engineering Management, pp. 453–463. Springer (2018) 8. Fisk, P.: Marketing Genius. Wiley, Hoboken (2009) 9. Guri-Rosenblit, S.: Internationalization of higher education: navigating between contrasting trends. In: The European Higher Education Area, pp. 13–26. Springer, Cham (2015) 10. Jarvis, P.: Paradoxes of Learning: On Becoming an Individual in Society, vol. 80. Routledge, Abingdon (2011) 11. M´ arquez-Ramos, L., Mourelle, E.: Selecting a suitable approach to analyze the future of higher education. Procedia-Soc. Behav. Sci. 228, 86–91 (2016) 12. Muravska, T., Berlin, A.: Towards a new European neighbourhood policy (ENP): what benefits of the deep and comprehensive free trade agreements (DCFTAS) for shared prosperity and security? In: Political and Legal Perspectives of the EU Eastern Partnership Policy, pp. 23–37. Springer (2016) 13. National Bureau of Statistics of the Republic of Moldova: The youth in the Republic of Moldova in 2018 (1988). https://statistica.gov.md/newsview.php?l=en& idc=168&id=6431. Accessed 10 Jan 2020 14. Noukakis, D., Ricci, J.F., Detterli, M.: Riding the globalization wave: EPFL’s strategy and achievements. In: Paths to a World-Class University, Brill Sense, pp. 177–193 (2011) 15. Readings, B.: The University in Ruins. Harvard University Press (1996) 16. Reddy, P.: The evolving role of universities in economic development: the case of university–industry linkages. In: Universities in Transition, pp. 25–49. Springer (2011) 17. Rieckmann, M.: Future-oriented higher education: which key competencies should be fostered through university teaching and learning? Futures 44(2), 127–135 (2012) 18. Robertson, S.L.: Colonising the future: mega-trade deals, education services and global higher education markets. Futures 94, 24–33 (2017) 19. Scott, P.: Society for Research into Higher Education: The Globalization of Higher Education. Society for Research into Higher Education & Open University Press (1998) 20. Strogetskay, E.: In search of a model of a modern university. High. Educ. Today (3), 15–17 (2009). (in Moldova) 21. Stryazhev, V.: Education in the 21st century - forecasts and prospects. Sociology 1, 54 (2000). (in Moldova) 22. Uralov, O.S.: Internationalization of higher education in Uzbekistan. Soc. Sci. Hum. Open 2(1), 100015 (2020)

790

G. Belostecinic et al.

23. World Economic Forum: Policy pathways for the new economy. Shaping economic policy in the fourth industrial revolution, vol. 15. Platform for Shaping the Future of the New Economy and Society (2019) 24. Zakharov, I., Lyakhovich, E.: The mission of universities in European culture. New Millennium (1994). (in Moldova)

New Approaches on Maintenance Management for Wind Turbines Based on Acoustic Inspection Pedro José Bernalte Sánchez(B) and Fausto Pedro Garcia Marquez Ingenium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, Spain [email protected] Abstract. Nowadays, maintenance management is changing due to the new technologies in inspection and monitorization systems to reduce the production costs for the companies and risks for the operator. Maintenance management is a key factor in some industries as renewable energy, due to the high-cost consequences of a wrong failure detection in a wind turbine. Therefore, advances in condition monitoring systems are required for an early failure diagnosis. This paper contributes to the actual wind turbines diagnosis methods with a novel non-destructive inspection system based on acoustic analysis of the wind turbine condition. The paper presents a condition monitoring system based on an acoustic sensor embedded in an unmanned aerial vehicle to collect acoustic signals emitted by the wind turbine. The signals are sent to a ground remote-control centre, and then they are analysed. This data acquisition system needs of a qualitative and quantitative analysis to classify and identify the condition of the wind turbine. Wavelet transforms are employed for filtering the signals and pattern recognition. Several scenarios are considered and analysed considering the main mechanical parts and components of a wind turbine. Keywords: Fault detection and diagnosis · Non-destructive test · Wind turbines maintenance · Condition monitoring system · Acoustic inspection · Wavelet transforms

1

Introduction

In recent years, there is an important evolution in designs, materials, mechanical electronic, electrical, and control of wind turbines (WTs) [33]. The objective is to support the of energy production capacity and to improve the competitiveness of this industry [30,52]. Other key factor for the evolution of an industry is the cost reduction and the system efficiency by new strategies based on advance analytics [22,40], for example, the optimization of maintenance resources or the correct use of them [41,49]. Maintenance management is considered as transcendental to improve the benefit margin [50]. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 791–800, 2021. https://doi.org/10.1007/978-3-030-49889-4_61

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The wind farm maintenance management is complex due to the machine locations and meteorological conditions [55]. These preventive and corrective works are done over the time [20,38], but they are expensive and generate risk for the operators, working in high altitude, see Fig. 1. The generation of false alarm or deceptive signals of the monitorization system is a fundamental issue in the management [21,27,35]. The main interest in maintenance management is to employ a condition monitoring system (CMS) capable to predict failures [24]. A WT is composed of static parts, e.g. tower or support, blades and nacelle, and rotative or mechanical components, e.g. hubs, gearbox or generator [37]. Those components are exposed to physical efforts as stress or compression, and chemical or environmental conditions as erosion or surface degeneration [44]. During the performance of the installations appear mechanical or electrical failures due to the working conditions. For this reason, it is necessary the use of a maintenance plan and a correct CMS to study different failure scenarios [5]. There are some studies about WT maintenance and repair costs that conclude that between 12% and 23% of the total cost are belongs to operation and maintenance (O&M) costs [26,39]. The correct design of maintenance operations and a correct monitorization will reduce these costs, minimizing the downtimes [4,36]. Vibration analysis has been developed and applied previously with positive results; it is required the installation of different sensors joined in the components [10]. The methodology proposed in this paper is suggested to be employed together to this technique due to the similarities of the origin of physics perturbation. The novelty of the paper is based on the capacity of acoustic pattern recognition to detect a fault or wrong performance of some parts analysing the acoustic signals emitted by the machine [1]. The acoustic inspection does not require necessarily a physical contact between the surface and the sensors.

Fig. 1. Maintenance technician making a repair labor in a wind turbine [19]

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Acoustic propagation ways present two characteristics, noise generated by mechanical rotative elements of the WT (hub, generator, gearbox, couplings) and the aerodynamics acoustic generated mainly by blade movement. The WT acoustic emissions depend on the dimensions of the machine, although the acoustic level range is 80 to 100 dB according to the rotation speed conditions [47]. The aerodynamic influence of turbulences area depends on the dimensions of blades and the rotation velocity will be an important factor for this operation [48]. Unmanned aerial vehicles (UAVs), or drones, are used to reduce the human risk or imprecisions in maintenance inspections [58], e.g. steel pipes leak detection inspection [46], power lines structures surveys [7] or solar panels supervision [45]. These vehicles allow the installation of different sensors and cameras as thermographic technology [31]. These tools enable the operator to develop the maintenance activities or tests remotely in safety conditions [25,54]. The use of UAVs must conform to the current legislation and aerial permissions of the operation. The CMS designed by Moraleda et al. [28] and used in this study, composed by an acoustic sensor embedded in the bottom of UAVs, see Fig. 2. This sensor will transmit a wireless signal to a remote centre receiver, where the signal will be analysed in a ground station by a filtering algorithm. The filtering signal is required in order to ensure the elimination of noise or undesirable data [9]. The contribution of this work is resumed in: • The development of a novel CMS and fault diagnosis based on acoustic computation. The WT acoustic emissions machinery is captured using a UAV and an acoustic sensor. • Different mathematical and computational tools are applied for filtering and posterior acoustics characterization of the signals. • It is used a test bench simulating a real scenario to validate this fault detection method.

Fig. 2. UAV with an acoustic sensor embedded

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Methodology and Fundaments

The WT is simulated in laboratory according to Fig. 3. A structural alteration of a solid material under thermic or mechanical stress spreads a transielastic event generating an Acoustic Emission (AE) [29]. These emissions are related with cracks, defects or imperfections both internal and superficial of the material [17]. AE penetrates inside to find the origin and predicts the fail propagation [8]. The acoustic data acquired in the tests are analysed in this paper. A preliminary computational analysis is about a graphical representation of the signals in time domain, see Fig. 4. 5

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The acoustic signal can be analysed mathematically in time-frequency [13], therefore, the signal analysis can be studied by mathematical tools as Fourier Transform (FT) [43]. The advantages of the Wavelet Transform (WT) prove that this technique is efficient for acoustic signals [61]. WT is defined by Eq. (1).   t−τ 1 +∞ s (t) √ Ψ ∗ dt (1) S (τ, a) = ∫−∞ a a Obtaining the conjugate of the mother wavelet ψ∗, moved and scaled point to point to detect the levels of contrast of the signal s(t), being f (t) the digitized signal in the time domain, a = f /f0 (a = 0) the magnitude factor or delay of the wavelet, with f0 as central frequency and τ the translation in time [60]. Other common expression in acoustic representation is a frequency domain spectrum, shown in Fig. 5, to study the frequency distribution range of the signal [34]. The wavelet transform is employed to obtain the signal energy decomposition divided in levels with the pyramidal algorithm and the decomposition tree showed in Fig. 6. This method is very for a acoustics characterization and filtering [11,15]. There are various wavelet transform modes, e.g. discrete or continue [12,14]. WT has been different offspring families depending of the case of application, being Dauchebies family the commonly used in acoustic signal treatment [32,51]. SINGLE SIDED AMPLITUDE SPECTRUM OF SIGNAL

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3

Results

The experiments are employed to validate the reliability of the approach. The mechanical WT components analysed are gearbox, generator and hubs, that are usually subjected to high stress, speed, abrasion and corrosion [3,6]. These scenarios can be classified by function of the acoustic response due to the variation of the generated AE. It has been proved that the gearbox presents more faults in

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the WT machinery, close to 60% of the total faults [59]. The studies about electrical machinery failures have concluded that bearings failures are about 40%, the stator system 38%, the rotor round 10% and 12% to other components of the machine [18]. For this reason, this papers analysis acoustics due to the rotational components to fault detection, reducing the high costs of the operational maintenance [2,42,53]. It is required a deep analysis of the samples by the signal energies to obtain the acoustics characterization. It has been employed WT Dauchebies family analysis [57]. Considering the acoustic samples signals acquired by the CMS embedded in the UAV in off, and the signals come from the engine and considering the UAV on. Figure 7 shows the patterns of the signals and the recognition between both cases. It was found the different responses in some levels at the frequencies range determined by Wavelet transform, exactly in levels 2 and 6. They have a frequency range that will need a posterior analysis to compare the energy magnitude in each level [56]. This analysis allows the analysis of different scenarios to classify and identify a relation between components and the energy level

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pattern [16,23]. The treatment and filtering approach allows the diagnosis between the characteristic acoustic signal of UAV, engine and structure AE, being it a novelty regarding to the state of the art.

4

Conclusions

This work presents a new fault diagnosis technique for wind turbines based on acoustics analysis acquired by an acoustic monitoring system. This system is composed by an acoustic sensor embedded in an aerial vehicle manned, and a ground station receiving acoustic signal in real time that save it for a postprocessing filtering. The signal processing leads to develop the acoustic characterization about possible mechanical or structural faults. A test bench has been designed to simulate a wind turbine. The energy filtering is obtained by Wavelet transforms. It is employed to identify the main wind turbine failures for a suitable maintenance management. Acknowledgements. The work reported herewith has been financially by the Dirección General de Universidades, Investigación e Innovación of Castilla-La Mancha, under Research Grant ProSeaWind project (Ref.: SBPLY/19/180501/000102).

References 1. Akishita, S., Li, Z., Kato, T.: Failure diagnosis system for automobile engine. US Patent 5,932,801 (1999) 2. Amari, S.V., McLaughlin, L., Pham, H.: Cost-effective condition-based maintenance using Markov decision processes. In: 2006 Annual Reliability and Maintainability Symposium (RAMS 2006), pp. 464–469. IEEE (2006) 3. Arcos Jiménez, A., Gómez Muñoz, C.Q., García Márquez, F.P.: Machine learning for wind turbine blades maintenance management. Energies 11(1), 13 (2018) 4. Bangalore, P., Patriksson, M.: Analysis of SCADA data for early fault detection, with application to the maintenance management of wind turbines. Renew. Energy 115, 521–532 (2018) 5. Benmessaoud, T., Mohammedi, K., Smaili, Y.: Influence of maintenance on the performance of a wind farm. Przegląd Elektrotechniczny 89(03a), 174–178 (2013) 6. Chan, D., Mo, J.: Life cycle reliability and maintenance analyses of wind turbines. Energy Procedia 110, 328–333 (2017) 7. Deng, C., Wang, S., et al.: Unmanned aerial vehicles for power line inspection: a cooperative way in platforms and communications. J. Commun. 9(9), 687–692 (2014) 8. Elforjani, M., Mba, D.: Accelerated natural fault diagnosis in slow speed bearings with acoustic emission. Eng. Fract. Mech. 77(1), 112–127 (2010) 9. García Márquez, F.P., García-Pardo, I.P.: Principal component analysis applied to filtered signals for maintenance management. Qual. Reliab. Eng. Int. 26(6), 523–527 (2010) 10. Garg, D., Kaushiek, S., et al.: Condition based monitoring and fault diagonistics of a machine. J. Exp. Appl. Mech. 9(2), 84–89 (2018)

798

P. J. Bernalte Sánchez and F. P. Garcia Marquez

11. Gokgoz, E., Subasi, A.: Comparison of decision tree algorithms for EMG signal classification using DWT. Biomed. Sig. Process. Control 18, 138–144 (2015) 12. Goudarzi, M., Vahidi, B., et al.: Improved fault location algorithm for radial distribution systems with discrete and continuous wavelet analysis. Int. J. Electr. Power Energy Syst. 67, 423–430 (2015) 13. Hammond, J.: Fundamentals of signal processing. In: Modal Analysis and Testing, pp. 35–52. Springer (1999) 14. de la Hermosa Gonzalez, R.R., Márquez, F.P.G., et al.: Pattern recognition by wavelet transforms using macro fibre composites transducers. Mech. Syst. Sig. Process. 48(1–2), 339–350 (2014) 15. de la Hermosa González, R.R., Márquez, F.P.G., Dimlaye, V., et al.: Maintenance management of wind turbines structures via MFCS and wavelet transforms. Renew. Sustain. Energy Rev. 48, 472–482 (2015) 16. Jian, X., Dong, F., et al.: Frequency domain analysis of multiwavelength photoacoustic signals for differentiating tissue components. Int. J. Thermophys. 39(5), 58 (2018) 17. Larizza, F., Howard, C., et al.: Detection and location of defects in rolling element bearing using acoustic emission. In: 18th Australian International Aerospace Congress (AIAC 2018): HUMS-11th Defense Science and Technology (DST) International Conference on Health and Usage Monitoring (HUMS 2019): ISSFD-27th International Symposium on Space Flight Dynamics (ISSFD), p. 843. Royal Aeronautical Society, Engineers Australia (2019) 18. Li, J., Chen, X., et al.: A new noise-controlled second-order enhanced stochastic resonance method with its application in wind turbine drivetrain fault diagnosis. Renew. Energy 60, 7–19 (2013) 19. Maintenance works. http://archsafety.com/ngg/_tag/wind-turbine-maintenanceireland/ 20. Marquez, F.G., Singh, V., Papaelias, M.: A review of wind turbine maintenance management procedures. In: The Eighth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, pp. 1–14 (2011) 21. Márquez, F.P.G.: A new method for maintenance management employing principal component analysis. Struct. Durab. Health Monitor. 6(2), 89–99 (2010) 22. Márquez, F.P.G., Lev, B.: Advanced Business Analytics. Springer, Heidelberg (2015) 23. Márquez, F.P.G., Muñoz, J.M.C.: A pattern recognition and data analysis method for maintenance management. Int. J. Syst. Sci. 43(6), 1014–1028 (2012) 24. Márquez, F.P.G., Pedregal, D.J.: Applied RCM 2 algorithms based on statistical methods. Int. J. Autom. Comput. 4(2), 109–116 (2007) 25. Márquez, F.P.G., Ramírez, I.S.: Condition monitoring system for solar power plants with radiometric and thermographic sensors embedded in unmanned aerial vehicles. Measurement 139, 152–162 (2019) 26. Márquez, F.P.G., Karyotakis, A., Papaelias, M.: Renewable Energies: BusinessOutlook 2050. Springer, Heidelberg (2018) 27. Marugán, A.P., Chacón, A.M.P., Márquez, F.P.G.: Reliability analysis of detecting false alarms that employ neural networks: a real case study on wind turbines. Reliab. Eng. Syst. Saf. 191(106), 574 (2019) 28. Moraleda, V.B., Marugán, A.P., Márquez, F.P.G.: Acoustic maintenance management employing unmanned aerial vehicles in renewable energies. In: International Conference on Management Science and Engineering Management, pp. 969–981. Springer (2018)

Maintenance Management for Wind Turbines

799

29. Morhain, A., Mba, D.: Bearing defect diagnosis and acoustic emission. Proc. Inst. Mech. Eng. Part J: J. Eng. Tribol. 217(4), 257–272 (2003) 30. Muñoz, C.Q.G., Márquez, F.P.G.: Future maintenance management in renewable energies. In: Renewable Energies, pp. 149–159. Springer (2018) 31. Muñoz, C.Q.G., Márquez, F.P.G., Tomás, J.M.S.: Ice detection using thermal infrared radiometry on wind turbine blades. Measurement 93, 157–163 (2016) 32. Muñoz, C.Q.G., Jiménez, A.A., Márquez, F.P.G.: Wavelet transforms and pattern recognition on ultrasonic guides waves for frozen surface state diagnosis. Renew. Energy 116, 42–54 (2018) 33. Njiri, J.G., Söffker, D.: State-of-the-art in wind turbine control: trends and challenges. Renew. Sustain. Energy Rev. 60, 377–393 (2016) 34. Pandarakone, S.E., Mizuno, Y., Nakamura, H.: Distinct fault analysis of induction motor bearing using frequency spectrum determination and support vector machine. IEEE Trans. Ind. Appl. 53(3), 3049–3056 (2016) 35. Pedregal, D.J., García, F.P., Roberts, C.: An algorithmic approach for maintenance management based on advanced state space systems and harmonic regressions. Ann. Oper. Res. 166(1), 109–124 (2009) 36. Pérez, J., Márquez, F.: Condition monitoring and fault diagnosis in wind energy systems. In: Eco-Friendly Innovation in Electricity Transmission and Distribution Networks, pp. 221–241. Elsevier (2015) 37. Pérez, J.M.P., Márquez, F.P.G., et al.: Wind turbine reliability analysis. Renew. Sustain. Energy Rev. 23, 463–472 (2013) 38. Pérez, J.M.P., Asensio, E.S., Márquez, F.P.G.: Economic viability analytics for wind energy maintenance management. In: Advanced Business Analytics, pp. 39– 54. Springer (2015) 39. Pérez, J.M.P., Márquez, F.P.G., Hernández, D.R.: Economic viability analysis for icing blades detection in wind turbines. J. Cleaner Prod. 135, 1150–1160 (2016) 40. Petković, D., Pavlović, N.T., Ćojbašić, Ž.: Wind farm efficiency by adaptive neurofuzzy strategy. Int. J. Electr. Power Energy Syst. 81, 215–221 (2016) 41. Pliego Marugán, A., García Márquez, F.P.: Advanced analytics for detection and diagnosis of false alarms and faults: a real case study. Wind Energy 22(11), 1622– 1635 (2019) 42. Pliego Marugán, A., García Márquez, F.P., Lev, B.: Optimal decision-making via binary decision diagrams for investments under a risky environment. Int. J. Prod. Res. 55(18), 5271–5286 (2017) 43. Portnoff, M.: Time-frequency representation of digital signals and systems based on short-time fourier analysis. IEEE Trans. Acoust. Speech Sig. Process. 28(1), 55–69 (1980) 44. Qiao, W., Lu, D.: A survey on wind turbine condition monitoring and fault diagnosis - part I: components and subsystems. IEEE Trans. Ind. Electron. 62(10), 6536–6545 (2015) 45. Ramírez, I.S., Marugán, A.P., Márquez, F.P.G.: Remotely piloted aircraft system and engineering management: a real case study. In: International Conference on Management Science and Engineering Management, pp 1173–1185. Springer (2018) 46. Ramon-Soria, P., Gomez-Tamm, A., et al.: Autonomous landing on pipes using soft gripper for inspection and maintenance in outdoor environments (2019) 47. Rogers, A.L., Manwell, J.F., Wright, S.: Wind turbine acoustic noise. Renewable Energy Research Laboratory, University of Massachusetts at Amherst (2006) 48. Rogowski, K.: Numerical studies on two turbulence models and a laminar model for aerodynamics of a vertical-axis wind turbine. J. Mech. Sci. Technol. 32(5), 2079–2088 (2018)

800

P. J. Bernalte Sánchez and F. P. Garcia Marquez

49. Sarker, B.R., Faiz, T.I.: Minimizing maintenance cost for offshore wind turbines following multi-level opportunistic preventive strategy. Renew. Energy 85, 104–113 (2016) 50. Shafiee, M., Sørensen, J.D.: Maintenance optimization and inspection planning of wind energy assets: models, methods and strategies. Reliab. Eng. Syst. Saf. 192(105), 993 (2019) 51. Sheikh, J.A., Parah, S.A., et al.: Compression and denoising of speech transmission using daubechies wavelet family. Int. J. Wirel. Mobile Comput. 12(4), 313–334 (2017) 52. Spiess, H., Lobsiger-Kägi, E., et al.: Future acceptance of wind energy production: exploring future local acceptance of wind energy production in a Swiss alpine region. Technol. Forecast. Soc. Change 101, 263–274 (2015) 53. Stenström, C., Norrbin, P., et al.: Preventive and corrective maintenance-cost comparison and cost-benefit analysis. Struct. Infrastruct. Eng. 12(5), 603–617 (2016) 54. Stokkeland, M., Klausen, K., Johansen, T.A.: Autonomous visual navigation of unmanned aerial vehicle for wind turbine inspection. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 998–1007. IEEE (2015) 55. Tavner, P., Gindele, R., et al.: Study of effects of weather & location on wind turbine failure rates. In: Proceedings of the European Wind Energy Conference (EWEC), vol. 2010 (2010) 56. Teng, W., Ding, X., et al.: Multi-fault detection and failure analysis of wind turbine gearbox using complex wavelet transform. Renew. Energy 93, 591–598 (2016) 57. Todorova, M., Parvanova, R.: Application of wavelet functions in signal approximation. In: The 1st International Conference Applied Computer Technologies (ACT 2018), pp. 86–89 (2018) 58. Wang, L., Zhang, Z.: Automatic detection of wind turbine blade surface cracks based on UAV-taken images. IEEE Trans. Ind. Electron. 64(9), 7293–7303 (2017) 59. Wang, L., Zhang, Z., et al.: Wind turbine gearbox failure identification with deep neural networks. IEEE Trans. Ind. Inform. 13(3), 1360–1368 (2016) 60. Zhang, D.: Fundamentals of Image Data Mining, pp. 35–44. Springer, Heidelberg (2019) 61. Zhang, D.: Wavelet transform. In: Fundamentals of Image Data Mining, pp 35–44. Springer (2019)

A Review of the Policy Incentive on Electric Vehicle Market Based on Citespace Wen Zhang1 , Lurong Fan1(B) , Guojiao Chen2 , and Hao Ye3 1 2

Business School, Sichuan University, Chengdu 610065, People’s Republic of China [email protected] Information School, Capital University of Economics and Business, Beijing 10007, People’s Republic of China 3 The School of International Studies, Sichuan University, Chengdu 610064, People’s Republic of China

Abstract. As the environmental problems increasing seriously, governments have to take environmental protection as one of the most important development directions in the future. Large emissions of greenhouse gases (GHGs) will accelerate the greenhouse effect. Comparing with the traditional fuel vehicles, electric vehicle (EV) is a cleaner technology with lower emissions, which can slow the pace of global warming effectively and it has been promoted by governments around the world vigorously. However, there are still some challenges in the development of EV, such as range anxiety, battery safety and so on which will influence consumers’ choices. In order to promote the promotion of new energy vehicles, the government has promulgated a series of incentive policies on EV area. Scholars from all over the world have also studied the policy impact in the field of new energy vehicles. By using CiteSpace literature visualization tool, this paper analyzes relevant literature on the web of science (WOS) to determine the policy influence in EV area. The results indicate the research background of this field. In another hand, costumer and energy supply are the two important impact factors in this area.

Keywords: Electric vehicle

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Introduction

As environmental problems have become more and more serious, governments all over the world have paid more attention on environmental protection and air pollution control. The Paris climate agreement marks a global commitment to environmental governance [25]. As a technology that can reduce vehicle emissions and mitigate global warming effectively, EV has received extensive attention and has also been developed continuously in various fields in recent years [7,15,31]. c The Editor(s) (if applicable) and The Author(s), under exclusive license  to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 801–816, 2021. https://doi.org/10.1007/978-3-030-49889-4_62

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Research on EV area mainly focuses on technology, power supply, consumer behavior and policy impact [5,10,18,27]. EV has faced a serious problems in the development process, which is a chicken or egg problem [8]. Consumer anxiety about the range of electric vehicles has become one of the obstacles to the development of new energy vehicles [19]. Without sufficient electricity demand, the power supply of EV will bear the loss, such as the operation of charging and changing stations. It is difficult to develop the new energy automobile industry only depend on the market strength. To solve this problem, the government can stimulate the development of the industry by issuing incentive policies for EV enterprises, consumers, power grid and other stakeholders [32]. Nowadays, there were many scholars have made efforts on the policy impact of new energy automobile industry. Eoin et al. took Ireland as example to determine the barriers of EV uptake at the perspective of car-dealers and policy-makers. The results showed that the incentive policies need clear signals [20]. Diana et al. discussed the charging equipment in Multi-Unit Residential Buildings in the Canadian province of British Columbia, summarizing three kinds of policies to improve the decision process in establishing charging equipment [14]. Wang et al. determined different factors in the EV market, the results indicated the effect incentive policy has been reduced [32]. Although there were many articles exploring the EV area in policy aspect. The systematic review on the policy influence of EV is barely seen. A summary of the policy impact in the EV field can provide a more comprehensive understanding of the policy background in this field so that people can understand well of the policy impact. It can also clarify the hot issues in this area and help point out a way to the future research direction. In order to support this weak aspect, this paper hopes to make a more integrated review of the policy impact in the EV field by summarizing the literature. To understand the comprehensive information of policy impact requires a lot of literature reading, which is a very heavy workload. The first problem is how to screen out useful information from the massive literature database. Secondly, the theoretical researches on EV have been developed for some time. Moreover, as a hot field, the literature after screening is still difficult to read completely. Finally, how to summarize the results concisely and clearly is also a big problem. In order to solve these problems, citespace, a tool for literature visualization, is selected in this paper to realize the visualization of a large number of literature. Through the search of keywords on WOS, suitable literature was screened out. And the literature data were imported into CiteSpace to obtain satisfactory results. As a summary article, the structure of this paper is as follows. Section 2 introduces the process of literature visualization. The results are summarized in Sect. 3. Section 4, is the conclusion part of this article.

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This paper studies the policy impact of CiteSpace on EV industry development. By searching relevant literature in the field of EV on the WOS and conducting

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preliminary artificial screening, 521 English literature index data from 1990 to 2020 were derived. By using CiteSpace software to calculate and analyze the data, this paper studies the role of policies in the development of EV industry. 2.1

CiteSpace

The tool CiteSpace selected in this paper is a Java application program for analysis and visual co-citation network. It was designed by Dr. Chen chaomei, an internationally renowned information visualization expert. It can be used for a large number of literature statistical calculations and presented in the form of visual knowledge map [4]. In addition to summarizing the basic information of literature data, CiteSpace can also achieve automatic clustering and generate clustering words through algorithms, as well as co-citation analysis of articles. 2.2

Basic Analysis

This paper firstly analyzes the basic information of literature data, and understands the background and general development status of EV policy research field. The basic information mainly includes author, organization and country analysis and journal overlays. • Author analysis The author collaboration network can visually analyze the cooperative relationship between scientific research authors. Through understanding this cooperative relationship, we can intuitively find the research teams at home and abroad. Figure 1 shows the main collaborative researchers in this field. According to the statistical results of CiteSpace, the authors with more than 10 collaborations are Axsen J, Sovacool BK, Noel L and DE Ruben GZ. Among them, the author who has cooperated with others the most at 14 times is Axsen J, with the earliest cooperation starting from 2013. But a more complete collaborative network has occurred with other authors. The cooperative network in Fig. 1(a) shows the cooperative network graph of the leading authors in the field of EV policy research. Figure 1(b) indicates the cooperation relationship of Axsen J. The author collaboration relationship is the cited author in CiteSpace which describe the relationship between authors. The cited author can reflect the situation that two authors are cited by the same article at the same time. Through the analysis of cited author network, the academic community in the same research field can be obtained. At the same time, through the special clustering function of CiteSpace software, the common points of cited author can be obtained by generating clustering tags. The cited author network diagram in Fig. 2(a) and the cluster of cited author network diagram in Fig. 2(b) convey similar information. Figure 2(b) is the clustering graph obtained by clustering co-cited authors according to keywords. It can be seen from the graph that the keywords that the authors

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Fig. 1. Cooperation between authors

focus on in the process of cooperation are consumer attitude, design optimization and so on. The network has a modularity of 0.8204 which can be seen as a high score. It means the policy research in EV area is defined clearly into cluster. • Country analysis The country analysis is mainly composed of the national cooperation network graph and the national cooperation timeline. The country cooperation network shows which countries have developed better policy research in the EV field. The timeline shows when the different countries started their research in this area. The circle size in Fig. 3 represents the number of papers published, and the line represents the partnership. As can be seen from Fig. 3, China and the United States are the major countries in the field of EV policy research, followed by some European countries such as the United Kingdom and Germany. Figure 4 also shows that the first countries to study the impact of policies on EV are Ireland and England. China and the United States have been mainly developing this field since 2010. However, the emphasis in their research fields are different. The United States prefer road transport, while China considered plug-in EV. The other two directions are innovation business model and battery switching station.

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Fig. 2. Cited author analysis

Fig. 3. Cooperation between countries

The Chinese government has implemented policies related to new energy vehicles since 2009 [33]. It not only issued a list of recommended models for the demonstration, promotion and application of EV, but also established a notice on expanding the work related to the demonstration and promotion of EV in public services. Since then, the Chinese government has played an important role in the development of new energy vehicles. Since 1993, the United States has established the partnership for a new generation of vehicles, dedicated to the development of new energy vehicle technologies and industries [29]. However, as can be seen from Fig. 4, researches of the policy influence in EV field in the United States also broke out in 2010. It can be seen that the policy influence is important in the EV development process Although countries such as China, the United States and Europe have conducted policy research on EV since 2010, their research focuses are

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Fig. 4. Timeline of countries

different. European and American countries focus on road traffic, while Chinese researchers focus on plug-in electric vehicles. This may related to the incentive policy on plug-in EV in China in 2010. • Organization analysis The organization cooperation network diagram can show the cooperation between different organizations. We can see from Fig. 5 the closeness of the linkages between national institutions. Among them, Tsinghua university has the closest cooperation with other institutions, with 28 partnerships in this network diagram. Next is Aarhus university, which has 15 partnerships with other institutions. It is worth mentioning that the university of Michigan suddenly started to do policy research in the EV field in 2011 and the burst score is 3.75. In another hand, the university of California, Davis, suddenly launched a policy study on EV in 2012 and the burst score is 3.68. • Research field From the category cluster, the main study area can be seen obviously in Fig. 6. As can be seen from Fig. 6, policy research in EV area is mainly focuses on environment, energy and economy. Journal dual-map overlays can reflect the flow of research between different disciplines through citations. On the left of the superposition diagram are the subject areas where download literature is located, indicating that the main research problems in the current literature focus on these areas. On the right of the superposition diagram is the subject area of the cited literature, indicating the theoretical basis of the current literature. The details can be shown in the Fig. 7, Dual-map overlay of Figs. 7 both illustrate the major disciplinary flows of policy research in the EV field. Figure 7(a) shows a more detailed flow diagram while Fig. 7(b) is a summary based on Fig. 7(a) to make the flow path more significant. The circles in the diagram represent how many articles there are in the field. From Fig. 7(b), we can see that there are mainly 7 flow paths as shown in Table 1:

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Fig. 5. Cooperation between organizations

Fig. 6. Category

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Category of cited literature

Veterinary, animal, science

Environmental, toxicology, nutrition 1.8181733

Veterinary, animal, science

Economics, economic, political

Mathematics, system, mathematical Systems, computing, computer

z score 2.21596 2.634683

Mathematics, system, mathematical Environmental, toxicology, nutrition 1.6925564 Mathematics, system, mathematical Economics, economic, political

4.142085

Mathematics, system, mathematical Psychology, education, social

1.7553648

Economics, economic, political

3.3674479

2.3

Economics, economic, political

Article Analysis

Literature content analysis is mainly carried out from three aspects: keywords, cited reference and cited journal. • Keywords The keywords are mainly embodied in co-occurrence research and burst detection. The meaning of keywords co-occurrence refers to the keywords that appear together in the literature, mainly for the purpose of studying the

Fig. 7. Journal overlays

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Table 2. Top 6 keywords with the strongest citation bursts Keywords

Strength Begin

Adoption

6.3534

2017

Attitude

6.2896

2017

Consumer preference 4.8988

2018

Incentive

4.2812

2018

Purchase

4.2476

2017

Climate change

3.4865

2018

correlation between keywords. The keywords co-occurrence in this paper is mainly reflected in Fig. 8. Except for keywords “electric vehicle” and “policy”, there are many other important keywords in this area such like “plug in hybrid”, “adoption” and “demand”. Through the burst detection of keywords, we can see which keywords suddenly become hot in a certain year. Table 2 shows the top 6 keywords with the strongest citation bursts and their begin years. Figure 9 takes ‘adoption’ and ‘attitude’ as examples to show the citation quantity of these burst keywords. From the burst detection, we can see that most of the keywords of the burst year concentrated in 2017 and 2018. In addition to “climate change” as a keyword in environmental research, the other five of the 6 emergent keywords are related to customers. Research areas include customer attitudes, customer

Fig. 8. Co-occurrence of key words

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Fig. 9. Burst detection

behavior, customer incentives. This indicates that the policy research of EV has focused on consumers since 2017. The formulation of policies should not only consider the factors of EV manufacturers, but also consider consumers’ acceptance of EV. How to promote consumers to choose EV through the implementation of policies is an important issue that decision makers should consider. • Cited reference Co-citation is one of the core functions of CiteSpace, which can indicate the relevance of articles in content and the commonality of research fields. Cited reference charts can indicate which articles are highly cited in the field. The high number of citations indicates that the article has great influence in this field. The higher the intensity of co-citation, the closer the correlation of the article. Some popular articles can be found from Fig. 10(a). Article of Egbue O. had the largest cited frequency at about 91 times while the article of Rezvani Z had the biggest burst score at about 16.71 in 2015. Red circles in Fig. 10(a) indicate the burst of references. Here we choose top 10 references with the strongest citation bursts and their begin years (see Table 3).

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Table 3. Top 10 cited references with the strongest citation bursts References Strength Publish year Burst begin year [24]

16.7117

2015

2017

[6]

13.9429

2012

2016

[28]

13.6267

2014

2016

[2]

11.0028

2016

2017

[3]

10.2911

2013

2016

[12]

9.4909

2011

2016

[11]

8.3647

2015

2018

[17]

8.3431

2016

2017

[13]

8.1352

2013

2016

[22]

7.8710

2014

2017

• Cited journal Cited journal indicates important journals in EV policy research and also the relevance between different journals in this field. Details can be found in Fig. 11. From Fig. 11(a), we can find the journals that play an important role in EV policy research. For example, a total of 388 articles published on Energy Policy were cited in the downloaded literature data. The second is the TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, with a total of 307 articles published in this journal. The third is the TRANSPORT RES A-POL TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, with 244 references cited. Figure 11(b) shows the cluster of cited journals, the main cluster words are “electric vehicle adoption”, “capability”, “coal-fired electric generation” and so on. These clusters indicate the urgent issues of these journals.

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Fig. 10. Cited reference analysis

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Fig. 11. Cited journal analysis

3

Summary

Through visual analysis, we have a further understanding of policy research in the EV field. The research background and key issues in this field are determined. This chapter summarizes the visualization results and draw the following conclusions: • The research background of policy impact in EV field is clarified As can be seen from the author cooperation network diagram in Fig. 1, most scholars can be classified into the same cooperation network. Only a small number of authors are in a single, small-scale collaborative network. This shows that the cooperative relationship between the authors is relatively concentrated, forming a broad cooperative network. The author co-citation diagram in Fig. 2 also shows the close relationship between authors. The research problems can be summarized as new energy automobile product related research, incentive policy related research and power management. On the other hand, the United States, China and Europe are the main forces of policy research in the EV field. A large number of articles come from these three regions. Studies of the impact of policy also begin earlier in these regions. This is related to the EV incentive policies enacted by these countries. At the same time, as important economies in the world, these three regions also bear the burden of emission reduction. Also, as a new energy industry, EV industry is expected to develop consistently. Although policy research on EV has been started in these three regions since 2010, their research focuses are different. Europe and the United States focus more on road traffic, while China focuses more on the development of EV itself. Institutions studying the impact of policies in the EV field are also mostly located in these regions. For example, Tsinghua university, Beijing institute of technology, North China electric power university in China; university of Michigan, university of California in the USA. The European area has Aarhus university, Sussex university and so on.

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• Major areas of study were identified It can be seen from Figs. 6, 7 and Table 1 that the main focuses of policy research in EV field, which are environment, economy and energy. The theoretical flow path between literature also focuses on these three aspects. As can be seen from Table 1, most EV policy studies in the past 30 years have been devoted to exploration by combining mathematical model methods with economic theories. From the burst test, we also found that a large number of literature focused on the burst years from 2016 to 2018. This indicates that this is a period of rapid development in policy research in the EV field. • Consumers are one of the focus of the study From the process of visual analysis of the content of the article, it can be concluded that a large number of studies focus on the consumer side. It is committed to studying consumers consumption behavior, consumers attitudes, consumers preferences of EV and incentive policies for consumers are all worthy of discussion. This shows that the impact of policies on EV market can be more successful from inducing consumers. Through a series of subsidies and preferential policies, consumers can be encouraged to choose EV instead of fuel vehicles. In this method, the scale of EV industry can be expanded and traditional fuel vehicles can be replace by EV gradually. • Energy supply is one of the main problems In addition to guiding consumers, the energy supply of EV charging market is also one of the key research objects. It can be concluded from Figs. 10, 11 that the energy supply of EV includes battery technology, charging method and power grid [21,31]. Batteries include battery capacity, battery safety, battery life and other aspects [1,16]. Charging methods cover power technology, transportation, location allocation, investment economy and other fields [9,30]. Power grid is mainly from power generation, power load, smart grid and other areas of power management [23,26].

4

Conclusion

This paper studies the policy impact in the field of EV and clarifies the research background in this field. It also identifies the core issues and hot topics in this research area. Through the use of CiteSpace visualization software, research on different issues in different countries in different years was sorted out. The research on policy impact in the field of EV mainly focuses on European and American countries and China, which is related to the promotion of the development of the EV industry in these regions. Secondly, the research on policy influence in the EV area mainly focuses on environment, economy and energy. The major journals in which articles are published also focus on these categories. The combination of mathematical model and economic theory is the most important research mode. Finally, consumer behavior and energy supply are major concerns in this process. On the other hand, there are some disadvantages in this paper. For example, literature analysis is time-sensitive and the publication of important new articles

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may have an impact on the research field. CiteSpace can only analyze the general content of articles which mainly covering topics, keywords and summaries so that there may be biased. In the future, the research can have a deeper understanding of the key articles of this field. Literature analysis can also be conducted on other influencing factors, such as the influence from the power grid and consumers.

References 1. Amamra, S.A., Tripathy, Y., et al.: Electric vehicle battery performance investigation based on real world current harmonics. Energies 13(2), 489 (2020) 2. Bjerkan, K.Y., Nørbech, T.E., Nordtømme, M.E.: Incentives for promoting battery electric vehicle (BEV) adoption in Norway. Transp. Res. Part D Transp. Environ. 43, 169–180 (2016) 3. Carley, S., Krause, R.M., et al.: Intent to purchase a plug-in electric vehicle: a survey of early impressions in large us cites. Transp. Res. Part D Transp. Environ. 18, 39–45 (2013) 4. Chen, C.: Citespace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inform. Sci. Technol. 57(3), 359–377 (2006) 5. Dom´ınguez-Navarro, J., Dufo-L´ opez, R., Yusta-Loyo, J., Artal-Sevil, J., BernalAgust´ın, J.: Design of an electric vehicle fast-charging station with integration of renewable energy and storage systems. Int. J. Electr. Power Energy Syst. 105, 46–58 (2019) 6. Egbue, O., Long, S.: Barriers to widespread adoption of electric vehicles: an analysis of consumer attitudes and perceptions. Energy Policy 48, 717–729 (2012) 7. Gan, L., Topcu, U., Low, S.H.: Optimal decentralized protocol for electric vehicle charging. IEEE Trans. Power Syst. 28(2), 940–951 (2012) 8. Gnann, T., Pl¨ otz, P., Wietschel, M.: How to address the chicken-egg-problem of electric vehicles? Introducing an interaction market diffusion model for EVS and charging infrastructure. In: Proceedings of the 2015 ECEEE Summer Study, Toulon, France, pp. 873–884 9. Gong, D., Tang, M., et al.: Achieving sustainable transport through resource scheduling: a case study for electric vehicle charging stations. Adv. Prod. Eng. Manag. 14(1) (2019) 10. Green, E.H., Skerlos, S.J., Winebrake, J.J.: Increasing electric vehicle policy efficiency and effectiveness by reducing mainstream market bias. Energy Policy 65, 562–566 (2014) 11. Helveston, J.P., Liu, Y., et al.: Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the US and China. Transp. Res. Part A Policy Pract. 73, 96–112 (2015) 12. Hidrue, M.K., Parsons, G.R., Kempton, W., Gardner, M.P.: Willingness to pay for electric vehicles and their attributes. Resour. Energy Econ. 33(3), 686–705 (2011) 13. Jensen, A.F., Cherchi, E., Mabit, S.L.: On the stability of preferences and attitudes before and after experiencing an electric vehicle. Transp. Res. Part D Transp. Environ. 25, 24–32 (2013) 14. Lopez-Behar, D., Tran, M., et al.: Charging infrastructure for electric vehicles in multi-unit residential buildings: mapping feedbacks and policy recommendations. Energy Policy 126, 444–451 (2019)

816

W. Zhang et al.

15. Luin, B., Petelin, S., Al-Mansour, F.: Microsimulation of electric vehicle energy consumption. Energy 174, 24–32 (2019) 16. Lyu, Y., Siddique, A., et al.: Electric vehicle battery thermal management system with thermoelectric cooling. Energy Reports 5, 822–827 (2019) 17. Mersky, A.C., Sprei, F., Samaras, C., Qian, Z.S.: Effectiveness of incentives on electric vehicle adoption in Norway. Transp. Res. Part D Transp. Environ. 46, 56–68 (2016) 18. Muratori, M., Elgqvist, E., et al.: Technology solutions to mitigate electricity cost for electric vehicle dc fast charging. Appl. Energy 242, 415–423 (2019) 19. Noel, L., de Rubens, G.Z., Sovacool, B.K., Kester, J.: Fear and loathing of electric vehicles: the reactionary rhetoric of range anxiety. Energy Res. Soc. Sci. 48, 96–107 (2019) 20. O’Neill, E., Moore, D., Kelleher, L., Brereton, F.: Barriers to electric vehicle uptake in Ireland: perspectives of car-dealers and policy-makers. Case Stud. Transp. Policy 7(1), 118–127 (2019) 21. Peterson, S.B., Whitacre, J., Apt, J.: The economics of using plug-in hybrid electric vehicle battery packs for grid storage. J. Power Sources 195(8), 2377–2384 (2010) 22. Pl¨ otz, P., Schneider, U., Globisch, J., D¨ utschke, E.: Who will buy electric vehicles? Identifying early adopters in germany. Transp. Res. Part A Policy Pract. 67, 96– 109 (2014) 23. Quddus, M.A., Shahvari, O., et al.: A collaborative energy sharing optimization model among electric vehicle charging stations, commercial buildings, and power grid. Appl. Energy 229, 841–857 (2018) 24. Rezvani, Z., Jansson, J., Bodin, J.: Advances in consumer electric vehicle adoption research: a review and research agenda. Transp. Res. Part D Transp. Environ. 34, 122–136 (2015) 25. Rogelj, J., Den Elzen, M., et al.: Paris agreement climate proposals need a boost to keep warming well below 2 c. Nature 534(7609), 631–639 (2016) 26. Shao, C., Wang, X., Shahidehpour, M., Wang, X., Wang, B.: Partial decomposition for distributed electric vehicle charging control considering electric power grid congestion. IEEE Trans. Smart Grid 8(1), 75–83 (2016) 27. Shimizu, K., Masuta, T., Ota, Y., Yokoyama, A.: Load frequency control in power system using vehicle-to-grid system considering the customer convenience of electric vehicles. In: 2010 International Conference on Power System Technology, pp. 1–8. IEEE (2010) 28. Sierzchula, W., Bakker, S., Maat, K., Van Wee, B.: The influence of financial incentives and other socio-economic factors on electric vehicle adoption. Energy Policy 68, 183–194 (2014) 29. Sperling, D.: Public-private technology R&D partnerships: lessons from us partnership for a new generation of vehicles. Transp. Policy 8(4), 247–256 (2001) 30. Vazifeh, M.M., Zhang, H., Santi, P., Ratti, C.: Optimizing the deployment of electric vehicle charging stations using pervasive mobility data. Transp. Res. Part A Policy Pract. 121, 75–91 (2019) 31. Wang, C.S., Stielau, O.H., Covic, G.A.: Design considerations for a contactless electric vehicle battery charger. IEEE Trans. Industr. Electron. 52(5), 1308–1314 (2005) 32. Wang, N., Tang, L., Pan, H.: A global comparison and assessment of incentive policy on electric vehicle promotion. Sustain. Cities Soc. 44, 597–603 (2019) 33. Zheng, J., Mehndiratta, S., Guo, J.Y., Liu, Z.: Strategic policies and demonstration program of electric vehicle in China. Transp. Policy 19(1), 17–25 (2012)

Author Index

A Ahmad, Haseeb, 613, 717 Ahmad, Waseem, 106 Ahmed, Shariq, 436 Akbar, Muhammad Waqas, 717 Aktas, Daiva, 131 Ali, Syed Nayyer, 538 Ameen, Bilal, 538 Avornic, Gheorghe, 143 B Bai, Yue, 704 Bai, Yufan, 355 Baig, Sajjad Ahmad, 106 Belostecinic, Grigore, 445, 778 Benea-Popuşoi, Elina, 676, 742 Bernalte Sánchez, Pedro José, 791 C Calmâş, Valentina, 179 Camelia-Cristina, Dragomir, 445 Cao, Qilin, 226, 456 Chen, Charles Weizheng, 487 Chen, Guojiao, 801 Chen, Jialu, 226 Chen, Jingdong, 243, 259, 301 Chen, Lingling, 763 Chen, Mo, 243, 259, 301 Chen, Xiaoxiu, 420 Chen, Yuanli, 215 Chen, Yuheng, 730 Copǎceanu, Cristina, 143 Corlǎteanu-Granciuc, Silvia, 524 Cui, Xinyuan, 93

D Deng, Yanfei, 154 Duan, Jie, 339 Duca, Gheorghe, 445, 500, 512, 524, 583 Duca, Maria, 778 Duca, Svetlana, 676 E EI Ghini, Ahmed, 189 El-Karimi, Mounir, 189 F Fan, Fengchun, 568 Fan, Jiaqi, 167 Fan, Lurong, 801 Fang, Taowenyu, 380 Fedorciucova, Svetlana, 179 Fu, Pengxue, 226, 405 G Garcia Marquez, Fausto Pedro, 119, 791 Geng, Yuyu, 93 Gómez Muñoz, Carlos Quiterio, 119 Gong, Zaiwu, 35 Gu, Xin, 687 Guo, Chunxiang, 68, 93 Guo, Qiao, 355 H Hafeez, Muhammad, 613, 717 Hashim, Muhammad, 106 He, Dongmei, 339 He, Jia, 472 He, Yuxi, 647

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 J. Xu et al. (Eds.): ICMSEM 2020, AISC 1191, pp. 817–819, 2021. https://doi.org/10.1007/978-3-030-49889-4

818 Huang, Huang, Huang, Huang, Huang, Huang,

Author Index Chao, 167 Jingwei, 755 Lu, 763 Qing, 405 Yidan, 13 Yong, 763

J Jahangir, Junaid, 717 Ji, Xuanming, 285 Jiang, Qiang, 405 Jie, Xiaowen, 200 K Kamran, Asif, 538 Khan, Abdullah, 436 L Lev, Benjamin, 35 Li, Guangjin, 325 Li, Jiamei, 647 Li, Kun, 420 Li, Lan, 273 Li, Shuanghai, 380 Li, Tingting, 273 Li, Xiaoping, 200 Li, Yang, 613 Liu, Haiyue, 339, 355 Liu, Huichao, 154 Liu, Jiawei, 243 Liu, Tianyu, 215 Liu, Tingting, 456 Liu, Wendi, 627 Liu, Xin, 730 Lu, Yi, 592, 603 Luo, Kuankuan, 627 M Mao, Youjia, 226 Meng, Zhiyi, 24 N Nazam, Muhammad, 106 Ni, Ting, 663 O Ou, Limei, 568 P Paredes Alvarez, Christian, 119 Peng, Hui, 613

Peng, Xinying, 13, 24 Petrescu, Ion, 445 Pinar-Pérez, Jesús María, 45, 57 Pliego-Marugán, Alberto, 45, 57 Q Qiu, Rui, 13 R Railean, Elena, 131 Ren, Han, 487 Ren, Yelin, 456 Rizvi, S. M. Ahsan, 538 Ruiz-Hernández, Diego, 45, 57 Rusu, Ecaterina, 742 S Sarwar, Adnan, 315 Scutaru, Iurie, 583 Serotila, Igor, 524, 778 Sha, Sha, 553 Sheeraz, Alia, 315 Shi, Liu, 663 Siscan, Zorina, 392 Şpac, Ghenadie, 179 Spinei, Victor, 524 Sturza, Rodica, 583 Sun, Deguo, 13, 24 Syed, Nadeem A., 538 T Tabunscic, Olga, 179 Tan, Lindan, 568 Tang, Yingkai, 285 Tao, Zhimiao, 81 Travin, Sergey, 500, 512 Trofimov, Victoria, 131 W Wan, Ling, 704 Wan, Xuxian, 472 Wan, Yan, 755 Wan, Yuezhen, 259 Wang, Fei, 355 Wang, Huan, 687 Wang, Jiayi, 93 Wang, Kun, 285 Wang, Peng, 755

Author Index Wang, Qiongmei, 663 Wang, Tingting, 627 Wang, Yile, 339 Wang, Yusheng, 35 Wen, Yaqi, 603 X Xie, Xulian, 154 Xiong, Xiyue, 456 Xu, He, 285 Xu, Jiuping, 1 Xu, Lei, 154 Y Yan, Jinjiang, 763 Yang, Xue, 687 Yang, Yongfang, 592 Ye, Hao, 801 Ye, Ziming, 405 Yin, Qifeng, 200 Yuan, Ling, 568

819 Z Zafar, Aqsa, 315 Zafar, Muqaddas, 315 Zhang, Liming, 627 Zhang, Luyang, 472 Zhang, Mingtao, 647 Zhang, Tian, 568 Zhang, Wen, 801 Zhang, Yunjie, 763 Zhang, Zhaobohan, 647 Zhao, Gang, 755 Zhao, Guohao, 717 Zhen, Weili, 647 Zheng, Han, 301 Zheng, Hanmei, 200 Zhong, Zhengqiang, 487 Zhou, Guichuan, 627 Zhou, Qiyang, 68 Zhu, Qingsong, 273 Zhuo, Rongyao, 325 Zou, Liang, 755