Study on China’s Industrial Competitiveness 9811998442, 9789811998447

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Yanyun Zhao

Study on China’s Industrial Competitiveness Translated by Chi Wei Su Yannong Xie

Study on China’s Industrial Competitiveness

Yanyun Zhao

Study on China’s Industrial Competitiveness

Yanyun Zhao Center for Competitiveness and Assessment Renmin University of China Beijing, China Translated by Chi Wei Su School of Economics Qingdao University Qingdao, China

Yannong Xie School of Economics Qingdao University Qingdao, China

ISBN 978-981-19-9844-7 ISBN 978-981-19-9845-4 (eBook) https://doi.org/10.1007/978-981-19-9845-4 Jointly published with Economic Science Press The print edition is not for sale in Chinese Mainland. Customers from Chinese Mainland please order the print book from: Economic Science Press. © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are reserved by the Publishers, whether the whole or part of the material is concerned, specifically the rights of 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 publishers, 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 publishers nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Main Member of the Research Group CHEN Fang CHEN Weiping GUO Danbo LI Jingping LI Yajie LI Zhenghui TAN Yingping ZHANG Mingqian ZHEN Feng

Preface

At present, China’s development is facing an important period of opportunity, the opportunity is greater than the challenge, therefore, a comprehensive understanding of the potential and development path of China’s industrial competitiveness is a very important research. The Ministry of Education has established the major key project of “China’s Industrial Competitiveness Research” to meet the needs of the times, and it is also a concrete embodiment of giving full play to the role of social science research guidance and scientific decision-making. Our research strives to pursue the academic frontier of the world, but at the same time pays attention to the very specific characteristics of competitiveness, deeply studies and deeply understands the theories of scholars in developed countries, and puts forward the diamond model of industrial competitiveness for us in the light of the reality of China. Our academic research is closely related to the practical problems of our country, and makes a lot of use of statistical data to make various model analysis, which has great academic value. Therefore, in the extensive international exchanges, it has been recognized by many international counterparts. Our research on industrial competitiveness has always been aimed at solving major practical problems in our country, therefore, we have been maintaining a close interactive relationship with government departments, banks and related units. Our research results on the competitiveness of manufacturing industry have been provided to the Ministry of Commerce, National Development and Reform Commission, National Bureau of Statistics, China Development Bank, Industrial and Commercial Bank of China (ICBC) and so on. The achievements in the seven elements of industrial competitiveness, the main determining factors, international comparison and the evaluation of inter-industry advantages and disadvantages serve the actual sector more directly. The study of tourism competitiveness in China, which directly serves the Ministry of Culture and Tourism, has played an active role in the international comparison of tourism development and the analysis of tourism powers in China. The research on the competitiveness of Chinese cultural industry is carried out from the international and domestic regional and urban levels, highlighting the role of cultural industry, the foundation and promotion of culture on economic development, providing a new and systematic empirical analysis for China’s cultural competitiveness and cultural industry competitiveness, and providing a scientific and vii

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realistic basis for China to give full play to its cultural advantages and enhance its national economic competitiveness and industrial competitiveness. In view of the relatively lagging situation of China’s service industry, based on the comparison of international competitiveness, we comprehensively analyze the existing problems, explore the experience of developed countries, and provide a scientific and objective basis for promoting China’s service industry and realizing overall revitalization. The competitiveness of environmental protection industry in China is an unprecedented research. Based on the theory of sustainable development, we deeply study the statistical problems, put forward the analysis framework of competitiveness of environmental protection industry in China, and make an empirical analysis, and get a very valuable conclusion. In the aspect of competitiveness of China’s agricultural industry, we highlight the research from the perspective of trade and technical efficiency, pursue to evaluate the competitiveness of the main agricultural areas of China from the in-depth analysis of intra-industry trade and put forward countermeasures to solve the problem. In the process of changing the mode of economic growth in China, it is a fundamental problem to enhance the competitiveness of the industry. Our research constructs the information platform of industrial competitiveness, which provides scientific design and application case study for the integrated analysis and decisionmaking facilities and mechanisms of enterprises, industries, financial institutions and government departments, which can make up for the lack of effective information in the market operation of our country, especially the repeated construction of the lack of industrial information in systematic processing, the low level of prosperity, haphazard competition, vicious competition and so on. As a result, great social benefits will be produced. We not only pursue the innovation of technical methods and application theories but also pursue the collection, processing, processing and application of relevant data at home and abroad, so as to provide basic results for the database of industrial competitiveness to meet the needs of government management. This is the basic premise of scientific analysis and scientific decision-making of information technology, and our research has made great efforts to this end, and has also been recognized by the society. Our research has been interacting with government departments and social needs. The research results have been affirmed by relevant government departments such as Ministry of Commerce, National Development and Reform Commission, Ministry of Culture and Tourism and financial institutions, such as ICBC, China Development Bank, and Beijing, Shenzhen, Tibet and other local governments. Our research results have been highly evaluated by participating in academic conferences or forums at home and abroad many times. China Paper Industry Development Analysis Research Group of World Bank in Finland specially consults us on the analysis methods, data and analysis results of industrial competitiveness. Research Group on industrial development of developing countries, United Nations University in the Netherlands commissioned us to provide them with an analysis report on the competitive advantages and leading advantages of China’s textile and garment industry since the reform and opening up. A Spanish professor Montero Lorenzo commissioned us to provide an analytical report on the development of economic cooperation between China and

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the European Union, which was translated into Spanish and published in important Spanish magazines. When we attended the Vietnam International Conference, our research papers were comprehensively introduced by Vietnamese English newspapers. Our research results also have a great impact in Australia, Italy, Japan and South Korea. The research on China’s industrial competitiveness is in the ascendant. I hope our research can lay an important foundation for this, and we also hope that our research will make a positive contribution to the overall promotion of China’s industrial competitiveness. Beijing, China

Yanyun Zhao

Contents

Part I 1

2

Theory, Methodology and Model Investigation of China’s Industrial Competitiveness

Theory of China’s Industrial Competitiveness . . . . . . . . . . . . . . . . . . . . 1.1 The Basic Issues Relating to the Research of China’s Industrial Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Current Research on China’s Industrial Competitiveness . . . . . . . 1.3 Basic Theory of the Research on China’s Industrial Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 The Relationship Between National Competitiveness, Industrial Competitiveness and Enterprise Competitiveness . . . . . . . . . . . . . . . . . . . . . 1.3.2 Competitive Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.3 Competitive Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.4 Industrial Agglomeration Regional Competitiveness . . . Research on China’s Industrial Competitiveness with Diamond Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Theoretical System of Decisive Factors on China’s Industrial Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Models and Applications of Manufacturing Sector’s Competitiveness of China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 The Factor Variables of Competitiveness Analysis of China’s Manufacturing Industry . . . . . . . . . . . . . . . . . . 2.2.2 China’s Manufacturing Industry Competitiveness Model 2.2.3 The Descriptive Statistical Analysis Based on of China’s Regional Manufacturing Competitiveness Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 Model Estimation of China’s Manufacturing Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Problems of Manufacturing Sector’s Competitiveness of China .

3 3 5 9

9 11 13 14 17 17 19 20 22

25 27 31

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2.4 3

4

Basic Strategies and Policies to Promote Regional Manufacturing Sector’s Competitiveness of China . . . . . . . . . . . . .

33

Research on China’s Industrial Cluster Competitiveness . . . . . . . . . . 3.1 Economic Model of China’s Industrial Cluster and Its Applied Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 Design of Economic Measurement Model of Industrial Agglomeration . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2 Economic Measurement Model of Industrial Agglomeration in China . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3 Statistical Description and Analysis of Industrial Agglomeration Economy in China . . . . . . . . . . . . . . . . . . 3.1.4 Application and Analysis of Industrial Agglomeration Economic Model in China . . . . . . . . . . . . 3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Regional Differences of Innovation Activities in China’s Manufacturing Industry . . . . . . . . . . . . . . . . . . 3.2.2 Model and Application Analysis of Industrial Agglomeration Innovation in China . . . . . . . . . . . . . . . . . 3.3 Model of China’s Industrial Innovation Cluster of the Entry of New Enterprise and Its Applied Studies . . . . . . . . . . . . . . . . . . . 3.3.1 The Theoretical Framework of Influencing Factors of New Enterprise Entry . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Determination of Data and Analytical Models . . . . . . . . . 3.3.3 Negative Binomial Regression Model Analysis Results .

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Analysis of China’s Input–Output International Competitiveness . . 4.1 Analysis of Added Value and Its Composition in I–O Tables . . . . 4.1.1 Value Added Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Labor Remuneration Rate . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Production Tax Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.4 Operating Surplus Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.5 Industrial Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Analysis of Import and Export in I–O Tables . . . . . . . . . . . . . . . . . 4.2.1 Export Rate Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Import Rate Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Import and Export Rate Analysis . . . . . . . . . . . . . . . . . . . . 4.3 Analysis of Industrial Interdependent Relationship in I–O Tables 4.3.1 Study on Yield Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Influence Coefficient Analysis . . . . . . . . . . . . . . . . . . . . . . 4.3.3 Study on Total Consumption Coefficient of Main Industries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

67 67 67 69 71 71 73 74 74 76 76 78 78 80

35 36 36 37 38 44 44 49 60 61 61 63

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5

Research on Soft International Competitiveness of China’s Enterprise Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Research Model on Soft International Competitiveness of China’s Enterprise Management . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Enterprise Governance Structure . . . . . . . . . . . . . . . . . . . . 5.1.2 Enterprise Management System . . . . . . . . . . . . . . . . . . . . . 5.1.3 Enterprise Employee Management . . . . . . . . . . . . . . . . . . 5.1.4 Enterprise Ethics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Assessment on Soft International Competitiveness of China’s Enterprise Management . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Analysis on the Soft International Competitiveness of China’s Enterprise Management by Competitiveness Factors . 5.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Part II 6

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87 87 88 89 89 90 90 96 99

Study on the International Competitiveness of China’s Manufacturing Sector

Assessment and Analysis of China’s Manufacturing International Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Assessment System of China’s Manufacturing International Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Assessment and Analysis of Manufacturing International Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 International Competitiveness of Manufacturing Industry 6.2.2 Advantages and Disadvantages of International Competitiveness of China’s Manufacturing Industry . . . 6.3 Characteristics of China’s Manufacturing International Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessment and Analysis of International Competitiveness of China’s Manufacturing Environment . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Assessment System of International Competitiveness of Manufacturing Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Assessment and Analysis of the International Competitiveness of Manufacturing Environment . . . . . . . . . . . . . . 7.2.1 Evaluation of International Competitiveness of Manufacturing Environment . . . . . . . . . . . . . . . . . . . . . 7.2.2 Advantages and Disadvantages of the International Competitiveness of China’s Manufacturing Environment 7.3 Characteristics of International Competitiveness of China’s Manufacturing Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

103 103 107 107 112 112 115 115 117 117 118 121

Assessment and Analysis of Basic International Competitiveness of China’s Manufacturing Industry . . . . . . . . . . . . . 123 8.1 Assessment System of Basic International Competitiveness of China’s Manufacturing Industry . . . . . . . . . . . . . . . . . . . . . . . . . . 123

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8.2

8.3 9

Assessment and Analysis of Basic International Competitiveness of China’s Manufacturing Industry . . . . . . . . . . . 8.2.1 Evaluation of Basic International Competitiveness of Manufacturing Industry . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.2 Advantages and Disadvantages of China’s Basic International Competitiveness of Manufacturing Industry Characteristics of Basic International Competitiveness of China’s Manufacturing Industry . . . . . . . . . . . . . . . . . . . . . . . . . .

Foreign Trade Development of China’s Industrial Sector and Its International Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Characteristics and Development of Foreign Trade in China’s Industrial Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1.1 The Total Volume of Foreign Trade in Industrial Products Continued to Grow . . . . . . . . . . . . . . . . . . . . . . . . 9.1.2 The External Trade of Industrial Products is Generally in a State of Surplus, and the Dependence on Exports Continues to Increase . 9.1.3 Fundamental Changes in the Structure of Export Trade . 9.2 International Competitiveness Index of Trade in China’s Industrial Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Index of Relative Export Performance of Trade in China’s Industrial Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 Analysis of the International Competitiveness of Trade in China’s Major Industrial Industries . . . . . . . . . . . . . . . . . . . . . . . 9.4.1 Labor-Intensive Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.2 Capital, Technology-Intensive Industries . . . . . . . . . . . . . 9.4.3 Industry that Produces Primary Products Such as Raw Materials and Fuels . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10 Industrial Competitiveness Among China’s Industrial Sectors and Sector Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.1 Assessment on Industrial Competitiveness Among China’s Industrial Sectors in 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Basic Characteristics of Industrial Sectors in Sustaining the Economic Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2.1 Macro Target Feature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2.2 Industrial Competition Characteristics . . . . . . . . . . . . . . . 10.3 Consumption of Energy and Environmental Protection with the Development of the Industrial Sectors . . . . . . . . . . . . . . . 10.3.1 Industry Energy Consumption . . . . . . . . . . . . . . . . . . . . . . 10.3.2 Industry Environmental Impact . . . . . . . . . . . . . . . . . . . . . 10.4 Industry Selection and Strategic Industry for Industrial Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4.1 Select the target’s Quantization Method . . . . . . . . . . . . . .

125 125 127 128 131 132 132

132 133 133 137 141 141 141 142 142 143 143 151 153 154 156 156 157 157 160

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10.4.2 Industry Selection Information Display . . . . . . . . . . . . . . 160 Part III China’s Industrial Competitiveness Research by Subjects 11 Research on Industrial Competitiveness of China’s Service Sector . 11.1 Background of the Research and Current Development of Service Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1.1 Research Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1.2 The Status Quo of China’s Service Sector . . . . . . . . . . . . 11.2 Overview of Domestic and International Research on International Competitiveness of Service Sector . . . . . . . . . . . . 11.3 Theory and Methodology of Research on International Competitiveness of Service Sector . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3.1 Research Ideas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3.2 Design of the Evaluation Index System for the Competitiveness of China’s Service Industry . . . 11.4 Assessment and Comparative Analysis of International Competitiveness of China’s Service Sector . . . . . . . . . . . . . . . . . . . 11.4.1 Comparative Analysis of the Overall Ranking of Service Industry Competitiveness . . . . . . . . . . . . . . . . . 11.4.2 Evaluation and Analysis on the International Competitiveness of the Core, Foundation and Environment of China’s Service Industry . . . . . . . . . 11.4.3 Factor Advantage Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 Selection of Strategies for Upgrading Competitiveness of China’s Service Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5.1 Accelerate Economic Development, Raise the Level of Social Income, Accelerate the Process of Urbanization, and Create a Good Competitive Environment for the Development of the Service Industry 11.5.2 Optimize the Industrial Structure of the Service Industry 11.5.3 Accelerate the Training of Service Industry Personnel . . 11.5.4 Relying on Scientific and Technological Progress to Improve the Technological Content of the Service Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5.5 Implement the Strategy of “Bringing in and Going Global” to Enhance the International Competitiveness of China’s Modern Service Industry . .

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12 Research on Industrial Competitiveness of China’s Tourism Sector 12.1 Background and Significance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Theory and Assessment System of International Competitiveness of China’s Tourism Sector . . . . . . . . . . . . . . . . . . 12.2.1 The Basic Theory and Method of the International Competitiveness Design of China’s Tourism Industry . .

181 181

165 165 166 167 168 168 168 171 171

173 177 177

177 179 179

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12.2.2 Design of China’s Tourism Industry Competitiveness Evaluation Index System . . . . . . . . . . . . 12.3 Assessment and Comparative Analysis of the International Competitiveness of China’s Tourism Sector . . . . . . . . . . . . . . . . . . 12.3.1 Evaluation and Analysis of the International Competitiveness of China’s Tourism Industry Elements 12.3.2 Evaluation and Analysis of the International Competitiveness of China’s Tourism Industry Core, Foundation and Environment . . . . . . . . . . . . . . . . . . 12.3.3 Analysis of International Tourism Competitiveness Model 12.3.4 Comparative Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3.5 Summary of International Tourism Competitiveness . . . 12.4 Design, Assessment and Analysis on Tourism Sector’s Competitiveness of Thirty-one Provinces, Autonomous Regions and Municipalities in China . . . . . . . . . . . . . . . . . . . . . . . . 12.4.1 Structural Design and Evaluation Index System of Tourism Industry Competitiveness of 31 Provinces, Autonomous Regions and Municipalities . . . 12.4.2 Comprehensive Evaluation and Analysis of Tourism Industry Competitiveness of 31 Provinces, Autonomous Regions and Municipalities . . . 12.4.3 Comprehensive Evaluation and Analysis of the Competitiveness of Tourism Industry Factors of 31 Provinces, Autonomous Regions and Municipalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.4.4 Analysis of the Structural Balance of Tourism Industry Competitiveness in 31 Provinces, Autonomous Regions and Municipalities . . . . . . . . . . . . . 12.4.5 Summary of the Competitiveness of Tourism Industry in 31 Provinces, Autonomous Regions and Municipalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Research on Industrial Competitiveness of China’s Culture Sector . 13.1 Background of the Research on Culture Sector’s Competitiveness 13.2 Structural Model of Culture Sector’s Competitiveness . . . . . . . . . 13.3 Assessment Indicator System of Culture Sector’s Competitiveness 13.3.1 Construction of Competitiveness Index System . . . . . . . . 13.3.2 Validity Test of Competitiveness Index System . . . . . . . . 13.4 Overall Assessment and Analysis of International Culture Sector’s Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.4.1 Evaluation and Analysis Ideas . . . . . . . . . . . . . . . . . . . . . . 13.4.2 Specific Content of Evaluation and Analysis . . . . . . . . . . 13.5 Conclusions and Suggestions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

183 187 187

192 193 203 204

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214 217 217 218 219 219 224 226 226 226 234

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14 Research on Industrial Competitiveness of China’s Environmental Protection Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.1 Definition of Environmental Protection Sector . . . . . . . . . . . . . . . . 14.2 Identification and Classification of Environmental Protection Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2.1 Basic Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2.2 Classification Basis and Industry Identification . . . . . . . . 14.3 Analysis of Industrial Competitiveness of China’s Environmental Protection Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3.1 Theoretical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3.2 Selection of Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3.3 The Practical Analysis of China’s Environmental Protection Industry Competitiveness . . . . . . . . . . . . . . . . . 14.4 Policy Suggestions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4.1 Establishing a Comprehensive Environmental Industrial Policy System . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4.2 Vigorously Promote the Market-Oriented Development of Environmental Protection Industry . . . . 14.4.3 Speeding up the Establishment of Technological Innovation System for Promoting Environmental Protection Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Research on Industrial Competitiveness of China’s Agricultural Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.1 Status Quo of the Research on Industrial Competitiveness of China’s Agriculture Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 Comparative Advantage Analysis of China’s Agriculture Products 15.2.1 Evaluation Index of Comparative Advantage of Agricultural Products . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.2.2 Overall Evaluation of Comparative Advantage of Agricultural Products in China . . . . . . . . . . . . . . . . . . . 15.2.3 Prospect of the Future Development Trend of China’s Agricultural Products Trade . . . . . . . . . . . . . . . 15.3 Research on Inner-Sector Trade and Competitiveness of China’s Agriculture Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.1 The Basic Theory of Intra-industry Trade . . . . . . . . . . . . 15.3.2 Data and Analytical Method . . . . . . . . . . . . . . . . . . . . . . . . 15.3.3 Analysis of Empirical Conclusions . . . . . . . . . . . . . . . . . . 15.3.4 Analysis on the Trend of Agricultural Products Trade Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.3.5 Basic Policy Recommendations . . . . . . . . . . . . . . . . . . . . . 15.4 Research on Inner-Sector Trade Development and Competitiveness of China’s Food Processing Sector . . . . . . . 15.4.1 Current Situation of Intra-industry Trade of Processed Food in China . . . . . . . . . . . . . . . . . . . . . . . .

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237 238 243 243 243 248 254 256 256 273 273 273

274 275 275 276 276 277 278 281 281 282 285 285 288 288 289

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15.4.2 Determinants and Variable Selection of Intra-industry Trade in Processed Food . . . . . . . . . . . . 15.4.3 Econometric Models, Sample Selection and Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4.4 Test Results and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 15.4.5 The Basic Conclusions of the Research . . . . . . . . . . . . . . 15.5 Comprehensive Assessment and Analysis of China’s Regional Agriculture Sector’s Competitiveness of Thirty-One Provinces, Autonomous Regions and Municipalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5.1 The Basic Problems of Agricultural Industry Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5.2 Index System, Method and Process of Comprehensive Evaluation of Agricultural Competitiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.5.3 Results and Analysis of Comprehensive Evaluation of Agricultural Competitiveness of 31 Provinces Autonomous Regions and Municipalities in China . . . . . . . . . . . . . . . . . . . . . . . . 15.5.4 Main Conclusions and Policy Implications . . . . . . . . . . .

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Postscript . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315

Part I

Theory, Methodology and Model Investigation of China’s Industrial Competitiveness

Chapter 1

Theory of China’s Industrial Competitiveness

1.1 The Basic Issues Relating to the Research of China’s Industrial Competitiveness International competitiveness, which rose in the 1980s and became a hot spot in the world in the 1990s, driven by the economic globalization, information technology revolution and the rapid development of high-tech industry, has gradually become an important research field and attracted the attention of all countries in the world. Economic competition, in the final analysis, is industrial competition. The overall economic competitiveness of a country or region is determined by the competitiveness of its main industries. With the rapid development of economic globalization and the promise of China to accede to WTO, how to deal with the open international market become the concerned issue of corporate, industrial, government, research institution and the public. China has strong competitiveness in the market potential and human resource. But from 1994 to 2006, the international competitiveness of China was ranked in around 28th dues to the weakness of enterprise competitiveness. Industry competitiveness is the biggest bottleneck for China to improve the international competitiveness. As for the actual situation of China, industry scale and industry category have developed rapidly since the reform and opening up. And the proportion of manufacturing has reached high level in the three industries. However, the internal structure of manufacturing industry is still very unreasonable, mainly reflected in that the proportions of high value-added and high-tech industries and products are not high, and the market economy competition restraint mechanism is not mature enough. There are repeated constructions and haphazard expansions. General industrial products appear quite common accumulation of inventories and capacity idle. The development of high value-added high-tech industry is facing fierce competition in the international market, with slow development and many difficulties. The development and promotion of agriculture, as the basic industry, also face the influence from home and abroad. The proportion of the tertiary industry does not match the development stage of China’s per capita income, compared with developed countries, there is a bigger © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_1

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gap. It is an indisputable fact that the development of service industry lags behind the overall industrial level of the national economy. From the industrial organization structure perspective, it’s far from mature to enhance the international competitiveness of corporate and industry by the means of competition, not to mention the bias in cognition and practice. Nowadays, China lags behind not only in technical equipment of industrial enterprise and technological level, but also in the industrial organization structure, with numerous all-purpose enterprises and small enterprises in the market. What’s more, the low degree of specialization and the poor scale economic situation are outstanding expressions in the current status quo. Therefore, it has been the major issue to improve the core competitiveness of industries of China by strengthening the advantages of industrial agglomeration, attracting the competitive resources at home and abroad and promoting enterprise clustering. Since China accessed to the WTO, “the manufacturing center in the world” has been the hot topic. Therefore, it turns to be a critical subject to enhance manufacturing competitiveness. As far as China is concerned, the development of manufacturing industry is in a crucial period that from tradition to contemporary and from planned economy to market economy. It has similarity with other general countries and has internal characteristics at the same time. China is standing up to the challenge of international manufacturing with positive posture, and making efforts to get out the dilemma of manufacturing development, making sure the sustainable growth of China’s economy. To realize the purpose, there are many theoretical issues about industrial competitiveness to research, many rules to illustrate with model, many tendencies to estimate scientifically and many problems to analyze deeply. And we need scientific solution in some fields, such as structural adjustment, industrial upgrading, industrial competitiveness clustering and effective formulation of industrial policy. In consequence, it has been one of the most important subjects for Chinese manufacturing industry’s international competitiveness. How to judge the level of international competitiveness of China’s manufacturing industry from the perspective of empirical theory and method, find out the key problems and point out the way of development, which has important theoretical value and practical significance. The development and growth of the industry will eventually break through the national boundaries and form international competition. The industrial competitiveness is finally reflected in the market competition between countries. However, the phenomenon of industrial competition within a country and between different regions also exists and deserves attention. The research of professor Michael E. Porter from Harvard University also shows that the fierce domestic market competition plays an important role in the cultivation, formation and maintenance of international competitive advantages. Therefore, although the competition is increasingly internationalized, it is of great significance to study the competition situation of domestic industries and examine the competitiveness of various regions and industries.

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1.2 Current Research on China’s Industrial Competitiveness Study on China’s industrial competitiveness originates from the study of international competitiveness to a certain extent. The research of China’s international competitiveness deeply developed both in theory and application with the impetus of World Economic Forum (WEF) and annual international competitiveness evaluation report from International Institute for Management Development (IMD). It has become an crucial aspect for our country to participate in international competition, deepen market economy, promote the competitiveness of the whole system. Looking back on the research and development process of more than 20 years, the development of international competitiveness evaluation from 1980 when it started and to 2006 can be summarized as three stages. The first stage was in the 1980s. The evaluation of international competitiveness mainly focused on the comparison of economic competitiveness, including the reflection of industrial economic activities and natural resources. All the evaluation indicators are inflexible aims, and the index system is relatively large and the relationship between the indicators is loose. The research objects are mainly industrialized countries. The second stage was in the 1990s. The theory and evaluation methods of international competitiveness have been basically established and gradually improved, which is mainly reflected in the concept of international competitiveness, evaluation principles, worldwide survey of soft indicators, the establishment and mature development of the evaluation index system of the eight major factors. Moreover, in practice, the international competitiveness assessment is gradually expanded from the scope of industrialized countries to newly industrialized countries and regions, as well as the overall world scope of developing countries and countries with economies in transition, making the international competitiveness assessment system truly become a public competitive information platform for the economic and social development of all countries and regions in the world. The third stage began from 2001 after entering the twenty-first century, the theory of international competitiveness has gained new development. The application of international competitiveness in the 1990s benefited from globalization and the rapid development of information technology and high-tech industries, thus greatly contributing to the formation of innovation systems in the world’s major countries and regions, as well as to the optimization and adjustment of social structure and promoting the formation of the new competitive structures, such as people-centered approach, lifelong learning and interaction between the individual values and corporate values. We sum up this new concept as a new concept of international competitiveness in the twenty-first century. In Industrial Development Report 2002/2003, the United Nations Industrial Development Organization (UNIDO) published the evaluation results of the international competitiveness of industries in various countries and regions in the world, which is an important result of the measurement of the international competitiveness of China’s industries. China ranked 37th in the world, compared with the 61st place in 1985, it has increased 24 international competition places. In order to evaluate

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the international competitiveness of industry, UNIDO has selected four indicators to measure the industrial operation and production competitiveness, which were the per capita added value of manufacturing, the per capita export volume of finished products, the proportion of medium and high-tech products, and the proportion of medium and high-grade technical products in the export products. In addition, UNIDO used infrastructure as a fifth indicator to measure the internal and external drivers of infrastructure to support industry. Finally, an overall assessment, that is, an evaluation score, was used to indicate the overall level of international competitiveness of industry in each country or region. This kind of analytical research lead us to develop the econometric model in the study of China’s industrial competitiveness, which reflected the high-end level of a country’s industry to participate in international competition. However, the study on the international competitiveness of industry of UNIDO also had a relatively large gap, that is to ignore the influence of international investment on international capital flows. Our relevant research has completely changed the phenomenon that the theoretical coverage of industrial competitiveness is relatively insufficient. Professor Michael E. Porter’s theory of Industrial Competitiveness at Harvard University, has had a significant international impact. His famous trilogy: Competitive Strategy (1980), Competitive Advantage (1985) and The Competitive Advantage of Nations (1990) put forward a series of comprehensive methods and techniques of competitive analysis with creative thinking, which provided a relatively complete knowledge framework for understanding competitive behaviors and guiding competitive actions. He believes that the key to industrial competitiveness lies in whether the country can effectively form a competitive environment and promote the development of innovation. The competitive environment he said has a wide range of connotations, including the combination of factors such as factor conditions, demand conditions, relevant and supporting industries, enterprise strategies, structure and competition situation, as well as government and opportunities. Porter also emphasizes the role of industrial clusters, and points out that of the industrial clusters formed by the geographical concentration of interrelated enterprises, specialized suppliers, service providers, related enterprises and institutions (such as universities and authoritative trade institutions) can produce efficiency and other advantages, promote industrial innovation, so as to enhance the competitiveness of the industry. No matter how competitive a country or region is, it is impossible to achieve success in all industrial fields, but it can obtain competitive advantages in certain industrial clusters. In The Competitive Advantage of Nations, Porter also used his “diamond” method system to study the history of development and participation in international competition for specific industries in many countries. He also proposed the theory of international competition stage of industry, that is, the process of a country’s industry participating in international competition can be roughly divided into four progressive (turnback may also occur) stages: the first stage is factor-driven stage, the second is investmentdriven stage, the third is innovation-driven stage, and the fourth stage is wealth-driven stage. In these four stages, the first three stages are the rising period of industrial

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international competitiveness, and the fourth stage is the declining period of industrial international competitiveness. In 1993, British economist J. Dunning supplemented and revised Porter’s “diamond model”. In his opinion, while the technology and organization of transnational corporations are affected by “national diamond”, transnational corporations will also have an impact on the competitiveness of national resources and productivity, and Porter ignored this relationship between transnational corporations and “diamond”. Taking into account the impact of the nature of transnational corporations’ activities on the four elements of “diamond” of national competitiveness, Dunning introduced “business activities of transnational corporations” into Porter’s “diamond model” as a parallel factor with “opportunity” and “government”, forming a more perfect “Porter-Dunning Model”. On the basis of this model, some scholars have conducted empirical studies on the determinants of international competitiveness of industries in combination with specific national cases (Rugman and D’Cruz 1993; Hekitts 1993; Liu and Song 1997). Research Center for Competitiveness and Evaluation of Renmin University of China has made many research achievements in international competitiveness and industrial competitiveness. Report on the Development of China’s International Competitiveness (1996), Report on the Development of China’s International Competitiveness (1997): Thematic Study on Industrial Structure, Report on the Development of China’s International Competitiveness (1999): Thematic Study on the International Competitiveness of Science and Technology, China International Competitiveness Development Report (2001): A Study of Development Themes for the 21st Century, China International Competitiveness Development Report (2003): Thematic Study on Regional Competitiveness (published by China Renmin University Press, 1997, 1998, 1999, 2001, 2003). It comprehensively develops the systematic application of theories, methods, models and empirical analysis and countermeasure research of international competitiveness in China. In theory, this paper proposes to use the trinity model of core competitiveness, basic competitiveness and environmental competitiveness to understand China’s international competitiveness and industrial competitiveness. Because China is in the process of transformation from planned economy to market economy, the competitive structure is relatively loose, competitive resources flow problems such as energy shortage, they cause the competitiveness based on cumulative fatigue. Therefore, China’s industrial competitiveness need to system design and all-round advance strategic support. The research center also provide advisory reports which about the international competitiveness and industrial competitiveness for National Development and Reform Commission, National Bureau of Statistics of China, China Development Bank, former State Economic and Trade Commission, the Western Region Development Leading Group of the State Council, the People’s Government of Beijing Municipality, Xiamen Municipal People’s Government, the People’s Government of Dongguan, the People’s Government of Nanhai, Nanyang Municipal People’s Government, People’s Government of Guangxi Zhuang Autonomous Region, Zhongguancun Science Park, Dongpeng Group Limited. From 1999 to 2003, Renmin University of China published 10 doctoral theses, one postdoctoral research report and dozens of master’s theses on international competitiveness and industrial competitiveness.

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On the evaluation of China’s industrial competitiveness, Professor Zhao Yanyun proposed the establishment of China’s industrial competitiveness information platform, and the evaluation index proposed the theory and method of symmetry design to solve the objective situation of China’s industrial competitiveness relative information standard confusion and severe information asymmetry. To improve the competitiveness of Chinese industry, we must implement it in stages, adapt to the market economic environment, establish the basic information of competitiveness and apply it scientifically. In 2003, Research Center for Competitiveness and Evaluation of Renmin University of China, respectively, published Evaluation Report on Competitiveness of Service Industry in China’s 31 Provinces, autonomous regions and municipalities, Evaluation Report on the Competitiveness of Manufacturing Industries in China’s 31 Provinces, autonomous regions and municipalities, Evaluation Report on Competitiveness of Service Industry in China’s 31 Provinces, autonomous regions and municipalities, Evaluation Report on the Competitiveness of Tourism in China’s 31 Provinces, autonomous regions and municipalities, established the evaluation system of industrial competitiveness in China, analyzed the advantage and disadvantage of competitiveness for different industry and the development of regional industry competitiveness gradient, and studied the related development countermeasures and suggestions. Professor Ren Ruo’en of Beihang University uses purchasing power parity (PPP) to analyze the international competitiveness of China’s manufacturing industry based on total factor productivity, unit labor cost, relative price level and fixed market share. He believes that the comparative advantage of China’s manufacturing products comes from cheap labor cost, and the way to maintain the international competitiveness of China’s product cost is to improve labor productivity. Although total factor productivity (TFP) is an indispensable part of competitiveness research, there are many controversies about PPP which is the basic segment. Jin Bei, a researcher of Chinese Academy of Social Sciences, established a causal analysis framework of industrial competitiveness including display index (the market share of a country’s industrial products), direct factor index and indirect factor index. Porter’s “diamond model” points out that there are broad economic links between the elements of competitiveness. Moreover, the competitiveness of the manufacturing industry of a country (region) is shown as its market share. The continuous upgrading and deepening of industrial technology level actually is the fundamental guarantee for a country (region) manufacturing industry to continuously improve its competitiveness and expand its market share. Therefore, this book will examine China’s industrial competitiveness and its determinants from a multi-dimensional and multi-perspective perspective.

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1.3 Basic Theory of the Research on China’s Industrial Competitiveness A basic view of the China’s industrial competitiveness research is that release pressure and improve adaptability is to enhance competitiveness under the background of market economy and globalization. The basic point of competitiveness is to establish the competitive information standard among competitors, so as to measure and compare the competitiveness among competitors, find out the competitive advantages and disadvantages, and accordingly formulate positive competitiveness improvement strategies and management measures to comprehensively improve their competitiveness. Industrial competitiveness or enterprise competitiveness is to pursue the sustainable development of comprehensive competitiveness, and to go after the unfailing and unique core competitiveness. The theory of China’s industrial competitiveness should be the most effective tool for the government to supervise industries, promote innovation, improve basic systems and regulations in China’s market economy, and also the fundamental means to deal with the relationship between the government and enterprises, scientifically mobilize competitive resources, and accelerate comprehensive innovation.

1.3.1 The Relationship Between National Competitiveness, Industrial Competitiveness and Enterprise Competitiveness As far as the subject management task of economic and social development is concerned, the concept of competitiveness can be applied to national competitiveness, industrial competitiveness and enterprise competitiveness. National competitiveness is ultimately determined by the industrial competitiveness and enterprise competitiveness of a country or region. The target national competitiveness realizes include the target of enterprise competitiveness and industrial competitiveness, such as technological innovation and the ability to create value. And the national competitiveness, of course, also have their own independent content of government competitiveness and competitiveness based on the market economy foundation, which has a direct effect for gathering competitive resources abroad. National competitiveness, industrial competitiveness and enterprise competitiveness are mutually supportive, mutually promoting and jointly realized. The improvement of national competitiveness is to create the foundation, competition and regulatory environment for the improvement of enterprises and industrial competitiveness and promote the comprehensive coordinated development of key points through the improvement of these competitiveness elements. In turn, industrial competitiveness and enterprise competitiveness should make full use of the national competitiveness to create the environment, basis and conditions, gather competitive energy, to achieve optimal sustainable development, in addition to improving their own internal system competitiveness.

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Many developed countries and regions actively promote the wide application of international competitiveness, and recognize the evaluation of national competitiveness and the positioning of national competitiveness by the WEF and IMD. The WEF emphasizes the evaluation of a country’s (or region’s) competitiveness through a comprehensive measure of government policies and systems supporting a country’s or region’s economic growth or development. On the way, they developed a macro label evaluation method, which establish a relatively unified evaluation index and competitiveness index for 105 world’s major countries and regions. And among these indexes, the most comprehensive competitiveness is national competitiveness index and growth competitiveness index, sub-indexes including technology innovation competitiveness index, public institutions and management competitiveness index, the macroeconomic environment competitiveness index, and 11 competitiveness indexes of the elements of content. They emphasized that national competitiveness is no longer the content of the world share of international trade in products, but the comprehensive competitiveness based on the investment environment and growth potential. Evaluation system of national competitiveness designed by IMD emphasis that do not put the national competitiveness as the stock of wealth, for which national competitiveness is not only a country’s economic strength. And the economic efficiency and the comprehensive ability of sustainable development expressed by a country is important, including the investment, enterprise research and development (R&D) of economic activity and investment attraction, and contains the original competitiveness of potential energy. At present, the implementation of the concept of national competitiveness is basically a direct evaluation at the national macro level and does not involve the specific content of the internal structure of industrial competitiveness and enterprise competitiveness. In this sense, the practice of Britain and other countries is to divide national competitiveness and industrial competitiveness into two closely related levels for evaluation and research respectively. National competitiveness needs to explain the development problems and challenges in the next 5–10 years. Industrial competitiveness evaluates and analyzes issues of development, policy and international competition for the enterprise group mainly. In a word, it stands in the industry group to seek fair competition environment and conditions for enterprises. Industrial competitiveness is the main tool for industry associations to contact the government and require the government to create positive conditions. It is a set of standard competitiveness information, which establishes a good communication channel and platform for the coordination of the development relationship between enterprises, industry and finance, education, basic research, and the government’s policy making. For example, the breakfast meeting between the British prime minister and entrepreneurs will be attended by five entrepreneurs each time and each one will talk about one aspect, so as to increase the prime minister’s direct understanding of the competitiveness of enterprises. Industry competitiveness should consider the specific stage of development and resources conditions, as well as the economic reform and development, both the above three aspects of the service and the basic principles of communication to established a set of standard competitive information and gradually develop into the

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industry competitiveness of application platform by using modern scientific statistics evaluation method based on the reality of country. And it should be done by the relevant government departments. A specific industrial competitiveness is determined by the factors at the level of industrial development strategy, industrial value chain and regional cluster, and the specific competitiveness at these levels is reflected in the competitiveness of different types of groups of enterprises or companies. The development of the international competitiveness of the world’s leading multinational companies is generally concentrated in 2–3 large companies. They are open, globalized and have the power to lead the development of the competitiveness structure of emerging enterprises, which determines the development of the strategic level of industrial competitiveness and the formation of enterprise competitiveness. Enterprise competitiveness is a concept based on building the capacity for sustainable development of a specific enterprise. Due to different industries, different stages of national development, different market economy basis, and differences in competitive advantages of enterprises, the understanding of the content of enterprise competitiveness are different. The most influential theory of corporate competitiveness in the world is the diamond model developed by Professor Michael E. Porter from Harvard University. For the enterprise competitiveness, there is a common point, that is, the enterprise’s sustainable development and the comprehensive ability to obtain increasing profits and added value to illustrate the level of enterprise competitiveness. The corresponding characteristics of enterprise competitiveness are the continuous improvement of comprehensive factor productivity, and the continuous improvement of the quality and price ratio of products or services. Therefore, compared with all competitors, enterprises have obvious competitive advantages and potential for sustainable development.

1.3.2 Competitive Structure The key to design competitiveness is to use the theory of market economy and statistical analysis method to find the key aspects and determinants of competitiveness improvement. The Porter’s model of competitiveness once used the metaphor of diamond to illustrate the structure of competitiveness. According to more than 10 years of in-depth interviews and research on world leading multinational companies conducted by Professor Peter Nolan of Cambridge University, six aspects of competitiveness structure of large international competitive enterprises have been accumulated, namely (1) brand and marketing capability; (2) innovative capability in R&D; (3) human resource aggregation and utilization ability; (4) procurement supply chain capability; (5) fund raising and application ability; (6) the ability of system integration and adaptation to changes. Professor Sutton of the London School of Economics believes that the competitiveness of enterprises depends on the comprehensive factor productivity and the price/quality ratio of products or services. The two key factors that affect these two aspects constitute the basic structure of

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enterprise competitiveness. Enterprise competitiveness is the foundation of industrial competitiveness structure. The structure of British industrial competitiveness mainly considers industrial investment and information communication technology competitiveness, industrial research and development and innovation competitiveness, industrial human resource competitiveness, enterprise competitiveness and market competitiveness. As the basis, background and environmental analysis of industrial competitiveness, Britain also establishes national competitiveness on the basis of industrial competitiveness. The main competitiveness structure includes macroeconomic stability, competitive environment, labor market, institutional organization and political environment, and quality of life. The WEF evaluates that there is more comprehensive competitive structure for international competitiveness. The main content which under the national competitiveness index is: the state’s overall operation, macroeconomic environment, technological innovation and diffusion, information and communication technology, infrastructure, national policies and regulations, government waste, the domestic competitiveness, regional cluster development, operations and strategy, environmental policies. The IMD national competitiveness is closer to the industry competitiveness and the competitiveness of enterprises competition environment, the foundation and condition analysis, and attaches great importance to the impact on the level of regional competitiveness. The competitiveness of national competitiveness structure is: the economic strength, government efficiency, business efficiency and infrastructure and government. Under the four elements, they design 20 aspects which reflect the competitive structure to describe competitive growth and change. IMD has the relative maturity of the method. Renmin University of China has been following up the study of the international competitiveness assessment system of WEF and IMD since its initial entry in 1993 and its formal entry in 1994. Up to now, there are many research results on the theory, method and analytical application of competitiveness. Professor Zhao Yanyun proposed to measure China’s national competitiveness with core competitiveness, basic competitiveness and environmental competitiveness, which is more suitable for the environment and conditions of developing countries of China and more conducive to analyze our advantages and disadvantages with international competitors. Under the competitive structure of core, foundation and environment, the in-depth analysis of the eight elements is more important for China’s reform and coordinated development. These eight elements are economic strength, internationalization, government management, financial system, infrastructure, science and technology, enterprise management and well-rounded development of all our people. In this book, we have studied the competitiveness of China’s manufacturing industry, including the evaluation and analysis of industrial competitiveness, the evaluation and analysis of regional industrial cluster competitiveness, and the competitiveness information and analysis of enterprise competitiveness in specific industries, and discussed the design and application of industrial competitiveness structure.

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1.3.3 Competitive Resources Competitive resource is one of the core concepts that we use competitive power today. The means nature of competitiveness is to establish a competitive information platform with the nature of systematic benchmarking. From an ideological point of view, competitiveness is mainly aimed at the objective activity system of investigation, discovering and establishing the competitiveness goal that can dominate the overall situation, discovering the key aspects and determinants of competitiveness through the competitiveness goal, that is, discovering the competitiveness structure, and then analyzing the advantages and disadvantages of competitiveness through the actual competitiveness data and information, so as to maintain the competitive advantage. Improving competitive disadvantage means pursuing the transformation of the intrinsic potential of competitiveness into reality. From the external perspective, the concentrated performance of competitiveness improvement is to gather competitive resources, support internal competitive resources fission to produce huge energy, promote sustainable, coordinated and high-quality development. Today’s competitive resources are no longer limited to natural resources, material conditions and capital strength. According to the analysis of the WEF and IMD, which has been tracking the changes of major countries and regions in the world for decades, today’s successful countries and regions, such as Singapore, Finland and Ireland, are all soft competitive resources that play an important role. Competitive hard resources can be viewed as the resources in the traditional sense, including natural resources, productivity material resources and capital resources, competitive soft resources including the soft resources, such as the government created by the system and rules, policies and supervision, opening and cultural influence, etc., and it also includes the soft environment for human resources development, research and development and soft environment which technology innovation transform, wellrounded development of all our people and living standard improvement of soft environment, etc. Today’s national competitive resources are characterized by various new combinations of hard and soft resources, such as the people-oriented and lifelong learning competitive resource system, the competitive resource system of government management and efficiency improvement, and the competitive resource system of productivity and sustainable development of economy, society and environment. The most important way for developing countries to catch up with developed countries is to develop government competitive resources first, then a people-oriented and lifelong learning competitive resource system, and a competitive resource system for the sustainable development of productivity and economy, society and environment. Industrial competitive resources should be more determined from a specific industrial development strategy level of competitive factors, upstream and downstream products or services industry value chain level of factors and regional cluster level of factors to understand the hard and soft resources. On the other hand, we can also understand the content of competitive resources from the core, basic and environmental resources. Specific content include core competitiveness resources created

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by determination of a specific industry core technology and core knowledge, the infrastructure including transportation, energy, water resources, basic facilities and modern information infrastructure, and the competitiveness of the basic resources, such as environment facilities system, regulations, policies, culture, values and the competitiveness of the environment resources. The purpose of our understanding of competitive resources is to tap into our current connotation of competitive resources, so as to coordinate them and motivate them and transform potential into actual productivity. On the other hand, we need to gather external competitive resources, promote the fission of internal resources, and generate enormous energy for development. Of course, in this process, we also need to create new core competitiveness in accordance with the law of competitiveness, so that China’s industries can achieve greater development.

1.3.4 Industrial Agglomeration Regional Competitiveness “Globalization” and “localization” are a pair of contradictions dominating the world economic operation in the late twentieth century. “Globalization” emphasizes the global connection in the process of economic development. Localization, on the other hand, emphasizes the use of local characteristics and advantages to occupy the global market. The realistic tension between the two highlights the importance of “regional scale”. The regional core competitiveness is often manifested in the cluster industry with characteristics, so the regional competition is often equal to the competition among the cluster industries. Proceeding from such logic, the key to regional economic development is how to develop industrial agglomeration in the region (Wang 2001). Bergman and Feser (1999) pointed out that industrial agglomeration is not only a conceptual innovation in regional theories and methods, but also provides a new way to analyze the current situation and development trend of regional economy. One of the keys of regional development and planning is how to develop industrial agglomeration in the region. It has also become an important strategy for the region to cope with economic globalization competition. Undoubtedly, industrial agglomeration has become the basis of regional competitive advantage. The competitive advantage of industrial agglomeration can be summarized as cost advantage (to reduce the production cost, provides the productivity), innovation advantage (speed, strong innovation ability and innovation), large industry attractiveness and expansion ability, etc. We can achieve the improvement of whole area competition capabilities by these advantages into full play advantage of the integration of resources. SRI1 combines Porter’s concept of competitive advantage and industrial agglomeration to construct an overall framework of industrial development environment with competitive advantages: (1) excellent agglomeration industry; (2) good economic 1

SRI is an international planning organization with its headquarters at Stanford University in the United States.

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foundation; (3) a good living and working environment. It can be seen that industrial agglomeration is the basis for the development environment of industries with competitive advantages. By extending it to regional development, it can be pointed out that the key to regional competitiveness promotion lies in the cultivation of industrial clusters with competitive advantages and regional characteristics. Hill and Brennan (2000) pointed out in more detail that industrial agglomeration composed of core industries and their complete upstream and downstream industries often has competitive advantages, thus driving the development of regional economy and enhancing regional competitive advantages. Therefore, promoting the formation of industrial agglomeration in the region is the key to the development and timely promotion of regional competitiveness. The phenomenon of industrial agglomeration is studied from the perspective of statistical model, which on the one hand verifies the content of industrial agglomeration theory, and on the other hand enriches the study of industrial agglomeration. For the first time, we put industrial agglomeration effect into the framework of competitiveness, and studied industrial agglomeration effect from three aspects of production efficiency, innovation ability and industrial expansion ability. This empirical study on industrial agglomeration in China relying on the huge enterprise database of the national bureau of statistics has rich information and wide coverage, which is not involved in the existing research results on industrial agglomeration in China, and it is an innovation and breakthrough in this field.

Chapter 2

Research on China’s Industrial Competitiveness with Diamond Model

2.1 Theoretical System of Decisive Factors on China’s Industrial Competitiveness The diamond model of industrial competitiveness is an overall illustration of the key factors of a country or region’s industrial competitiveness and their interactions. For a specific country, the diamond model of industrial competitiveness may not be exactly the same, because it is affected by the degree of perfection of the market economy system and mechanism, as well as the level of economic development, government management, regional culture and other factors, which will make some key determinants different. We put forward the diamond model of China’s industrial competitiveness, which is the basic judgment of the relationships between China’s competitiveness and the key factors of competitiveness improvement in the realistic development stage by applying the theory of competitiveness. Compared with the developed market economy countries and regions, China has special situations in many aspects, such as the imperfect market economy system and mechanism, the loose relationship of competitiveness, the uncoordinated quality of competitiveness attached to competitiveness resources, especially the immature understanding of activity rationality on soft resource, all these problems we must consider when using competitiveness evaluation and analysing. From a practical point of view, industrial competitiveness is a system revelation of industrial activities including the advantages and disadvantages of the competitiveness in reality, as well as a wide range of potential forces of China’s industrial competitiveness. In the application direction, the diamond model of China’s industrial competitiveness should be based on the aspects of industry cluster, enterprise cluster, innovation support and resource allocation to provide a theoretical framework for the establishment of a three-dimensional application system of China’s manufacturing industry competitiveness. At the level of analysis, it is conducive to the establishment of an analysis system for the competitiveness of China’s manufacturing industry from the aspects of the evaluation system design of industrial competitiveness, competitiveness survey and data collation, competitiveness factor system © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_2

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analysis, competitive advantages and disadvantages research, and countermeasures research to improve industrial competitiveness. Therefore, the diamond model of China’s industrial competitiveness reveals the key factors and their systematic relationships in the theoretical model from the perspective of the core competitiveness, basic competitiveness and environmental competitiveness of the industry, and we can see Fig. 2.1 for details. From the perspective of the actual development of the industrial international competitiveness, the competition reflected in the core competitiveness is mainly cost competition and research and development (R&D) competition. Cost competition is a relatively traditional way, which is often mainly reflected in the mature stage and later stage of industrial cycle development, while the competition of R&D is mostly emerging industries, which is often the growth stage of industrial cycle development, reflecting high-level competition, such as high-tech industries. At present, most industries in China are in the stage of cost competition, and some industries begin to enter the competition of international cutting-edge R&D. China is in the transition from the potential system of planned economy to a perfect market economy system, and the reform and improvement of enterprise system also have a serious impact on industrial competitiveness. Therefore, in the core competitiveness of Chinese industry, in addition to cost control and enterprise research and development, there

Fig. 2.1 Diamond model of China’s industrial competitiveness

2.2 Models and Applications of Manufacturing Sector’s Competitiveness …

19

is also a another significant factor that is enterprise management innovation. This is a basic feature of China’s industrial competitiveness today. On the support of China’s industrial basic competitiveness to its core competitiveness, technological innovation is the main line. National basic research, the research and development of universities and research institutions and enterprise R&D form an organic whole under the competitive mechanism of market economy. The support of the financial system is the basis of improving the competitiveness of the main line of technological innovation mentioned above. The key of how the flow and allocation of financial resources can stimulate the development of industrial competitiveness and how to promote financial innovation and defuse risk is to form a virtuous circle with the improvement of industrial competitiveness. Infrastructure and human capital are the basic platforms for medium-term and long-term development of industrial competitiveness. China must work hard on the basis of industrial competitiveness in order to have a leap forward development of industrial competitiveness. Based on the support of China’s industrial environmental competitiveness for core competitiveness and basic competitiveness, including two fulcrum, competitive environment and government management. Market system, institutional innovation, laws and regulations, opening up and values are the key elements to explain the basic environment of China’s industrial competitiveness. The double impact of government management on industrial competitiveness is mainly reflected in the efficiency of central government management and local government management.

2.2 Models and Applications of Manufacturing Sector’s Competitiveness of China After more than 40 years of reform and opening up, China’s manufacturing industry has made great progress, and some products are obviously competitive in the international market. Each regional manufacturing industry in China, however, the haphazard investment and repeated construction, cause that the resources of industrial competitiveness are extremely scattered and the technical levels linger about low level, the financial resources hard to cycle, land and other resources overuse. It indicates that we don’t have effective theory and policy in the manufacturing industry competitiveness. The reason is related to the serious asymmetry of information, the lack of empirical analysis, the unclear competition rules and the bad foundation of self-reliance.

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2.2.1 The Factor Variables of Competitiveness Analysis of China’s Manufacturing Industry The statistical model analysis system of China’s manufacturing competitiveness and its determinants can be established by referring to the relevant theories and empirical experience of the international frontier and combining with the characteristics of the development stage of China’s industrial competitiveness. The study highlights two measures, one is the direct measure of the competitiveness of China’s manufacturing industry, including five variables; the other is the measurement of the key factors determining or driving the development of China’s manufacturing industry competitiveness, including five variables. The empirical analysis of the model is to explain the various aspects and overall changes of the competitiveness of China’s manufacturing industry with the key factors that determine or drive it, so as to find out the basic characteristics and laws of the upgrading and development of China’s manufacturing industry competitiveness at the present stage.

2.2.1.1

Measurement Variable (or Measurement Index) of China’s Manufacturing Competitiveness

The reflection or direct measurement of the competitiveness of manufacturing industry is mainly based on the direct result or competitiveness level of the development of the competition in the manufacturing industry. In a certain sense, it deeply reflects the ability of the industry to create value and the strength level of external market competition, which is specifically reflected in the following important index variables. – Manufacturing labor productivity. Unlike per capita added value of manufacturing which UNIDO use to reflect competitiveness of manufacturing, the denominator of this study is not the total population of the region, but the number of personnel in manufacturing activities, that is, excluding the personnel of enterprises that have nothing to do with manufacturing activities. And it can more objectively reflect the regional competitiveness of manufacturing process of creativity. – Per capita manufacturing exports. It is a measure index reflecting the high-end market competition of manufacturing competitiveness based on international trade flows. In this respect it usually employed relative comparative advantage index (RCA). In view of the various provinces and cities in our country manufacturing exports and RCA index per capita present highly positive correlation (r = 0.958), the research chooses workers, the average manufacturing exports as a measure of our country’s manufacturing industry competitiveness of provinces and cities. – The content of high-tech products in manufacturing industry and the content of high-tech products exported by regional manufacturing industry. In order to reflect the conditions of the various provinces and cities in China’s manufacturing technology level and industrial upgrading, we put the measures which reflect the structure of regional manufacturing competitiveness into the category of analysis.

2.2 Models and Applications of Manufacturing Sector’s Competitiveness …

21

In view of there are not significant differences between the various provinces and cities in our country with senior technical product, in order to improve the sensitivity of the model, the content of high-tech products in regional manufacturing industry and the content of high-tech products exported by regional manufacturing industry are constructed as the measurement indexes of the technological structure of China’s regional manufacturing industry competitiveness. In order to comprehensively reflect the competitiveness level of the manufacturing industry in the region, the manufacturing competitiveness index is built on the basis of the above four indicators. The index construction process is as follows: The first step is to test the rationality of the construction of manufacturing competitiveness index. The above four competitive measures (manufacturing labor productivity, per capita manufacturing exports, the content of manufacturing high technology products and the content of regional manufacturing export high-tech products) show significant positive correlation. It shows that we can construct the competitiveness index of manufacturing industry to reflect the overall competitiveness level of regional manufacturing industry. The second step is to test the probability distribution of the above competitiveness indicators (approximately obeys the uniform distribution), and select the following formula for standardization. yi =

yi − min(yi ) max(yi ) − min(yi )

(2.1)

The third step is to construct the manufacturing competitiveness index. y=(

w1 y1α + w2 y2α + w3 y3α + w4 y4α 1 )α w1 + w2 + w3 + w4

(2.2)

where wi is the weight of each index, and α is the elasticity coefficient of each competitiveness measure index to the manufacturing competitiveness index. Determine wi = 1 by stability test (assign different values to w to ensure that the weight does not affect the index ranking), and further simplify to α = 1. Therefore, 1  y 4 i=1 i 4

y=

2.2.1.2

(2.3)

The Measurement Index of the Determinants of China’s Manufacturing Competitiveness

The change of the regional competitiveness of manufacturing industry in our country is mainly influenced by four aspects: one is the ability to gather investment resources, the second is the technological innovation efforts of regional manufacturing industry,

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and the third is the production factors of regional manufacturing industry, including the total amount, quality, level and cost of labor, capital and natural resources, the forth is the intensity of industrial competition in the region. The aggregation ability index of regional investment resources is: FDI input intensity. As the country with the largest inflow of foreign direct investment in developing country, we shouldn’t underestimate the role of foreign direct investment in the process of improving the competitiveness of manufacturing industry. The FDI input intensity (using the output value of manufacturing sales in various provinces and cities to adjust) was taken as an exogenous variable and introduced into the model of manufacturing competitiveness. The index of regional technology innovation effort is: intensity of R&D input. Cultivating their own core technology through their own technological innovation efforts is the effective way to improve overall level of China’s manufacturing competitiveness. In this study, the R&D expenditure of manufacturing enterprises in each province and cities was adopted to reflect the technical efforts within the manufacturing industry in each province. Indicators of productive factors in the region are: unit labor cost (price factor) and labor skill (non-price factor). Due to the dependence of manufacturing development on natural resources is decreasing, so the natural resources should not be brought into the analysis. The focuses on regional production factors are mainly on the conditions of the human capital of provinces and cities, including the factors of price (cost)— unit labor costs, as well as non-price factors (quality)—labor skills (proportion of middle and senior professional and technical personnel). The index of industry competition intensity in the region is: the concentration degree of manufacturing industry. The biggest correlative factor of creating and sustaining industrial competitive advantage is intense and extensive competition. In this study, industry concentration ratio (CR4—the market share of the first four enterprises in each small category of manufacturing industry) is selected as the measurement index of competition in each province and city. It comprehensively reflects the number and scale of enterprises, which are two important aspects that determine the market competition.

2.2.2 China’s Manufacturing Industry Competitiveness Model Based on the above theoretical framework and the international analytical mode, the following model is established: Yit = αi + β1 X 1it + β2 X 2it + β3 X 3it + β4 X 4it + β5 X 5it + eit

(2.4)

2.2 Models and Applications of Manufacturing Sector’s Competitiveness …

23

In the model: Yit is the measure index value of manufacturing competitiveness in the i province in the period t (respectively manufacturing competitiveness index, manufacturing labor productivity, per capita manufacturing exports, content of high-tech products in manufacturing products and content of high-tech products in manufacturing exports). X 1it is FDI intensity index of manufacturing industry in the province i in the period t. X 2it is R&D intensity index of manufacturing industry in the province i in the period t. X 3it is the manufacturing industry concentration index (CR4) in the province i in the period t. X 4it is the manufacturing labor skill indicators in the province i in the period t. X 5it is the manufacturing labor cost indicators in the province i in the period t. On the basis of “the spatiotemporal data” of manufacturing industry from 2000 to 2002 in 31 provinces, autonomous regions and municipalities, and in order to excavate the potential of data effectively, this book uses Panel Data model, which is suitable for multiple section individuals of different time observe the multidimensional time series data in a row. And it is able to reflect the variation rules of research object at the same time in time and cross section of both directions and characteristics of different times and different unit, analyze the mutual relationship between variables and predict its change tendency. In addition, it can make comprehensive use of the sample information to further the study and reduce the impact of multicollinearity. There are various basic types of Panel Data model. According to the analysis needs, we choose the current variable intercept model for equation fitting, and its basic form is: 

yit = αi + β xit + eit i = 1, · · · , N ; t = 1, · · · , T

(2.5)

In this model, the individual period constant αi represents the individual characteristics of the section unit, reflecting the influence of the omitted individual difference variables in the model, while the individual period variable ei represents the influence of the factors omitted that embodiment changes simultaneously with the cross section and time sequence. Before determining the specific form of the model, the cross-section effect and timing effect should be tested first. The test results are as shown in Table 2.1. At the significance level of 5%, it can be considered that there is no time difference in the sample data. When building the panel data model, only section (province, autonomous regions and municipalities) effect can be considered. The one-way fixed effects model and the one-way random effects model containing only the cross-section effect are established as follows: One-way fixed effects model:

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Table 2.1 F-test of cross-section effect and timing effect of China’s manufacturing competitiveness model Null hypothesis Prov intercept

λt = 0 t = 1, · · · , 3

Test statistic 18.09

F statistic distribution

P-value

F29,55

m} = 0.0378

Note (1) *, ** and *** represent the significance levels of 10%, 5% and 1% respectively. (2) In the process of model estimation, both the inverse index industrial concentration and labor cost are processed. (3) Hausman test: H0 : E(vi |xi ) = 0, the random effect model is a better estimation model under the original hypothesis. According to the Hausman test results, at the significance level of 1%, except for the technical structure model of manufacturing products, other models can be estimated using the one-way random effects model

From the Panel Data model estimation results, it can be seen that: (1) In the manufacturing competitiveness index model (see Table 2.6a), Hausman test shows that the random effect model is more appropriate. At the significance level of 1%, FDI input intensity and labor cost indicators passed the test, which to a certain extent reflects China’s current manufacturing industry’s hunger for capital and sensitivity to labor factors. y = 0.5x1 + 0.1008x2 + 0.2525x3 + 0.0685x4 + 0.2001x5 (5.96)

R = 0.687 2

(2.43)

(3.34)

m = 11.82

(1.84)

(3.92)

(2.8)

Model (2.8) verifies the driving effect of all determinants on the improvement of China’s manufacturing competitiveness. The elasticity coefficient of each driving factor on China’s manufacturing competitiveness index (elasticity coefficient = standardized coefficient × (dependent variable coefficient/explanatory variable coefficient)) is 0.2945, 0.093, 0.572, 0.1367 and 0.5806, respectively. As a result, the influencing structure of China’s manufacturing competitiveness is (in the order of influence) labor cost, industrial concentration, foreign direct investment, labor skills and enterprise R&D investment. (2) In the manufacturing labor productivity model (see Table 2.6b), Hausman test shows that the random effect model is more appropriate. At the significance level of 1%, the indicators of R&D input intensity and labor cost passed the test, the significance level was expanded to 5%, and the FDI input intensity index passed the test. If the significance level was 10%, the labor skill also showed a significant impact on the competitiveness of manufacturing industry.

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y1 = 0.2987x1 + 0.2627x2 + 0.0533x3 + 0.2195x4 + 0.5611x5 (2.19)

R = 0.6986 2

(2.32)

(1.48)

(1.67)

(6.28)

m = 13.73

(2.9)

Model (2.9) shows that except for the industrial concentration index, other driving factors all have a significant impact on the labor productivity of China’s manufacturing industry, and the elasticity coefficients are 0.0711, 0.098, 0.1771 and 0.6583, respectively. The order of influence is labor cost, labor skill, enterprise R&D investment and foreign direct investment. (3) In the per capita manufacturing export value model (see Table 2.6c), Hausman test shows that the random effect model is more appropriate. At the significance level of 1%, FDI input intensity index and industrial concentration index passed the test. If the significance level is 10%, labor cost also has a significant impact on it. y2 = 0.5599x1 + 0.0315x2 + 0.2607x3 + 0.0141x4 + 0.081x5 (7.19)

R 2 = 0.5688

(1.05)

(3.19)

(0.67)

(1.95)

m = 7.65

(2.10)

According to the statistical test, the elasticity coefficients of driving factors on the per capita manufacturing exports are 0.5105, 0.9144 and 0.3639 respectively. The competitiveness driving factors of the per capita manufacturing exports are industrial concentration, foreign direct investment and labor cost in the order of influence. (4) The Hausman test shows that the fixed effect model is more suitable for the hightech product content in the technical structure model of the whole manufacturing industry (see Table 2.6d). At a significance level of 5%, only the workforce skills index passed the test. y3 = −0.2967 + 0.0458x1 + 0.0046x2 + 0.1041x3 + 0.1382x4 + 0.0406x5 (−3.18)

R = 0.9921 2

(1.02)

(1.17)

(0.95)

(2.76)

(1.29)

m = 22.65 (2.11)

Model (2.11) shows that coefficient of labor skill on content of technology product in manufacturing is 0.2036, namely when labor skill increases 1%, the content of high technology products in manufacturing will raise 0.2036%. Therefore, it can be seen that the improvement of the overall technical level of China’s manufacturing industry largely depends on the improvement of the quality of China’s manufacturing workforce. (5) The model of the content of high-tech products in regional manufacturing exports that is, the technical structure of manufacturing exports (see Table 2.6e). Hausman test shows that the random effect model is more appropriate. Foreign direct investment and labor skill indicators passed the test at a significance level of 5%. The significance level was increased to 10%, and the industrial

2.3 Problems of Manufacturing Sector’s Competitiveness of China

31

concentration index also had a significant impact on the technical structure of manufacturing export. y4 = 0.3938x1 + 0.0807x2 + 0.1967x3 + 0.1971x4 + 0.0248x5 (3.13)

R = 0.532 2

(1.29)

(1.74)

(2.61)

(0.32)

m = 11.79

(2.12)

Model (2.12) shows that the elasticity coefficients of the driving factors through statistical test on the content of high-tech products exported by China’s manufacturing industry are respectively 0.237, 0.4554 and 0.402. The competitiveness driving factor structure of the content of high-tech products in manufacturing export is industrial concentration, labor skill and foreign direct investment index.

2.3 Problems of Manufacturing Sector’s Competitiveness of China The previous model analysis shows that there are some serious problems in the competitiveness of China’s manufacturing industry. (1) The overall model analysis of the competitiveness of China’s manufacturing industry shows that labor cost (elasticity coefficient is 0.5806), industrial concentration (0.572), foreign direct investment (0.2945), labor skill (0.1367) and enterprise R&D investment (0.093) are the basic order of degree of effect. From the perspective of elasticity coefficient, labor cost and industrial concentration have the same effect, followed by foreign direct investment, but the role of the former is less than 50%, and the investment in enterprise research and development is weak. Therefore, it can be concluded that the current development of China’s manufacturing industry and the improvement of its industrial competitiveness are still dominated by cost competition and the expansion of primary production factors. While the developed market dominated by research and development competition. The driving force of China’s manufacturing core competitiveness is seriously insufficient. (2) The analysis of labor productivity in China’s manufacturing industry shows that the labor cost is the most prominent among the four major influencing factors of labor cost, labor skill, enterprise R&D input and foreign direct investment, and its elasticity coefficient is 0.6583, which is 3.7 times, 6.7 times and 9.2 times of labor skill, enterprise R&D input and foreign direct investment, respectively. China does not put the use of human capital, especially advanced human capital and the use of enterprise research and development to support technological innovation to enhance the competitiveness of enterprises on an important level. The degree to obtain technology from utilizing foreign capital and improve labor productivity is very weak, and industrial concentration has no effect on labor

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productivity, which indicates that many key factors in the improvement of labor productivity in China’s manufacturing industry are weak. (3) The model analysis of per capita manufacturing exports shows that, according to the order of effect, the order of the main driving factors for improving international competitiveness are industry concentration (elasticity coefficient is 0.9144), foreign direct investment (0.5105) and labor cost (0.3639) in the order of influence. The important role of industry concentration in the explanation of China’s manufacturing industry’s participation in international competition indicates the positive effect of market economic mechanism and the correctness of the growth direction of industrial competitiveness, that is, the international market competitiveness of the industry is not only increasing, but also its competitiveness is becoming more mature. The results of Model (2.10) show that foreign direct investment is the main influencing factor, but the technological efforts of enterprises themselves have no significant impact on it. This over-dependence on foreign investment affects the competitiveness structure, which is not conducive to the continuous improvement of China’s manufacturing competitiveness in the international market. (4) The analysis of high-tech product content model shows that the improvement of high-tech innovation ability in the development process of China’s manufacturing industry mainly depends on the improvement of labor skills. Model (2.11) shows that elasticity coefficient of labor skill and content of high-tech products in manufacturing is 0.2036, the 1% labor skills development of China’s hightech products can promote manufacturing innovation ability of 0.2036%, The improvement of the overall technical level of China’s manufacturing industry, to a large extent, depends on the improvement of the quality and skills of China’s manufacturing labor force. (5) Taking the content of high-tech products in the export of manufacturing industry as the model analysis of the international competitiveness of China’s manufacturing industry in scientific and technological innovation, it shows that industrial concentration (elasticity coefficient is 0.4554), labor skills (0.402) and foreign direct investment (0.237) constitute the main influencing factors. From the perspective that enterprise R&D variables and labor cost variables did not pass the test in Model (2.12), it shows that these two factors in promoting the international competitiveness of manufacturing industry innovation in science and technology is not yet play a role, suggests that China’s manufacturing enterprises technical efforts don’t have great effect on the improvement of international competitiveness of regional manufacturing innovation in science and technology. China is obviously in the production and assembly process of peripheral components in the “international division of production process”, and presents the characteristics of foreign capital-led.

2.4 Basic Strategies and Policies to Promote Regional Manufacturing …

33

2.4 Basic Strategies and Policies to Promote Regional Manufacturing Sector’s Competitiveness of China (1) The key to enhance the competitiveness of China’s manufacturing industry is to increase investment in research and development and enhance the ability of technological innovation. IMD World Competitiveness Yearbook 2002 shows that China ranks only 32nd among 49 countries in terms of research and development factors, and it is one of the countries with weak technological innovation ability. It requires that in the process of manufacturing competitiveness in China, (1) to enhance investment in national development, namely the increase of national funds for basic research and key research funding, enhance national platform for the technical innovation ability and level; (2) while strengthening the ability of utilizing foreign capital to transform and innovate, we should also pay attention to attracting foreign research and development funds to comprehensively enhance the regional innovation ability and international competitiveness of China’s manufacturing industry; (3) the most important thing is to encourage Chinese enterprises to increase investment in research and development, and change from giving priority to the cost-competitive-oriented to giving priority to the innovation-oriented of research and development, so as to improve the international competitiveness of Chinese manufacturing enterprises. (2) The labor condition is still the key factor to enhance the competitiveness of China’s manufacturing industry. Driven by the inevitable rise in labor costs, the current crucial task is to improve the skills of manufacturers in manufacturing enterprises and increase the proportion of senior skilled workers. Currently, China’s senior workers account for only 3.5%, which is far from the level of 40% in developed countries. However, the technical levels of the vast majority of young workers in China are not up to the standards of the existing technical level. On the one hand, it requires the state to attach importance to the improvement of vocational education system; on the other hand, it also requires enterprises to pay attention to employee training. (3) We should continue to increase the introduction of foreign direct investment, China is the developing country with the largest inflow of foreign direct investment. Foreign direct investment in China’s manufacturing industry has played an obvious role in the process of upgrading. In order to avoid falling into the global value chain and becoming only the production and supplier of labor-intensive products and peripheral components of high-tech products, it is necessary to selectively attract foreign capital with high technology content, at the same time to increase its own technical efforts and accelerate the learning process of advanced technology. (4) The model verifies the theoretical hypothesis that the degree of market competition in a country (region) is positively related to its industrial competitiveness. In order to effectively improve the regional industrial competition, cultivate the dynamic incentive innovation competition environment, we should pay attention

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to the construction of industrial cluster, through the formation of relatively intensive community in a certain geographic region, to speed up the velocity of propagation technology, improve the motive force of enterprises’ improvement and innovation, and ultimately achieve the goal of enhancing the competitiveness of China’s overall manufacturing industry.

Chapter 3

Research on China’s Industrial Cluster Competitiveness Cluster Competitiveness

3.1 Economic Model of China’s Industrial Cluster and Its Applied Studies Though discusses about industrial agglomeration economy have already aroused widespread concerns of foreign scholars, but for our country, the researches of this aspect are still relatively weak. Pan Youhong and Zhang Fan (2002) on the basis of firm-level information from the 3rd National Industrial Census of China in 1995, the agglomeration effect (urbanization economy) was estimated for 28 manufacturing two-digit industries in 200 major cities, using the three forms of the Cobb–Douglas production function, the CES production function, and the transcendental logarithmic production function. The results showed that 1 time the city scale, the industry’s productivity will be increased by 8.6%. Ji Yuhua et al. (2004) selected the Cobb– Douglas aggregate production function of two-digital variable to verify the impact of agglomeration effect (urbanization economy) on the productivity of industrial sectors. These two studies are mainly aimed at the urbanization economy, and do not effectively distinguish the impact of regional economy and urbanization economy on industrial labor production. Moreover, both studies used cross-sectional data, and the stability of the research needs to be investigated. Ji Yuhua’s research is aimed at the industrial sector as a whole, and the merger level is too high. Based on the data of manufacturing enterprises in China from 2001 to 2003, this paper estimates agglomerative economies effects of 29 double-digit manufacturing industries in 236 prefecture-level cities in China. Its research features are as follows: 1. The panel data are used to estimate the two agglomeration economies of China’s manufacturing industry—regional economy and urbanization economy. The stabilities of the estimated results are also investigated. 2. The 29 double-digit manufacturing industries are divided into four categories— assembly manufacturing, basic raw material manufacturing, resource-dependent

© Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_3

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manufacturing and final consumer goods manufacturing. This paper respectively estimates the agglomeration economy of these four types of industries. 3. According to the population size, the 236 prefecture-level cities are divided into five categories—mega cities, super-large cities, large cities, medium-sized cities and small cities. And we also investigate the differences of agglomeration economy in cities of different sizes.

3.1.1 Design of Economic Measurement Model of Industrial Agglomeration Since industrial agglomerative economies effect is an external factor for enterprises, agglomerative economies effect can be obtained by multiplying the production function F (·) by the agglomeration factor g (·), that is Y = g(g)F(g)

(3.1)

Among them, Y represents the output of the enterprise; g(·) represents agglomerative economies effect as a converter of production function efficiency parameters of an enterprise. If the parameter in g(·) is a certain measurement of industrial scale within a regional scope, agglomerative economies effect is localization economies. If parameter in g(·) is a measure to overall economic activity in the region, agglomerative economies effect is urbanization economies.1 F(·) represents the production function of an enterprise, and it is often assumed that the return to scale is constant, which is a general model for measuring industrial agglomeration economy. It is generally assumed that the error term of Eq. (3.1) is the multiplier error term.

3.1.2 Economic Measurement Model of Industrial Agglomeration in China We used the Cobb–Douglas production function of two factors as the starting point for analysis: Y = g(g)F(K , L)

(3.2)

Among them, Y is the added value, K is the capital stock, L is the labor force, and g(g) is the conversion function of agglomeration economy. Under the assumption of constant return to scale, Eq. (3.2) can be rewritten as: Y /L = g(g)F(K /L) 1

(3.3)

Zhu Yingming, Theory of Industrial Agglomeration, Economic Science Press, 2003, pp. 59–60.

3.1 Economic Model of China’s Industrial Cluster and Its Applied Studies

37

Among them, Y /L is labor productivity and K /L is labor capital density. In this paper, the economic measurement parameters of industrial agglomeration in g(·) function are decomposed into: regionalization index (Loc) and urbanization index (Urb). Based on porter’s view on competition, this study introduces competition degree index (Comp). Logarithm transformation is applied to Eq. (3.3): log(Y /L)i j = α0 + α1 log(K /L)i j + α2 Ur b j + α3 Loci j + α4 Compi j + α5 Region j + εi j

(3.4)

Specific variables are explained as follows: (K /L)i j represents the capital density of industry i in region j, K is the net value of fixed assets, and L is the number of employees. The method to measure urbanization and regionalization presented by Henderson et al. (1995) was used as a reference in this study. ∑ Ur b j =

1/

1/

i ∑ i

si2j

2 sic

is the urbanization (diversification) index of region j, si j repre-

sents the sales share of manufacturing industry i in region j, and sic represents the sales share of industry i nationwide. The coefficient of Urb on labour productivity is positive if the urbanization economy exists. v /v Loci j = viicj /vcj is defined as the regionalization (specialization) index of manufacturing industry i in region j, vi j and vic represent the added value of manufacturing industry i in region j and the whole country, v j and vc represent the total added value of manufacturing industry in region j and the whole country. If the regionalized economy exists, the coefficient of Loc on labor productivity is positive. n /v Compi j = nici j /vici j is the competitiveness index, vi j and vic represent the added value of manufacturing industry i in region j and the whole country; n i j and n ic represent the number of employees of manufacturing industry i in region j and the whole country. Glaeser et al. (1992) believe that this indicator can well describe the competitive environment faced by enterprises. If the coefficient of Comp on labor productivity is positive, it indicates that the fierce competition in the same industry in the region is conducive to the improvement of production efficiency. Given that the marketization level difference in the eastern, central and western regions of China will lead to the difference in capital efficiency, Region i j , a dummy variable, is introduced in this study to control the productivity difference of the same capital in the three major economic regions.

3.1.3 Statistical Description and Analysis of Industrial Agglomeration Economy in China Before the regression analysis, we made a brief statistical description of the data first. Table 3.1 shows the five double-digit manufacturing industries with the highest

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index of regionalization, urbanization and competition. Among the 236 prefecturelevel cities, in terms of average levels, the industries with the highest degree of regionalization in turn are, tobacco processing industry, petroleum processing and coking industry, non ferrous metal smelting and rolling processing industry, wood processing and wood, bamboo, rattan, palm, grass products industry and beverage manufacturing industry, most of which are resource-dependent industries. The industrial environment of tobacco processing industry is also at a relatively high level of urbanization. Therefore, although regionalization and urbanization are two extreme forms of agglomeration economy, they are not mutually exclusive. And the regional industrial environment from which the industry emerges is relatively stable over time.

3.1.4 Application and Analysis of Industrial Agglomeration Economic Model in China Our applied research will examine the relationship between different types of agglomeration effects and industrial labor productivity, as well as the differences between agglomeration effects in different industries and cities of different sizes and their contributions to labor productivity. The Panel Data model can solve this problem well. Hausman test (χ 2 (5) = 74.57) rejects the Random effect model, and the estimated results of fixed effect model will be reported in this book.

3.1.4.1

The Overall Manufacturing Industry

We first used Model (3.4) for regression analysis of all industries, and Table 3.2 shows the actual analysis results of specific model estimation. Two control variables, factor input variable (ln(K /L)) and region characteristic (Region), are retained in all models. In the regression results (1.1)–(1.3), we successively add variables Loc, Urb and Comp that reflect the regionalization effect, urbanization effect and competition degree of agglomeration economy. Regression results (1.4)–(1.5) are the estimated results of the model with fixed effects and one-stage lag introducing all variables. As can be seen from the columns of Table 3.2 (1.1)–(1.5), the estimated results of the model are stable and credible, and the direction and significance of the coefficient of each variable maintain good stability. The results show that labor capital density (K /L) has a significant positive effect on labor productivity. When other conditions are the same, the economic effect of urbanization, that is, a diversified economic environment will help increase industrial labor productivity (see the columns [1.1], [1.4] and [1.5] of Table 3.2). The significant impact of this variable proves the importance of “inter-industry” externalities. This result shows that companies can benefit from the diversification of industries in the same city.

3.1 Economic Model of China’s Industrial Cluster and Its Applied Studies

39

Table 3.1 The industry with the highest degree of regionalization, urbanization and competition Item

Year 2003

Year 2002

Year 2001

Level of regionalization

Tobacco processing industry

Tobacco processing industry

Tobacco processing industry

Petroleum processing and coking industry

Nonferrous metal smelting and rolling processing industry

Nonferrous metal smelting and rolling processing industry

Nonferrous metal smelting and rolling processing industry

Petroleum processing and coking industry

Petroleum processing and coking industry

Wood processing and wood, bamboo, rattan, palm, grass products industry

Wood processing and wood, bamboo, rattan, palm, grass products industry

Wood processing and wood, bamboo, rattan, palm, grass products industry

Level of urbanization

Level of competition

Beverage manufacturing Chemical fiber industry manufacturing

Beverage manufacturing industry

Chemical fiber manufacturing industry

Chemical fiber manufacturing industry

Chemical fiber manufacturing industry

Culture, education and sports goods manufacturing industry

Culture, education and sports goods manufacturing industry

Culture, education and sports goods manufacturing industry

Tobacco processing industry

Tobacco processing industry

Tobacco processing industry

Electronic and telecommunication equipment manufacturing industry

Electronic and telecommunication equipment manufacturing industry

Electronic and telecommunication equipment manufacturing industry

Instrumentation and culture, office machinery manufacturing industry

Leather, fur, feather (down) and its products industry

Furniture manufacturing industry

Non-metallic mineral products industry

Non-metallic mineral products industry

Non-metallic mineral products industry

Food processing industry

Food processing industry

Food processing industry

Chemical raw materials and chemical products manufacturing industry

Chemical raw materials and chemical products manufacturing industry

Chemical raw materials and chemical products manufacturing industry

General machinery industry

Metal products industry General machinery industry

Textile industry

General machinery industry

Textile industry

40

3 Research on China’s Industrial Cluster Competitiveness

Table 3.2 Model estimates of the overall manufacturing industry Variable

(1.1) FE

(1.2) FE

(1.3) FE

(1.4) FE

(1.5) A phase lag FE

0.3837***

0.3839***

0.3774***

0.3808***

0.3872***

0.0066

0.0066

0.0066

0.0066

0.0081

0.4815***

0.4111***

0.0643

0.0778

0.0045*

0.0041*

Factor input ln (K/L) Agglomerating economy 0.7588***

Urb

0.062 0.0076***

Loc

0.0023 Comp

0.0023

0.0024

0.4158***

0.3673***

0.3296***

0.021

0.022

0.0267

Region characteristic Region Constant terms

0.1856***

0.2074***

0.1544***

0.1484***

0.1581***

0.0075

0.0074

0.0078

0.0079

0.0094

2.1409***

2.0655***

2.2789***

2.2812***

2.1669***

0.0269

0.0264

0.0281

0.0286

0.0347

R2

0.5156

0.5092

0.5263

0.4315

0.6402

Inter-group R2

0.7166

0.7148

0.4588

0.5097

0.5075

sample size

17,074

17,074

17,074

17,074

11,066

Intra-group

Note The value below the coefficient is the standard deviation, *** means significant at 1% level, ** means significant at 5% level, and * means significant at 10% level

Regional economic effect, that is, the specialization trend of industry in specific regions, is also conducive to the improvement of industrial labor productivity (see the columns [1.2)], [1.4] and [1.5] of Table 3.2). The significant effect of this variable proves the importance of externalities “between enterprises in the same industry”. In other words, when a certain industry occupies a larger share in the industrial structure of a specific area, the “transaction cost” between enterprises will drop significantly, which will help enterprises to increase their labor productivity. However, Cecile (2001) studied and showed that such externality only appears in the initial stage of industrial development, and when production and technology develop to a certain stage, production will migrate. The significant positive influence of regional industrial competition degree variable on industrial labor productivity indicates that the degree of competition has a significant promoting effect on the improvement of industrial production efficiency (see the columns [1.3], [1.4] and [1.5] of Table 3.2). Compare the impact of regionalization, urbanization and competition on industrial labor productivity, for the manufacturing industry as a whole, the economic effect of industrial development urbanization is the key link to improve industrial production

3.1 Economic Model of China’s Industrial Cluster and Its Applied Studies

41

Table 3.3 Classification of location characteristics of manufacturing 2-SIC industries Manufacturing classification

ISIC code Rev 3.1

GB/T 4754–2002 code

Assembly manufacturing industry

28–35

35–42

Basic raw material manufacturing industry

23, 24, 27, 37

25–28, 32–34

Resource-dependent manufacturing industry

15, 16, 20, 21, 26

13.16, 20, 22, 31

Final consumer goods manufacturing industry

17–19, 22, 25, 36

17–19, 23, 29, 30, 21, 24, 43

Note The assembly manufacturing industry is the so-called “foot loose industry” without obvious geographical restrictions manufacturing of basic raw materials is a heavy industry with high requirements for transportation facilities. Resource-dependent manufacturing industry is concentrated in the manufacturing of raw materials. The final consumer goods manufacturing industry is the industry in the consumer gathering place (city)

efficiency. When the industry is concentrated in a region with high industrial diversity, the resulting “mutual breeding” can often enable the industry to obtain higher production efficiency. Secondly, the competitive environment of industrial development is also the main factor affecting the improvement of industrial production effect. The clustering of industries with regional competition as the main feature in specific regions leads to the improvement of regional industrial production efficiency by stimulating technological innovation and information diffusion among enterprises. The regional effect of industrial agglomeration is relatively weak in promoting industrial productivity.

3.1.4.2

Industry Type

Agglomeration economy showed great differences between different industries, in this study to verify the agglomeration economy in the form of China’s manufacturing sector as a whole, after further inquiry agglomeration economy in double digits different types of manufacturing industry in China forms, between reference Kyoung-Hwie Mihn (2004) classification, according to the geographical feature of the industry, it will be divided into: assembly manufacturing, basic raw material manufacturing, resource-dependent manufacturing and final consumer goods manufacturing (see Table 3.3). The model estimation results of sub-industry types given in Table 3.4 show that the input factor variables, regional control variables and constant terms are basically consistent with the model estimation results of non-industry types (direction and significance). Like the empirical research results of other countries, agglomeration economy has certain differences among different types of industries. The degree of industrial competition in a specific region has shown a high degree of consistency for

0.0119

0.0181

3,706

Sample size 4,029

0.4652

0.5545

4,379

0.8122

0.5619

0.0598

2.0428***

0.0143

0.1457***

0.0481

0.2042***

0.0044

0.0182***

0.1149

0.8038***

0.0131

0.4368***

(2.3) Resource-dependent manufacturing industry

5,158

0.5688

0.4056

0.0480

2.3859***

0.0150

0.1265***

0.0387

0.4432***

0.0079

0.0015

0.1263

0.5604***

0.0118

0.3113***

(2.4) Final consumer goods manufacturing industry

Note The value below the coefficient is the standard deviation, *** means significant at 1% level, ** means significant at 5% level, and * means significant at 10% level

Intra-group

0.5240

0.0559

0.0762

0.6197

2.5346***

1.9484***

Inter-group R2

0.0162

0.0178

0.0451

0.0499 0.1394***

0.3820***

0.3202***

0.1954***

0.0031

0.0135

0.0038

0.1299

0.1487

0.0427

0.2946**

0.1610

***

0.3719***

(2.2) Basic raw material manufacturing industry

0.4345 ***

(2.1) Assembly manufacturing industry

R2

Constant terms

Region

Region characteristic

Comp

Loc

Urb

Agglomeration economy

ln (K/L)

Factor input

Variable

Table 3.4 Fixed effect model estimation results of different industry types

42 3 Research on China’s Industrial Cluster Competitiveness

3.1 Economic Model of China’s Industrial Cluster and Its Applied Studies

43

the improvement of production efficiency in various types of industries. It can be seen that cultivating the competitive environment for regional industrial development is the key link to improve industrial competitiveness and even promote regional economic development.

3.1.4.3

Different City Sizes

In order to study in different scale of the city industry is benefit from specialization or diversification, and make theoretical preparation for different types of city to make regional industry development policies, in this book, 236 prefecture-level cities in China were divided into five categories according to population size—mega cities, super-large cities, large cities, medium-sized cities and small cities, and investigate the differences of agglomeration economy in cities of different sizes. The estimated results of the model are shown in Table 3.5. It can be seen from the results given in Table 3.5 that the labor productivity of manufacturing industries located in mega cities, super-large cities, large cities and medium-sized cities all benefit from the diversification of industrial structure, and the specialization of industrial structure improves the production efficiency of manufacturing industries in small cities. The actual research results of the model estimation in this book basically verify that the externality of industrial agglomeration development is conducive to improving industrial production efficiency. The empirical analysis results provide the following enlightenment for regional industrial agglomeration policies: (1) the improvement of industrial production efficiency largely depends on the diversification degree of the regional industrial structure. The “mutual penetration” of industries based on technical and economic links is an important link for China’s manufacturing industry to improve labor productivity; (2) The location characteristics of different industries restrict the influence of agglomeration economy on its production efficiency. For assembly manufacturing and resource dependent, manufacturing enterprises in a specific area of a large number of industry agglomeration has significant influence on its labor productivity, regionalization effect significant industry in the small urban agglomeration is more advantageous to improve the labor productivity, urbanization effect significant industries in large and medium-sized cities offer greater space for development.

44

3 Research on China’s Industrial Cluster Competitiveness

Table 3.5 Estimation results of fixed effect model based on city size Variable

(3.1) Mega cities

(3.2) Super-large cities

(3.3) Large cities

(3.4) Medium-sized cities

(3.5) Small cities

0.5052***

0.4150***

0.3718***

0.3473***

0.3614***

0.0278

0.0200

0.0134

0.0095

0.0263

0.8544***

0.9496***

0.2908**

0.6403***

0.2093

0.2247

0.2363

0.1273

0.1002

0.1819

0.019

0.0150

0.004

0.0003

0.0152***

0.0191

0.0103

0.0055

0.0034

0.0059

0.1346

0.3932***

0.4649***

0.2902***

0.4182***

0.0973

0.0190

0.0453

0.0317

0.0946

0.1157***

0.2264***

0.1028***

0.1589***

0.1639***

0.0195

0.0162

0.0177

0.0115

0.0332

1.8373***

2.1928***

2.3039***

2.3884***

2.2905***

0.1214

0.0870

0.0569

0.0399

0.1164

0.5392

0.5492

0.6835

0.6115

0.5031

Factor input ln (K/L) Agglomeration economy Urb Loc Comp Region characteristic Region Constant terms Intra-group R2 Inter-group

R2

Sample size

0.6553

0.4913

0.4843

0.4908

0.3565

1,118

2,309

4,674

7,891

1,204

Note The value below the coefficient is the standard deviation, *** means significant at 1% level, ** means significant at 5% level, and * means significant at 10% level

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies 3.2.1 Regional Differences of Innovation Activities in China’s Manufacturing Industry 3.2.1.1

Measurement of Innovation Activities

To reflect the regional distribution characteristics of innovation activities in China’s manufacturing industry, the first thing to be solved is the measurement of innovation activities (Griliches 1979). Relevant researches mainly define innovation activities as “patent data”, “patent citations” and “innovation record”. Jaffe (1986, 1989) and Acs et al. (1990) used patent data to conduct research on innovation activities. Jaffe et al. (1993), Kelly and Hageman (1999), and Verspagen and Schoenmakers (2000)

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies

45

believed that knowledge absorption ability was an important factor restricting the efficiency of knowledge spillover, so they used patent citation in their research on knowledge spillover. The method of using patent data and patent citation data to study innovation and knowledge spillover is controversial in the academic circle. As early as before Jaffe (1989), F. M. Scherer (1983) and Griliches (1980) pointed out that the applied invention patent was not a direct indicator to measure the innovation output value (Acs et al. 1992). Griliches (1980) pointed out the shortcomings of patents for innovation output. For example, many innovation activities were not patented, and the economic value brought by patents was quite different. Acs et al. (1990) adopted a more direct measurement index—new product release, which was used in Audretsch and Feldman’s research. Our research believes that the new product index is more authentic to measure innovation activities under the condition of market economy, and it measures innovation activities based on the principle of value realization. Therefore, this study uses new product data to measure innovation activities.

3.2.1.2

The Spatial Distribution of Innovation Activities

By merging the data of manufacturing enterprises in 2003, we can study the distribution of manufacturing enterprises in 31 provinces, autonomous regions and municipalities. Due to the absolute scale of each region is quite different, so in the specific analysis, the new product density index (new product output/population) was constructed by dividing the population of each province. China’s manufacturing innovation activities are largely concentrated in the eastern coastal provinces.2 And the manufacturing industry in inland provinces generally lacks innovation vitality. Among the 2,857 county-level administrative units involved in the study of this book, 1,425 have no innovation activities, among which 461 are from the county-level administrative units in central provinces and 678 are from the county-level administrative units in western provinces. The innovation activities in eastern provinces account for 74.31% of all the innovation activities. In order to further understand the regional distribution of innovation activities in different industries in China, this study describes the regional distribution of innovation activities in 465 4-SIC industries in China’s manufacturing industry, and the regional level is divided into county-level cities. By examining the share of 4-SIC industry’s innovation output value in manufacturing innovation output value, this study chose the automobile manufacturing industry (3721), mobile communications and equipment manufacturing (4014) and home video equipment manufacturing (4071), and other 12 4-SIC industries. These 12 industries generate more than 50% of the total 4-SIC industries’ innovation output, which can be defined as the most innovative manufacturing 4-SIC industry. Furthermore, the innovation activities of 2

This book divides the Chinese economy into three economic belts (Huang et al. 2005). Eastern region: Beijing, Fujian, Guangdong, Hebei, Jiangsu, Liaoning, Shanghai, Shandong, Tianjin, Zhejiang; Central region: Anhui, Heilongjiang, Henan, Hubei, Hunan, Jiangxi, Jilin, Shanxi; Western region: Chongqing, Hainan, Inner Mongolia, Guangxi, Gansu, Guizhou, Ningxia, Qinghai, Shaanxi, Sichuan, Tibet, Xinjiang, Yunnan.

46

3 Research on China’s Industrial Cluster Competitiveness

these 12 industries are investigated at the county level, and the regional distribution of the 4-SIC industries with the most innovative vitality is summarized in Table 3.6. In order to measure the regional agglomeration degree of China’s manufacturing innovation activities and production activities, this book draws on the Lorentz curve and Gini coefficient adopted by Krugman (1991) when he measures the industrial agglomeration degree of the United States. In this book, the geographical Gini coefficient was used to study the spatial distribution characteristics of innovation activities in China’s three-digit manufacturing industry in 2,850 county-level administrative units. The basic method √ is as follows: √ Suppose Is = qi j qi Ps = q j q i = 1, · · · , n, j = 1, · · · , m Among them, qi j is the output value of industry i in region j (or the output ∑nvalue qi j of innovative activities and the number of innovative enterprises), q j = i=1 represents the total output value of manufacturing industry in region j (or the total output∑ value of innovative activities and the total number of innovative enterprises), qi = mj=1 qi j represents the total national output value of industry i (or the total output ∑ of innovative activities and the total number of innovative enterprises), ∑value q = j i qi j represents the total output value of China’s manufacturing industry (or the total output value of innovative activities and the total number of innovative enterprises). Taking PS as the horizontal axis and Is as the vertical axis, Lorentz curve is obtained as shown in Fig. 3.1. It is recorded that the combined area of Lorentz curve and the square diagonal is S A , and the area of other parts of the lower triangle is S B . Calculate Gini coefficient according to Lorentz curve: G=

SA = 2S A , 0 ≤ G ≤ 1 S A + SB

(3.5)

In addition, the ∑ lower trapezoid algorithm in the area algorithm ∑k can be used m−1 (M Q − M Q ), and M = to obtain: G = k k+1 k+1 k k k=1 s=1 Is , Q k = ∑k s=1 Ps , Mn = Q n = 1. The histogram of location Gini coefficient of China’s manufacturing industry 3.SIC industry production and innovation activities is further drawn, as shown in Fig. 3.2. On the basis of the location Gini coefficient of 3.SIC industry, this book uses the simple arithmetic average method to give the location Gini coefficient of China’s manufacturing industry 2-SIC industry production and innovation activities and the location Gini coefficient of each industry, the corresponding standard deviation is shown in Table 3.7. Through the exploratory analysis of the three-digit manufacturing industry data in China, it is not difficult to draw the following conclusions: firstly, the three-digit manufacturing industries in China all have different degrees of regional agglomeration, which shows the unbalanced spatial distribution characteristics in the 2,850 county-level administrative units in China. Compared with production activities, the regional agglomeration of three-digit innovation activities in China’s manufacturing industry is more prominent. Secondly, the regional agglomeration of production and

Automobile manufacturing industry

Mobile communication and terminal equipment manufacturing industry

Home video equipment manufacturing industry

Home air conditioner manufacturing industry

Steel rolling processing industry

Electronic computer manufacturing industry

3721

4014

4071

3952

3230

4041

Manufacturing 4-SIC industry

7.03%

2.36%

319.48

3.29%

445.14

3.93%

532.30

5.56%

752.73

11.80%

Fenghua District, Ningbo

16.73%

Jiading District, Shanghai

18.25%

70.81%

Haidian District, Beijing

19.55%

Zhangjiagang, Changshu

52.88%

15.81%

8.68%

Xiqing District, Tianjin

4.41%

Changping District, Beijing

7.70%

Siming District, Xiamen

4.19%

Caidian District, Wuhan

17.06%

Shijingshan District, Beijing

8.18%

Beichen District, Tianjin

8.06%

8.22%

10.02%

Pingshan District, Benxi

8.08%

Jiujiang District, Wuhu

7.67%

10.85%

Yuetang District, Xiangtan

5.54%

Hailing District, Taizhou

7.07%

Huicheng Huli District, Wujin District, Huizhou Xiamen District, Changzhou

11.09%

Daxing District, Beijing

12.86%

Pudong New Area, Shanghai

Lixia District, Huicheng Jinan District, Huizhou

15.48%

Jiancaoping District, Taiyuan

11.85%

Laoshan District, Xiangzhou Qingdao District, Zhuhai

18.34%

Fucheng District, Shinan Mianyang District, Qingdao

23.35%

Tanggu District, Tianjin

20.86%

18.55%

951.45

Lvyuan District, Changchun

Major agglomeration areas and their share of innovation

2,509.70

Innovative output value (RMB 100 million yuan)

Table 3.6 The most innovative 4-SIC industries in China’s manufacturing industry and the regional distribution of their innovation activities

(continued)

8.05%

Dongli District, Tianjin

6.07%

Pudong New Area, Shanghai

7.63%

Huicheng District, Huizhou

4.02%

Zhangwan District, Huangshi

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies 47

271.24

Communication switching equipment manufacturing industry

Auto parts and accessories manufacturing industry

Steelmaking industry

Electronic computer peripherals manufacturing industry

Household refrigeration electrical appliance manufacturing industry

Electronic components and components manufacturing industry

4012

3725

3220

4043

3951

4061

1.52%

205.11

1.54%

208.51

1.81%

245.49

1.95%

263.24

1.96%

265.20

2.00%

Innovative output value (RMB 100 million yuan)

Manufacturing 4-SIC industry

Table 3.6 (continued)

15.78%

Binhu District, Wuxi

26.71%

Shunde District, Foshan

29.45%

Futian District, Shenzhen

16.86%

Pingshan District, Benxi

11.13%

Pudong New Area, Shanghai

95.08%

Nanshan District, Shenzhen

4.54%

13.25%

Hexi District, Tianjin

25.24%

Huangdao District, Qingdao

28.25%

Xiqing District, Tianjin

12.50%

5.42%

Chaoyang District, Beijing

12.36%

Hongqi District, Xinxiang

12.39%

Chaoyang District, Beijing

11.78%

Tiexi District, Qingshan Anshan District, Wuhan

6.05%

Nanchang Xuhui District, District, Wuxi Shanghai

4.51%

Xiqing District, Tianjin

9.60%

Baohe District, Hefei

5.97%

Longgang District, Shenzhen

8.55%

Hedong District, Tianjin

3.40%

Jiading District, Shanghai

Major agglomeration areas and their share of innovation

4.14%

Huicheng District, Huizhou

7.13%

Hailing District, Taizhou

5.92%

Baixia District, Nanjing

7.97%

Lubei District, Tangshan

3.17%

Yuhuatai District, Nanjing

3.62%

Tongzhou District, Nantong

3.35%

Haidian District, Beijing

6.27%

Licang District, Qingdao

2.86%

Luwan District, Shanghai

48 3 Research on China’s Industrial Cluster Competitiveness

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies

49

Fig. 3.1 Lorentz curve

Fig. 3.2 Regional Gini coefficient histogram of production and innovation activities of 3.SIC industries in China’s manufacturing industry

innovation activities shows great differences among different industries. The innovation activities of resource-dependent industries such as bamboo and rattan furniture manufacturing industry, refined tea processing industry, sugar manufacturing industry and pulp manufacturing industry show strong regional agglomeration, and most of them are resource-dependent industries.

3.2.2 Model and Application Analysis of Industrial Agglomeration Innovation in China 3.2.2.1

Data Used by the Model

The basic data of this study were obtained from the database of state-owned and non-state-owned manufacturing enterprises above designated size in China in 2003. The basic data were combined at the regional and industrial levels to obtain the panel

50

3 Research on China’s Industrial Cluster Competitiveness

Table 3.7 Regional Gini coefficient of China’s manufacturing 2-SIC industry production and innovation activities 2-SIC industry

Production Innovation 2-SIC industry activity activity

Production Innovation activity activity

13

0.180

0.337

0.090

0.092

(0.214)

(0.186)

(0.029)

(0.016)

Food manufacturing industry

0.149

0.310

(0.124)

(0.179)

15

Beverage industry

0.149

0.353

(0.096)

(0.318)

16

Tobacco processing industry

0.410

0.507

(0.174)

(0.005)

Textile industry

0.050

0.167

(0.048)

(0.184)

Textile clothing, shoes, hats manufacturing industry

0.067

0.227

(0.096)

(0.034)

Leather, fur, feather (down) and its products industry

0.073

0.093

(0.035)

(0.080)

14

17

18

19

20

21

22

Agricultural and sideline food processing industry

Wood 0.090 processing and (0.093) wood, bamboo, rattan, palm, grass products industry

0.354

Furniture manufacturing industry

0.233

0.372

(0.177)

(0.313)

Papermaking and paper products industry

0.197

0.325

(0.136)

(0.253)

28

29

Chemical fibre manufacturing

Rubber products 0.068 industry (0.024)

0.151

30

Plastic products industry

0.165

31

Non-metallic 0.126 mineral products (0.080) industry

0.208

Ferrous metal smelting and rolling processing industry

0.252

0.313

(0.035)

(0.104)

Nonferrous metal smelting and rolling processing industry

0.211

0.215

(0.139)

(0.192)

Metal products industry

0.097

0.198

(0.081)

(0.156)

General equipment manufacturing industry

0.126

0.114

(0.070)

(0.113)

Specialized equipment manufacturing industry

0.127

0.197

(0.090)

(0.122)

Transportation equipment manufacturing industry

0.160

0.270

(0.091)

(0.159)

32

33

34

35

(0.161)

36

37

0.084 (0.068)

(0.112)

(0.105) (0.136)

(continued)

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies

51

Table 3.7 (continued) 2-SIC industry 23

24

25

26

27

Production Innovation 2-SIC industry activity activity

Reproduction 0.075 of printing (0.066) industry and recording media industry

0.355

Culture, education and sports goods manufacturing industry

0.131

0.242

(0.137)

(0.204)

Petroleum processing, coking and nuclear fuel processing industry

0.429

0.226

(0.340)

(0.120)

Chemical raw materials and chemical products manufacturing industry

0.130

0.132

(0.065)

(0.146)

Pharmaceutical 0.086 manufacturing (0.080) industry

39

(0.366)

0.194 (0.116)

40

41

42

43

Electrical machinery and equipment manufacturing industry

Production Innovation activity activity 0.126

0.155

(0.101)

(0.115)

Communications 0.108 equipment, (0.058) computers and other electronic equipment manufacturing industry

0.179

Instrumentation 0.185 and culture, (0.106) office machinery manufacturing industry

0.126

Crafts and other manufacturing industry

0.109

0.212

(0.083)

(0.159)

Waste resources and waste materials recycling and processing industry

0.157

0.297

(0.022)

—

(0.143)

(0.125)

Note The standard deviation of Gini coefficient in the 2-SIC industry area is shown in brackets

data of 2,850 county-level administrative units (including municipal districts) and 164 3.SIC manufacturing industries in China in 2003. Since the National Bureau of Statistics reclassified the industrial standard in 2002, the classification standard of the industry was not consistent with that before 2002, therefore, the data in this book only refer to the data of 2003.

3.2.2.2

Description of Variables in the Econometric Model

According to the studies of de Lucio (1997), Grossman and Helpman (1991), Martin and Ottaviano (1996) and others, innovation is determined by the distribution of

52

3 Research on China’s Industrial Cluster Competitiveness

economic activities in regions and industries, and innovation is the linear and monotonic increasing function of all the factors determining innovation. Therefore, when studying the spillover effect of diversification and specialization on innovation activities, a simple linear function should be considered: y = f (x, w, z)

(3.6)

among them, y represents the innovation output of a specific industry in a specific region, x represents the innovation input of a specific industry in a specific region, w represents the characteristics of a specific region, and z represents the characteristics of a specific industry. For the measurement of Marshall externality (specialization) and Jacobs externality (diversification), this study draws on the measurement method adopted by Henderson et al. (1995). The specific index P Si j of industry i in region j is defined as the ratio of the share of the total industrial output value of industry i in the overall manufacturing industry of region j to the share of this industry in the overall manufacturing industry of the whole country, that is: total industrial output valuei j /

∑

total industrial output valuei j ∑i ∑ P Si j = ∑ ( j total industrial output valuei j / i j total industrial output valuei j ) (3.7) This index reflects the degree of specialization of industry i in region j relative to the national level. If the coefficient of this variable is positive, it indicates that the Marshall externality of production activities improves the innovation efficiency of enterprises. For the purpose of estimation, we normalize the specialized index by using the formula (P S − 1)/(P S + 1), and the normalized index is still represented by PS for convenience. In this book, the standardized Herfindhal concentration index was used to measure the level of diversification, that is, for region j the diversity of its industrial structure was defined as the share of each industry in the total industrial output value of the region, and the formula was:

S B Si j =

(total industrial output valueikj −total industrial output valuei j ) ∑ total industrial output valuei j (

∑ j

i

∑ total industrial output valueikj − total industrial output vailuei j ) j ∑∑ total industrial output valuei j i

(3.8)

j

If the agglomeration of production activities has Jacobs-type externality to the innovation output of enterprises, the coefficient of this index should be greater than 0. In order to measure the development degree of relevant industries (groups) in specific industry i within the region j to which the industry belongs, this book

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies

53

defines the specialization degree index (S B Si j ) of relevant industry groups.

S B Si j =

(total industrial output valueikj −total industrial output valuei j ) ∑ i total industrial output valuei j ∑ ∑ ( j total industrial output valueikj − j total industrial output vailuei j ) ∑ ∑ i j total industrial output valuei j

(3.9)

If the degree of development of relevant industries in a specific industry has a promoting effect on the innovation output of that industry, the coefficient of this index should be positive. In order to satisfy the estimate, we use the formula (S B S − 1)/(S B S + 1) to normalize the index of industry group specialization. For convenience, the index after normalization is still represented by SBS. Two groups of dummy variables were introduced to control the differences between marketization level and technology intensity level. The marketization level (DM) is distinguish if it is the city above the sub-provincial level, otherwise it is the opposite. The technology intensity level dummy variable (DHT) is used to distinguish whether it is a high-tech industry. { DMj = { DT Hi =

1 The region is subordinate to cities above the sub - provincial level 0 Otherwise 1 High technology industry 0 Otherwise

(3.10)

Statistics catalogue of high-tech industry and the specific definitions of model variables are shown in Table 3.8 and Table 3.9. In this book, innovation output density (INN), that is, new product output/total industrial output, was set as the dependent variable of the model. The proportion of R&D investment in product sales revenue is used to reflect the level of innovation investment in specific industries in specific regions.

3.2.2.3

The Setting and Analysis of the Empirical Model

The data used in this book were panel data of 2,850 county-level administrative units (including municipal districts) and 164 3.SIC manufacturing industries in China in 2003, with a sample size of 62,780. Among them, 54,433 samples whose dependent variable innovation output density index was 0, accounting for 86.7% of the total samples. In this study, the dependent variable innovation output density I N Ni j , namely new product output/industrial total output, is equal to 0 when the new product output of a specific 3.SIC industry in a specific region is 0. The results obtained by the least square estimation method from processing such data are biased estimates (Green 1997).

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Table 3.8 Statistics catalogue of high-tech industry Industry code

Firm name

Industry code

Firm name

253

Nuclear fuel processing

405

Electronic device manufacturing

2665

Information chemical manufacturing

4051

Electronic vacuum device manufacturing

27

Pharmaceutical industry

4052

Semiconductor discrete device manufacturing

2710

Chemical raw drug manufacturing

4053

Integrated circuit manufacturing

2720

Chemical preparation manufacturing

4059

Optoelectronic devices and other electronic devices manufacturing

2730

Processing of Chinese herbal decoction pieces

406

Electronic components and components manufacturing

2740

Chinese patent medicine manufacturing

4061

Home video equipment manufacturing

2750

Veterinary medicine manufacturing

4062

Printed circuit board manufacturing

2760

Biological, biochemical products manufacturing

407

Home audio-visual equipment manufacturing

2770

Sanitary materials and medical 4071 supplies manufacturing

Home video equipment manufacturing

368

Medical equipment and equipment manufacturing

4072

Home audio equipment manufacturing

3681

Medical diagnosis, monitoring and treatment equipment manufacturing

409

Other electronic equipment manufacturing

3682

Dental equipment and appliances manufacturing

411

General instrument manufacturing

3683

Manufacture of laboratory and 4111 medical disinfection equipment and appliances

Industrial automatic control system device manufacturing

3684

Manufacturing of medical, surgical and veterinary instruments

Electrical instrument manufacturing

3685

Mechanical treatment and ward 4113 care equipment manufacturing

Drawing, calculating and measuring instrument manufacturing

3686

Prostheses, artificial organs and 4114 implants are manufactured

Experimental analysis instrument manufacturing

2689

Other medical equipment and instruments manufacturing

4115

Testing machine manufacture

376

Aerospace manufacturing

4119

Supply instrumentation and other general instrument manufacturing

4112

(continued)

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies

55

Table 3.8 (continued) Industry code

Firm name

Industry code

Firm name

3761

Aircraft manufacturing and repair

412

Special instrument manufacturing

3762

Spacecraft manufacturing

4121

Manufacturing of special instruments for environmental monitoring

3769

Other aircraft manufacturing

4122

Automobile and other counting instruments

40

Manufacturing of 4123 communications equipment, computers and other electronic equipment

Manufacture of special instruments for navigation, meteorology and oceanography

401

Communication equipment manufacturing

4124

Agriculture, forestry, animal husbandry and fishery special instrument manufacturing

4011

Communication transmission equipment manufacturing

4125

Manufacture of special instruments for geological exploration and earthquake

4012

Communication switching equipment manufacturing

4126

Teaching equipment manufacturing

4013

Communication terminal equipment manufacturing

4127

Nuclear and nuclear radiation measurement equipment manufacturing

4014

Mobile communication and terminal equipment manufacturing

4128

Electronic measuring instrument manufacturing

4019

Other communication equipment manufacturing

4129

Manufacture of other special instruments

402

Radar and supporting equipment manufacturing

4141

Optical instrument manufacturing

403

Radio and television equipment manufacturing

4154

Copy and offset printing equipment manufacturing

4031

Radio and television program production and transmission equipment manufacturing

4155

Calculator and currency special equipment manufacture

4032

Radio and television receiving equipment and equipment manufacturing

4190

Manufacture and repair of other instruments

4039

Application television equipment and other broadcast television equipment manufacturing

621

Common software services

404

Electronic computer manufacturing

6211

Basic software services (continued)

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3 Research on China’s Industrial Cluster Competitiveness

Table 3.8 (continued) Industry code

Firm name

Industry code

Firm name

4041

Electronic computer manufacturing

6212

Application software services

4042

Computer network equipment manufacturing

4043

Electronic computer peripherals manufacturing

Source National Bureau of Statistics Table 3.9 Model variables and descriptions Variable

Item

Definition

I N Ni j

Innovation ability

New product outputij /Total industrial output valueij

R&Di j

Innovation input

R&Dij /Sales revenueij

P Si j

Professionalization (Marshall externality)

(Total industrial output valueij /

∑

Total

i

industrial output valueij ) / ∑ ∑∑ ( Total industrial output valueij / j

PDj

Diversification (Jacobs externality)

i

j

Total industrial output valueij ) ∑ ∑ [1/ (Total industrial output valueij / i

i

Total industrial output valueij ) 2 ]/[1/ Total industrial output valueij /

∑ ∑ (

∑∑ i

i

j

Total

j

industrial output valueij ) 2 ] S B Si j

Industry group specialization Degree of specialization in related industries

((Total industrial output valuek ij − Total ∑ industrial output valueij ) / Total i

∑ industrial output valueij ) / (( Total j

industrial output valuek ij −

∑

Total

j

industrial output valueij ) /

∑∑ i

Total

j

industrial output valueij ) DMj

Metropolis

Metropolis, D1 j = 1, otherwise 0

DT Hi

High-technology

High-technology, D2i = 1, otherwise 0

Note i stands for industry, j stands for region, k stands for industry group with common scientific foundation, and related industries are those with common scientific foundation

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies

57

Consider Tobit model firstly, by censoring the samples with 0 innovation output density, we can estimate the explained variables to the influence degree of the innovation ability and innovation of zero probability for all samples, the influence of the parameter estimation is more accurate. Random Effects Tobit model can be defined as the empirical model of this study, such as the latent variable model: '

I N Ni∗j = a + X i j β + μi + vi j

(3.11)

among them, vi j | X i j ~ Normal (0, σv2 ), β is the parameter to be estimated. I N Ni∗j = I N Ni j I N Ni j I N Ni∗j = 0

I N Ni j ≤ 0

(3.12)

I N Ni∗j can be understood as the unobserved “innovation ability” of the sample. When an industry in a given province innovates during the observation period, I N Ni∗j is equal to the actual observed innovation output density I N Ni j . When a certain industry of specific province is 0 during observation period, I N Ni∗j is 0, I N Ni∗j also known as an index variable. In this book, Model (3.11) is regarded as Restricted model. Secondly, considering a more general model form proposed by Cragg (1971), the probability of restricted observations is independent of the regression model of unrestricted data. This model is divided into two steps to study the impact of industrial agglomeration structure on innovation ability in China’s manufacturing regions. In the first step, we focus on the impact of regional industrial agglomeration structure on the innovation ability of regional industries, and use the Probit model based on panel data for estimation. First, we set: P I N Ni j = 1 I N Ni j > 0 P I N Ni j = 0 I N Ni j ≤ 0

(3.13)

Random effects Probit model can be defined as: '

Prob(P I N Ni j = 1) = ϕ(α + X i j β + μi + vi j )

(3.14)

among them, vit | X it ~ Normal (0, σv2 ), β is the parameter to be estimated. In the second step, this book focuses on the impact of regional industrial agglomeration structure on regional industrial innovation capacity. Truncate model only considers subpopulations with innovation capability greater than 0. '

I N Ni j |I N Ni j > 0 = a + X i j βi + σ λi + νi j Equations (3.14) and (3.15) are the unrestricted model in this study.

(3.15)

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3 Research on China’s Industrial Cluster Competitiveness

Likelihood ratio statistics λ = −2[ln L T −(ln L P +ln L T R )] = 2,119.936, Prob ≥ χ 2 = 0.00. where, L T is the likelihood value of the constrained Tobit model, L P is the likelihood value of the individually fitted Pobit model, and L T R is the likelihood value of the individually fitted Truncate model. According to the likelihood ratio test, the constrained Tobit model is rejected. The empirical models of this study respectively are as follows: P I N Ni j = α + β1 R&Di j + β2 P Si j + β3 P D j + β4 S B Si j +β5 D M j × P D j + β6 DT Hi × P D j + εi j { where,

(3.16)

P I N Ni j = 1 I N Ni j > 0 P I N Ni j = 0 I N Ni j = 0 I N Ni j = α + β1 R&Di j + β2 P Si j + β3 P D j + β4 S B Si j +β5 D M j × P D j + β6 DT Hi × P D j + εi j

(3.17)

where, I N Ni j > 0. According to the estimated results in Table 3.10, the innovation input of regional industry has significant positive effects on the cultivation of its innovation ability and the level of innovation. When the innovation input density of the regional industry increases by 1%, the industrial innovation probability of the region, that is, the value of Prob (I N Ni j = 1) increases by 0.22%. For the regional industry with innovation ability, the innovation input density increases by 1%, and the innovation level of the regional industry increases by 0.0924%. The model estimation results show that the regional industrial specialization index PS, namely Marshall externality, has a significant positive effect on the cultivation of regional industrial innovation ability and the level of innovation. When a specific industry gathers in a certain region, the innovation activity of the industry is more active than the general level of the manufacturing industry. When the specialization level of the regional industry increases by 1 standard unit, the innovation probability of the regional industry, that is, the value of Prob (I N Ni j = 1), increases by 0.108%. For the regional industry with innovation ability, the innovation level of the regional industry will increase by 0.0058% if the specialization level increases by 1 standard unit. This conclusion is in contrast to the empirical conclusions on American Studies of Audretsch (1999) and Kelly (1999) and is consistent with the empirical conclusion of Pacci (2001) using Italian data. Diversity index of PD on the regional industrial structure, namely the externality of Jacobs, of regional industry in the cultivation of innovation ability and the level of innovation is not consistent, the effect of the structure of the industrial concentration degree of diversification for regional industry has a significant role in the cultivation of innovation ability. When the diversification level of the regional industry increases by 1 standard unit, the industrial innovation probability of the region, i.e., the value

3.2 Model of China’s Industrial Innovation Cluster and Its Applied Studies

59

Table 3.10 Model estimation results of influencing factors of regional industrial innovation ability Estimating methods

Restricted model

Unrestricted model

Random effect Tobit model

Random effect Probit model

Truncate model (Maximum Likelihood Method)

Coefficient

DF/DX

Coefficient

DF/DX

Coefficient

DF/DX

0.5514***

0. 1086

1.0753***

0.2154

0.2181***

0.0926

Innovation input R&D

0.0802

0.1593

0.0198

Cluster structure PS

0.2139***

0.0421

0.0066 PD

0.2091*** 0.0201***

0.108

0.013 0.0412

0.0452 SBS

0.5392*** 0.9131***

0.0039

0.0158

0.0058

0.0009 0.1828

0.0797

0.0077

0.0136*** −0.0034

−0.0015

0.0065 0.0032

0.0155

0.0071

0.003

0.0111

Regional characteristics PD* DM

0.2062***

0.0406

0.0424

0.3147***

0.063

0.086

0.0264***

0.0112

0.0074

Industrial characteristics PD* DTH Constant term

−0.3331***

−0.0656

−0.1202

−0.0241 0.2071***

0.0768

0.1665

−0.1224*** –

−1.3509*** –

0.0291***

0.0346

0.0139

0.0008

0.0879 –

DM = 0 DTH = 0.4513 1

–

1.2278

–

0.023

–

DM = 1 DTH = 0

–

0.7929

–

0.2037

–

–

1.1076

–

0.2301

–

−0.124

DM = 1 DTH = 0.0822 1 Log Likelihood

−20,181.863

−22,051.979

2,930.084

Likelihood-ratio test of rho = 0 P > χ2

0

0

0

Sample size

62,780

62,780

8,347

Note ***The significance level is 0.01%

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3 Research on China’s Industrial Cluster Competitiveness

of Prob (I N Ni j = 1) increases by 0.182%. This conclusion is consistent with those of Glaeser et al. (1992) and Henderson et al. (1995), who conducted similar studies using high-tech industries in the metropolitan areas of the United States. Through descriptive analysis of regional industry innovation activities of manufacturing industry and its influencing factors of model estimation results, it is not difficult to draw the following conclusions: firstly, the regional agglomeration of China’s regional manufacturing innovation activities and that of the production activities are consistent. The two effects of industrial agglomeration promote regional innovation activities to varying degrees. Secondly, two structures of industrial agglomeration: specialization and diversification, namely Marshall externalities and Jacobs externalities, driven to the regional industry innovation are not mutually exclusive, Marshall externalities play a major role in technology flow in the industrial area, while Jacobs externalities play a more prominent role in promoting innovation activities in the metropolitan area. Thirdly, the role of Jacobs externality in promoting regional industrial innovation activities is influenced by regional attributes (whether it is a metropolis) and industrial attributes (whether it is a high-tech industry). Jacobs externalities play a more significant role in promoting the cultivation of innovation ability of high-tech industries in the metropolitan area. In conclusion, the empirical analysis of how China’s regional industrial agglomeration structure affects the diffusion of knowledge spillovers and ultimately promotes industrial development is made by using the recent data, which is a supplement to the existing studies. At present, existing studies fail to consider the possible spatial correlation between regional industries. The next step of the study of this book is to use spatial econometric technology to investigate the impact of regional interaction on regional knowledge innovation and diffusion.

3.3 Model of China’s Industrial Innovation Cluster of the Entry of New Enterprise and Its Applied Studies Empirical studies have shown that industrial agglomeration gives birth to new enterprises. For example, Silicon Valley produces 11 new enterprises every week (Business Week, 1997), and one new enterprise is born in Zhongguancun every 5 min (Zhang 2005). The positive effect of industrial agglomeration on the entry of new enterprises has also attracted the attention of scholars (Port 2000; Todd 2003; Michael 2004). In this book, the two-dimensional cross-sectional data of 3.SIC industries3 in Zhejiang province from 1999 to 2002 were used to explore the impact of industrial agglomeration on the entry of new enterprises. The study is divided into three levels: firstly, the book studies the influence of the absolute scale and relative scale of industrial agglomeration on the entry of new enterprises. Secondly, the book studies the impact of the average size of enterprises in industrial agglomeration area on the 3

Only consider 3.SIC industries shared in 1999 and 2002.

3.3 Model of China’s Industrial Innovation Cluster of the Entry of New …

61

birth of new enterprises. Finally, the book examines the impact of urbanization level of industrial agglomeration on new enterprise activities.

3.3.1 The Theoretical Framework of Influencing Factors of New Enterprise Entry Industrial agglomeration is a fertile ground for new enterprise activities. Since a concentrated customer base reduces the investment risk of setting up a new business, investors can easily find market opportunities. The barriers to entry in industrial clusters are lower than in other regions, and the equipment, technology, inputs and employees needed can be solved within the region, so it is much easier to start a new enterprise than in other regions. In addition, factors affecting the entry of new enterprises include fiscal and tax policies, optimal economic scale, industry entry threshold, industry market conditions, abor costs and so on. Regional population size, to a certain extent, reflects the local market size (Reynolds 1995), the population size at the same time also can be used as the iconic indicators of regional urbanization level (McDonald 1997), the level of urbanization in the region also restricts the quality of local infrastructure and the degree of close internal economic exchanges, which affect the decision of enterprises to choose the site (BJK Associates 2002), the enterprise entry model illustrates the negative impact of industry entry threshold on entrepreneurs’ entrepreneurial decisions (Audretsch 1995). The growth rate of the industry (employment) reflects the market demand, and usually venture capital tends to enter the high-growth industry.

3.3.2 Determination of Data and Analytical Models 3.3.2.1

Data and Variables

This book used the state-owned and non-state-owned enterprises database of Zhejiang province in China from 1999 to 2002. Since the study focused on the situation of new enterprises, only 3.SIC industry data from 1999 to 2002 were considered. Under the theoretical framework of influencing factors of new enterprises’ entry, the indexes involved in this book and their descriptive statistical analysis results are shown in Table 3.11:

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3 Research on China’s Industrial Cluster Competitiveness

Table 3.11 Indicat or s and descriptive statistical analysis results Indicator

Number of sample Mean

Number of newly-added enterprises from 1999 to 2002

1,959

5.57

12.61

Number of counties-industry enterprises in 1999

1,959

2.78

4.69

County-industry location quotient in 1999

1,959

3.62

8.06

County-industry tax rate in 1999

1,959

0.07

0.04

Per capita fiscal expenditure of the county in 1,959 1999 (RMB thousand yuan)

0.78

0.8

Population of the county in 1999 (100,000)

1,959

8.26

3.85

County-industry per capita wage in 1999 (RMB thousand yuan)

1,959

9.38

3.87

Industry growth rate from 1999 to 2002

1,959

0.04

1.3

Industry entry barriers in 1999 (RMB million yuan)

1,959

9.6

18.26

County-industry enterprise scale in 1999 (person)

1,959

3.3.2.2

Standard deviation

272.55 546.13

Model Selection

According to the statistical results of the description of the number of newly added enterprises (see Table 3.11), the mean value is 5.57 and the standard deviation is 12.61, which violates the assumption that the mean value of Poisson distribution is equal to the variance and is closer to the negative binomial distribution. The frequency distribution of number of newly added enterprises was further investigated, the number of newly added enterprises in 553 county-industry was 0; that is, the frequency of 0 was 27.31%; it indicates the existence of Zero-Inflated phenomenon to the number of newly added enterprises. The results of AIC statistic4 and Vuong test5 show that the negative binomial regression model is the best fitting model.

4

The amount of Akaike information in negative binomial regression model, zero pile-up Poisson regression model and zero pile-up negative binomial regression model are: N B R : AI C = 4.816, Z I N B : AI C = 4.969, Z I P : AI C = 8.354. 5 The Vuong test is usually used to compare the negative binomial regression model with the zeroaccumulation negative binomial regression model. The test results given by Stata software in this book are as follows: Vuong test of zinb vs. standard negative binomial: z = − 4.89 Pr > z = 0.0000.

3.3 Model of China’s Industrial Innovation Cluster of the Entry of New …

63

3.3.3 Negative Binomial Regression Model Analysis Results 3.3.3.1

Analysis of the Influence of Industrial Agglomeration on New Enterprise Activities

In this study, the Negative Binomial Regression Model (NBREG) was used to estimate the influence of factors such as the agglomeration status of manufacturing industry in each county (city) of Zhejiang province on the entry of new enterprises. In model (1), β is the regression coefficient matrix, X i represent the influence factor matrix of the number of newly added enterprises in county-industry from 1999 to 2002. Table 3.12 shows the maximum likelihood estimation results of the negative binomial regression model. Table 3.12 The negative binomial regression results of the influencing factors of the number of newly added enterprises in county-industry Number of new enterprises

Coefficient

Standard deviation

z-value

p-value

%

dy/dx

County-number of industry enterprises

0.183

0.01

18.67

0.000

20

0.636

County-industry location quotient

0.013

0.004

3.48

0.001

1.3

0.045

County-industry tax rate

−3.386

0.795

−4.26

0.000

−96.6

−11.793

County per capita fiscal expenditure

−0.049

0.039

−1.28

0.202

−4.8

−0.172

County population size

0.044

0.009

5.12

0.000

4.5

0.153

County-industry per capita wage

−0.022

0.008

−2.59

0.009

−2.2

−0.077

0.022

7.73

0.000

18.5

0.592

Industry entry threshold

Industry growth rate 0.17 −0.01

0.003

−3.07

0.002

−1

−0.036

County-industry enterprise scale

−0.00003

0.00007

−0.48

0.631

0

−0.0001

Intercept term

0.9

0.113

7.97

0.000

χ2

Sample size = 1,959 LR (9) = 1,003.20 p = 0.000 Log likelihood = − 4,706.3853 α = 0 likelihood ratio test: χ 2 (01) = 9,840.99 p = 0.000 Note % = percentage change due to variable unit change dy/dx = variation of due variables caused by variable unit changes

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3 Research on China’s Industrial Cluster Competitiveness

Conclusion from the Results The situation of industrial agglomeration has a significant positive effect on the entry of new enterprises. When other factors remain unchanged, the absolute scale change of industrial agglomeration area increases the expected number of new enterprises by 0.636, with an increase of 20%; the relative scale change of industrial agglomeration area increases the expected number of new enterprises by 0.045, with an increase of 1.3%. Otherwise, the model also shows that the size of the county population and the growth rate of the industry have a significant positive effect on the entry of new enterprises; county-industry tax rate, county-industry per capita wage and industry entry threshold for new enterprises have a significant negative effect; county-per capita fiscal expenditure and county-industry enterprise scale index has no significant impact on the number of new enterprises.

3.3.3.2

Model Analysis on the Influence of Enterprise Scale on the Activities of New Enterprises in Industrial Agglomeration Area

The scale of enterprises in industrial agglomeration is one of its important characteristics. Marshall pointed out that the cooperation between small enterprises is more obvious in the industrial agglomeration area. Assuming that information spillover in favor of new enterprises often occurs in the industrial agglomeration area with extensive communication, the number of new enterprises should be inversely proportional to the scale of enterprises in the industrial agglomeration area. The model estimation results of Table 3.12 show that the county-industry enterprise scale index has a negative effect on the number of new enterprises, but the result is not significant, further modeling of small, large and medium-sized enterprises6 can be further modeled in Table 3.13. The results show that the positive impact of industrial agglomeration on new enterprises is more obvious. The relative change of the number of new enterprises brought by the change of the absolute scale of industrial agglomeration increases from 20% of the mixed model to 21.3%, and the model coefficient increases from 0.1827 to 0.1931; in the relatively concentrated industrial agglomeration area of large and medium-sized enterprises, the absolute scale and relative scale of industrial agglomeration have weakened the positive effect on the activities of new enterprises. New enterprises prefer small business agglomeration areas. 6

The division of the scale of enterprises in this book implements the Interim Measures for Statistical Definitions of Large, Medium and Small Enterprises formulated by the National Bureau of Statistics in May 2003.

3.3 Model of China’s Industrial Innovation Cluster of the Entry of New …

65

Table 3.13 Negative binomial regression results of industrial agglomeration effect in different enterprise scale New enterprises

Hybrid model coefficient

%

Small-sized enterprise coefficient

%

Large and medium-sized enterprise coefficient

%

County-number of firms

0.1827***

20

0.1931***

21.3

0.1565**

16.9

County-industry location quotient

0.01294***

1.3

0.01297***

1.3

0.0125*

1.3

Samples capacity 1,959 Log likelihood

−4,706.3853

1,487

472

−3,599.2634

−1,096.6921

Note ***, **, *represent significance level: 1%, 5%, 10%

3.3.3.3

Model Analysis of the Influence of the Location of Industrial Agglomeration Area on the Activities of New Enterprises

It is generally believed that the production cost of urban industrial agglomeration will decrease with the increase of total output in urban areas, and the characteristics of higher industrial differences in cities can often make the agglomeration industry get a faster development (Jacobs 1969). However, the high urban labor cost, land and other operating costs make new enterprises tend to choose non-urban areas. This study makes that 1959 county-industry samples in Zhejiang province are modeled according to the administrative level of their location, and the model estimates are shown in Table 3.14. It can be seen from Table 3.14, when other conditions remain the same, the scale of industrial agglomeration changes in counties or cities at the county level, the expected value of newly enterprises will increase 20.1%, while the expected value of Table 3.14 Negative binomial regression results of industrial conglomeration effects in different location Newly enterprise

Mixture model Coefficient

County and county-level cities

City

%

Coefficient

%

Coefficient

%

County-number of firm in industry

0.1827***

20

0.1828***

20.1

0.17996**

19.7

County-location quotient

0.01294***

1.3

0.01414***

1.4

0.00811*

0.8

Sample capacity

1,959

1,408

551

Log likelihood

−4,706.3853

−3,330.5509

−1,364.6391

Note ***, ** and *represent different significance level 1%, 5% and 10% respectively

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3 Research on China’s Industrial Cluster Competitiveness

Fig. 3.3 Lorentz curve of the number of new enterprises

newly enterprises located in industrial agglomeration of cities only increase 19.7%. The scale of industrial agglomeration changes in counties or cities at the county level leads to number of new firms increase 1.4%, and only increase 0.8% in cities. The result shows that the high cost of operations in cities offsets the attractiveness of industrial diversity to enterprises. The study reveals by descriptive analysis, the newly add-up firms in Zhejiang province from 1999 to 2002 was 10,909, however, these new business activities are not evenly distributed in the 72 × 150 counties (cities) -industries covered by this study. The Lorentz curve of the number of new businesses (see Fig. 3.3) shows that nearly 40% of new enterprises are concentrated in the industrial agglomeration of the absolute scale of the top 10% counties-industry, more than 20% new enterprises appear in the industrial agglomeration relative scale of the first 10% counties-industry. The estimation results of negative binomial regression models further confirm the theoretical and descriptive analysis conclusions of the absolute scale and relative scale of industrial agglomeration areas, which have a significant positive impact on the activities of new enterprises, that is, new enterprises tend to build factories in industrial agglomerations with relatively dense enterprises. Moreover, Marshall’s small business agglomeration is more attractive to new businesses, and small towns provide a lower entry threshold for new businesses because of their lower cost of manpower and land, as opposed to cities.

Chapter 4

Analysis of China’s Input–Output International Competitiveness

The important aspect of industrial international competitiveness is mainly the cost level of industrial production consumption, international trade and industrial correlation level. This chapter mainly focuses on the international comparative analysis of industries’ inputs and outputs using data from China’s 1997 input–output tables and those of Organisation for Economic Cooperation and Development (OECD) countries in similar years, with the aim of revealing the characteristics of the input–output levels of China’s industries’ international competitiveness relative to the levels of the OECD countries (It needs to be explained that input–output data is generally released 5 years, the 1997 data is relatively new, and its changes are very tiny; industrial classification because of the OECD countries involved, therefore, it is different from China’s national standard classification in 2002, please refer to Table 4.1 for specific country list and industry classification).

4.1 Analysis of Added Value and Its Composition in I–O Tables 4.1.1 Value Added Rate The value added rate is the ratio of the value added to the total output, it can reflect the ability of each production unit in a country’s industries to create its own value in the production process. The comparison between China and OECD countries (see Fig. 4.1) shows the characteristics of value added rates in various industries in China. From the primary and secondary industries, it can be seen that the valueadded ratio of the industry grow faster is agro-forestry and animal husbandry fishery, mining and selection industry, electric coal water supply industry, aviation industry, daily necessities, pharmaceutical industry and medical industry, the value added rate reached more than 35%, of which agro-forestry and mining industry reached more © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_4

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Table 4.1 List of OECD countries participating in the comparison and input–output table industry classification Countries 1. Australia, 2. the United States, 3. Canada, 4. the United Kingdom, 5. the Czech Republic, 6. Germany, 7. Denmark, 8. Spain, 9. Finland, 10. France, 11. Greece, 12. Hungary, 13. Italy, 14. Japan, 15. South Korea, 16. Netherlands, 17. Norway, 18. Poland Industries 1. Agriculture, forestry, animal husbandry and fishery, 2. Mineral mining and dressing industry, 3. Food, beverage and tobacco processing industry, 4. Textile, clothing, leather and footwear manufacturing, 5. Wood processing and furniture manufacturing, 6. Pulp, paper, printing and publishing industry, 7. Petroleum processing and coking industry, 8. Chemical manufacturing, 9. Pharmaceutical manufacturing, 10. Rubber and plastic products manufacturing, 11. Non metallic mineral products manufacturing industry, 12. Iron and steel smelting industry, 13. Nonferrous metal smelting industry, 14. Metal calendering and products manufacturing, 15. Machinery manufacturing industry, 16. Instrument and office equipment manufacturing industry, 17. Electrical machinery and equipment manufacturing industry, 18. Home appliance, electronic and communication equipment manufacturing industry, 19. Medical Precision, 20. Automobile and transportation equipment manufacturing industry, 21. Shipbuilding Industry, 22. Aerospace instrument manufacturing industry, 23. Automobile and transportation equipment manufacturing industry, 24. General merchandise manufacturing industry, 25. Electricity, gas and water supply, 26. Construction, 27. Wholesale, retail and repair, 28. Hotel and catering industry, 29. Transportation and logistics, 30. Posts and Telecommunications, 31. Finance and insurance, 32. Real estate industry, 33. Equipment leasing industry, 34. IT industry, 35. Scientific research, 36. Other business services (legal accounting etc.), 37. Administration and defense, 38. Education, 39. Medical and health services, 40. Other social services, 41. Family service industry

than 50%. Compared with the average level in OECD countries, the value added rate of secondary industry is about 20% lower on average.

Fig. 4.1 Comparison of the value added rate of primary and secondary industries between China and OECD countries

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Fig. 4.2 Comparison of China’s tertiary sector value added rate with that of OECD countries

The value added rate of the tertiary sector (see Fig. 4.2) shows that, even when compared to OECD countries with a medium level of development, China is still at a lower level of value added in the health care, education and administration and defence sectors. Compared with the world’s advanced level, China’s tertiary sector is even at a rather low level of value added rate, except for the real estate industry, finance and insurance, transport and logistics and scientific research business, which have a relatively small gap with the advanced level, the post and telecommunications, education, administration and defence, health care and other social services sectors in China have a gap of more than 45% compared with the highest figures of various countries.

4.1.2 Labor Remuneration Rate The Labor remuneration rate (labor remuneration divided by the total output) reflects the ratio of labor remuneration to total output in industrial activities. As can be drawn from Fig. 4.3, the rate of labor remuneration in the primary and secondary industries, China’s agroforestry labor compensation rate, up to 52%, is higher than other countries. The labor return rate in secondary industries has been significantly reduced, with only the aviation and mining industries exceeding 20%. Most of China’s secondary industry are located below the OECD medium level of labor compensation rate, only the aviation industry, mining industry, nonferrous industry, oil industry above or similar to the medium level. From the tertiary industry’s labor compensation rate (see Fig. 4.4) can be seen: from the domestic industries themselves comparison, labor compensation rate is generally higher than secondary industry, basically distributed between 20 and 30%.

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Fig. 4.3 Comparison of labour remuneration rates in primary and secondary industries between China and OECD countries

Fig. 4.4 Comparison of labour remuneration rates in the tertiary sector between China and OECD countries

Compared with the medium-level value-added rate of OECD countries, the labour return rates of the most tertiary industries are significantly lower than the medium level of other countries. Only the ratio of the real estate industry exceeds the OECD medium level, and is at the highest level in all countries; transport, wholesale industry close to and slightly lower than the medium level, while the gaps between other tertiary industries and the medium level are all widened to 10 percentage points, the highest is postal service, the gap widened to 22%.

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Fig. 4.5 Comparison of production tax rates between China and OECD countries for primary and secondary industries

4.1.3 Production Tax Rate The production tax rate (net production tax divided by the total output) reflects the proportion of the production tax in total output. As can be seen from the production tax rates of the primary and secondary industries (see Fig. 4.5), the tax rates of the medium level in OECD countries fluctuate between 0 to1%, and China’s production tax rates are at relatively high levels, largely higher than the secondary tax rates of 3% to 8% for each industry. With the exception of the oil industry, the electricity and coal industries, the automotive, aviation, medical and construction industries are slightly below the highest levels, and the net production tax rate for other secondary industry is higher than for all OECD countries. As can be seen from the production tax rate of the tertiary industry (see Fig. 4.6): The medical profession, education and administration are basically the same as the OECD average, and the other tertiary industries are above the OECD level. Apart from the gap between the real estate industry and the maximum tax rate, the tax rates of other tertiary industries are close to or equal to the highest level of OECD tax rates, and the production tax rates of the financial, wholesale and hotel industries are at the highest level in all countries.

4.1.4 Operating Surplus Rate The operating surplus rate (ratio of gross operating surplus to total output) reflects the proportion of the operating surplus in total output. From the operating surplus rate of the primary and secondary industries (see Fig. 4.7), it can be seen that only

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Fig. 4.6 Comparison of production tax rates in the tertiary industry between China and OECD countries

Fig. 4.7 Comparison of operating surplus ratios of primary and secondary industries between China and OECD countries

the household and aviation industries are significantly higher than the OECD level, and most of the remaining secondary industry fluctuate at medium level. From the tertiary industry’s operating surplus rate (see Fig. 4.8) can be seen that more than 20% of domestic industries for the real estate industry, post and telecommunications industry, transportation and science. With the exception of a lower ratio of health care and education to less than 5%, the rest of the industries are distributed up and down 10%. Most of the tertiary industry’s gross operating surplus rates are equal to the average level of OECD.

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Fig. 4.8 Comparison of China’s operating surplus ratio with that of OECD countries in the tertiary industry

Table 4.2 Average distribution table of value added ratio of each industrial category Item

Labor compensation/value added

Net production rate/value added

Operating surplus/value added

Category I mean value 0.84

0.02

0.14

Category II mean value

0.46

0.10

0.44

Category III mean value

0.43

0.18

0.38

Category IV mean value

0.56

0.12

0.32

Category V mean value

0.37

0.31

0.32

Category VI mean value

0.25

0.13

0.62

4.1.5 Industrial Classification Through the multivariate statistical method, 38 industries with data in the input– output table in China can be classified into six categories according to the above core indicators (see Table 4.2), among them: Category I: 1 Agriculture, forestry, animal husbandry and fishery, 38 Education, 39 Medical and health services, 37 Administration and defense, 26 Construction. The labor rate of return accounts for the proportion of absolute superiority, and the other two ratios are relatively small.

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Category II: 2 Mineral mining and dressing industry, 18 Home appliance, electronic and communication equipment manufacturing industry, 19 Medical Precision, 28 Hotel and catering industry, 29 Transportation and logistics, 35 Scientific research. The net production tax rate is a smaller share, the labor remuneration and the operating surplus rate are equally. Category III: 4 Textile, clothing, leather and footwear manufacturing, 5 Wood processing and furniture manufacturing, 8 Chemical manufacturing, 10 Rubber and plastic products manufacturing, 11 Non-metallic mineral products manufacturing industry, 14 Metal calendering and products manufacturing, 15 Machinery manufacturing industry, 16 Instrument and office equipment manufacturing industry, 17 Electrical machinery and equipment manufacturing industry, 20 Automobile and transportation equipment manufacturing industry, 23 Automobile and transportation equipment manufacturing industry. Category IV: 6 Pulp, paper, printing and publishing industry, 21 Shipbuilding Industry, 22 Aerospace instrument manufacturing industry, 36 Other business services, 40 Other social services. Labor compensation rate as the main point, production tax and operating surplus rate each accounted for a different proportion. Category V: 12 Iron and steel smelting industry, 13 Nonferrous metal smelting industry, 27 Wholesale, retail and repair, 3 Food, beverage and tobacco processing industry, 7 Petroleum processing and coking industry, 31 Finance and insurance. The three ratios are roughly the same. Category VI: 9 Pharmaceutical manufacturing, 24 General merchandise manufacturing industry, 25 Electricity, gas and water supply, 30 Posts and Telecommunications, 32 Real estate industry. The proportion of operating surplus ratio is large.

4.2 Analysis of Import and Export in I–O Tables 4.2.1 Export Rate Analysis From the export rates of the primary and secondary industries (see Fig. 4.9), we can see that the export rates of the primary and secondary industries in China are basically below the OECD medium level export rate, and there are certain gaps. The only industries above the medium export rate are the medical precision industry, the shipping industry, the pharmaceutical industry and the daily necessities industry. The OECD highest export rate of more than 100% is in the instrumentation, medical precision, household appliances, textile, electrical, chemical, steel and automotive industries, In these industries, in addition to the instrument industry, medical precision industry and the shipping industry export rate of about 50%, the export rate of other industries are less than 25%.

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Fig. 4.9 Comparison of export rates of primary and secondary industries between China and OECD countries

Fig. 4.10 Comparison of our export rates in the tertiary industry with those of OECD countries

From the export rate data of the tertiary industry (see Fig. 4.10), it can be seen that most of China’s tertiary industry is near the OECD intermediate export rate. Among them, the hotel industry, the wholesale industry, other social and post and telecommunications industries have a more obvious advantage over the medium export level, while the transport and financial sectors have a larger gap than the OECD medium level.

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Fig. 4.11 Comparison of the import rates of primary and secondary industries between China and OECD countries

4.2.2 Import Rate Analysis From the import rate data of the primary and secondary industries (see Fig. 4.11), we can see that the import rate and export rate of China’s industries are roughly the same. In addition to the aviation industry, the import rate of other primary and secondary industries is below the OECD medium level. From the tertiary industry import rate data (see Fig. 4.12) can be seen: China’s tertiary sector import rate is quite low, only the hotel and other social industries more than 5%, transport and post and telecommunications and financial industry more than 1%, the rest of the tertiary industry import rate is close to 0 level. The import rate of most tertiary industries is lower than the OECD medium level, especially in the transport and logistics, post and communication, financial insurance, IT, scientific research, other business activities have large gap with OECD.

4.2.3 Import and Export Rate Analysis The import and export rate is the addition of the import rate and the export rate in the industry in summary, which reflects the size of a country’s extroversion in the industry. From the import and export rate data of the primary and secondary industries (see Fig. 4.13), it can be seen that most of our secondary industry, with the exception of the aviation industry, are below the OECD medium level of import and export rates. In terms of the OECD high import and export rate, most industries have import and export rates of more than 100%, some of them up to 744%, there is still a large gap in our country.

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Fig. 4.12 Comparison of import rate of tertiary industry between China and OECD countries

Fig. 4.13 Comparison of import and export rates of primary and secondary industries between China and OECD countries

From the import and export rate data of the tertiary industry (see Fig. 4.14), we can see that China’s hotel and catering industry, other social services and wholesale, retail and repair industries are above the OECD level. However, compared with the highest level of openness of OECD, there is still a big gap.

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Fig. 4.14 Comparison of import and export rates of tertiary industry between China and OECD countries

4.3 Analysis of Industrial Interdependent Relationship in I–O Tables The link of production consumption between the various industrial sectors of the national economy forms the basis of mutual influence between industry sectors. By calculating the output coefficient, influence coefficient and total consumption coefficient of the input–output model, we can study the degree of interdependence and influence of the industrial sector.

4.3.1 Study on Yield Factors From the output coefficient data of the primary and secondary industries (see Fig. 4.15), we can see that the differences of output coefficients of each industries are still relatively large in the primary and secondary industries of our country. The output coefficient of the instrument industry reached 350%, while the lowest agroforestry, the output coefficient is only 197%, nearly double the difference. The output coefficients of the primary and secondary industries in China are basically between the intermediate level and the highest value of the OECD, in which the food industry is about the same as the medium level, while the metal industry, construction industry, textile industry, medical precision industry, non-metallic industry and pharmaceutical industry are equal to or similar to the highest levels in various countries. From the output coefficient data of the tertiary industry (see Fig. 4.16), it can be seen that more than half of China’s tertiary industry is at the highest level of OECD output coefficient, such as other social industries, health care, other business, hotel industry, administration, post and telecommunications industry and education. Other

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Fig. 4.15 Comparison of output coefficients of primary and secondary industries between China and OECD countries

Fig. 4.16 Comparison of output coefficient of tertiary industry between China and OECD countries

tertiary industries, such as wholesale, science and so on, are slightly lower than the highest values in OECD countries, but also significantly higher than the medium level. Only the output factors of the transport, financial and the real estate industries are close to the OECD level.

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Fig. 4.17 Comparison of influence coefficients of primary and secondary industries between China and OECD countries

4.3.2 Influence Coefficient Analysis The influence coefficient is weighted by the overall average, which reflects the relative influence of domestic industries, while the comparabilities of influence coefficients among different countries are relatively weak. From the influence coefficients of the primary and secondary industries (see Fig. 4.17), most of the influence coefficients of China’s secondary industries are greater than 1, concentrated between 100 and 130%, relatively balanced, with little difference from the OECD medium level. It can be seen from the influence coefficient of the tertiary industry (see Fig. 4.18) that the influence coefficient of most of the tertiary industries in China is less than 1, with an average level of about 80% to 90%. Except for the IT and equipment leasing industry, which is significantly different from the medium level of OECD, other industries are close to the medium level of OECD.

4.3.3 Study on Total Consumption Coefficient of Main Industries According to the input–output tables of OECD countries, through the analysis of the level of total consumption coefficient of some important industries, we can figure the core problems involved in the industrial development of a country out. For example, the oil processing industry, water and electricity gas supply industry complete consumption coefficient can be a general understanding of the energy consumption of various industries; through the study of the complete consumption

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Fig. 4.18 Comparison of influence coefficient of tertiary industry between China and OECD countries

coefficient of mechanical industry and electrical machinery industry, it is helpful to grasp the mechanization level of various industries; the total consumption coefficient of scientific research and education industry reflects the level of scientific and technological research and development in industry and the quality of labor force. The analysis will focus on the characteristics of 4 countries, including Japan, South Korea, Germany1 and the United States, in order to understand the differences between the developed countries of the world and Asia and our country. From the complete consumption coefficient of mineral mining and dressing industry (see Fig. 4.19), compared with the other four countries, the consumption level of mineral resources of most industries in China is the first in all countries, and far higher than the level of other countries. From the comparison of domestic industries, the top five industries with the largest mineral consumption in China are petroleum industry, nonferrous metals industry, iron and steel industry, electricity and coal industry and non-metal industry, with total consumption coefficients of 68%, 43%, 30%, 29% and 24%. The industries that consume the least mineral resources in China are financial industry, real estate industry, agriculture and forestry, hotel industry and food manufacturing industry. The consumption coefficients of mineral resources in these industries are 3.3%, 3.7%, 4.3%, 4.6% and 4.9% (less than 5% industries are not included in the figure). The top five industries with the largest consumption coefficient of China’s oil processing industry (see Fig. 4.20) are transportation industry, steel industry, 1

Germany’s input–output table are missing data on five industries: 9. Pharmaceutical manufacturing, 13. Nonferrous metal smelting industry, 22. Aerospace instrument manufacturing industry, 23.Automobile and transportation equipment manufacturing industry and 41.Family service industry.

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Fig. 4.19 Comparison of complete consumption coefficient of mineral mining and dressing industry between China and the US, Germany, Japan and South Korea

Fig. 4.20 Comparison of complete consumption coefficient of petroleum processing industry between China and the US, Germany, Japan and South Korea

oil industry, electricity and coal industry and construction industry. The highest consumption coefficient of the other four countries in these industries is 19% (South Korea), 15% (South Korea), 31% (South Korea), 17% (South Korea) and 6.4% (South Korea); the lowest consumption coefficient is 3.9% (Germany), 1.5% (the US), 10% (the US), 1.6% (the US) and 1% (Germany). The consumption level of oil processing industry is lower than that of other countries, and the total consumption coefficient of most other industries is lower than that of South Korea but higher than that of the other three countries. From a comparison of the domestic industries themselves, China’s top five industries with larger consumption coefficients for the machinery industry (see Fig. 4.21) are machinery manufacturing, ship manufacturing, railway transportation

4.3 Analysis of Industrial Interdependent Relationship in I–O Tables

83

Fig. 4.21 Comparison of complete consumption coefficient of machinery industry between China and the US, Germany, Japan and South Korea

facility manufacturing, automobile and transportation equipment manufacturing, and aerospace instrument manufacturing, all with complete consumption coefficients of over 14%, close to South Korea, and with a large gap between Japan and Germany. The industries with the least consumption of machinery industry in China are equipment leasing, IT industry, family service industry in these industries, the consumption coefficient of the machinery industry is close to zero, lower than other countries. In terms of the total consumption coefficient of each industry to the machinery industry, compared with the other four countries, China’s consumption levels are basically at the highest level except for individual industries. The top five industries with the largest total consumption coefficient of electrical machinery industry (see Fig. 4.22) are instrumentation industry, household appliances industry, electrical industry, medical industry and post and telecommunications industry. Compared with other four Asian and European countries, the consumption levels for electric industry of the most industries are the leaders of all countries, except for some industries, such as automobile industry, which is higher than that in the United States and lower than that in other three countries, and the consumption levels of instrument industry, household appliance industry and railway industry are slightly lower than that in South Korea. According to the total consumption coefficient of water, electricity and gas supply industry (see Fig. 4.23), compared with other four countries in Asia and Europe, China’s consumption level is at a relatively high level. Only in the electric coal industry, textile industry, hotel industry, food industry and agroforestry industries, the total consumption coefficient of hydro-power and gas supply industry are at the medium level in all countries, and the total consumption coefficients of other industries to the electricity and coal industry are significantly higher than those of all countries. According to the total consumption coefficient of the transportation and logistics industry (see Fig. 4.24), most of our countries are at a medium level compared to the

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Fig. 4.22 Comparison of complete consumption coefficient of electrical machinery industry between China and the US, Germany, Japan and South Korea

Fig. 4.23 Comparison of complete consumption coefficient of electricity, gas and water supply between China and the US, Germany, Japan and South Korea

other four Asian and European nations, of which only a few number of industries are at the highest and lowest consumption levels in various countries, such as administration, education, electrical, electricity and coal industry, science, other commercial and other social industries, their total consumption coefficients for transport are the top of all countries, and the gaps are more obvious, while the transport industry, timber industry are significantly lower than the consumption level of others. According to the total consumption coefficient of the finance and insurance industry (see Fig. 4.25), compared with other countries in Asia and Europe, the consumption coefficients of each industries to the financial insurance industry are all at a relatively low levels, and most of the industries’ consumption rates for the

4.3 Analysis of Industrial Interdependent Relationship in I–O Tables

85

Fig. 4.24 Comparison of complete consumption coefficient of transportation and logistics industry between China and the US, Germany, Japan and South Korea

Fig. 4.25 Comparison of complete consumption coefficient of finance and insurance industry between China and the US, Germany, Japan and South Korea

finance industry are the smallest or the penultimate among all countries. Moreover, the complete consumption coefficients for financial industry are relatively stable, and the complete consumption coefficients of most industries are all at the levels of 3% to 4%. From the comparison of domestic industries, China’s total consumption levels of R&D (see Fig. 4.26) are relatively stable. There are considerable gaps between the utilization levels of R&D in various industries and those of other 4 countries, especially those of Japan and South Korea. Among them, the larger gaps are exist in non-ferrous metal manufacturing, shipbuilding, chemical, pharmaceutical, electrical,

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4 Analysis of China’s Input–Output International Competitiveness

Fig. 4.26 Comparison of complete consumption coefficient of R&D between China and the US, Germany, Japan and South Korea

rubber, home appliances, automotive, instrumentation, aviation, machinery, textile, medical precision industry and so on. The coefficients of complete consumption of education (see Fig. 4.27) are mainly concentrated in the levels of 0.2% to 0.3%. The top five industries with the largest total consumption coefficient of education are administration, science, transportation, education and health care. The maximum consumption factors for minerals in these industries in the other four countries are 0.3% (South Korea), 12% (Germany), 0.19% (the US), 1% (Germany) and 0.24% (South Korea). Most of industries in China are in dominant positions.

Fig. 4.27 Comparison of complete consumption coefficient of education between China and the US, Germany, Japan and South Korea

Chapter 5

Research on Soft International Competitiveness of China’s Enterprise Management

Looking at the course of China’s reform and opening up, behind our preference for expansion is the strength of companies that prefer to participate in international competition, including the increase of capital size and market share, but we ignore the improvement of the soft international competitiveness of corporate management. Management is an important competitive resource and productivity of enterprises, and an important part of the success or failure of enterprises, especially for Chinese enterprises. Improving management means a more efficient use of enterprise resources, that is, the process of shifting resources from inefficient use to efficient use. The purpose of this research is to pursue the thoughts and evaluation methods of the international competitiveness of enterprise management in The IMD World Competitiveness Yearbook of the IMD, to establish a research model for the soft international competitiveness of Chinese enterprise management, and to deeply study the soft international competitiveness of Chinese enterprises in the growth of China. It provides an objective basis for exploring the comprehensive revitalization of the development and enhancing international competitiveness of Chinese enterprises.

5.1 Research Model on Soft International Competitiveness of China’s Enterprise Management In The IMD World Competitiveness Yearbook, the factors of corporate management are specifically listed to evaluate the international competitiveness of corporate management in various countries. It is based on five sub-categories: productivity, labor costs, company performance, management efficiency and corporate culture. Factors to specifically evaluate and analyze the international competitiveness of enterprise management. This book mainly discusses and analyzes its soft indicators reflecting the management structure system and management system. Mainly on the basis of analyzing the soft competitiveness of the three aspects of company © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_5

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5 Research on Soft International Competitiveness of China’s Enterprise …

performance, management efficiency and company culture, understand the connotation of these soft indicators in the design of corporate management competitiveness in the West under the conditions of a relatively complete market economy system, fair competition and symmetry of information. The article focuses on considering the four factors of enterprise governance structure, enterprise management system, enterprise employee management and enterprise ethics, and selects the following specific indexes to evaluate and analyze the soft international competitiveness of Chinese enterprise management.

The following is the explanation of the specific indicators of these four factors (all positive indicators).

5.1.1 Enterprise Governance Structure The enterprise governance structure is also known as the corporate governance structure. Enterprise governance structure is the foundation of enterprise management. Corporate governance itself is a dynamic development process, mainly containing two aspects, from the governance structure, including the shareholding structure, the board of directors, the supervisory board, the management team, etc.; from the governance mechanism, including the employment mechanism, supervision mechanism and incentive mechanism, for example, the employment mechanism can be subdivided into the chairman candidate, independent director candidate, CEO candidate, etc. The two together determine the level of governance efficiency. Therefore, the

5.1 Research Model on Soft International Competitiveness of China’s …

89

evaluation of the international competitiveness of corporate governance structure includes the design of the following five specific soft competitiveness indicators. (1) Shareholder value, indicates the effectiveness of managers in creating value for shareholders, emphasizing the contribution of managers to shareholder value, that is, whether the managers selected by the board of directors can create benefits for them, and the interaction between shareholders and management. (2) Corporate boards, it means that the company’s board of directors can guarantee the reasonable operation of the company, and emphasizes whether the company’s board of directors has played an active role. (3) Corporate credibility, indicates the degree to which the company’s manager is trusted by the public. (4) Availability of senior managers, refers to the availability of competent senior management personnel in the market, reflecting the number and quality assurance of senior management personnel in a company in a country and region, as well as the importance the company attaches to senior management personnel. (5) International experience of senior managers, indicates the degree to which senior managers generally has significant experience in international business and posting abroad.

5.1.2 Enterprise Management System The enterprise management system emphasizes the enterprise’s response to the change of the external market, the ability to learn about market sales knowledge, and the service design of consumer objects or subconscious consumer objects, etc., reflecting the overall comprehensive capabilities of the enterprise. The specific soft indicators include the following three. (1) Adaptability, refers to the speed to which the company adapts to market changes. (2) Marketing, it means that marketing is conducted efficiently in your country’s enterprises. (3) Customer satisfaction, reflecting the degree to which customer orientation is valued in a country, it is mainly considered from the aspects of whether the company starts from the needs of customers, whether it provides high-quality services, and establishes a scientific customer relationship management system.

5.1.3 Enterprise Employee Management Enterprise employees are the foundation of the enterprise. With the gradual improvement of the market economy system, companies’ emphasis on employee resources has become more and more obvious, which is specifically listed as an important aspect affecting the management of enterprises, mainly from the employees themselves, their working environment, and the alignment of their interests with the company. Specific soft indicators include the following four aspects. (1) Health, safety and environment, indicates the degree to which health, safety and environment are valued by managers. (2) Worker motivation, reflects the degree of consistency

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between employees and company objectives. (3) Employee training, the extent to which the company values employee training. (4) Labor relations, reflects the extent to which the relationship between the manager and the employee promotes the efficiency of the company’s management. It can also properly handle and maintain the relationship between the manager and the employee, and play an intangible role in promoting the development of the enterprise.

5.1.4 Enterprise Ethics The connotation of enterprise ethics embodies a kind of culture of enterprise, which plays an inestimable positive role in improving the competitiveness of enterprises in the long run. The specific soft competitiveness indicators in this area include the following three. (1) Entrepreneurship, emphasizes the entrepreneurial spirit of managers and reflects a kind of centripetal force. (2) Social responsibilities, reflects how much sense of social responsibility the company leaders and managers have. (3) Ethical practices, indicates the inclination of the company to adopt ethical practices.

5.2 Assessment on Soft International Competitiveness of China’s Enterprise Management According to IMD’s international competitiveness evaluation principles and calculation methods (refer to The IMD World Competitiveness Yearbook for details), the key points and rankings of the soft competitiveness elements of enterprise management in some countries and regions of the world in 2001–2005 are obtained (take 2005 as an example, the exact ranking is shown in Table 5.1). Countries and regions ranking in the top 10 comprehensively in terms of soft competitiveness in corporate management, in addition to Australia, Chile, Canada, the Hong Kong SAR of China and other developed countries and regions, are basically European countries, indicating that the soft competitivenesses of European business management are at a strong level. Some countries and regions with developed economies in Asia, as well as other developed countries and regions, are gradually entering the forefront, continuously improving their own level of competitiveness in corporate management, and have achieved certain results. According to the comprehensive ranking of the top ten countries and regions in the soft competitiveness of enterprise management, the average level of each factor and comprehensive competitiveness of the top ten countries and regions is obtained (see Fig. 5.1). On the whole, the competitiveness level of the four factors in the past few years is the direction of the trend of concentration, the overall level of soft competitiveness of enterprise management has risen slightly, and the score value has been between 70 and 90. There is a certain correlation between the factors, the

3

1

7

14

18

12

15

6

13

17

20

89.37

80.49

86.32

78.88

93.52

81.01

80.30

80.80

74.50

67.77

78.40

72.82

82.15

77.92

49.27

51.72

69.44

66.22

Hong Kong, China

Austria

Finland

Australia

Chile

Switzerland

Canada

Swiss

The United States

Taiwan, China

Singapore

Bavaria, Germany

Holland

Ireland

Zhejiang, China

New Zealand

Sao Paulo, Brazil

Brazil

32

35

8

10

11

4

9

5

85.94

Iceland

79.30

78.75

69.46

91.24

54.98

54.82

59.46

72.58

87.26

93.53

81.08

80.25

69.80

91.22

88.17

68.37

84.17

95.12

89.73

12

13

18

3

27

28

23

16

7

2

10

11

17

4

6

19

9

1

5

8

Ranking

Score

2

86.76

Score

89.63

Ranking

Management system

Governance structure

Denmark

Country and region

57.93

54.20

75.48

64.82

77.93

79.29

87.66

83.15

75.65

73.06

79.36

78.68

93.65

65.72

82.80

90.73

90.85

71.61

87.62

94.56

Score

27

29

16

22

14

12

5

7

15

17

11

13

2

21

9

4

3

18

6

1

Ranking

Employee management

62.61

65.56

85.88

85.94

71.56

67.40

68.83

54.25

76.10

79.60

74.42

85.08

78.14

77.75

84.77

82.73

79.39

79.91

86.80

83.73

Score

23

19

3

2

15

17

16

30

13

9

14

4

11

12

5

7

10

8

1

6

Ranking

Enterprise ethics

65.90

66.46

68.44

69.14

72.06

72.97

73.31

73.67

75.44

78.94

79.19

80.81

81.56

82.49

82.96

83.19

83.77

83.89

87.32

89.19

Score

(continued)

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

Ranking

Soft competitiveness of enterprise management

Table 5.1 International comparison of the scores and rankings of the soft international competitiveness factors of enterprise management in the 2005

5.2 Assessment on Soft International Competitiveness of China’s Enterprise … 91

16

33

29

30

24

23

45

25

37

34

72.24

50.68

63.32

63.25

55.95

53.44

52.20

43.81

51.86

61.33

61.75

25.90

61.27

46.66

49.63

54.09

54.95

Luxembourg

Norway

Israel

Malaysia

Thailand

Turkey

South Korea

Germany

Rona-Alps, France

Philippine

Colombia

Japan

Hungary

Scotland, the UK

South Africa

France

India

27

28

31

39

26

22

21

19

55.15

35.19

45.79

31.52

51.62

58.02

42.71

62.05

42.88

36.29

73.44

76.80

67.47

53.23

55.26

41.34

39.87

53.76

26

42

34

45

31

24

36

22

35

41

15

14

21

30

25

38

39

29

Ranking

Score

Ranking

Score

66.57

Management system

Governance structure

Belgium

Country and region

Table 5.1 (continued)

36.44

41.13

41.96

66.79

46.54

81.33

43.00

32.06

49.51

71.14

40.04

43.00

46.55

60.57

52.11

82.80

64.12

59.22

Score

41

38

37

20

33

10

36

43

31

19

39

35

32

24

30

8

23

25

Ranking

Employee management

34.32

55.96

55.20

41.69

34.25

42.67

51.96

49.63

63.35

55.42

53.20

58.51

59.37

53.88

64.60

63.54

56.51

66.60

Score

44

27

29

38

45

37

34

35

22

28

33

25

24

32

20

21

26

18

Ranking

Enterprise ethics

45.93

47.23

47.93

48.00

50.01

50.46

50.98

51.33

51.74

51.92

53.41

56.34

56.43

58.66

58.97

59.95

60.45

62.05

Score

(continued)

38

37

36

35

34

33

32

31

30

29

28

27

26

25

24

23

22

21

Ranking

Soft competitiveness of enterprise management

92 5 Research on Soft International Competitiveness of China’s Enterprise …

47

42

38

52

44

48

49

60

51

53

24.91

39.10

31.13

47.21

40.43

45.73

22.29

25.23

23.44

27.80

23.87

23.53

4.32

23.31

19.82

9.02

13.09

13.94

Chech

French Isle, France

Estonia

Maharashtra, India

Catalonia, Spain

Jordan

Slovakia

Slovenia

Lombardy, Italy

Greece

Spain

Mexico

China

Russia

Romania

Italy

Venezuela

Portugal

54

56

57

50

46

41

36

43

40

7.51

14.72

18.84

12.31

6.86

17.56

13.81

23.50

20.56

24.30

21.06

42.38

23.31

39.70

32.92

47.09

45.93

67.61

33.43

57

54

51

56

58

53

55

47

50

46

49

37

48

40

44

32

33

20

43

Ranking

Score

Ranking

Score

41.66

Management system

Governance structure

The United Kingdom

Country and region

Table 5.1 (continued)

13.63

6.92

12.86

11.59

10.66

25.38

17.31

20.02

18.68

28.64

26.79

37.16

25.65

28.32

31.17

43.48

36.06

56.77

58.73

Score

53

58

54

55

56

49

52

50

51

45

47

40

48

46

44

34

42

28

26

Ranking

Employee management

11.29

17.04

14.55

6.82

15.54

17.64

12.85

19.67

21.62

30.10

46.98

29.24

25.06

38.71

37.30

37.96

54.04

34.80

40.05

Score

56

52

54

58

53

51

55

50

49

46

36

47

48

40

42

41

31

43

39

Ranking

Enterprise ethics

12.04

12.56

13.11

13.52

15.09

15.25

17.79

21.93

22.68

26.33

29.16

31.66

31.76

36.71

38.09

38.98

42.64

43.93

44.24

Score

(continued)

57

56

55

54

53

52

51

50

49

48

47

46

45

44

43

42

41

40

39

Ranking

Soft competitiveness of enterprise management

5.2 Assessment on Soft International Competitiveness of China’s Enterprise … 93

55

58

59

8.64

7.50

Indonesia

Poland

3.41

3.85

17.58 60

59

52

Ranking

Score

Ranking

Score

13.21

Management system

Governance structure

Argentina

Country and region

Table 5.1 (continued)

3.68

8.50

2.48

Score

59

57

60

Ranking

Employee management

9.71

5.55

5.90

Score

57

60

59

Ranking

Enterprise ethics

6.10

7.03

9.76

Score

60

59

58

Ranking

Soft competitiveness of enterprise management

94 5 Research on Soft International Competitiveness of China’s Enterprise …

5.2 Assessment on Soft International Competitiveness of China’s Enterprise …

95

Fig. 5.1 Changes in the average level of comprehensive competitiveness of top 10 national and regional factors in the soft competitiveness of enterprise management

Pearson correlation coefficient between the factors of competitiveness is basically between 0.7 and 0.9, and are significant under the condition of a confidence level of 1%, which explains the interaction between the factors and the complementarity of complementary supplements. Enterprises in these areas more balanced attention to the development of enterprises will be more favorable. Since the beginning of the twenty-first century, the number of countries and regions in Asia participating in the evaluation of international competitiveness has gradually increased, from 13 in 2001 to 16 in 2005. Compared with Asian countries and regions, except for the comprehensive ranking of soft competitiveness in business management in 2001, China was almost at the bottom during 2002–2005. These levels are far from Singapore, and Malaysia. This is the goal that Chinese companies learn in business management. Finally, it focuses on describing the changing trend of soft international competitiveness of Chinese enterprise management and the change of its factor structure. From 2001 to 2005, the international comprehensive ranking of the international competitiveness of Chinese enterprise management software ranked 28, 44, 52, 46, 52 in order. Among them, China ranked in the bottom ten in 2002, 2003 and 2005. This is one of the major shortcomings facing the competitiveness of Chinese enterprises going international. It can be said that, in general, the international competitiveness of Chinese enterprises’ soft management has been stagnant in recent years, lagging behind, and there is no advantage at all. The changes in the four elements of China’s soft international competitiveness of enterprise management in recent years, as shown in Fig. 5.2 more intuitive performance, factors and comprehensive competitiveness level has not reached 60, in recent years have been swinging around 30, the gap between them is not too large.

96

5 Research on Soft International Competitiveness of China’s Enterprise …

Fig. 5.2 Changes in the comprehensive competitiveness level of soft international competitiveness factors of Chinese enterprise management

5.3 Analysis on the Soft International Competitiveness of China’s Enterprise Management by Competitiveness Factors Since 1994, China has formally participated in the evaluation of international competitiveness of World Economic Forum and International Institute for Management Development in Lausanne, Switzerland. This part uses our international competitiveness database to describe and analyze the specific indexes of the four factors of the soft international competitiveness of enterprise management, and look at the changes in the soft indicators of various aspects of Chinese corporate management soft international competitiveness over the past few years and the current situation, the current level of development, and the basic reasons for its changes. As can be seen from Fig. 5.3, in terms of the competitiveness of corporate governance structure factors, shareholder value, corporate board meeting and the overall level of corporate reputation in the past few years are higher than the availability of senior managers and international experience of senior managers, reflecting the neglect of management talents by Chinese companies, and the understanding of the role of corporate management human capital is far from enough. As can be seen from Fig. 5.4, in terms of the competitiveness of enterprise management system factors, the overall level of customer satisfaction and marketing has been higher than adaptability, indicating that the overall management structure and system of Chinese enterprises are less adaptable to market changes, and has a greater impact on the development of enterprises. In the future, Chinese enterprises should pay more attention to mastering and applying sales methods, the ability to predict, adapt and prevent market changes needs to be improved, and the value of customer satisfaction index is gradually increasing, which is currently at a medium level.

5.3 Analysis on the Soft International Competitiveness of China’s …

97

Fig. 5.3 Changes in the competitive level of factors of enterprise governance structure in China from 1994 to 2005

Fig. 5.4 Changes in the competitive level of factors of enterprise management system in China from 1994 to 2005

As can be seen from Fig. 5.5, the level of the four indicators is comparable in terms of the competitiveness of the management factors of enterprise employees, and the trend of changes in recent years is relatively similar, and the overall trend is declining, reflecting the high correlation of these indicators. Chinese companies need to look farther, the increased investment today is to provide more returns for tomorrow, and improvements should be made in terms of employee training, motivation enhancement, and creation of a safe and healthy production environment. As can be seen from Fig. 5.6, in terms of the competitiveness of corporate ethical factors, the level of these three indicators is comparable, especially in the past few years the index value is closer, the trend of change is similar. Chinese enterprises have always neglected the positive role of moral restraint in enterprises or employees.

98

5 Research on Soft International Competitiveness of China’s Enterprise …

Fig. 5.5 Changes in the competitiveness level of factors of employee management in Chinese enterprises from 1996 to 2005

Fig. 5.6 Changes in the competitive level of ethical factors in Chinese enterprises from 1994 to 2005

They have not paid much attention to the intangible power of morality or ethnicity, for enterprises, managers, employees, etc., they lack some cohesion or spiritual unity. This power is also a big loss.

5.4 Conclusion

99

5.4 Conclusion This book mainly focuses on the four elements of enterprise governance structure, management system, employee management and enterprise ethics, through the international evaluation and analysis of China’s soft international competitiveness of enterprise management, it also analyzes the changes in the four-factor competitiveness index over the years and the current level of development. In terms of description, we have a certain understanding of the international competitiveness and development trend of the world’s developed countries and Chinese enterprise management software, and mainly draw the following basic conclusions. (1) From the perspective of the overall international level, the soft competitiveness of European business management is strong, and some countries and regions with developed Asian economies (such as Singapore; Hong Kong [China]), as well as other developed countries and regions (such as the United States, Canada, Australia) are at medium level. (2) Compared with the economically developed Western countries and Asian countries, China’s soft international competitiveness of enterprise management is at a low level, especially far from the top 20 countries and regions in the world is far apart, which reflects the specific reality of Chinese enterprises Human capital, market technology and the special culture or concept formed by enterprises is still relatively backward in the world. (3) The overall level of international competitiveness of Chinese enterprise management software has not been greatly improved in the observation period, after China’s entry into the WTO, it has promoted the promotion of enterprise production, efficiency and profitability, but the backward enterprise management structure system and management system have become one of the main reasons hindering the improvement of enterprise management level in China. (4) Regardless of the economically developed countries and regions or the actual situation in China, the correlation between the factors of soft competitiveness of enterprise management and specific indicators is greater, if Chinese enterprises do not favor each other in terms of governance structure, management system, employee management and enterprise ethics and other aspects, it will be more conducive to the survival and development of enterprises, and further enhance the international competitiveness of enterprise management.

Part II

Study on the International Competitiveness of China’s Manufacturing Sector

Chapter 6

Assessment and Analysis of China’s Manufacturing International Competitiveness

China’s total economic volume and manufacturing value added has entered the world’s forefront, however, measuring the international competitiveness of China’s manufacturing industry from the perspective of output, efficiency, market, system, and innovation has shown us a different picture. they contribute to an objective understanding of China’s manufacturing industry international competitive position, comprehensive analysis of China’s manufacturing industry international competition level and development direction.

6.1 Assessment System of China’s Manufacturing International Competitiveness International competitiveness of manufacturing industry based on the indicators and data of The IMD World Competitiveness Yearbook 2005 of the International Institute for Management Development (IMD), 50 specific indicators closely related to the international competition of the manufacturing industry are selected to form the evaluation system, with 41 the world’s major economies are the objects of evaluation and research, which evaluate and analyse the international competitiveness of the manufacturing industry in China and major countries and regions. Firstly, 7 evaluation factors closely related to the competition of manufacturing industry are selected, namely: productivity, labor cost, product market, employee motivation, enterprise system, independent innovation and Innovation network, and then classify 50 relevant indicators into categories. Evaluate the factors, calculate the international competitiveness of the manufacturing industry and the factors of the international competitiveness on this basis, display and analyse the international competitiveness of China’s manufacturing industry from the three levels of indicators, factors and comprehensive (see Table 6.1). In terms of calculation method, first obtain comparable data through standardization for all indicators, obtain the competitiveness standard score data ranging from © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_6

103

104

6 Assessment and Analysis of China’s Manufacturing International …

Table 6.1 Evaluation index system of international competitiveness of manufacturing industry Characteristic*

Factor

Code

The index name

Year of data

Productivity

1.1

Added value of secondary industry (US$ billion)

2004

1.2

Industrial productivity, GDP created by each employee (PPP, US$)

2004

1.3

Comprehensive productivity, GDP per employed person (US$)

2004

1.4

Labor productivity, GDP per 2004 employee per hour (PPP, US$)

1.5

Service productivity, corresponding GDP generated per service sector employee (PPP, US$)

2004

2.1

Compensation of manufacturing workers in every hour (US$)

2004

N

2.2

Annual growth rate of unit labor cost in manufacturing sector (%)

2004

N

2.3

Gross annual income of senior managers (US$)

2004

N

2.4

Annual total engineer’s income 2004 (US$)

N

2.5

Total annual income of manufacturing manager (US$)

N

3.1

Final consumption expenditure 2004 of residents (US$ billion)

3.2

Real growth in residents’ final consumption expenditure (%)

3.3

Government final consumption 2004 expenditure (US$ billion)

3.4

Growth rate of government 2004 final consumer expenditure (%)

3.5

Exports of industrial products (US$ billion)

2004

3.6

Imports of industrial products (US$ billion)

2004

3.7

Balance of trade (US$ billion)

2004

3.8

Exports of goods (US$ billion) 2004

3.9

Is customer satisfaction valued 2005

Labor cost

Product market

2004

2004

N

S (continued)

6.1 Assessment System of China’s Manufacturing International …

105

Table 6.1 (continued) Factor

Code

The index name

Year of data

Characteristic*

Employee motivation

4.1

Whether the employee’s motivation is consistent with the company’s goals

2005

S

4.2

Whether employee training is valued by the company

2005

S

4.3

Whether employees’ health, safety and environment are valued by managers

2005

S

4.4

Whether the employment relationship is efficient

2005

S

4.5

Whether the company value takes full account of the employee’s interests

2005

S

5.1

Whether large enterprises are efficient against international standards

2005

S

5.2

Efficiency of small and medium-sized enterprises against international standards

2005

S

5.3

Can the company’s board ensure the reasonable operation of the company

2005

S

5.4

Whether accounting and auditing systems are fully implemented

2005

S

5.5

Does the manager have the entrepreneurial spirit innovation consciousness

2005

S

5.6

Whether managers attach importance to the responsibility of society

2005

S

5.7

Whether ethical practices are taken by the company

2005

S

6.1

Corporate research and 2003 development expenditure (US$ million)

6.2

Per capita enterprise research and development expenditure (US$)

2003

6.3

Number of enterprise research and development employee (1,000 people of full-day equivalent unit)

2003

Enterprise system

Enterprise system

Independent innovation

(continued)

106

6 Assessment and Analysis of China’s Manufacturing International …

Table 6.1 (continued) Factor

Innovation network

Characteristic*

Code

The index name

Year of data

6.4

Number of enterprise research and development per capita (full-day equivalent unit per 1,000 people)

2003

6.5

Exports of high-tech products (US$ million)

2003

6.6

Exports of high-tech products per capital in the workforce (US$)

2003

6.7

Exports of high-technology products as a proportion of manufacturing exports (%)

2003

6.8

Number of approved patents granted (annual average)

2002

6.9

Number of patents per capital (pieces / million people)

2002

6.10

Number of patents obtained abroad

2002

6.11

Number of commercial patent awards (thousands of pieces)

2002

7.1

Whether qualified engineers are adequate in the market

2005

S

7.2

Whether qualified information technology employees are easily available in the market

2005

S

7.3

Whether enterprise technical cooperation is common

2005

S

7.4

Whether the research on cooperation between institutions and enterprises is adequate

2005

S

7.5

Whether the development and application of technology is supported by a legal environment

2005

S

7.6

Technical standard support or restriction of enterprise development

2005

S

7.7

Whether the legal environment 2005 supports scientific research

S

7.8

Whether intellectual property rights are well protected

S

2005

Note The characteristics column is marked with the inverse index (N) and the survey indicator (S). Source The IMD World Competitiveness Yearbook 2005

6.2 Assessment and Analysis of Manufacturing International Competitiveness

107

0 to 100 through the calculation of the normal distribution function value, and on this basis, the factors within the elements are equally weighted to obtain the factors competitiveness standard score. The equal right of 7 factors standard score gets the comprehensive score of the international competitiveness of manufacturing industry on average. The two-level equal weight average reflects the equal treatment of the competitiveness information reflected by each index and the emphasis on the competitiveness structure, that is, without sufficient reasons and proof, we should not blindly determine the multiple relationship of the weights among the indexes.

6.2 Assessment and Analysis of Manufacturing International Competitiveness 6.2.1 International Competitiveness of Manufacturing Industry Based on the data reported by IMD in 2005, the international competitiveness level of manufacturing industry in 41 economies was evaluated. Judging from the comprehensive evaluation results of industrial international competitiveness (see Fig. 6.1), China’s industrial international competitiveness scored 38 points, ranking 30th, 32 points less than the first place Finland. Except for Spain, Italy and Portugal, it lags behind other developed countries and regions, and also lags behind developing countries such as Chile (21), Malaysia (22), Brazil (25), India (26), Thailand (28) and the Philippines (29). The productivity competitiveness (see Fig. 6.2), the United States ranked first with an absolute advantage of 94 points. China only scored 23 points, which is

Fig. 6.1 Ranking of international competitiveness of manufacturing industry in 2005

108

6 Assessment and Analysis of China’s Manufacturing International …

Fig. 6.2 Ranking of international competitiveness of manufacturing production efficiency in 2005

71 points behind the United States. All productivity indicators lag behind, ranking 39–40. The scores of developed countries and regions are clear from developing countries. Developed countries and regions generally have higher scores, most of which are above 60 points, which are significantly better than developing countries; while developing countries score mostly below 25 points, ranking 30th. In terms of labor cost competitiveness (see Fig. 6.3), Malaysia has the lowest overall cost with a score of 91 points; Switzerland has the highest labor cost country with 14 points. China ranks 8th with 75 points, and the score distribution is characterized by high costs in developed countries and regions, low costs in developing countries and regions, with the result that production plants are shifting to countries and regions in East, South and South-East Asia. Product market competitiveness (see Fig. 6.4) is the competitive factor with the smallest score gap. The top three advantages are obvious, and the latter four disadvantages are obvious. The United States is undoubtedly the largest market, but its high imports have weakened its product market competitiveness, ranking 2nd, Japan as the 2nd largest market, product market competitiveness ranked ahead of the United States due to higher customer satisfaction scores. China ranks third with 63 points, showing the characteristics of a large market, high growth, and high imports, but it does not pay enough attention to customer satisfaction. Employee motivation competitiveness (see Fig. 6.5), China to 26 points ranked 31th, relatively belong to the staff is not motivated by the competitive group. The national and regional score distribution of this element can be divided into 4 groups: Denmark and other 5 countries are the highest score groups, staff dynamic competitiveness advantage is obvious, harmonious development momentum is sufficient; staff motivations of Australia to Chile (18th) have competitive advantage, can support the harmonious development of manufacturing industry; staff motivations of Belgium to the Philippines (30th) are relatively inadequate, China to Argentina are the countries lack of staff motivations.

6.2 Assessment and Analysis of Manufacturing International Competitiveness

109

Fig. 6.3 Ranking of international competitiveness of manufacturing labor cost in 2005

Fig. 6.4 Ranking of international competitiveness of manufacturing products market in 2005

Enterprise system competitiveness (see Fig. 6.6), China scored only 12 points, ranking 38th, which is the worst ranked factor among the seven competitive factors. As a whole, developed countries and regions are still ahead, while developing countries and regions lag behind. But there are still special phenomena. For example, Chile ranks 6th, Brazil and Malaysia rank 18th and 21st respectively; while the United States ranks 11th and Japan ranks 30th. Independent innovation competitiveness (see Fig. 6.7), Japan has an absolute advantage, the United States, Germany, South Korea and France’s competitive advantage is also very prominent. China scored 47 points, ranking 16th. It has a very high total in terms of input indicators and output indicators for independent innovation,

110

6 Assessment and Analysis of China’s Manufacturing International …

Fig. 6.5 Ranking of international competitiveness of motivation of manufacturing employees in 2005

Fig. 6.6 Ranking of international competitiveness of manufacturing enterprise system in 2005

but it is very insufficient according to the average output value and labor force; the export of high-tech products is still insufficient. Compared with comprehensive national strength and innovative investment, the efficiency of independent innovation needs to be improved. Innovation network competitiveness (see Fig. 6.8) is the most competitive factor of the score gap, Finland has the highest score of 95 points, and 14 developed countries and regions with a score of 72 or higher have relatively complete innovation networks and obvious competitive advantages; the countries between India (15th)

6.2 Assessment and Analysis of Manufacturing International Competitiveness

111

Fig. 6.7 Ranking of international competitiveness of manufacturing independent innovation in 2005

Fig. 6.8 Ranking of international competitiveness of manufacturing innovation network in 2005

and France (23rd) scored between 52 and 62 points, and the competitiveness of innovation network was at a medium level; The Philippines (24th) After the country score is less than 50 points, and the decline is fast, innovation network competitiveness is insufficient. China is in a lack of competitiveness of the group, and there is a lot of work to do in the construction of innovation network.

112

6 Assessment and Analysis of China’s Manufacturing International …

6.2.2 Advantages and Disadvantages of International Competitiveness of China’s Manufacturing Industry From the results of factor analysis (see Figs. 6.2–6.8), China’s dominant factors are mainly labor costs, product market, all of which are in the top 10, independent innovation competitiveness also has a certain advantage. Among them, the labor cost is lower, the factor ranks 8th, the product market is broad, and the factor ranks 3rd; the overall R&D investment and the export of high-tech products are relatively large, and the independent innovation factor ranks 16th. Other factors ranks after 30th, of which the productivity is 31st. Only the total value added of the second production is higher, the other four efficiency indicators are in the last 3, employee motivation ranks 31st, and several evaluation indicators are all above 30th. Innovation network ranks 35th, except for technical standards and legal environment ranking 24th, other indicators are close to the bottom; corporate system ranks 38th, close to the bottom in indicators such as corporate standards and company boards. Judging from the index ranking (see Table 6.2), China’s advantage indicators mainly focus on the lower wages at different levels, in addition to the total export of industrial goods, total R&D expenditures of enterprises, and total patents. In terms of indicators, the advantages of per capita and efficiency indicators are insufficient. The key disadvantage indicators are mainly low productivity, both purchasing power and current prices, and there is a big gap with developed countries, per capital patents are insufficient, and the number is low, insufficient attention is paid to staff training, insufficient qualified engineers, large enterprises are less efficient, institutions and enterprises lack of cooperation and so on.

6.3 Characteristics of China’s Manufacturing International Competitiveness From the analysis of the comprehensive level of international competitiveness, factor competition level and index performance of the above manufacturing industry, the international competitiveness of China’s manufacturing industry presents the following characteristics. (1) The total level of manufacturing industry is outstanding, the efficiency is not high, and the comprehensive competitiveness is insufficient. China’s manufacturing industry has a good performance in the total level of output, the output level of high-tech products, labor input, international trade volume, as well as R&D funds and personnel input, and the number of patents. The total index ranking also enters the top 5 in the world. However, in the efficiency index and per capita level of manufacturing industry, China is not only far behind developed countries, but also has a certain gap with some developing countries, and is in a disadvantaged group with insufficient competitiveness.

32,553

54,409

550

656

Gross annual income of senior managers (US$)

Annual income of engineers (US$)

Total annual income of manufacturing manager (US$)

Exports of manufacturing products (US$ billion)

Corporate research and development expenditure (US$ million)

Number of approved national patents granted

2.3

2.4

2.5

3.5

6.1

6.8

5,913

71,418

0.75

Compensation of manufacturing workers (US$)

2.1

Value

Indicator name

Code

Advantage indicator

10

1

3

1

1

1

5

Ranking

110,053 (Japan)

China

866 (Germany)

China

China

China

0.33 (Indonesia)

Optimum value

0.51

3.81

4.91

2,187

20,929

Value

Whether qualified engineers are adequate in the market Cooperation between institutions and enterprises

7.4

3.60

4.00

Patents per capital 4.55 (Pieces / million people)

Average number of corporate research and development

Large enterprise

Employee training

Comprehensive productivity (US$)

Industrial productivity (PPP, US$)

Indicator name

7.1

6.9

6.4

5.1

4.2

1.3

1.2

Code

Disadvantage indicator

Table 6.2 Comparison of international competitiveness advantages and disadvantages of China’s manufacturing industry

36

40

32

30

40

31

40

39

Ranking

7.31 (Finland)

8.64 (India)

1,188 (Taiwan, China)

5.82 (Finland)

8.64 (Chile)

7.75 (Denmark)

110,942 (Norway)

126,509 (Norway)

Optimum value

6.3 Characteristics of China’s Manufacturing International Competitiveness 113

114

6 Assessment and Analysis of China’s Manufacturing International …

(2) The low cost advantage of labour force still exists, but the cost increases more quickly. The low cost of labour is an important advantage of China’s development of manufacturing industry and has played an important role in the reform and development. The characteristics of low labor cost and high growth in China are beneficial for the country and enterprises to seek new advantages and growth points of manufacturing competition, and it is conducive to the increase in worker welfare and the improvement of social welfare, and play a positive role in promoting the development of international competitiveness of China’s manufacturing industry. (3) The vast domestic market is broad and is an important position for industrial development. While China is concentrating on developing outward economy and export trade, the eyes of the whole world are on China’s vast domestic consumer market. In today’s prosperous international trade, sufficient foreign exchange, and limited resources, paying attention to the domestic market will be a long-term adjustment process. Although it is slow but it is conducive to improving the international competitiveness of the industry, and improving the national welfare. It is sustainable development. (4) Insufficient motivation of employees, harmonious development needs to be further emphasized. As China is still in the period of reform and transformation, there are many contradictions in the flow of labour, organization and protection of rights and interests, the normative and long-term nature of enterprise development is poor, there are still many contradictions in the welfare and training of enterprise employees, labour relations and so on, which is still a challenge to the promotion of international competitiveness of manufacturing. (5) The backward corporate system cannot meet the needs of international competition in manufacturing industry. There are not many high-level enterprises in China that can be integrated into international competition by international standards, and the governance structure, long-term operation, social responsibility and so on of enterprises need to be improved. (6) The investment of independent innovation is very high, but the output efficiency is insufficient, and the innovation network needs to be constructed. The total amount of funds and personnel input for innovation by our country and enterprises is first-class, and the competitiveness of independent innovation ranks in the middle level and output efficiency needs to be improved. When the world is shocked by the development of China’s manufacturing industry, we still need to discuss how to improve the international competitiveness of China’s manufacturing industry, whether to develop a “manufacturing factories” or the construction of “manufacturing centrals”, and how to further improve the efficiency of output, promote the emergence of more large enterprises that can participate in international competitiveness, so that the improvement of manufacturing international competitiveness can not only promote economic development, but also improve the welfare of the whole people and promote scientific and technological progress and social progress.

Chapter 7

Assessment and Analysis of International Competitiveness of China’s Manufacturing Environment

7.1 Assessment System of International Competitiveness of Manufacturing Environment The international competitiveness of manufacturing environment is based on the indicators and data of The IMD World Competitiveness Yearbook 2005 and selects 30 specific indicators closely related to the international competition in manufacturing industry to form an evaluation system, and take 41 major economies in the world as the evaluation and research objects to evaluate and analyse the environmental competitiveness of the manufacturing industry in China and major countries and regions. The evaluation system selects 5 factors of environmental competitiveness closely related to the competition of manufacturing industry, namely, public service, taxation, financial market, capital flow, international trade, and then classifies 30 relevant indicators into the evaluation elements. on the basis, the international competitiveness of the manufacturing environment and the international competitiveness of elements are calculated, and the international competitiveness of China’s manufacturing industry is displayed and analysed from the three levels of indicators, factors and comprehensive (see Table 7.1). In terms of calculation method, first obtain comparable data through standardization for all indicators, and then through the calculation of normal distribution function value to obtain a change range of 0 to 100 competitiveness standard score data, and on this basis, the elements within the elements are equally weighted to obtain the elements competitiveness standard score, the weighted average of the five factor standard scores get the comprehensive score of the international competitiveness of the manufacturing environment. The two-level equal weight average reflects the equal treatment of the competitiveness information reflected by each index and the emphasis on the competitiveness structure, that is, without sufficient reasons and proof, we should not blindly determine the multiple relationship of the weights among the indexes. © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_7

115

116

7 Assessment and Analysis of International Competitiveness of China’s …

Table 7.1 Evaluation index system of international competitiveness of manufacturing industry environment Factor

Code

The index name

Public service

1.1

Whether public services are subject to political interference

2005

S

1.2

Whether bureaucracy hinders the development of enterprises

2005

S

1.3

Whether inappropriate behavior, such as bribery or corruption, is prevalent in the public sphere

2005

S

1.4

Whether the government controls the prices of most industrial products

2005

S

1.5

Government subsidies (for private and public enterprises) as a percentage of GDP (%)

2003

N

1.6

Does competition law prevent unfair competition in your country

2005

S

2.1

Average corporate tax rate on profits as a percentage of pretax profits (%)

2005

N

2.2

Tax on corporate profits, income and capital gains as a percentage of GDP (%)

2003

N

2.3

Whether the effective corporate tax encourages entrepreneurial behavior

2005

S

2.4

Goods and services tax share of GDP (%)

2003

N

2.5

Whether tariff management impedes the effective re-export of goods

2005

S

3.1

Whether the cost of capital hinders the development of competitive enterprises

2005

S

3.2

Whether credit can flow easily from Banks to businesses

2005

S

3.3

Whether financial institutions provide adequate information about their activities

2005

S

3.4

Whether the stock market (including secondary market) can provide sufficient capital for enterprises

2005

S

Taxation

Financial markets

Year of data

Characteristics

(continued)

7.2 Assessment and Analysis of the International Competitiveness …

117

Table 7.1 (continued) Factor

Capital flow

International trade

Code

The index name

3.5

Stock market funds raised (US$ billion)

Year of data 2003

3.6

Stock market turnover (US$ per capita)

2003

3.7

Share of stock market funds raised in GDP (%)

2003

4.1

Fdi flows (US$ billion)

2004

4.2

Stock of outward direct investment (US$ billion)

2003

4.3

Attracting fdi flows (US$ billion)

2004

4.4

Stock of fdi attraction (US$ billion)

2003

4.5

Proportion of foreign direct investment in GDP (%)

2004

4.6

Proportion of foreign direct investment in GDP (%)

2004

5.1

Current account balance (US$ billion)

2004

5.2

Current account balance as a percentage of GDP (%)

2004

5.3

Balance of trade (US$ billion)

2004

5.4

Trade balance as a percentage of GDP (%)

2004

5.5

Goods exports (US$ billion)

2004

5.6

Goods exports as a percentage of GDP (%)

2004

Characteristics

Note The characteristics column is marked with the inverse index (N) and the survey index (S). Source The IMD World Competitiveness Yearbook 2005

7.2 Assessment and Analysis of the International Competitiveness of Manufacturing Environment 7.2.1 Evaluation of International Competitiveness of Manufacturing Environment Based on the data reported by IMD in 2005, the international competitiveness level of manufacturing environment in 41 economies was evaluated. From the comprehensive evaluation results of the environmental competitiveness of manufacturing industry (see Fig. 7.1), China’s manufacturing environmental competitiveness ranks 26th, 32 points less than the highest score of Singapore, ranking ahead of developed countries

118

7 Assessment and Analysis of International Competitiveness of China’s …

Fig. 7.1 International competitiveness ranking chart of manufacturing industry environment in 2005. Source The IMD World Competitiveness Yearbook 2005

such as Portugal and Italy, but behind developing countries such as Malaysia (17th), Chile (19th) and Thailand (25th). From the perspective of factor competitiveness, China’s public service competitiveness (see Fig. 7.2) ranks 32nd, 57 points less than the highest score of New Zealand, and is among the less competitive groups. Tariff competitiveness needs to be strengthened. The competitiveness of the financial market (see Fig. 7.4) is still far from that of developed countries and regions. The competitiveness of capital flows (see Fig. 7.5) is relatively strong, the capital to attract foreign investment to support the development of the manufacturing industry is relatively sufficient, and the capital outflow is relatively small. International trade competitiveness (see Fig. 7.6) China ranks 8th. The trade environment for manufacturing development is more competitive, but there is still a certain gap compared to Germany, Singapore, Malaysia and other countries.

7.2.2 Advantages and Disadvantages of the International Competitiveness of China’s Manufacturing Environment From the perspective of factor competitiveness (see Figs. 7.2–7.6), China’s corporate tax rate and the proportion of indirect tax income are relatively low, ranking 15th. Attracting more foreign investment and ranking 10th in capital flows; the total volume and surplus of international trade are relatively large, and this factor ranks the 8th. But public services and financial market factors rank 32nd and 35th, respectively, and their competitiveness was insufficient.

7.2 Assessment and Analysis of the International Competitiveness …

119

Fig. 7.2 International competitiveness ranking of manufacturing public service environment in 2005. Source The IMD World Competitiveness Yearbook 2005

Fig. 7.3 International competitiveness rankings for the manufacturing tax environment in 2005. Source The IMD World Competitiveness Yearbook 2005

From the perspective of index level (see Table 7.2), the advantage indicators are: government subsidies account for a low proportion of the total economy, ranking 6th; lower corporate and indirect taxes; stock market financing is ranked 9th; foreign direct investment flows are ranked 2nd, and stocks are ranked 5th, the proportion ranks 7th; the export of goods ranks 3rd, and the current account and trade surplus are both in the top 10. Disadvantages: bureaucracy and corruption need to be improved, price control is still strong, the government needs to strengthen a level playing field;

120

7 Assessment and Analysis of International Competitiveness of China’s …

Fig. 7.4 International competitiveness ranking chart of manufacturing financial market environment in 2005. Source The IMD World Competitiveness Yearbook 2005

Fig. 7.5 International competitiveness ranking chart of capital flow environment in manufacturing industry in 2005. Source The IMD World Competitiveness Yearbook 2005

financial institutions have poor transparency and credit circulation, and foreign direct investment flows are small.

7.3 Characteristics of International Competitiveness of China’s …

121

Fig. 7.6 International competitiveness ranking chart of manufacturing international trade environment in 2005. Source The IMD World Competitiveness Yearbook 2005

7.3 Characteristics of International Competitiveness of China’s Manufacturing Environment From the above analysis of the comprehensive level of the international competitiveness of the manufacturing environment, the level of factor competition and the performance of indicators, the environmental competitiveness of China’s manufacturing environment presents the following characteristics: the overall competitive strength is at a medium level, and there is room for improvement. Public services need to be strengthened, especially bureaucracy and corruption need to be improved and punished. The financial market needs to be reformed and improved in order to provide convenient financial support for enterprises under risk control. The steady inflow of capital has effectively supported the improvement of the competitiveness of the manufacturing industry. However, there has not yet been a large-scale capital outflow to international investment, making it difficult for domestic enterprises to compete in the international market. The international trade environment is good, tariff management needs to be improved.

6.19

681.2

62

Does corporate tax encourage entrepreneurial behavior

Stock market funds raised (US$ billion)

Foreign direct investment flows (US$ billion)

Export value of goods (US$ billion)

2.3

3.5

4.3

5.5

593.4

3

2

9

8

11

915 (Germany)

121 (the United States)

14,266 (the United States)

7.93 (Iceland)

1.28 (Germany)

4.1

3.4

3.2

2.5

1.3

1.2

2.49

0 (Singapore)

Tax rate levied on profits as a percentage of profit before tax (%)

6

2.1

0.19

Government subsidies as a percentage of GDP (%)

1.5

Foreign direct investment flow (US$ billion)

Whether the stock market can provide sufficient funds for enterprises

Is it easy for credit to flow from banks to businesses

Does tariff management hinder the re-export of goods

Is bribery or corruption prevalent

Bureaucracy

Indicator name

Code

Optimal value

Disadvantage indicator ranking

Indicator name

Value

Advantage indicator

Code

37

40

−0.15

39

30

35

31

Ranking

4.17

3.23

5.04

1.45

1.94

Value

Table 7.2 Comparison table of international competitiveness advantages and disadvantages of China’s manufacturing environment

203 (the United States)

8.14 (the United States)

8.82 (Finland)

8.52 (Singapore)

9.41 (Finland)

6.71 (Singapore)

Optimal value

122 7 Assessment and Analysis of International Competitiveness of China’s …

Chapter 8

Assessment and Analysis of Basic International Competitiveness of China’s Manufacturing Industry

8.1 Assessment System of Basic International Competitiveness of China’s Manufacturing Industry Based on the indicators and data of The IMD World Competitiveness Yearbook 2005, this chapter selects 23 specific indicators closely related to the international competitiveness of manufacturing industry to form an evaluation system. Taking 41 major economies in the world as the evaluation and research objects, this chapter evaluates and analyzes the basic competitiveness of manufacturing industry in China and major countries and regions. The evaluation system selects four basic competitiveness factors that are closely related to the competition in the manufacturing industry, namely, transportation facilities, information and communication, energy environment and labor quality (see Table 8.1), and then classifies 23 related indicators into evaluation factors, based on which the basic international competitiveness and factor international competitiveness of the manufacturing industry are calculated. In terms of calculation method, first obtain comparable data through standardization for all indicators, and then through the calculation of normal distribution function value to obtain a change range of 0 to 100 competitiveness standard score data, and on this basis, the elements within the elements are equally weighted to obtain the elements competitiveness standard score, the equal weight average of the standard scores of the four factors can get the comprehensive score of the basic international competitiveness of the manufacturing industry. The two-level equal weight average reflects the equal treatment of the competitiveness information reflected by each index and the emphasis on the competitiveness structure, that is, without sufficient reasons and proof, we should not blindly determine the multiple relationship of the weights among the indexes.

© Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_8

123

124

8 Assessment and Analysis of Basic International Competitiveness …

Table 8.1 Basic International competitiveness evaluation index system of manufacturing industry Factor

Code

The index name

Traffic facilities

1.1

Road network density (km/ km2 )

2002

1.2

Railway network density (km/ km2 )

2003

1.3

Number of passengers by air (1,000 people)

2003

1.4

Whether the water transport infrastructure meets the needs of enterprises

2005

S

1.5

Whether the maintenance and development of infrastructure is adequately planned and financed

2005

S

1.6

Whether the infrastructure for the distribution of goods and services is efficient

2005

S

2.1

Investment in telecommunications as a percentage of GDP

2003

2.2

The number of computers per thousand people

2004

2.3

Number of connected households per thousand people

2004

2.4

The number of cellular mobile phone users per thousand households

2003

2.5

Number of broadband subscribers per thousand people

2003

2.6

Number of landlines per thousand households

2003

3.1

Energy intensity, the amount of commercial energy consumed per dollar of GDP (kilojoules)

2001

3.2

Total domestic energy production as a percentage of total demand (%)

2002

3.3

Whether the energy infrastructure is adequate and efficient

2005

Information and communication

Energy environment

Year of data

Characteristics

N

S

(continued)

8.2 Assessment and Analysis of Basic International Competitiveness …

125

Table 8.1 (continued) Factor

Labor quality

Code

The index name

3.4

Industrial carbon dioxide emissions (tons) of US$1 million GDP

Year of data 2002

3.5

Proportion of population receiving wastewater treatment services (%)

2002

3.6

Whether the environmental act impedes business

2005

4.1

Proportion of labor force in population (%)

2004

4.2

Whether skilled labor is readily available

2005

4.3

Total employed population (million people)

2004

4.4

Whether the foreign high-tech labor force is attracted by the domestic business economic environment

2005

4.5

The proportion of the population who have obtained advanced degrees

2002

Characteristics N

S

S

S

Note The characteristics column is marked with the inverse index (N) and the survey index (S). Source The IMD World Competitiveness Yearbook 2005

8.2 Assessment and Analysis of Basic International Competitiveness of China’s Manufacturing Industry 8.2.1 Evaluation of Basic International Competitiveness of Manufacturing Industry Based on the data reported by IMD in 2005, the international competitiveness level of the manufacturing base of 41 economies was evaluated. From the comprehensive evaluation results of the basic competitiveness of the manufacturing industry (see Fig. 8.1), China’s basic competitiveness of the manufacturing industry ranks 30th, 43 points less than the highest score of Switzerland. It lags behind not only developed countries and regions, but also developing countries such as Malaysia (24th), Chile (26th) and Thailand (29th). From the perspective of factor competitiveness, the competitiveness of transportation facilities (see Fig. 8.2) ranks 34th in China. The total transportation volume is large, but the density of transportation network is low and the operation efficiency is not high. Information and communication competitiveness (see Fig. 8.3), China

126

8 Assessment and Analysis of Basic International Competitiveness …

Fig. 8.1 Basic international competitiveness ranking of manufacturing industry foundation in 2005. Source The IMD World Competitiveness Yearbook 2005

Fig. 8.2 International competitiveness ranking of transportation facilities of manufacturing industry in 2005. Source The IMD World Competitiveness Yearbook 2005

ranked 30th, with high investment in telecommunications but low per capita infrastructure ownership. In terms of the competitiveness of energy and environment (see Fig. 8.4), China ranks 39th, only slightly higher than India and Romania. Except for the relatively high proportion of energy self-sufficiency, other indexes rank after 30th. China ranks 22nd in labor quality competitiveness (see Fig. 8.5), 33 points less than the highest score of the United States. The total labor force and employment are sufficient, but the proportion of skilled labor force and advanced education is very backward.

8.2 Assessment and Analysis of Basic International Competitiveness …

127

Fig. 8.3 International competitiveness ranking of information and communication of manufacturing industry in 2005. Source The IMD World Competitiveness Yearbook 2005

Fig. 8.4 International competitiveness ranking of energy environment of manufacturing industry in 2005. Source The IMD World Competitiveness Yearbook 2005

8.2.2 Advantages and Disadvantages of China’s Basic International Competitiveness of Manufacturing Industry From the perspective of factor competitiveness, except for the labor quality ranking 22nd, which is in the middle level, other factors are all after the 30th, which are in a competitive disadvantage group (see Table 8.2). From the perspective of index level, 5 of the 23 indicators ranked before the 20th place, respectively, with the

128

8 Assessment and Analysis of Basic International Competitiveness …

Fig. 8.5 International competitiveness ranking of labor quality of manufacturing industry in 2005. Source The IMD World Competitiveness Yearbook 2005

largest number of labor force and employment, the highest proportion of investment in telecommunications, the 3rd place for air passengers, and the 12th place for domestic energy production to meet the demand. There are many indicators at disadvantage, including 7 after the 35th place. The main disadvantages are insufficient traffic network density, low infrastructure efficiency, low per capita ownership, high energy consumption intensity, high emissions, low proportion of high-tech talents and insufficient attraction and so on.

8.3 Characteristics of Basic International Competitiveness of China’s Manufacturing Industry From the above analysis of the comprehensive level, factor competition level and index performance of the basic international competitiveness of manufacturing industry, China’s basic competitiveness of manufacturing industry presents the following characteristics: there is still a big gap in the overall competitive strength. The construction of transportation and information networks still needs to be significantly improved, and the operational efficiency of infrastructure needs to be fundamentally improved. Energy consumption and waste remain serious, and input in energy conservation and environmental governance needs to be strengthened. Basic labor force is sufficient, but the quality of labor force needs to be improved.

99.4

60.56

754.12

Energy production as a percentage of demand, %

The labor force as a percentage of the population, %

Total employed population, million

3.2

4.1

4.3

1

1

12

1

China

China

875.8 (Norway)

China

Whether skilled labor is readily available Percentage of the population with advanced degrees, %

4.5

Industrial carbon dioxide emissions per million US$ GDP, tons

Energy consumption per US$ GDP (kJ)

Number of Internet householders per thousand people

Road network density, km/km2

4.2

3.4

3.1

2.3

1.1

1.89

588,997 (the US)

Telecommunications investment as a percentage of GDP, %

3

2.1

87,590

Air passengers, thousand

1.3

Indicator name

Disadvantage indicators Optimal value

Code

Ranking

Indicator name

Code

Value

Advantage indicators

5

4.3

3,077.7

27,435

78.53

0.18

Value

40

38

40

37

38

35

Ranking

Table 8.2 Comparison of basic international competitiveness advantages and disadvantages of China’s manufacturing industry

51 (Canada)

7.85 (the Philippines)

154.6 (the Swiss)

4,245 (the Swiss)

708.5 (Iceland)

4.9 (Belgium)

Optimal value

8.3 Characteristics of Basic International Competitiveness of China’s … 129

Chapter 9

Foreign Trade Development of China’s Industrial Sector and Its International Competitiveness

With the continuous expansion of opening up, China’s economy has maintained rapid growth, and foreign trade has made great progress both in terms of scale and structure. Especially after China’s accession to the WTO, the adjustment of the global economic structure and the opportunity of international industry transfer have made China’s foreign trade growth rate increase rapidly in recent years, maintaining over 20% rapid growth for three consecutive years. However, it is undeniable that compared with developed countries, China’s overall level of foreign trade is not high, and the trade structure is still relatively backward. Therefore, it is of great significance to systematically grasp China’s foreign trade and understand the competitiveness of China’s industrial industries in order to formulate foreign trade development strategies and policies and improve the international competitiveness of foreign trade. This chapter mainly evaluates and analyzes the international trade competitiveness of 22 major categories of industries including mining industry and manufacturing industry in the industry standard classification of China’s national economy. This paper first describes the characteristics and evolution trend of China’s industrial industry’s foreign trade, and then measures and analyzes the foreign trade competitiveness of China’s industrial industry by using the index of international trade competitiveness and the index of explicit comparative advantage.

© Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_9

131

132

9 Foreign Trade Development of China’s Industrial Sector and Its …

Fig. 9.1 Total volume of China’s industrial products import and export and its growth from 1999 to 2004 (Source China Statistical Yearbook 2000–2005)

9.1 Characteristics and Development of Foreign Trade in China’s Industrial Sector 9.1.1 The Total Volume of Foreign Trade in Industrial Products Continued to Grow From 1999 to 2004, under the favorable economic environment at home and abroad, China’s total foreign trade of industrial products continued to grow, with an average annual growth rate of 26.8% (see Fig. 9.1). Rapid industrial growth during this period was the main force to promote foreign trade exports. In addition, the recovery of the world economy, the implementation of export tax rebate policy, the reform of foreign trade system, and the stability of RMB exchange rate have expanded the market space of China’s foreign trade development to a certain extent, so as to promote the development of industrial foreign trade.

9.1.2 The External Trade of Industrial Products is Generally in a State of Surplus, and the Dependence on Exports Continues to Increase With the increase of China’s economic openness, the scale of foreign trade of industrial products has continued to expand. From 1999 to 2004, the trade surplus was realized for six consecutive years, and the surplus was gradually expanding. In 2004, the proportion of China’s industrial products exports to total industrial output value increased significantly compared with 1999, reaching 24.9 percentage points, an increase of 22%. However, its proportion in the total industrial output value

9.2 International Competitiveness Index of Trade in China’s Industrial Sector

133

is not a trend growth, but a rise and a fall, indicating that during this period, due to China’s system reform and changes in the world pattern, the increase and decrease of export volume is uncertain.

9.1.3 Fundamental Changes in the Structure of Export Trade From the basic situation that the export volume of major industrial sectors accounts for the proportion of total exports in China, the export of industrial products has experienced the stage from light industrial textiles to high-tech products as the main support and new growth point, and successfully controlled the gradual upgrading process of export product structure. High-tech products will become the main products of China’s exports in the next few years. In the mid-1980s, the export of industrial products was dominated by textiles and clothing, accounting for 24% of total exports. In the 1990s, the export value of communication equipment, computers and other electronic equipment manufacturing industries increased from the third to the second; by 2004, high-tech products represented by information technology have increasingly shown active vitality and become a new bright spot to promote China’s rapid export growth, accounting for half of total exports. From the situation that the import volume of major industries accounts for the total import volume, the types of imported products remain basically unchanged over time, and most of them belong to technology-intensive industries, there are mainly including that communications equipment, computers and other electronic equipment manufacturing, specialized equipment manufacturing, metal manufacturing, and chemical raw materials and chemical manufacturing. Among them, the fastest growing proportion of imports to total imports was in communications equipment, computers and other electronic equipment manufacturing, from 37.6% in 2000 to 41.7% in 2004; the fastest falling industries were the textile industry, textiles, clothing, footwear and hat manufacturing, which fell from 2.5% and 0.47% in 2000 to 1.3% and 0.23% in 2004, respectively.

9.2 International Competitiveness Index of Trade in China’s Industrial Sector Internationally, the following indicators are commonly used to reflect the relative level and dynamic changes of international competitiveness of industries: trade specialization index (TSC), display comparative advantage index (RCA), export performance relative index (IREP), net export index and factor intensive degree index (auxiliary indicator), labor intensity index (LCI). Among them, TSC, RCA

134

9 Foreign Trade Development of China’s Industrial Sector and Its …

and IREP are based on the theory of international trade, as a measure of the comparative advantage of a certain type of industry exports and the strength of international competitiveness. This paper uses the international competitiveness index (TC) and the display comparative advantage index (RCA) to analyze the international competitiveness of China’s 22 industrial sectors. The basic formula of the trade international competitiveness index (TC) is: T C=

Exports - Imports Exports + Imports

(9.1)

It is mainly used to reflect the relative size of net imports or net exports and the competitiveness of a certain industry or product in a country in the international market. The value is between −1 and 1. This article lists products with a competitiveness index greater than or equal to 0.8 as products with a high comparative advantage or strong competitiveness; products with a competitiveness index between 0.5 and 0.8 are listed as products with higher comparative advantage or higher competitiveness; products between 0 and 0.5 are classified as strong competitive products; products equal to 0 are listed as generally competitive products. Similarly, products with a competitive index between −1 and −0.8, −0.8 and −0.5, and −0.5 and 0 are considered to be very low competitive, lower competitive, and low competitive products. Although the policies of encouraging exports or restricting imports are common in reality, the competitiveness index can not accurately reflect the actual situation of product competitiveness. However, as a comparative static analysis, it can examine competitiveness or comparative advantage at a specific time, specific level of protection. Table 9.1 shows the results of the analysis of the international trade competitiveness index of 22 industrial sectors from 1999 to 2004. It can be seen that the international competitiveness of China’s industrial sector has basically shown the following characteristics. Firstly, the overall TC index shows that the international competitiveness of China’s industrial industry is still low-level in the industry structure. Labor-intensive products are still the most advantageous industries in China, and most of the manufactured products that are exported are still primary and semi-processed products with low added value, shallow processing and low technical content. Export competitivenesses of technology or capital intensive products are still weak. Secondly, traditional labor-intensive export products are highly competitive, while the export competitiveness of technology-or capital-intensive products is still relatively weak. The food manufacturing, textile, leather, beverage, non-metallic mineral and handicraft manufacturing industries have always had comparative advantages. Among them, the international competitiveness index of trade in textiles, clothing, shoes and hats has been maintained at above 0.9, and there is a tendency to gradually become larger, which is in the trend of increasing international competitiveness of trade.

9.2 International Competitiveness Index of Trade in China’s Industrial Sector

135

Table 9.1 Analysis of the international competitiveness index of trade in major industrial sectors from 1999 to 2004 Code

Industries*

1999

B07

Oil and gas extraction industry

−0.3143

−0.4494

−0.3517

−0.3922

−0.4493

−0.5367

Low

Low

Low

Low

Low

Lower

−0.2348

−0.2151

−0.2088

−0.3539

−0.5364

Low

Low

Low

Low

Lower

B10

C13

C14

C15

C16

C17

Non-metallic −0.1171 mining and Low dressing industry Agricultural and −0.8120 sideline food Very low processing industry Food industry

C19

C20

C22

2001

2002

2003

2004

−0.7760

−0.7360

−0.8720

−0.9164

−0.9275

Lower

Lower

Very low

Very low

Very low

0.8234

0.8420

0.7573

0.7903

0.8276

0.8177

Very strong

Very strong

Stronger

Stronger

Very strong

Very strong

Beverage manufacturing industry

0.5759

0.5076

0.5939

0.6027

0.5387

0.4800

Stronger

Stronger

Stronger

Stronger

Stronger

Strong

Tobacco products industry

0.5887

0.1937

0.1804

0.2811

0.2325

0.2750

Stronger

Strong

Strong

Strong

Strong

Strong

Textile industry 0.6121 Stronger

C18

2000

Textile clothing, 0.9197 shoes, hat Very manufacturing strong industry Leather, fur, 0.4031 feather (down) Strong and its products industry Wood processing −0.1493 and wood, Low bamboo, rattan, palm, grass products industry Papermaking and paper products industry

0.5980

0.5940

0.6345

0.6887

0.7086

Stronger

Stronger

Stronger

Stronger

Stronger

0.9290

0.9301

0.9358

0.9419

0.9452

Very strong

Very strong

Very strong

Very strong

Very strong

0.4041

0.4187

0.4502

0.4747

0.4549

Strong

Strong

Strong

Strong

Strong

−0.1651

−0.0921

−0.0780

−0.0341

0.0733

Low

Low

Low

Low

Strong

−0.6422

−0.5798

−0.5467

−0.5184

−0.4803

−0.4615

Lower

Lower

Lower

Lower

Low

Low

(continued)

136

9 Foreign Trade Development of China’s Industrial Sector and Its …

Table 9.1 (continued) Code

Industries*

1999

2000

2001

2002

2003

2004

C26

Chemical raw materials and chemical products manufacturing industry

−0.2859

−0.3302

−0.3082

−0.3377

−0.3376

−0.3799

Low

Low

Low

Low

Low

Low

C27

C28

C29

Pharmaceutical manufacturing industry

−0.0040

−0.0878

−0.1445

−0.1771

−0.2052

−0.1764

Low

Low

Low

Low

Low

Low

Chemical fiber manufacturing industry

−0.2902

−0.2501

−0.1876

−0.1222

−0.0243

0.0929

Low

Low

Low

Low

Low

Strong

Rubber products −0.1104 industry Low

C30

Plastic products industry

C31

Non-metallic mineral products industry

C34 C40

C37

C41

C42

Metal products industry Communication equipment, computers and other electronic equipment manufacturing industry Transportation equipment manufacturing industry

−0.3876

−0.1210

−0.1070

−0.1852

−0.1100

Low

Low

Low

Low

−0.3871

−0.3900

−0.3676

−0.3564

−0.3632

Low

Low

Low

Low

Low

Low

0.4465

0.3891

0.3824

0.4480

0.4503

0.4838

Strong

Strong

Strong

Strong

Strong

Strong

−0.0909

−0.1075

−0.1529

−0.1632

−0.2211

−0.0521

Low

Low

Low

Low

Low

Low

−0.0954

−0.0778

−0.0637

−0.0392

−0.0088

0.0288

Low

Low

Low

Low

Low

Strong

0.0453

0.1883

−0.0327

−0.0440

−0.0579

0.0377

Strong

Strong

Low

Low

Low

Strong

0.0206

−0.1144

−0.2046

−0.3327

−0.3682

Strong

Low

Low

Low

Low

0.4408

0.4350

0.4844

0.5370

0.5787

0.6032

Strong

Strong

Strong

Stronger

Stronger

Stronger

Instrumentation 0.0766 and culture, Strong office machinery manufacturing industry Crafts and other manufacturing industry

−0.0995 Low

Note The industry name is in bold and always maintains a strong competitive industry. The italics are always low-competitive industries Source China Statistical Yearbook 2000–2005

9.3 Index of Relative Export Performance of Trade in China’s Industrial Sector

137

Thirdly, the export competitivenesses of the most industries have increased, and only a few industries have declined. Among them, the TC index of capital technologyintensive industries such as chemical fiber and communication equipment manufacturing rose the fastest, increasing by 0.38 and 0.12 percentage points respectively. The instrumentation, culture and office machinery manufacturing industry showed a downward trend, from 0.0766 in 1999 to −0.3682 in 2004, which was in a process of transition from strong to weak.

9.3 Index of Relative Export Performance of Trade in China’s Industrial Sector The revealed comparative advantage index (RCA), also known as the relative export performance index (REP), refers to the share of a country’s exports of a product or industry in the world’s exports of the product and the share of exports of all products in the country to the world’s total exports. The basic formula is: RC Ai j = (X i j

/ ∑

/ ∑ / ∑ ∑ Xi Xi j ) ( Xi )

(9.2)

∑ X i j is the total X i j indicates the export amount of ∑ country i on commodity j; X i on commodity j; is the export amount of all the products export of national i ∑ ∑ X i represents the world’s total export share. According to the of the country. standards set by the Japan External Trade Organization (JERTO), if the RCA index is greater than 2.5, it indicates that the country’s products have extremely strong international competitiveness; less than 2.5 and greater than 1.25, indicating that the country’s products have strong international competitiveness; if it is greater than 0.8 and less than 1.25, indicating that the international competitiveness of the country’s products is average; if less than 0.8, it indicates that the international competitiveness of the country’s products is weak. This chapter uses the data published by the United Nations Statistics1 1 website and the data of the China Statistical Yearbook from 2002 to 2004 to calculate the total export products of 22 industries and the display comparative advantage index of the sub-sectors. Table 9.2 is arranged according to the international competitiveness of industries in 2004. Generally speaking, from 2002 to 2004, the display comparative advantage index of China’s industrial products showed an upward trend, both of which fluctuated around 1, indicating that although the international competitiveness of China’s industrial products has improved, the level is average. The RCA index shows that the industries with extremely strong international competitiveness are textile and clothing, 1

1 The data is classified according to the Coding and Coordination System for Commodity Names, referred to as the HS2002 classification. The classification criteria for the customs import and export commodity classification amount table in the China Statistical Yearbook are the same, and the data is comparable.

Industry name

Textile clothing, shoes, hat manufacturing

Leather, fur, down and its products industry

Textile industry

Crafts and other manufacturing industry

Chemical fiber manufacturing industry

Non-metallic mineral products industry

Communication equipment, computers and other electronic equipment manufacturing industry

Metal products industry

Food manufacturing industry

Code

C18

C19

C17

C42

C28

C31

C40

C34

C14

0.0236

∑ X ∑ ∑ i j Xi

0.0081 0.0246 0.0027

0.0146

Average

0.0581

Average

0.3149

Strong

0.0168

Strong

0.0152

0.0114

0.0533

0.2927

0.0117

0.0074

Extremely strong

0.0071

Extremely strong

0.0820

Extremely strong

0.0287

Extremely strong

0.0996

X ∑ i j Xi

2002

Table 9.2 Explicit comparative advantage index analysis of export products by industry

1.2865

1.0897

1.0759

1.4336

2.0500

2.6181

3.3289

3.5181

4.2212

RC Ai j 0.0239

∑ X ∑ ∑ i j Xi

0.0081 0.0258

0.0127

Average

0.0573

Average

0.3264

Strong

0.0158

Strong

0.0149

Strong

0.0065

0.0120

0.0555

0.2878

0.0116

0.0073

0.0028

Extremely strong

0.0784

Extremely strong

0.0264

Extremely strong

0.0889

X ∑ i j Xi

2003

1.0563

1.0330

1.1341

1.3603

2.0420

2.2971

3.0382

3.2418

3.7156

RC Ai j 0.0216

∑ X ∑ ∑ i j Xi

0.0076 0.0243

0.0118

Average

0.0737

Strong

0.3345

Strong

0.0157

Strong

0.0147

Strong

0.0060

0.0112

0.0654

0.2957

0.0113

0.0073

0.0026

Extremely strong

0.0724

Extremely strong

0.0230

Extremely strong

0.07650

X ∑ i j Xi

2004

(continued)

1.0496

1.1271

1.4124

1.3909

2.0020

2.3546

2.9801

3.0198

3.5428

RC Ai j

138 9 Foreign Trade Development of China’s Industrial Sector and Its …

Industry name

Wood processing and wood, bamboo, rattan, palm, grass products industry

Instrumentation and culture, office machinery manufacturing industry

Plastic products industry

Rubber products industry

Chemical raw materials and chemical products manufacturing industry

Non-metallic mining and dressing industry

Paper and paper products industry

Oil and gas extraction industry

Tobacco products industry

Transportation equipment manufacturing industry

Code

C20

C41

C30

C29

C26

B10

C22

B07

C16

C37

Table 9.2 (continued)

0.0324

Weak

0.0013

Weak

0.0259

Weak

0.0072

Weak

0.0130

Weak

0.0240

Weak

0.0061

Weak

0.0247

Weak

0.0292

Average

0.0110

Strong

X ∑ i j Xi

2002

0.1367

0.0033

0.0709

0.0204

0.0234

0.0423

0.0091

0.0327

0.0366

0.0111

∑ X ∑ ∑ i j Xi

0.2371

0.4032

0.3653

0.3517

0.5585

0.5677

0.6705

0.7539

0.7993

0.9832

RC Ai j

0.0356

Weak

0.0011

Weak

0.0254

Weak

0.0069

Weak

0.0112

Weak

0.0233

Weak

0.0058

Weak

0.0228

Average

0.0299

Average

0.0099

Average

X ∑ i j Xi

2003

0.1307

0.0030

0.0686

0.0197

0.0254

0.0429

0.0099

0.0330

0.0364

0.0108

∑ X ∑ ∑ i j Xi

0.2721

0.3771

0.3696

0.3513

0.4413

0.5434

0.5890

0.6910

0.8212

0.9232

RC Ai j

0.0354

Weak

0.0009

Weak

0.0244

Weak

0.0064

Weak

0.0110

Weak

0.0223

Weak

0.0064

Weak

0.0221

Average

0.0322

Average

0.0102

Average

X ∑ i j Xi

2004

0.1242

0.0026

0.0721

0.0182

0.0262

0.0426

0.0100

0.0344

0.0374

0.0109

∑ X ∑ ∑ i j Xi

(continued)

0.2849

0.3281

0.3387

0.3525

0.4222

0.5245

0.6398

0.6414

0.8610

0.9404

RC Ai j

9.3 Index of Relative Export Performance of Trade in China’s Industrial Sector 139

Beverage manufacturing industry

Agricultural and sideline food processing industry

Pharmaceutical manufacturing industry

C15

C13

C27

Source http://unstats.un.org

Industry name

Code

Table 9.2 (continued)

Weak

0.0024

Weak

0.0003

Weak

0.0018

Weak

X ∑ i j Xi

2002

0.0256

0.0035

0.0070

∑ X ∑ ∑ i j Xi

0.0950

0.0935

0.2636

RC Ai j

Weak

0.0021

Weak

0.0003

Weak

0.0014

Weak

X ∑ i j Xi

2003

0.0265

0.0038

0.0070

∑ X ∑ ∑ i j Xi

0.0789

0.0756

0.2030

RC Ai j

Weak

0.0019

Weak

0.0003

Weak

0.0013

Weak

X ∑ i j Xi

2004

0.0266

0.0036

0.0065

∑ X ∑ ∑ i j Xi

0.0697

0.0732

0.1933

RC Ai j

140 9 Foreign Trade Development of China’s Industrial Sector and Its …

9.4 Analysis of the International Competitiveness of Trade in China’s Major …

141

shoes and hats manufacturing industry, leather, fur, feather (down) and its products industry and textile industry. International competitiveness of trade are agricultural and sideline food processing, pharmaceutical manufacturing, oil and gas exploration, non-metallic mining and dressing industry, paper industry and paper products industry.

9.4 Analysis of the International Competitiveness of Trade in China’s Major Industrial Industries According to the calculation results of trade international competitiveness index and display comparative advantage index, this paper makes a comparative analysis on the inter-national competitiveness of trade in China’s major industrial industries.

9.4.1 Labor-Intensive Industry It mainly includes textile clothing, shoes, hats manufacturing industry, leather, fur, feather (down) and its products industry and textile industry. It is China’s most internationally competitive export industry. China is a country with a large population, and labor resources account for 26.3% of the world total. Coupled with the low level of economic development, this status quo determines China’s comparative advantage and competitive advantage in developing labor-intensive industries. Different from the analysis of the international competitiveness index of trade, the display comparative advantage index of these three industries showed a downward trend. In 2004, it decreased by 16%, 14% and 10% respectively compared with 2002. It shows that although the proportion of China’s traditional export products’ trade surplus to total exports has increased, it is still lower than the world’s development level and faces various challenges of international competition.

9.4.2 Capital, Technology-Intensive Industries Capital-intensive industries mainly include communication equipment, computers and other electronic equipment manufacturing, chemical raw materials and chemical products manufacturing, and metal products. The calculation results of the TC index and the RCA index show that in 2004, the export products of capital and technologyintensive industries showed a certain degree of differentiation. The international competitiveness of the communications equipment, computers and other electronic equipment manufacturing industries is on the rise, and the chemical raw materials and chemical products manufacturing and metal products industries have been in a relatively low comparative advantage.

142

9 Foreign Trade Development of China’s Industrial Sector and Its …

9.4.3 Industry that Produces Primary Products Such as Raw Materials and Fuels The industries that produce primary products such as raw materials and fuels mainly include agricultural and sideline food processing industries and oil and natural gas mining. With the rapid development of China’s economy, China’s energy supply has become increasingly difficult to meet domestic demand, and has gradually become a pure importer of raw materials and fuels, losing its comparative advantage in the international market. With the development of China’s industrialization process, primary products such as energy and resources will become the limiting factors for China’s economic development, and the degree of external dependence will continue to deepen.

9.5 Conclusions Firstly, the total import and export volume of China’s industrial industry continues to grow rapidly, the structure of export products is continuously optimized, and the international competitiveness of trade is gradually improving. On the one hand, due to the sustained rapid economic growth and the active promotion of the government, it has provided a good macroeconomic environment for import and export trade; on the other hand, the increase in foreign direct investment has greatly affected the scale of China’s import and export and become the main driving force for rapid growth of import and export. Secondly, according to the analysis of the international competitiveness index of trade index and the indicative comparative advantage index, 22 industrial industries can be basically divided into the following four categories: industries with stable comparative advantages represented by the textile industry, clothing, shoes and hat manufacturing industries; industries represented by instrumentation and cultural office machinery which are in the decreasing transformation from comparative advantage to comparative disadvantage; industries which are transformed from comparative disadvantage to comparative advantage, represented by communication equipment, computers and other electronic equipment manufacturing industries; industries at a long-term comparative disadvantage represented by raw materials and chemical products manufacturing. Thirdly, labor-intensive industries are still the leading industries of China’s foreign trade, and the international competitiveness of trade in capital and technologyintensive industries has steadily increased.

Chapter 10

Industrial Competitiveness Among China’s Industrial Sectors and Sector Selection

This chapter evaluates and analyzes the industrial competition and development direction of 39 major industries in the mining, manufacturing, power, gas and water production and supply industries in China’s industry standard classification, including three levels: firstly, the competitiveness among industrial sectors is evaluated according to the evaluation index system and calculation method of China’s manufacturing industry competitiveness; secondly, this chapter observes the basic characteristics of various industries supporting employment and creating added value to support economic and social development; thirdly, the energy consumption and environmental protection of the industry development are discussed again. On the basis of three levels of discussion, this chapter discusses the industry selection of China’s industrial development.

10.1 Assessment on Industrial Competitiveness Among China’s Industrial Sectors in 2006 The chapter first quotes China’s regional manufacturing industry competitiveness evaluation index system and calculation method (Zhao et al. 2005). The evaluation of their competitiveness is based on the evaluation of 39 national standard industries under the industrial industry. The data cited in the calculation are the survey data of China’s state-owned and non-state-owned industrial enterprises in 2005, including more than 269,000 industrial enterprises. Comprehensive competitiveness (see Fig. 10.1), except for the top 5 industries with obvious scoring advantages, other industries scored relatively close. The first of these, communication equipment, computers and other electronic equipment manufacturing industry, scored highest in innovation and market competitiveness, but was average in growth competitiveness (29th); the oil and gas extraction industry ranks first in terms of competitiveness, cost, investment and management competitiveness, but its performance in market and innovation is average, showing the characteristics © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_10

143

144

10 Industrial Competitiveness Among China’s Industrial Sectors …

of its energy industry; ferrous metal smelting and rolling processing industry ranks the closest in terms of various factors, except for the growth competitiveness ranking 14th, other factors are all within the top 10. Competitive strength (see Fig. 10.2), the textile industry’s previous 12 industries have obvious advantages. The performance of the energy industry’s competitive advantage is very obvious. In the performance of the 21 measurement points of the top 3 absolute advantages of the 7 indicators, the energy industry accounted for 43%. The ferrous metal smelting and rolling processing industry is the industry with the highest added value; the oil and gas extraction industry is the industry with the highest profit, and the value-added rate and capital profit rate are also the highest; the electricity and heat production and supply industry is the industry with the highest

Fig. 10.1 Ranking of comprehensive competitiveness among China’s industrial sectors

10.1 Assessment on Industrial Competitiveness Among China’s Industrial …

145

capital; textile industry is the industry with the highest labor force; tobacco products industry is the industry with the highest labor capital. Growth competitiveness (see Fig. 10.3), all other mining industry indicators are in the top 5, all indicators of ferrous metal mining and dressing industry are in the top 7, its performance is the most balanced. The performance of electricity and heat

Fig. 10.2 Ranking of competitive strength among China’s industrial sectors

146

10 Industrial Competitiveness Among China’s Industrial Sectors …

production and supply industry in the capital, profit, and labor capital is very prominent. The capital and labor capital of the three industries in the production and supply of electricity, gas and water are much higher than other industries. As an emerging industry, waste resources and waste materials recycling and processing industry have shown strong growth in sustainable development strategies that are environmentally friendly. Relatively speaking, the growth competitiveness of industries such as medicine, petroleum processing, chemical fiber, and transportation equipment manufacturing are insufficient. Market competitiveness (see Fig. 10.4), the best performers in terms of market share (total and ratio indicators) are followed by communication equipment, computers and other electronic equipment manufacturing industry, electrical machinery and equipment manufacturing industry, and textile industry. The four indicators for market share are ranked in the top 10. The best performing industries in terms of market growth (growth rate indicators) are ferrous metal mining and dressing industry, waste resources and waste materials recycling and processing industry, other mining industry and furniture manufacturing industry, and all three indicators related to market growth are ranked top 10. Industries with a ratio of export products approaching and exceeding 50% are followed by culture and education and sports goods manufacturing industry, communication equipment, computers and other electronic equipment manufacturing industry, instrumentation and culture, office machinery manufacturing industry, furniture manufacturing industry, leather, fur, feathers (down) and its products industry, handicrafts and other manufacturing industry, textile clothing, shoes, hat manufacturing industry and many more, their product exports are much higher than other industries. Cost competitiveness (see Fig. 10.5), there are no industries with consistent advantages, but the cost advantages of oil and gas extraction industry, tobacco products industry, waste resources and waste materials recycling and processing industry are more obvious. The oil and gas exploration industry is the most cost-competitive, with most of the indicators ranked in the top 8 of the lowest cost, but its labor cost is the highest 2nd; the tobacco products industry has the highest labor cost, faster growth, and higher sales costs. In addition, other costs are lower, with the lowest cost of sales; waste recycling and waste materials recycling and processing industry is the third highest cost of sales, and other costs are lower. Innovation competitiveness (see Fig. 10.6), the advantages of advantageous industries are obvious, and the gaps between industries are large. The top 10 industries have obvious competitive advantages, especially in the past three industries. The communication equipment, computers and other electronic equipment manufacturing industry has absolute advantages, and all indicators are in the top 3, and the scores are close to perfect scores; all indicators of electrical machinery and equipment manufacturing industry are in the top 10; transportation equipment manufacturing industry, instrumentation and cultural, office machinery manufacturing industry, general equipment manufacturing industry, except for the unit export delivery value ranked about 15, other indicators are in the top 10. Investment competitiveness (see Fig. 10.7), the oil and gas extraction industry has obvious advantages, and the other industries have little difference before and after.

10.1 Assessment on Industrial Competitiveness Among China’s Industrial …

147

Fig. 10.3 Ranking of growth competitiveness among China’s industrial sectors

The three industries of electricity, gas and water production and supply are at the bottom, as a public sector, the investment competitiveness is obviously inferior. From the performance indicators of six performance returns, oil and gas extraction industry occupies three No. 1; the tobacco products industry occupies three No. 2; the ferrous

148

10 Industrial Competitiveness Among China’s Industrial Sectors …

Fig. 10.4 Ranking of market competitiveness among China’s industrial sectors

metal mining and mining industry occupies four of the top three positions; nonferrous metal mining and dressing industry occupies three of the top three positions; the waste resources and waste materials recycling and processing industry occupy one first position and four of the top ten positions. They are all industries with high return on investment.

10.1 Assessment on Industrial Competitiveness Among China’s Industrial …

149

Fig. 10.5 Ranking of cost competitiveness among China’s industrial sectors

Management competitiveness (see Fig. 10.8), the first four industries have obvious advantages, and the water production and supply industry are inferior. In addition to the rapid increase in net receivables, the oil and gas exploration industry ranked the top 10 in other indicators; in addition to the slowest turnover of current assets, the

150

10 Industrial Competitiveness Among China’s Industrial Sectors …

Fig. 10.6 Ranking of innovation competitiveness among China’s industrial sectors

tobacco products industry ranked the top 10 in other indicators, and its net receivables grew the fastest. Waste resources and waste materials recycling and processing industry performs better on most indicators and support their growth.

10.2 Basic Characteristics of Industrial Sectors in Sustaining the Economic …

151

Fig. 10.7 Ranking of investment competitiveness among China’s industrial sectors

10.2 Basic Characteristics of Industrial Sectors in Sustaining the Economic Development At this stage of China, the formulation of industrial policies and the coordination of industrial development need to observe the supporting force of different industries

152

10 Industrial Competitiveness Among China’s Industrial Sectors …

Fig. 10.8 Ranking of management competitiveness among China’s industrial sectors

for macro-level objectives. This chapter selects different indicators from two levels to show the supporting force of various industries for macro-level targets, and the performances of key indicators of their participation in industrial competition.

10.2 Basic Characteristics of Industrial Sectors in Sustaining the Economic …

153

10.2.1 Macro Target Feature Support for macro goals as a basic feature of industry selection and development can be described in four aspects: creating value, providing employment, supporting innovation, and guaranteeing exports. They can also be summarized as four specific indicators described in terms of total volume.

10.2.1.1

Create Value: Added Value

The creation of added value is the basic role of enterprises in the economic cycle. There are large disparities among 39 industries. The ferrous metal smelting and rolling processing industry, communication equipment, computers and other electronic equipment manufacturing industry, electricity and heat production and supply industry are the three industries with the highest added value, with added value of more than RMB550 billion, accounting for 24% of the added value of all industries; 8 industries with an added value of more than RMB300 billion, 11 industries with less than RMB50 billion, and 2 industries with less than RMB10 billion.

10.2.1.2

Provide Employment: Labor Force

Due to the large population of China and the pressure of employment, while the development of the industry is improving the level of technology and innovation, the absorption of labor force is one of the important macro goals. There are 22 industries with a labor force of more than 1 million, of which 9 industries have more than RMB3 million, and the textile industry is close to RMB6 million. It is the industry with the most labor force. There are five industries with a workforce of less than 200,000.

10.2.1.3

Support Innovation: New Product Output Value

Innovation is the core of industrial development. The selection for innovative industries and the continuous innovation in production, R&D and management within the existing industries are the key to improve the competitiveness of China’s industries and the direction of future industrial development. There are 24 industries with output value of more than RMB10 billion, of which 5 industries have more than RMB100 billion, and communication equipment, computers and other electronic equipment manufacturing industry, and transportation equipment manufacturing industry have exceeded RMB500 billion. There are 15 industries with a new product output value of less than RMB10 billion, of which 6 industries are less than RMB1 billion.

154

10.2.1.4

10 Industrial Competitiveness Among China’s Industrial Sectors …

Guarantee Export: Export Delivery Value

As a developing large manufacturing country, China plays a special role in the world trade system. Increasing exports is one of the important supports for economic development at this stage. Improving the scientific and technological content of export products and reducing the resource content of export products are the future development directions. There are 20 industries with export delivery value of over RMB50 billion, of which 13 industries have more than RMB100 billion. The communication equipment, computers and other electronic equipment manufacturing industry is much higher than other industries, reaching RMB1.6 trillion. There are 9 industries with export delivery value less than RMB10 billion.

10.2.2 Industrial Competition Characteristics In addition to the four key characteristic indicators analyzed above, the following indicators are worthy of attention in the industry competition, they are: capital amount, profit amount, labor productivity, R&D expenses, R&D funds per unit, export product ratio, product sales profit, capital profit rate, market share, R&D return rate, total asset contribution rate and other 11 competitive indicators reflecting total amount, innovation, market and efficiency. The top 10 industries and the last industry of these indicators are as follows.

10.2.2.1

Capital Amount

Among the 39 industries, there are 33 industries with capital of more than RMB100 billion, and 6 industries with more than RMB1 trillion, and RMB3.7 trillion of capital for power and heat production and supply. The only industry with capital less than RMB10 billion is other mining industry.

10.2.2.2

Profit Amount

There are 26 industries with a profit of more than RMB10 billion, of which 3 industries have more than RMB100 billion, and the oil and gas exploration industry is nearly RMB300 billion. There are five industries with a profit of less than RMB5 billion, among them the water production and supply industry, petroleum processing industry, coking and nuclear fuel processing industry are negative.

10.2 Basic Characteristics of Industrial Sectors in Sustaining the Economic …

10.2.2.3

155

Labor Productivity

There are 16 industries with labor productivity (increased annual value added by employees) of more than RMB100,000, of which 5 industries have more than 200,000, of which tobacco products industry exceeds RMB1 million yuan, and oil and natural gas use is as high as RMB560,000. There are 4 industries with labor productivity of less than RMB50,000.

10.2.2.4

R&D Expenses

There are 16 industries with research and development fees of more than RMB1 billion, of which 5 industries with more than RMB5 billion, and more than RMB20 billion for communication equipment, computers and other electronic equipment manufacturing industry. There are 6 industries with research and development costs of less than RMB100 million.

10.2.2.5

R&D Expenses Per Unit

There are 16 industries with R&D expenses per unit invested of per RMB10,000 of sales revenue more than RMB20 and 7 industries with more than RMB50. There are 8 industries with a unit R&D expenses per unit of less than RMB10.

10.2.2.6

Export Product Ratio

There are 13 industries with an export product ratio of over 20%, of which 50% have 5 industries. There are 13 industries with an export product ratio of less than 5%, and less than 1% have 4 industries.

10.2.2.7

Product Sales Profit

There are 17 industries with a sales profit of over RMB50 billion, of which 6 industries have more than RMB150 billion, and three seats in energy industry. There are 4 industries with a sales profit of less than RMB10 billion.

10.2.2.8

Capital Profit Rate

There are 30 industries with a capital profit rate above 5%, and 10% of them have 5 industries. There are 5 industries with a capital profit margin of less than 3%, and 2 industries with negative values.

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10.2.2.9

10 Industrial Competitiveness Among China’s Industrial Sectors …

Market Share

There are 10 industries with a market share of more than 5%, of which 10% have 3 industries. There are 11 industries with a market share of less than 1%.

10.2.2.10

R&D Return Rate

R&D rate refers to the ratio of new product output value brought by unit research and development funds. There are 16 industries with a ratio of more than 30 times, of which there are 3 industries with 50 times or more, waste recycling and waste materials recycling industry up to 83.3 times. There is only one industry with a R&D return of less than one.

10.2.2.11

Total Asset Contribution Rate

The contribution rate of total assets reflects the profitability of all assets of the company. There are 34 industries with more than 10% of the ratio, of which 15% have 10 industries and more than 50% have 2 industries. There are two industries with a total asset contribution rate of less than 5%.

10.3 Consumption of Energy and Environmental Protection with the Development of the Industrial Sectors Sustainable development requires industries to develop in the direction of low energy consumption and low pollution. The report selects 10 indicators describing the energy consumption and environmental protection of the industry (see Table 10.1), and calculates the index value of the unit output value for the total industrial output value of 39 industries. On this basis, the standardized values of a single index in 39 industries are calculated and returned to the normal score, and then the energy consumption index and environmental protection index are obtained by simple average.

10.3.1 Industry Energy Consumption From the perspective of energy consumption in 39 industries (see Fig. 10.9), the output value of communication equipment, computers and other electronic equipment manufacturing industry units is the least. There are 7 industries scored above 80 points, 11 industries scored 70–80 points, and 3 industries scored 60–70 points,

10.4 Industry Selection and Strategic Industry for Industrial Development

157

Table 10.1 Indicator composition of energy consumption and environmental index Energy index

Energy consumption per unit of output value, ton of standard coal / RMB10,000 Electricity consumption per unit of output value, kWh/ RMB10,000*

Environmental protection index

Waste water discharge per unit of output value, ton / RMB10,000* Emissions per unit of output value, cubic meters / RMB10,000* Industrial sulfur dioxide emissions per unit of output value, tons / RMB100 million* Soot emissions per unit of output value, tons / RMB100 million* Dust emissions per unit of output value, tons / RMB100 million* Production of industrial solid waste per unit of output value, tons / RMB 100,000* Emissions of industrial solid waste per unit of output value, tons / RMB 10,000*

Note The indicator marked with * is the inverse indicator, that is, the larger the value, the lower the score

the top 21 enterprises had little difference in energy consumption, the energy consumption of the next 18 industries increased rapidly.

10.3.2 Industry Environmental Impact Judging from the emission of pollutants from 39 industrial units (see Fig. 10.10), the 18 industries with a score of more than 63 have little difference, that is, each industry has its own advantages and disadvantages in pollutant emission per unit output value, and the difference is not great. The other 21 industries have large differences in pollutant emissions.

10.4 Industry Selection and Strategic Industry for Industrial Development Different countries will choose different industries as their strategic industries at different stages of development, and protect and give priority to such industries. For example, the United States is currently focusing on the energy industry. Due to the historical development stage and the characteristics of the national conditions,

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10 Industrial Competitiveness Among China’s Industrial Sectors …

Fig. 10.9 Comparison of energy consumption indices between China’s industrial sectors

China needs to consider multiple factors and objectives in the selection of strategic industries. The specifics can be summarized as follows: (1) Strong performance in terms of output size and efficiency, and can or has the promise of participating in international competition;

10.4 Industry Selection and Strategic Industry for Industrial Development

159

Fig. 10.10 Comparison of environmental protection index between China’s industrial sectors

(2) It is conducive to the realization of macro goals such as wealth creation and employment increase; (3) The environmental cost is small and is conducive to sustainable development. The report believes that we can take the improvement of China’s industrial international competitiveness as the basic consideration, comprehensively consider the

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10 Industrial Competitiveness Among China’s Industrial Sectors …

industrial competitiveness, macro-level and energy and environmental protection issues between industries, and select the comprehensive competitiveness of the industry and the competitiveness of the factors, which is conducive to the realization of macro-achievement and low energy consumption. Low energy consumption and low pollution industry is the key support direction for China’s future industrial development, so as to improve the international competitiveness of China’s industry as a whole.

10.4.1 Select the target’s Quantization Method The eight competitiveness scores (comprehensive competitiveness and seven factor competitiveness), four macro target indicators and two energy environmental protection indexes were selected as the selection factors to describe the priority of 39 industries. The method is to sort the scores of the 39 industries on the above 14 selection factors, and assign scores 5, 4, 2 and 1 to the industries with rankings 1–10, 11–20, 21–30, and 31–39 for a single selection factor. We can observe which industries get high scores on different selection factors, and we can also observe the total scores of 39 industries on 14 selection factors.

10.4.2 Industry Selection Information Display According to the above method, the scores of the selection factors of 39 industries are shown in Table 10.2, and the total scores are shown in Table 10.2. The top 6 industries in the total score scored 5 points on the factor scores. They were followed by communication equipment, computers and other electronic equipment manufacturing industry, transportation equipment manufacturing industry (including automobiles, communications, aerospace vehicles, etc.), ferrous metal smelting and rolling processing industry (steel industry), general equipment manufacturing industry (mechanical equipment manufacturing), electrical machinery and equipment manufacturing industry, chemical raw materials and chemical products manufacturing industry, the top 10 industries are also textile industry, textile clothing, shoes, hat manufacturing industry, instruments meters and culture, office machinery manufacturing industry, agricultural and sideline food processing industry.

10.4 Industry Selection and Strategic Industry for Industrial Development

161

Table 10.2 Industry selection scores for industry development Code

Industry

Industrial characteristics

A

B

C

D

E

F

G

H

I

G

K

Sustainable development Total score L M N

06

Coal mining and washing industry

4

5

5

5

1

4

2

1

5

2

2

5

1

2

44

07

Oil and gas extraction industry

5

5

5

4

5

2

5

5

5

2

1

2

2

4

52

08

Ferrous metal mining and dressing industry

4

4

5

4

4

1

5

4

1

1

1

1

2

1

38

09

Non-ferrous metal mining and dressing industry

2

2

5

1

4

1

5

4

1

1

1

1

1

1

30

10

Non-metallic mining and dressing industry

1

2

5

1

1

2

1

4

1

1

1

1

1

1

23

11

Other mining industry

4

2

5

1

1

1

4

5

1

1

1

1

1

1

29

13

Agricultural and sideline food processing industry

4

4

4

4

5

1

4

5

4

4

4

4

5

2

54

14

Food manufacturing industry

1

2

4

2

1

2

2

4

2

4

2

2

4

4

36

15

Beverage manufacturing industry

2

4

2

1

2

2

2

5

2

2

2

2

4

2

34

16

Tobacco products industry

5

5

1

1

5

2

5

5

4

1

4

1

5

5

49

17

Textile industry

4

4

2

5

4

4

4

2

5

5

5

5

4

2

55

18

Textile clothing, shoes, hat manufacturing industry

4

4

2

5

2

4

4

2

4

5

4

5

5

5

55

19

Leather, fur, feather (down) and its products industry

4

2

4

4

4

4

4

4

2

4

2

5

5

4

52

20

Wood processing and wood, bamboo, rattan, palm, grass products industry

2

1

5

2

4

2

2

4

2

2

2

2

4

2

36

21

Furniture manufacturing industry

2

1

4

4

2

4

2

2

1

2

1

4

5

5

39

22

Papermaking and paper products industry

1

2

1

2

2

2

1

1

2

4

2

2

2

1

25

23

Reproduction of printing industry and recording media

1

1

1

1

2

2

1

1

2

2

2

2

4

5

27

24

Culture, education and sports goods manufacturing industry

1

1

1

2

4

4

1

2

1

2

2

4

5

5

35

25

Petroleum processing, coking and nuclear fuel processing industry

2

2

1

2

5

1

1

5

4

2

4

2

2

2

35

26

Chemical raw materials and chemical products manufacturing industry

5

5

4

5

1

5

5

5

5

5

5

5

1

1

57

27

Pharmaceutical manufacturing industry

2

4

1

2

1

5

4

1

4

4

5

2

4

4

43

28

Chemical fiber manufacturing industry

1

1

1

1

5

4

2

4

2

1

4

2

2

2

32

Industrial competition

(continued)

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10 Industrial Competitiveness Among China’s Industrial Sectors …

Table 10.2 (continued) Code

Industry

Industrial characteristics

A

B

C

D

E

F

G

H

I

G

K

Sustainable development Total score L M N

29

Rubber products industry

2

1

2

2

2

5

1

2

2

2

4

4

2

4

35

30

Plastic products industry

1

2

1

4

4

4

2

2

4

4

4

4

4

5

45

31

Non-metallic mineral products industry

2

4

2

4

1

2

2

1

4

5

4

4

1

1

37

32

Ferrous metal smelting and rolling processing industry

5

5

4

5

5

5

5

5

5

5

5

4

2

1

61

33

Non-ferrous metal smelting and rolling processing industry

4

4

4

2

5

2

4

4

4

2

5

4

1

2

47

34

Metal products industry

4

4

4

4

4

4

4

2

4

4

4

5

2

4

53

35

General equipment manufacturing industry

5

5

4

5

2

5

5

1

5

5

5

5

4

4

60

36

Specialized equipment manufacturing industry

2

4

2

4

1

5

2

1

4

4

5

4

4

4

46

37

Transportation equipment manufacturing industry

5

5

1

5

5

5

5

2

5

5

5

5

5

4

62

39

Electrical machinery and equipment manufacturing industry

5

5

2

5

2

5

4

2

5

5

5

5

5

5

60

40

Communication equipment, computers and other electronic equipment manufacturing industry

5

5

2

5

5

5

5

5

5

5

5

5

5

5

67

41

Instrumentation and culture, office machinery manufacturing industry

5

2

4

4

4

5

4

4

2

2

4

5

5

4

54

42

Crafts and other manufacturing industry

2

1

2

2

2

4

2

4

2

4

2

4

2

5

38

43

Waste resources and waste materials recycling and processing industry

4

1

5

2

5

1

5

5

1

1

1

1

4

5

41

44

Electricity and heat production and supply industry

5

5

5

5

1

1

1

1

5

4

2

1

1

1

38

45

Gas production and supply industry

1

1

2

1

4

1

1

2

1

1

1

1

2

2

21

46

Water production and supply industry

1

2

5

1

2

1

1

1

1

1

1

1

1

2

21

Industrial competition

Note A: Comprehensive competitiveness; B: Competitive strength; C: Growth competitiveness; D: Market competitiveness; E: Cost competitiveness; F: Innovation competitiveness; G: Investment competitiveness; H: Management competitiveness; I: Create value; J: Provide employment; K: Support innovation; L: Guarantee export; M: Energy index; N: Environmental protection index.

Part III

China’s Industrial Competitiveness Research by Subjects

Chapter 11

Research on Industrial Competitiveness of China’s Service Sector

11.1 Background of the Research and Current Development of Service Sector 11.1.1 Research Background China’s future international competitive ability depends largely upon the development level of service industry. The service industry referred to in this book refers to the tertiary industry in a broad sense, including transportation, post and telecommunications, wholesale and retail trade, catering, and real estate. The global economic structure is undergoing profound changes and the economic center of gravity is being repositioning. The service industry gradually occupies a dominant position in economic activities, and the focus of global competition tends to shift to the service industry. The proportion of global service industry output in the entire economy has reached more than 60%, and the employment share of the service industry has continued to rise steadily. In some developed countries, nearly three-quarters of people are engaged in service industries. Global trade in services is booming, and its growth rate is far faster than that of trade in goods. The service industry has also become the focus of international direct investment. The strength of the international competitiveness of the service industry is not only related to the survival and the development of the service industry itself, but also directly affects the competitiveness of other industries and the overall economic development of a country. It is very important to enhance the international competitiveness of the service industry.

© Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_11

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11.1.2 The Status Quo of China’s Service Sector Since China’s reform and opening up, the service industry has developed rapidly. Some emerging service industries have grown from scratch, and a relatively complete service industry system has basically taken shape. As shown in Table 11.1, the added value of China’s service industry in 2004 was RMB4,338.4 billion, 50 times that of 1978. The status and role of the service industry in the national economy is increasing. The proportion of service industry output in the whole economy is basically on the rise. At present, the added value of the service industry accounts for more than 30% of the GDP. The degree of opening up of China’s service industry is not high. The total volume of trade in services has increased year by year, reaching more than US $130 billion in 2004, and was 26 times that of 1985. China has entered the ranks of the world’s major service trade countries. In 2004, its service exports ranked 9th in the world, and imports ranked 8th in the world. However, as shown in Table 11.2, the openness of China’s trade in services is only 8.2%, which is much lower than that of 68.4% of the goods trade in the same year, and lower than the level of more than 10% in Western countries in recent years. In 2004, China’s service industry’s openness to foreign investment was 0.82 and 0.85% respectively. Compared with the rapid development of the world’s service industry, China’s service industry is still relatively backward (only 1/3 of GDP), and the level of service trade competitiveness is relatively low. After China’s accession to the WTO, in accordance with the “WTO accession” commitments, the service industry has been gradually opened up, and the service industry is undergoing fundamental changes in terms of market access, national treatment, and transparency. Taking 2005 as the critical point, China’s service industry began to enter the post transition period of deep opening after China’s accession to WTO, and the domestic service market will introduce more fierce international competition. Domestic service enterprises are facing greater pressure from the competition of large international multinational companies. It is an urgent task to improve the international competitiveness of China’s service industry. Table 11.1 Contribution rate of China’s service industry to GDP Year

Service industry added value (RMB100 million)

Service industry as a (%)

1978

60.5

23.7

1985

2,556.2

28.5

1990

5,813.5

31.3

1995

17,947.2

30.7

2000

29,904.6

33.4

2004

43,384

31.8

Source Data before 2000 are from the National Bureau of Statistics. China Statistical Yearbook (2004), China Statistics Press; Statistical Bulletin of the People’s Republic of China on National Economic and Social Development in 2004

11.2 Overview of Domestic and International Research on International … Table 11.2 Comparison of China’s service trade openness and trade openness in goods Unit: %

Year

167

Openness of service trade Openness of trade in goods

1985 1.7

21.2

1990 2.6

24.5

1995 6.1

33.5

2000 6.2

42.9

2004 8.2

68.4

Source The service trade and trade openness before 2000 is calculated according to the relevant year data of the China Statistical Yearbook of the National Bureau of Statistics; the openness of 2004 is based on the National Bureau of Statistics (2005) 2004 National Economic and Social Development of the People’s Republic of China Development of Statistical Bulletin and Calculation of Relevant Data in the 2004 Balance of Payments Account of the State Administration of Foreign Exchange

11.2 Overview of Domestic and International Research on International Competitiveness of Service Sector After entering the 1990s, with the development of world economic integration and trade globalization, the research on the service industry’s industrial competitiveness has become the focus of the theoretical circles. The research perspective is not limited to the service industry itself, but also linked with the development strategy of service industry in various countries. J. Johansson (1990) studied important service sectors in Japan, such as information service, advertising, banking, insurance, commerce and consulting, and evaluated the international competitiveness of Japan’s service industry by reanalyzing the advantages and disadvantages of the industries. R. Johnston (1988) analyzed the importance of the service industry to economy of the UK, and compared the UK service industry with the Japanese service industry, and proposed to enhance the competitiveness of the UK service industry in four aspects: service quality, price, availability and the scope of services. In China, the research on the competitiveness of the service industry has just started. In addition to Evaluation Report on Competitiveness of Service Industry in China’s 31 Provinces, Municipalities and Autonomous Regions published by Competitiveness and Evaluation Research Center of Renmin University of China, which focuses on the evaluation of the competitiveness of domestic provincial service industry, there are few studies on the comprehensive evaluation of the competitiveness of other service industries. Wu Yuming’s Newly Assessment of Synthetical Development Levels of Tertiary Industry of 31 Provincial Regions of China, its evaluation indicators are mainly designed from the development level of the city, without involving the internal situation of the service industry, and the operability is not strong. Yu Meizhen’s Comparative Analysis of the International Competitiveness of Chinese and Foreign Service Industries uses an international comparative approach to analyse the current situation and basic positioning of the competitiveness of China’s service industries, but fails to put forward

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11 Research on Industrial Competitiveness of China’s Service Sector

operational suggestions and countermeasures on how to enhance the international competitiveness of China’s service industries.

11.3 Theory and Methodology of Research on International Competitiveness of Service Sector 11.3.1 Research Ideas On the basis of years of research, we try to use IMD’s international competitiveness index data base to study the international competitiveness of the industry, and propose a trinity of international competitiveness system, namely: core competitiveness, basic competitiveness and environmental competitiveness. Specifically in the study of service industry competitiveness (see Fig. 11.1), we understand the connotation of core, basic, and environmental competitiveness of the core: core competitiveness refers to the already realized competitive advantages of the service industry of each country. This advantage is not only reflected in the scale, structure, and growth of the service industry, but also in the strategic ability of the individual service companies in the industry. Basic competitiveness refers to the support of service industry, including infrastructure, information technology infrastructure to support the development of service industry, resource endowment ability determines the investment characteristics of service industry development. Environmental competitiveness reflects the impact of a country’s macroeconomic level on the service sector. The development of the industry can only develop normally under the macro-economic environment, and the four factors of economic level, economic efficiency, urbanization level and openness are selected for analysis.

11.3.2 Design of the Evaluation Index System for the Competitiveness of China’s Service Industry Service industry competitiveness is a complex system. Under the principles of science, system, dynamics and operability. From The IMD World Competitiveness Yearbook, 35 indicators were selected to analyze the core, foundation and environmental international competitiveness of service industry. The core international competitiveness of the service industry is analyzed from 4 factors and 12 indicators (see Table 11.3). Competitive strength measures the output and production efficiency of the service industry; structural competitiveness understands the competition structure of the service industry through the three core perspectives of tourism, finance and high technology; international market competitiveness describes the level of its international market through its import and export of services and its proportion in a country or region; enterprise strategic ability is characterized by soft evaluation.

11.3 Theory and Methodology of Research on International Competitiveness …

169

Fig. 11.1 Analysis framework of international service industry competitiveness

Table 11.3 Core international competitiveness indicators of service industry Factor design

Indicator name

Competitive strength

Service industry output as a percentage of GDP (%) Service industry output growth rate (calculation) Service industry productivity, corresponding GDP created by each service industry employee (in purchasing power parity) (US$)

Structural competitiveness

Tourism income, tourism revenue from abroad as a percentage of GDP (%) Stock market transaction volume (US$ per capita) High-tech product exports (US$ million)

International market competitiveness Service balances as a percentage of GDP (%) Exports of business services (US$ billion) Business service export growth rate, percentage change in US$ (%) Corporate strategic capability

Sales method, whether domestic companies effectively master sales methods Customer satisfaction, whether it is valued in your country Entrepreneurship, whether the manager has a strong entrepreneurial spirit

The basic international competitiveness of the service industry is analyzed from 4 factors and 12 indicators (see Table 11.4). The innovation ability examines from the R&D investment and the proportion of innovation to support the service industry;

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11 Research on Industrial Competitiveness of China’s Service Sector

Table 11.4 International competitiveness index of service industry Factor design

Indicator name

Creativity

Total research and development expenditure Per capita research and development expenditure, per capita at current prices and exchange rates (US$) Research and development expenditure as a percentage of GDP (%)

Infrastructure

Highway: highway network density (km/ km2 ) Railway: railway network density (km/ km2 ) Air transport: number of passengers carried by major companies (thousands people)

Information technology infrastructure

Investment in telecommunications: annual average as a percentage of GDP Per capita computer: number of computers per thousand people Internet line: number of connected households per thousand people

Competitiveness of production factors

Labor: employment and registered unemployed labor force (million people) Service industry employment: the proportion of total employed population (%) Proportion of higher education (%)

infrastructure through the basic infrastructure density to examine the support of the service industry; information technology infrastructure focuses on the development of network technology led by Internet computers; the competitiveness of production factors consider the dynamic factors of people. The international competitiveness of the service industry environment is analyzed from 4 factors and 11 indicators (see Table 11.5). Economic strength examines added value and consumption; economic efficiency examines productivity; urbanization examines urban population and its role in national development; the degree of openness examines the level of opening to the outside world through exchange rates and foreign rate.

11.4 Assessment and Comparative Analysis of International …

171

Table 11.5 International competitiveness index of service industry environment Factor design

Indicator name

Economic strength

GDP Per capita personal final consumption expenditure (US$) Per capita government final consumption expenditure (US$)

Economic efficiency

Comprehensive productivity (purchasing power parity) Comprehensive productivity growth rate Labor productivity (purchasing power parity)

The level of urbanization

Urban population as a percentage of total population Urbanization: cities support national development (↑) city wastes national resources (↓)

Openness

Your country’s exchange rate policy: support the company’s competitiveness (↑) hinder the company’s competitiveness (↓) Attracting foreign direct investment stock (US$ billion) Foreign trade dependence

11.4 Assessment and Comparative Analysis of International Competitiveness of China’s Service Sector 11.4.1 Comparative Analysis of the Overall Ranking of Service Industry Competitiveness The comprehensive competitiveness of the service industry is an overall ranking of comprehensive international competitiveness obtained by using equal weight method, which integrates core competitiveness, basic competitiveness and environmental competitiveness (see Fig. 11.2). The top five were the United States, Hong Kong (China), Luxembourg, Ile-de-France (France) and the United Kingdom, all scoring more than 66 points. China scored 42.9 points, ranking 37th, which was lower in all 60 samples. There are basically three development models for the service industry. The first can become the “American mode”. Its typical characteristics are to first vigorously develop the industry (the necessary resources required), and the development of developed industries and people’s living standards to generate service demand. This is a step-by-step “industry upgrading mode”, as shown in Fig. 11.3. The second mode is the so-called “shortcut mode” (see Fig. 11.4). For example, in Spain, from the sixteenth and seventeenth centuries, the service industry was developed. However, it has not experienced the industrial development path in the traditional sense. The third is the “isolated island” mode, represented by Luxembourg. There is no industry and agriculture, just a city. Its development depends on the service industry. But this small country mode is indispensable to the world economy.

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11 Research on Industrial Competitiveness of China’s Service Sector

Fig. 11.2 Comprehensive ranking of international competitiveness of service industry

With the core, basic and environmental competitiveness are clustering indicators. Through clustering methods, the participating countries and regions can be divided into 5 categories (see Table 11.6). Under the idea of benchmarking analysis, we choose the United States and Luxembourg in the first category of competitive powers, Japan, the United Kingdom as the second category, and Spain in the third category

11.4 Assessment and Comparative Analysis of International …

173

Fig. 11.3 “Industrial upgrading” mode

Fig. 11.4 Shortcut mode

as the reference countries for comparison. In the fourth category, India, a country with similarities with China, was chosen for comparison.

11.4.2 Evaluation and Analysis on the International Competitiveness of the Core, Foundation and Environment of China’s Service Industry 11.4.2.1

Core Competitiveness

In the comparison of the core international competitiveness of the service industry, China scored 50.55, ranking 33rd, which is a medium level. In this comparison of competitiveness, the top spot is Hong Kong (China), with a score of 78.95, followed by the United States, Luxembourg, the United Kingdom, and Greece with 71.67,

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11 Research on Industrial Competitiveness of China’s Service Sector

Table 11.6 Countries and regions grouping Category

Characteristics

Countries and regions

First type

Star group

The United States, Hong Kong (China), Luxembourg, and Ile-de-France (France)

Second type

Strength group

Australia, Austria, Bavaria (Germany), Belgium, Canada, Denmark, France, Germany, Iceland, Japan, Netherlands, Norway, Singapore, Sweden, Switzerland, the United Kingdom, Finland, Israel, Scotland (the UK), Taiwan (China)

Third type

Average level

Catalonia (Spain), Czech Republic, Estonia, Greece, Hungary, Ireland, Italy, Lombardy (Italy), New Zealand, Slovenia, Spain

Fourth type

The level is still relatively low

China, Argentina, Brazil, Chile, Colombia, Croatia, India, Jordan, Maharashtra (India), Malaysia, Mexico, Poland, Portugal, Russia, Slovakia, South Africa, Thailand, Turkey, Zhejiang (China)

Fifth type

Level needs to be greatly improved

Indonesia, Philippines, Romania, SaoPaulo (Brazil), Venezuela

Table 11.7 Scores of core international competitiveness factors in the service industry of the reference country Country

Competitive strength

Structural competitiveness

International market Corporate competitiveness strategic capability

The United States

79.77

73.34

57.23

76.33

Luxembourg

96.42

50.55

78.13

59.20

The United Kingdom

67.48

69.15

66.27

56.27

France

78.69

59.59

56.20

57.70

Japan

49.23

62.18

63.55

54.37

Spain

59.24

57.27

57.68

55.43

China

32.37

50.75

64.90

54.17

India

39.29

25.20

64.90

46.80

71.07, 64.79, and 64.74 points. From the benchmark analysis of representative countries (see Table 11.7), Luxembourg’s competitiveness has achieved an-absolute high score of 96.42. The scores of the United States and France are 79.77 and 78.69 respectively, while China’s score is only 32.37.

11.4 Assessment and Comparative Analysis of International …

175

From the perspective of the structure, China’s structural competitiveness scored 57.27 points, about 16 points lower than 73.34 of the US. The gap is still acceptable. The United Kingdom and Japan were 69.15 points and 62.18 points respectively. India’s score on this indicator is relatively low, only 25.20 points. China’s competitiveness in the international market was 64.90 points, Luxembourg scored 78.13 points, and the UK scored 66.27 points. Luxembourg’s high score is that the balance of service revenue and expenditure accounts for a large proportion of GDP. In terms of the volume of exports of business services and the growth rate of exports, Luxembourg did not perform well. China scored 54.17 points on corporate strategic capability, with only the United States having a significant advantage over China, scoring 76.33 points, and other countries are close to each other.

11.4.2.2

Basic Competitiveness

The top five of the basic competitiveness in the service industry were Japan, the United States, Singapore, Ile-de-France (France) and the United Kingdom, with scores of 74.74, 72.23, 67.75, 67.26, and 66.36. China scored 40.28, ranked 33rd, and was at a medium level of competitiveness. Japan and the United States scored 96.85 and 94.26 points respectively on the innovative ability, far ahead (see Table 11.8). China scored only 38.94, which is a clear gap between the United States and Japan. China’s R&D human resources ranks among the world’s foremost in terms of absolute value comparison, which is equivalent to that of the general developed countries; but in terms of relative quantity comparison, it is far from developed countries. Infrastructure of Japan and the United Kingdom scored relatively high, 63.22 and 60.90 points respectively, while China only 32.88 points, which was the lowest in the reference countries. China still has a big gap between the road density and the number of air passengers compared with the US and Japan. The information technology infrastructure set China scored 38.52, which was far behind by the United Kingdom, Japan, and the United States. China still has a big gap with the developed countries in terms of the per capita computer, network and telecommunication facilities. The United States and Japan scored 85.99 and 75.23 respectively, while China scored 50.80. China’s labor force population has an absolute advantage, but the proportion of employment in the service industry is only 30.6%. The highest proportion of the high-educated students is only 7% in the control sample. The quality of the service industry needs to be improved.

11.4.2.3

Environmental Competitiveness

In the comparison of international competitiveness of service industry environment, the top five are Luxembourg, the United States, Ile-de-France (France), Austria and France, with scores of 74.36, 72.82, 68.82, 67.38, and 67.32, respectively (see Table 11.9).

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Table 11.8 Scores of international competitiveness factors in the service industry of the reference country Country

Innovative ability

Infrastructure

Information technology infrastructure

Competitiveness of production factors

The United States

94.26

45.38

63.30

85.99

Luxembourg

64.67

54.65

64.00

51.19

The United Kingdom

66.93

60.90

69.42

68.19

France

77.01

45.73

48.05

68.89

Japan

96.85

63.22

63.65

75.23

Spain

37.70

39.67

39.86

61.97

China

38.94

32.88

38.52

50.80

India

28.00

33.33

16.38

36.82

Table 11.9 Scores of international competitiveness factors of the service industry environment of the reference country Country

Economic strength

Economic efficiency

The level of urbanization

Openness

The United States 90.68

74.33

67.14

59.15

Luxembourg

75.96

70.46

69.39

81.61

The United Kingdom

81.39

59.66

70.85

56.00

France

78.03

67.38

67.30

56.57

Japan

83.13

61.41

44.16

42.80

Spain

57.11

68.54

52.05

46.39

China

42.29

37.74

20.59

51.29

India

39.54

32.53

21.81

36.59

The economic strength of China scored only 42.29, and the United States, Japan, the United Kingdom and France scored 90.68, 83.13, 81.39, and 78.03 respectively. China’s GDP has certain advantages, but the per capita consumption level is poor, which restricts the development of the service industry. Economic efficiency of China scored 37.74 points, and there is a big gap with the United States, Luxembourg, France, Japan and other countries. The per China’s overall productivity is (US$) 10,846 per capita, and the United States is 8 times that of China. China’s urbanization level is 20.59 points, which is a big gap compared to 70.85 points in the UK and 67.14 points in the US. China’s urbanization has a long way to go. China’s openness scored 51.29 points, which is not much different from the US, the UK, and France. China’s FDI flow and excellent performance of import and export support this level.

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11.4.3 Factor Advantage Analysis Defining the top 15 factors for each factor is the dominant factor. In a total of 16 factors, the top ten countries and regions with the highest comprehensive strength are the United Kingdom, with a total of 10 advantages. The United States, Hong Kong (China), Luxembourg, and France are all closely followed by nine dominant factors. There is only one advantage factor in China, and the gap is large (see Table 11.10).

11.5 Selection of Strategies for Upgrading Competitiveness of China’s Service Sector The importance and urgency of developing China’s service industry has been widely recognized. Vigorously developing service industry is the inevitable requirement of accelerating industrialization and modernization. This is of great significance for promoting the coordinated development of the national economy, optimizing the industrial structure, improving the industrial competitiveness, expanding employment, and improving people’s lives.

11.5.1 Accelerate Economic Development, Raise the Level of Social Income, Accelerate the Process of Urbanization, and Create a Good Competitive Environment for the Development of the Service Industry The level of economic development and the level of social income are the basic environment for the development of modern service industry, raising the level of social income, expanding the service consumption of urban and rural residents, and improving the service consumption environment, so as to promote the development of the service industry at the demand level. Accelerate the process of urbanization, expand the development space of modern service industry, promote urban modernization while urbanization, pay attention to the construction of the best investment and entrepreneurial environment, and lay a solid foundation for the development of service industry.

Sweden

Denmark

China

9

10

37

1

7

7

6 5

Japan

Singapore

7

8

9

France

6

6 10

Ile-de-France

The United Kingdom

4

9

9

9

Number of advantages

5

Hong Kong, China

Luxembourg

2

The United States

1

3

Country and region

Overall ranking

33

14

12

11

17

7

4

6

3

1

2

1

4

1

1

2

3

3

1

2

3

4

33

7

10

3

1

15

5

4

17

14

2

0

2

3

2

3

3

4

2

3

3

2

Number of advantages

Ranking

Ranking

Number of advantages

Basic competitiveness

Core competitiveness

Table 11.10 Comparative analysis of China and the top ten dominant countries and regions

46

7

9

19

21

5

6

3

1

8

2

Ranking

0

1

3

2

1

3

3

3

4

3

3

Number of advantages

Environmental competitiveness

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179

11.5.2 Optimize the Industrial Structure of the Service Industry We will vigorously develop knowledge intensive and technology intensive services. In order to cultivate the competitive advantages of emerging service industries, we should develop high-level service industries such as design, consulting, technology patent, finance, communication and so on, and the competitive advantages of these industries are mainly reflected in reputation, popularity, management level and so on. For industries that have a greater impact on other service industries, they can fully leverage the overall relevance and agglomeration effect on the whole service industry.

11.5.3 Accelerate the Training of Service Industry Personnel The service industry is based on the “people-based” industry. The core of competitiveness is talents. Only with a large number of high-level and high-quality professionals can China’s modern service industry remain invincible in the competition. Use universities and research institutes to train professionals in modern service industries. Enhance the quality of employees by strengthening the short-term training of existing personnel in the service industry through professional organizations. We should strengthen post vocational training, comprehensively promote the vocational qualification certificate system, establish a service industry qualification standard system, and expand the scope and field of implementation in an orderly manner.

11.5.4 Relying on Scientific and Technological Progress to Improve the Technological Content of the Service Industry The modern service industry presents the trend of technicalization, internationalization and standardization. The boundaries between traditional service industries are gradually disappearing. Priority should be given to the development of modern service industries with great technology content and high relevance, and the use of modern operation methods, service technologies and management. Transforming means to improve the traditional service industry and comprehensively improve the quality, management level and economic benefits of the enterprise.

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11.5.5 Implement the Strategy of “Bringing in and Going Global” to Enhance the International Competitiveness of China’s Modern Service Industry With the further expansion of opening to the outside world, foreign capital, resources, technology and people will flow into the service industry, which will certainly is bound to promote the development of modern service industry. Expanding the opening up of the country requires establishing an investment environment that is in line with international standards, including convenient and convenient transportation, convenient and comfortable living and tourism environment. We will strengthen the construction of support systems such as consulting, finance, and intermediary, and accelerate industrial cultivation and overall strength improvement. At the same time of “bringing in”, we must implement the strategy of “going global” and strive to open up the modern service market in foreign countries.

Chapter 12

Research on Industrial Competitiveness of China’s Tourism Sector

12.1 Background and Significance Tourism has become one of the most important ways for people to improve their quality of life and pursue spiritual enjoyment. In view of the large-scale, multitype and multilevel tourism demand, the participation of multiple departments across industries is required to be met, thus generating tourism and related industries vome into being. Tourism is therefore hailed as the most promising modern industry. The tourism industry covers an extremely wide range and is a highly related and comprehensive industry in the national economy of a country or a region. Tourism is the integration of “food, housing, travel, tourism, shopping, entertainment” and other aspects, and its role in other industries is also full-face. The development of global tourism only took shape in the 1960s. However, with nearly the development of nearly 40 years, tourism has quickly become the world’s largest industry. According to estimation of the World Tourism Organization (WTO), the scale of global tourism has accounted for more than 10% of the world’s GDP, about US$3.5 trillion, greatly exceeding the scale of the automobile industry and information industry, becoming the number one industry in the world.1 The World Tourism Organization predicts that by 2020, the number of international tourists will reach 1.6 billion, and their annual spending will exceed US$2 trillion, with an average daily travel cost of US$5 billion. Since China’s reform and opening up in 1978, the tourism industry has experienced several phases of initiation, development and maturity. Especially after the 1990s, The rapid growth of China’s tourism industry has accelerated the process of the tourism economy’s industrialization. Tourism has become one of the new growth points of the national economy, which has played an increasingly prominent role in 1

Qiang, Ling. 2005. The Revelation of Japan’s Tourism-based Country Strategy. Journal of Harbin University of Commerce (Social Science Edition) 1: 109–111.

© Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_12

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promoting and linking the whole society. How competitive is China in the international tourism market? Can China be called a world tourism power? How can China’s international tourism industry achieve sustained and long-term development in the fierce international market competition? All these questions require detailed answers with data. Under the “trinity” framework of the core competitiveness, basic competitiveness and environmental competitiveness, this paper firstly establishes a multilevel and comprehensive three-dimensional evaluation index system based on the international competitiveness theory of the IMD to evaluate and analyze the international competitiveness of China’s tourism industry between China and major countries and regions in the world. Secondly, combined with the development of domestic tourism, the evaluation and analysis system of tourism industry competitiveness in 31 provinces, autonomous regions and municipalities in China was designed.

12.2 Theory and Assessment System of International Competitiveness of China’s Tourism Sector 12.2.1 The Basic Theory and Method of the International Competitiveness Design of China’s Tourism Industry The international competitiveness of tourism regards tourism destinations as an enterprise for international tourists to provide food, accommodation, travel, tourism, shopping and entertainment services for international tourists as a whole, and examine their ability to develop, occupy the international tourism market and obtain profits. According to the definition of tourism power, and Porter’s competitiveness theory, the analysis of a country’s international tourism competitiveness can be divided into core competitiveness, basic competitiveness and environmental competitiveness (see Fig. 12.1), which are interrelated, mutually supportive and constrained. The core competitiveness of tourism industry directly reflects the ability to directly reflect the tourism products created by a country and the recovery of tourism revenue. It is divided into two sub-elements of “international tourism” and “domestic and outbound tourism”. It comprehensively reflects the core competitiveness of a country’s tourism industry from the aspects of tourism input, efficiency, output and potential ability. Among them, “domestic and outbound tourism” mainly reflects the domestic tourism demand and the development potential of outbound tourism. The domestic demand situation and the size of the domestic market not only affect the scale of production, but also more importantly, affect the speed and scope of the renewal and transformation of products and services by domestic enterprises. The development of outbound tourism will effectively enhance China’s image in the world’s tourism industry. Only when China becomes an influential source of tourists in the international tourism market, can it really be called a world tourism power.

12.2 Theory and Assessment System of International Competitiveness …

183

Fig. 12.1 Analysis framework of international tourism competitiveness

The basic competitiveness mainly reflects the development status of industries or industries directly related to tourism. It focuses on the analysis of the capacity of a country’s resources, infrastructure and services to support the development of tourism in a country. The tourism-related and auxiliary industries here mainly refer to the upstream industry and auxiliary industries of the tourism industry, as well as industries that share certain technologies with the tourism industry, share certain marketing channels or services, or complement each other. Specifically, it is divided into four sub-elements of “tourism resources”, “tourism infrastructure”, “financial services” and “human resources”. Environmental competitiveness is the support of national and regional environment to tourism, and the role of tourism in macroeconomic society. Here, it is divided into three sub-elements: “openness”, “social stability and security” and “industrial development”.

12.2.2 Design of China’s Tourism Industry Competitiveness Evaluation Index System Tourism competitiveness is a complex system, constructing a concise and comprehensive competitiveness evaluation index system of regional tourism, still following the principles of science, system, dynamics and operational principles, and selecting 37 from The IMD World Competitiveness Yearbook. The indicators analyze the international competitiveness of tourism’s core, basic and environmental. The core international competitiveness of tourism industry is analyzed from two factors and six sub-factors, with a total of 11 specific indicators (see Table 12.1).

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It is measured and measured from the perspectives of tourism income, industrial efficiency, residents income and consumption, and tourism tendency. The basic international competitiveness of tourism industry is analyzed from four factors and eight sub-factors, including twenty-four specific indicators (see Table 12.2). It is investigated from the perspectives of natural resources, environment, traffic information facilities, health and life services, education, finance and human capital. The international competitiveness of the tourism environment is analyzed from three factors and six Sub-factors, a total of 12 specific indicators (see Table 12.3), from the openness of economic and cultural measurement, from the stability and security to social development, from the management environment and business efficiency investigate the industrial environment, most of which are soft evaluation indicators for senior managers. Table 12.1 Indicators of core international competitiveness of tourism industry Factor design

Secondary sub-factor

1. International tourism competitive competitiveness

(1) International tourism income

Indicator name International tourism income Tourism revenue from abroad as a percentage of GDP (%) Comparable international tourism income

(2) Business travel

Proportion of international tourism income and total foreign investment International tourism income and total international trade (import + export) ratio

2. Domestic tourism and outbound tourism competitiveness

(3) Productivity

International tourism revenue generated by each service employee

(1) Resident income level

Per capita GDP is calculated at current prices and exchange rates (Year 2001, US$) Per capita GDP is calculated based on current price and purchasing power parity (US$)

(2) Household consumption level

Individual per capita final consumption expenditure (US$) Government per capita final consumption expenditure (US$)

(3) Residents’ tourist inclination

The people of your country have full flexibility and adaptability to new challenges (↑) lack of flexibility and adaptability to new challenges (↓)

12.2 Theory and Assessment System of International Competitiveness …

185

Table 12.2 Basic international competitiveness index of tourism industry Factor design

Secondary sub-factor

Indicator name

Resource status

Natural resources

Land area (thousand square kilometers) Ecological imprint (per capita biological production area, hectares)

Environmental protection

Sustainable development Environmental pollution Carbon dioxide emitted by industrial processes per US$ million of GDP (tons) The proportion of the population receiving the services of the wastewater treatment plant to the total population (%)

Tourism infrastructure

Transport infrastructure

Road network density (kilometre/km2 ) Railway network density (kilometre/km2 ) Number of passengers carried by major companies (thousand people) Logistics facility efficiency, universal efficiency (↑) universal inefficiency (↓)

Information technology infrastructure

Internet use cost (20 h of online access per month) Broadband costs monthly cost of 100 K/sec traffic (US$) The number of main trunks per thousand households in fixed telephones The cost of every three minutes to the United States during the peak period of international call charges (for the United States means to Europe, US$)

Health and living services

Health infrastructure can meet social needs (↑) Can’t meet social needs (↓) Quality of life 2002 high quality of life (↑) Low quality of life (↓)

Financial services

Financial services

Per capita credit card ownership Credit card transaction volume US$1 billion per capita (continued)

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Table 12.2 (continued) Factor design

Secondary sub-factor

Indicator name Banks and financial services effectively support the vitality of the economy (↑) Does not effectively support the vitality of the economy (↓)

Human resources

Education

Student-teacher ratio (secondary education) corresponding number of students per teacher Public education expenditure GDP Proportion of higher education (%)

Labor quality

Foreign language level meets business needs (↑) Not meeting business needs (↓) Adult (over 15 years old) illiterate proportion of the total population (%)

Table 12.3 International competitiveness index of tourism industry environment Factor design

Secondary sub-factor

Indicator name

Openness

Cultural openness

Attitude towards globalization is negative in your country (↓) is active in your country (↑) National culture is open to foreign cultures (↑) closed to foreign cultures (↓)

Economic openness

Cooperate with foreign partners to deal with international affairs (↑) not fully communicate (↓) Foreign trade dependence (export + import) / (GDP × 2)

Social stability and security Social stability

The risk of political instability is very low (↑) very high (↓) Unrest and violence are not the cause of serious job instability (↑) is the cause of serious job instability (↓)

Social security

Health problems AIDS, alcoholism, and drug abuse have not become serious problems in the workplace (↑) become a serious problem in the workplace (↓) (continued)

12.3 Assessment and Comparative Analysis of the International …

187

Table 12.3 (continued) Factor design

Secondary sub-factor

Indicator name People are full of confidence in the protection of personal and property safety (↑) People have no confidence in the protection of personal and property safety (↓)

Industrial development environment

Industrial environment

Business environment and business rules do not hinder the competitiveness of enterprises (↑) hinder the competitiveness of enterprises (↓) Your country’s exchange rate policy supports the company’s competitiveness (↑) hinders the company’s competitiveness (↓)

Business efficiency

Large domestic enterprises are effective against international standards (↑) inefficient (↓) Domestic SMEs are effective against international standards (↑) inefficiency (↓)

12.3 Assessment and Comparative Analysis of the International Competitiveness of China’s Tourism Sector To evaluate the international competitiveness of China’s tourism industry, the international competitiveness data we use are mainly from international competitiveness database of IMD, Switzerland. The evaluation method adopts the symmetry design theory proposed by us. Firstly, we standardize each index data, and then synthesize the sub elements and the overall competitiveness index according to the evaluation system.

12.3.1 Evaluation and Analysis of the International Competitiveness of China’s Tourism Industry Elements Table 12.4 shows the ranking of various sub-elements of core competitiveness, basic competitiveness and environmental competitiveness in various countries and regions. According to the number of advantages and disadvantages, it shows the distribution of advantages and disadvantages of each country or region’s tourism competitiveness.

Table 12.4 Results of the international competitiveness evaluation of tourism industry factors in some countries or regions in 2006

(continued)

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189

Table 12.4 (continued)

(continued)

12.3 Assessment and Comparative Analysis of the International …

Note Bold numbers indicate that factors are ranked in the top 15 and are strong factors; light grey indicates that the factor is ranked in the bottom 13 and is a weak factor

Table 12.4 (continued)

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12.3 Assessment and Comparative Analysis of the International …

191

In terms of international tourism, China ranks 28th, which is the highest level in the world. China’s more international tourism revenue has played a greater role in enhancing competitiveness, but it also contains the efficiency of competitiveness and the basic structural impact. The degree of openness of a country plays an important role in the international competitiveness of its tourism industry. In some countries, domestic tourism is quite developed, but the degree of openness in the international arena is not high, which will directly affect the level of international competitiveness. Western developed countries have shown strong competitiveness in international tourism. In terms of domestic and outbound tourism competitiveness, China ranks 59th and is at a disadvantage. China has great potential for domestic tourism and overseas travel, but it is still in the development stage. It is difficult to produce innovation pressure on domestic tourism enterprises in terms of product types, quality and services, and it cannot play a role in stimulating and enhancing the competitiveness of domestic tourism enterprises. China’s resource situation is relatively backward, ranking 52nd. Tourism resources are the premise and material basis for the development of tourism. China has abundant tourism resources, numerous attractions, and diverse tourism resources, is rich in history and culture. These aspects have absolute advantages. However, the resource situation here refers not to tourism resources, but to the land, ecology and environmental protection of natural resources. This is the most fundamental resource for attracting tourists. China is only weak in this respect. How to improve the environment and coordinate the development of human and nature has become one of the biggest problems in China’s tourism development. Tourism infrastructure in China is relatively poor, ranking 49th. This is closely related to China’s economic and cultural development. China’s economy is in the process of taking off, and there is a lag period for the follow-up of various facilities. It is believed that the tourism infrastructure will be greatly improved with the development of the economy. Financial services in China are relatively poor, ranking 52nd. Without perfect finance or service trade, it is impossible to have a very developed or progressive service industry and tourism industry. China should take advantage of the further opening up of the financial industry, standardize regulate the financial market and financial service order, and further improve the quality of financial services, thereby enhancing its support for tourism. China ranks 58th in human resources. The quality of tourism services and the quality of tourism products are closely related to the quality and service level of service personnel. In this regard, China should also learn from the experience of foreign personnel and service personnel to fundamentally improve the quality of services. It can be seen that China’s neighboring India ranks first. India and China have similar developments in all aspects and a large population. China can learn from India’s experience in developing education and attracting talents. China’s openness ranks 46th. Although it is at the middle and lower levels, it is undeniable that China’s openness is gradually increasing. Since the reform and

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opening up, China’s southeast coast has been opened to a great extent, and the inland areas of the central and western regions will gradually open up. China ranks 42nd in industrial development, mainly because the efficiency of enterprises is not high. Hotels, restaurants, public transportation, travel agencies, culture and sports and leisure services have developed rapidly in recent years, but there is still a certain gap compared with the international advanced level.

12.3.2 Evaluation and Analysis of the International Competitiveness of China’s Tourism Industry Core, Foundation and Environment 12.3.2.1

Core International Competitiveness Evaluation

The core international competitiveness of China’s tourism industry ranked 51st in 2005, at a relatively low level. Although China has more international tourism revenue, it shows weakness in the structural ratio of competitiveness and its efficiency is relatively poor. The core international competitiveness of tourism in western developed countries shows strong competitiveness, and the fundamental thing is to enter a development stage of optimizing competitiveness structure, interactive coordination of competitiveness elements and relatively high efficiency level.

12.3.2.2

Basic International Competitiveness Evaluation

The level of international competitiveness of China’s tourism industry is also low, ranking 56th overall. This reflects a development constraint of China’s tourism industry. There is a certain gap in scale, level and efficiency, that is, China’s infrastructure has not been able to keep up with world-class standards.

12.3.2.3

Environmental International Competitiveness Evaluation

China also lacks competitiveness in tourism environment, ranking 50th in terms of comprehensive environmental international competitiveness. Experience shows that the government should play a primary role in the international competitiveness of the tourism environment. The government directly influences the international competition of enterprises and industries through policies in the capital market, production standards, subsidies, and competition regulations. Most tourist destinations have implemented a “government-led” tourism development strategy, with regions such as Spain, France, Singapore, the United Kingdom, and Thailand, which are more developed in international tourism. The government has done a lot of work in the

12.3 Assessment and Comparative Analysis of the International …

193

overall promotion of tourism destinations, development planning, human resources development, market research, and other aspects of tourism infrastructure.

12.3.2.4

Comprehensive Evaluation of International Competitiveness of Tourism Industry

The comprehensive evaluation results of international competitiveness of tourism industry can be obtained by integrating all the indexes of the three elements. The comprehensive evaluation of China’s tourism international competitiveness ranked 53rd (see Fig. 12.2). This is a comprehensive evaluation of the overall competitiveness of China’s tourism. Although China has a high international tourism revenue, these incomes are attracted by China’s own rich tourism resources. In terms of infrastructure and environment, China is far from being world-class and not enough to attract more tourists.

12.3.3 Analysis of International Tourism Competitiveness Model 12.3.3.1

Cluster Analysis, Select Strong Country (Regions) Samples

The two basic preconditions of the world’s tourism power are that “strong tourism country” must be a “major tourism country” and a tourism power must has international tourism influence. Therefore, the international tourism income, the tourism income from foreign countries as a percentage of GDP (%), the international tourism income created by each service industry employee and the comparable international tourism income to show the characteristics of the strong country (regions) through cluster analysis.

Clustering from a Scale Perspective Using the clustering method of multivariate statistics, we choose two indicators of international tourism income and comparable international tourism income as clustering indicators, clustering 60 countries and regions into five categories, and Table 12.5 shows four core indicators of five categories. The average level (Mean), the number of countries or regions classified by each category (N), and the standard deviation (Std. Deviation) that constitutes the horizontal distribution among various countries and regions. The first category of countries (regions) account for the majority, their international tourism income is relatively small, tourism income as a percentage of GDP

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Fig. 12.2 Overall ranking of tourism international competitiveness

12.3 Assessment and Comparative Analysis of the International …

195

Table 12.5 Scale angle clustering results Average linkage (between groups)

1

2

3

4

5

Total

Tourism International income comes tourism revenue from foreign (US$ billion) (outbound) tourism income as a percentage of GDP (%)

Service industry employment per capita international tourism income (US$/person)

Comparable international tourism revenue (US$ billion)

Mean

2.9059

5.4340

1,958.0874

6.6462

N

53

53

53

53

Std. Deviation

2.37949

4.27795

2,451.07454

5.01756

Mean

1.0867

22.9614

760.6133

26.3233

N

3

3

3

3

Std. Deviation

0.14012

2.70205

646.80784

4.47554

Mean

2.1000

38.7748

2,594.1550

43.2250

N

2

2

2

2

Std. Deviation

0.04243

4.26880

190.33193

7.67211

Mean

4.9300

48.9105

4,429.3400

60.7600

N

1

1

1

1

Std. Deviation

.

.

.

.

Mean

0.5900

69.2277

640.6500

90.4200

N

1

1

1

1

Std. Deviation

.

.

.

.

Mean

2.7832

9.2096

1,938.6462

11.1475

N

60

60

60

60

Std. Deviation

2.30786

12.51024

2,351.37121

15.39112

and service industry personnel level is at a medium level, which is the situation in most countries (regions), that is, 53 countries and regions fall into this one category. The second category of countries (regions) are China, Germany and the United Kingdom. The common characteristics of these three countries are that the proportion of international tourism income is not high in GDP, international tourism income is relatively high, and the per capita international tourism income created by service employees is less. Although such a country’s tourism industry is not superior in efficiency, its scale advantage is obvious, and the future development path can start from improving efficiency.

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The third category of countries are France and Italy. The common characteristics of these two countries are that the proportion of international tourism income accounts for a high proportion of GDP, international tourism income is quite high, and service industry employees create a large amount of international tourism income per capita. Such a country can be called a “tourism power”, with balanced development of scale and efficiency. The fourth category of country is Spain, which has further improved in scale and efficiency compared with the third category of countries, especially its tourism efficiency is the highest. In fact, Spain’s tourism development has formed a “Spanish development mode”, characterized mainly by taking tourism as a pillar industry of the national economy, rapid tourism development targeting the mass market. The fifth category of countries is the United States. The distinguishing feature of the United States is that international tourism has the highest income, while efficiency is average. This is also the characteristic of the “American mode” in the development of the world’s tourism industry, that is, the tourism industry is developing relatively early, domestic and international tourism are relatively developed, and the development of tourism is the main goal of expanding employment and stabilizing the economy. The tourism management system is semi-official tourism. Institution-based, tourism management system is dominated by companies, small business-based, industry organizations play an important role.

Clustering from the Perspective of Efficiency Levels Using the clustering method of multivariate statistics, we clustered from the perspective of development efficiency and level, that is, clustered into two core indicators: tourism revenue from foreign countries (%) and international tourism revenue created by employees in each service industry. The five categories, the results are shown in Table 12.6. The first category of countries (regions) is the majority, with low levels of tourism revenue as a percentage of GDP and low levels of efficiency of service sector personnel and medium levels in terms of size, and includes 41 countries and regions. The second category of countries (regions) is Austria and the Autonomous Community of Catalonia in Spain, a category characterised by a high share of tourism revenues in GDP and the efficiency of service sector personnel, but on a smaller scale. As many as 12 countries (regions) in the third category are Belgium, Denmark, Estonia, France, Ireland, Italy, New Zealand, Portugal, Singapore, Slovenia, Switzerland and Hong Kong (China), which are characterised by a higher share of tourism revenues in GDP and a more efficient but smaller service sector workforce. The fourth category of countries (regions) are Greece, Iceland, Spain and Ilede-France, France. These countries (regions) have a very balanced development, no matter the scale or level, the degrees of development are relatively high. The fifth category of countries is Luxembourg, which is a special country. International tourism revenue accounts for 10% of its GDP. Per capita international tourism

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Table 12.6 Efficiency level angle clustering results Average linkage (between groups)

1

2

3

4

5

Total

Tourism International income comes tourism revenue from foreign (US$ billion) (outbound) tourism income as a percentage of GDP (%)

Service industry employment per capita international tourism income (US$/person)

Comparable international tourism revenue (US$ billion)

Mean

1.9120

7.5229

769.7227

9.4937

N

41

41

41

41

Std. Deviation

1.83254

11.59203

649.55256

14.78168

Mean

6.1450

13.4076

7,230.9000

15.2850

N

2

2

2

2

Std. Deviation

0.89803

3.79238

277.21414

2.97692

Mean

3.9742

11.4469

3155.1367

12.7575

N

12

12

12

12

Std. Deviation

1.72413

13.16192

481.89626

14.74671

Mean

4.5875

19.1735

4,574.6950

23.0200

N

4

4

4

4

Std. Deviation

1.48316

20.77235

309.16136

26.08402

Mean

10.2700

3.2659

14,137.9200

3.8700

N

1

1

1

1

Std. Deviation

.

.

.

.

Mean

2.7832

9.2096

1938.6462

11.1475

N

60

60

60

60

Std. Deviation

2.30786

12.51024

2,351.37121

15.39112

income from service sector employment up to US$14,138 per person, with efficiency first. The tourism industry is regarded as the pillar industry of the national economy, and its development is relatively specialized.

12.3.3.2

Factor Analysis

Given that the countries (regions) selected in the above two cluster analyses have their own characteristics in terms of their respective tourism development, as well as the common characteristic of being superior in size or level. The following factor

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Table 12.7 Core indicator factor analysis variables commonality Initial Extraction

Indicator

Tourism income comes from foreign (outbound) tourism income as a share 1.000 0.862 of GDP (%) 1.000 0.996

International tourism income

Service industry employment per capita international tourism income (US$ 1.000 0.860 billion/thousand people) 1.000 0.995

Comparable international tourism income Note Factor extraction methods: principal component analysis

Table 12.8 Core indicator factor analysis total variance interpretation Component 1

Initial eigenvalues Total

% of Variance

2.012

50.301

Extraction sums of squared loadings Cumulative %

Total

% of Variance

Cumulative %

50.301

2.012

50.301

50.301

1.701

42.522

92.823

2

1.701

42.522

92.823

3

0.280

7.005

99.828

4

0.007

0.172

100.000

Note Factor extraction methods: principal component analysis

analysis is carried out for all countries (regions) to extract the main information and reduce the variables, and then the model analysis is carried out for the above group of world tourism powerhouse countries (regions).

Extracting Factors for Four Tourism Core Indicators As can be seen from Table 12.7, the commonality of the variables is quite high, and the factor analysis is quite successful, retaining most of the information of the original indicators. Two factors were extracted to explain 92% of the original variation of the four variables (see Table 12.8). From the factor load matrix (see Table 12.9), we can see that the first factor mainly explains the international tourism income and comparable international tourism income, which can be named as the international tourism income factor, and the second factor mainly explains the tourism income from foreign tourism income as a percentage of GDP (%) and service industry employment per capita international tourism income (US$/person), can be named as international tourism efficiency factor.

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Table 12.9 Core indicator factor analysis load array Component

Indicator

1

2

Tourism income comes from foreign (out bound) tourism income as a share of GDP (%)

0.125

0.920

International tourism income

0.984

−0.170

Service industry employment per capita international tourism income (US$/person)

0.260

0.890

Comparable international tourism income

0.980

−0.183

Note Factor extraction methods: two factors were extracted by principal component analysis

Extraction Factors for Other Supporting Explanatory Indicators According to the remaining index extraction factors that play a role in tourism competitiveness, the calculation results show that the commonality of each variable is relatively high, and the lowest index information is explained by more than 72%. The six factors are extracted according to the law that the eigenvalue is greater than one, which explains 82% of the total variation of all the original variables. The factor is named according to the rotated factor load matrix (see Table 12.10): the first factor is called the “social environment factor”, the second factor is the “openness factor”, and the third factor is called the “traffic communication factor”. The fourth factor is called “foreign trade and foreign investment factor”, the fifth factor is called “air transportation factor”, and the sixth factor is called “human resource factor”.

12.3.3.3

Model Analysis

So far, the four indicators of tourism competitiveness are taken as the dependent variables, and the “international tourism income factor” and “international tourism efficiency factor” are extracted as two explanatory variables, while other explanatory variables also propose the above mentioned explanatory variables of the six aspects of “social environment factors”, “openness factor”, “traffic communication factor”, “foreign trade and foreign investment factor”, “air transport action factor” and “human resource factor” can be considered by regression analysis. The following model for establishing the dependent variable factor and the independent variable factor is established as follows:

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Table 12.10 Explanatory indicator factor analysis score matrix Indicator

Component 1

Proportion of international tourism income and total foreign investment

2 0.028 −0.045

4 0.049

−0.033

5

6

0.496 −0.184

0.069

0.487 0.232

−0.042

Per capita GDP is calculated at current prices and exchange rates (Year 2001, US$)

0.122 −0.088 −0.091 −0.084 0.051

0.030

Per capita GDP is calculated based on current price and purchasing power parity (US$)

0.079 −0.042 −0.038 −0.078 0.135

0.052

Individual per capita final consumption expenditure (US$)

0.106 −0.068 −0.083 −0.058 0.083

0.100

International tourism income and total international trade ratio

−0.033 0.043

3

Flexibility and adaptability: People −0.112 0.291 in your country are fully flexible and adaptable to new challenges (↑) lack of flexibility and adaptability to new challenges (↓)

−0.023 −0.019 0.207

0.124

Ecological imprint (per capita biological production area, hm2 )

0.033 0.024

−0.072 −0.012 0.253

0.203

Sustainable development is not considered to be an advantage of your country (↓) is considered to be an advantage of your country (↑)

0.113 0.019

−0.021

Pollution problems and infrastructure are affected by serious pollution problems (↓) are not affected by serious pollution problems (↑)

0.126 −0.032 −0.132

0.014 −0.312 −0.034

−0.096

0.054 0.003

Road network density (km/km2 )

−0.069 0.019

0.425 −0.059 −0.010 −0.051

Railway network density (km/km2 )

−0.051 −0.017

0.373 −0.093 0.057

Air transport: number of passengers carried by major companies (thousand people)

−0.008 0.033

−0.182

−0.022 −0.003 −0.076

0.615

0.013 −0.184

0.000

Infrastructure for the distribution of goods and services: general efficiency (↑) general inefficiency (↓)

0.095 −0.030

Broadband fees: monthly fees for 100 K/sec flow (US$)

0.148 −0.076 −0.489 −0.235 −0.010 −0.364

Fixed telephone: number of main trunks per thousand

0.068 −0.023 −0.023 −0.073 0.157

0.086

0.056 (continued)

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Table 12.10 (continued) Indicator

Component 1

2

3

4

5

6

Health infrastructure can meet social needs (↑) can not meet social needs (↓)

0.104 −0.058

0.082 −0.004 −0.174 −0.038

Quality of life in 2002: high quality of life (↑) low quality of life (↓)

0.130 −0.041 −0.066

0.017 −0.089

0.023

Banking and financial services: effectively support the vitality of the economy (↑) does not effectively support the vitality of the economy (↓)

0.038 0.123

0.062 −0.107

0.106

Student–teacher ratio (secondary education): corresponding number of students per teacher

0.054 −0.055 −0.054 −0.056 −0.536

0.093

0.010

Attitude towards globalization is −0.039 0.210 negative in your country (↓) is active in your country (↑)

0.057 −0.065 −0.091

National culture: open to foreign −0.115 0.294 cultures (↑) close to foreign cultures (↓)

0.042 −0.008 0.240

−0.029

International affairs: foreign partners can fully communicate with each other in handling international affairs (↑) not being able to fully communicate (↓)

0.017 0.099

0.061

−0.187

The risk of political instability is very low (↑) very high (↓)

0.149 −0.039 −0.120

0.033 −0.177 −0.039

Riots and violence are not the cause of serious job instability (↑) is the cause of serious job instability (↓)

0.049 0.069

0.006

0.071 0.091

Security: people are full of confidence in the protection of personal and property safety (↑) people have no confidence in the protection of personal and property safety (↓)

0.080 0.025

0.057

0.065 −0.139

Business rules do not hinder corporate competitiveness (↑) hinder corporate competitiveness (↓)

0.001 0.180

−0.036

0.008 0.132

0.020 0.039

0.078

−0.160

0.004

−0.021

Note Factor extraction methods: principal component analysis; rotation method: maximum variance method

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International Tourism Income Factor Model International tourism income factor = 0.32 + 0.237 × social environment factor − 0.408 × openness factor + 0.152 × traffic communication factor + 0.099 × foreign trade and foreign investment factor + 0.08 × air transportation factor + 0.751 × human resource factor It can be seen from the model that the international tourism income factor score reflecting the scale is mainly affected by social environment, traffic communication and human resource. These aspects bring environment, infrastructure and human resource support to the development of tourism.

International Tourism Efficiency Factor Model International tourism efficiency factor = 0.103 + 0.550 × social environment factor + 0.229 × openness factor + 0.138 × traffic communication factor + 0.272 × foreign trade and foreign investment factor + 0.468 × air transportation factor − 0.427 × human resources factor. From the international tourism efficiency factor model, it can be seen that the efficiency of countries with tourism as the main source of national economy is mostly caused by social environment and air transportation factors. It can be seen that the stability and security of the society and the improvement of people’s living standards are the direct guarantee for the development of tourism in a country. In addition, international tourism is of course closely related to the air transport capacity, especially in countries where tourism is the main industry. Of course, the leading effects of introduction and openness of foreign investment and international trade cannot be ignored.

International Tourism Revenue Model International tourism income = 16.897 + 400.030 × international tourism income and total international trade ratio + 0.001 × per capita GDP (current price, exchange rate, US$) − 1.080 flexibility and adaptability + 8.186E − 05 × air transportation number of passengers carried by major companies (thousand people) − 0.644 × international telephone charges during the peak period to the US every three minutes (US$) − 1.693 × student–teacher ratio (secondary education) number of students per teacher − 2.519 × illiterate adults (over 15 years old) illiterate proportion of total population (%). It can be seen from the model that the international tourism income of large-scale powers is directly caused by the large-scale effect of the induced effect of international trade. At the same time, the per capita GDP as a measure of the degree of economic development of a country also plays a certain role in promoting international tourism

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revenue. The air transport capacity has not contributed much to international tourism. The higher the cost of telecommunications, the reverse effect on international tourism revenue. The quality of the population has an impact on the income of international tourism. The quality of the population directly determines the stable and safe social environment of the country and the service quality and efficiency of the service industry, which is similar to the social environment factors mentioned above. Tourism development is also directly related to the development of tourism.

Per Capita International Tourism Revenue Model for Service Industry Employment International tourism income per capita created by service industry (US$/person) = − 531.807 − 26.791 × proportion of international tourism revenue and total foreign investment + 42,139.251 × proportion of international tourism revenue and total international trade + 0. 059 × per capita GDP (current price, exchange rate, US$) + 48.341 × security + 40.780 × flexibility and adaptability − 0.003 × air transport number of passengers carried by major companies (thousand people) − 80.793 × international telephone charges during the peak period to the US every three minutes (US$) + 0.392 × carbon dioxide emissions per million dollars from industrial emissions (ton) − 90.371 × student–teacher ratio (secondary education) number of students per teacher. It can be seen from the model that the tourism efficiency of the powerful countries is mainly determined by trade, per capita GDP, security, flexibility and adaptability, telecommunications cost, industrial efficiency and education level. In order to improve efficiency, China’s tourism industry should improve social security, ensure social security, strengthen economic and cultural exchanges with foreign countries, improve industrial efficiency, and reduce the harm of industry to environment.

12.3.4 Comparative Analysis From the above analysis, we can see that China’s development is similar to that of the powerful country with a large scale. The comparison between China’s various aspects and other six large-scale powers is as follows: Figure 12.3 shows that China’s international tourism revenue is in the weakest position among the powerful country groups. It can be seen that China’s international tourism revenue scale advantage has room for further expansion. China can target the powerful country group, catch up with the UK and Germany firstly, and take the level of France and Italy as the next development goal.

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Fig. 12.3 Comparison of international tourism income scales of different countries and regions

12.3.5 Summary of International Tourism Competitiveness To sum up, the China’s international tourism competitiveness has the following characteristics: (1) China is in a leading position in the total amount of international tourism income, which is regarded as one of the world’s tourism powers, and the per capita level is low. (2) China’s advantages lie in the potential of international tourism and domestic outbound tourism, tourism resources, etc., while human resources, openness, financial services, industrial development are relatively at a disadvantage. (3) China’s tourism industry’s core international competitiveness ranks 51st. China’s basic and environmental competitiveness is also weak which needs to be improved. (4) China still has great potential and development space in the international competitiveness of tourism. The international tourism revenue has a relatively large development space compared with developed countries. (5) China’s international tourism revenue has risen steadily over the past decade and its development has been stable. The world has learned too many lessons about the ecological problems caused by tourism. However, in many parts of China, which are expecting a miracle of profit from the tourism economy, people are still avoiding the warnings that “mismanagement of ecotourism can have disastrous consequences” and are too eager to make money and accelerate development to calmly look at the detours taken by others and reduce their own mistakes.2 In fact, implementing ecotourism is not an easy task in any type of country. The Chinese are reluctant, and national conditions do not allow China to repeat the detours taken by developed countries. Therefore, China should not blindly learn from the Western model of tourism development, but should study 2

Bosselman, Fred P., Craig A. Peterson, and Claire McCarthy. 2003. Managing Tourism Growth: Issues and Applications, trans. Chen Ye et al., 55–56. Beijing: China Social Sciences Press.

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and understand foreign experiences and lessons in a timely, adequate and extensive manner, keep up with the latest international concepts of environmental protection and the ideological understanding of tourism, and introduce new and important scientific discoveries, environmental theories, environmental perspectives and awareness in the world of environmental protection and sustainable development into the actual development of tourism in China.

12.4 Design, Assessment and Analysis on Tourism Sector’s Competitiveness of Thirty-one Provinces, Autonomous Regions and Municipalities in China In 2004, China’s tourism industry was fully revived after the devastating “SARS” outbreak. A total of 109,038,200 inbound tourists were received throughout the year, with foreign exchange earnings from international tourism amounting to US$25,739 million, an increase of 19.0 and 47.9% respectively over the previous year; domestic tourism accounted for 1.102 billion passengers and RMB471.071 billion in revenue, up 26.6 and 36.9% respectively over the previous year; the number of Chinese citizens leaving the border reached 28,852,900, an increase of 42.7% over the previous year, with total tourism revenue of RMB684 billion, an increase of 40.1% over the previous year; equivalent to 5.01% of the country’s GDP for the year, an increase of 0.83 percentage points over the previous year. In all provinces, autonomous regions and municipalities in China, due to the different developments of tourism resources, tourism services and tourism enterprises, there have been development differences on all sides. This part uses the theory of international competitiveness of tourism, closely links with the reality of China’s tourism development, and based on the theory of 31 provinces, autonomous regions and municipalities, in order to establish a competitiveness evaluation system, to provide an objective and scientific basis for the analysis and policy formulation of tourism development as a whole.

12.4.1 Structural Design and Evaluation Index System of Tourism Industry Competitiveness of 31 Provinces, Autonomous Regions and Municipalities The real activity of the tourism industry is a complex system. Therefore, the realization of its development theme depends on multiple levels, including resources, enterprises, markets, as well as international and domestic. Based on our years of statistical analysis and comparative research, we have designed the following basic analysis framework (see Fig. 12.4). The competitiveness of international tourism mainly reflects the attraction of tourist areas in one province or municipality directly to the

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Fig. 12.4 Relational diagram of tourism competitiveness index system of 31 provinces, autonomous regions and municipalities

city, and the willingness of inbound tourists to stay in the province. Domestic tourism competitiveness mainly reflects the willingness, demand and tourism consumption capacity of residents from one province. Market competitiveness mainly reflects the overall service quality and market attraction of tourism enterprises. The competitiveness of enterprises mainly reflects the overall differences in the business development of the tourism enterprises in terms of manpower, assets, scale and quantity. The competitiveness of tourism resources mainly reflects the natural and cultural tourism resources owned by a province, as well as the attraction of these resources to tourists, as well as the human resources necessary for tourism development. The competitiveness of tourism infrastructure mainly reflects the tourism infrastructure that provides various tourism services, namely, the service capacity of vehicles, ships, railways, highways, accommodation, and so on. The above six aspects comprehensively reflect the overall development of tourism in a province. It should be said that on the basis of current tourism statistics in China, comprehensive evaluation and systematic analysis of the above aspects can be achieved. According to the above design theories and ideas, we based on The Yearbook of China Tourism Statistics 2005, The Yearbook of China Tourism Statistics Yearbook 2005 (Supplement), the Inbound Visitor Sample Survey Data 2005, and the China Domestic Tourism Sample Survey Data 2005. An evaluation index system for evaluating the competitiveness of China’s tourism industry was established (see Table 12.11).

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Table 12.11 Evaluation index system of tourism industry competitiveness of 31 provinces, autonomous regions and municipalities International travel International tourism (foreign exchange) income

Average daily consumption of inbound tourists

Length of stay of inbound tourists

Number of inbound tourists received by region

Number of The flow of inbound inbound tourists tourists

US$10,000

US$10,000

Day

Person time

The percentage of the number of times (2nd–3rd)

Percentage of surveyed people going to the province

Domestic travel The average number of nights spent by rural residents on domestic tourism (excluding one-day tour)

The average number of nights spent by urban residents on domestic tourism (excluding one-day tour)

Per capita spending of rural residents in domestic tourism

Per capita spending of domestic tourism for urban residents

Domestic tourism travel rate of urban residents

Rural residents’ overnight travel rate

Night

Night

RMB Yuan/person

RMB Yuan/person

%

%

Market competitiveness Number of travel agencies

Inbound tourists’ evaluation of the quality of tourism services

Star hotel Travel agency hundred yuan operating fixed assets income create operating income

Star hotel revenue

Star hotel room occupancy rate

One

Score

RMB Yuan

RMB 10,000 yuan

RMB 10,000 yuan

%

Enterprise competitiveness Tourism enterprise operating income

Per capita profits and taxes for tourism enterprises

Total productivity of tourism enterprises

Total fixed assets of tourism

Number of employees in tourism enterprises

Number of tourism enterprises and institutions

RMB 10,000 yuan

RMB 10,000 yuan/person

RMB 10,000 yuan/person

RMB 10,000 yuan

person

One (continued)

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Table 12.11 (continued) Travel resources Inbound tourists’ interest in tourism resources

Number of tourist areas = number of companies-travel agencies-star hotels-other companies

Number of students in the provinces (municipalities)

Number of tourism institutions in the province (municipality)

Number of employees in the tourism industry

Number of cultural relics protection units

Score

One

Person

One

Person

One

Tourism infrastructure Number of star hotels

Evaluation of tourist reception facilities by inbound tourists

Number of coaches and boats

Star hotel bed number

Railway passenger traffic by region

Road transport passenger car ownership

One

Score

One

A piece of

Ten thousand people

Ten thousand a seat

12.4.2 Comprehensive Evaluation and Analysis of Tourism Industry Competitiveness of 31 Provinces, Autonomous Regions and Municipalities We have collected and collated the statistical data of tourism industry of 31 provinces, autonomous regions and municipalities of China in 2005, and made a comprehensive and systematic evaluation on the competitiveness of tourism industry of 31 provinces, autonomous regions and municipalities of China in 2005 by using the evaluation index system of China’s tourism industry competitiveness. The results are shown in Fig. 12.5. Beijing tops the list for tourism industry competitiveness, followed by Jiangsu, Guangdong, Zhejiang, and Shanghai. These four provinces and Beijing should be said to be in the first echelon of tourism and belong to the major tourism province. And then Shandong, Liaoning, Sichuan, and Henan should be at the uppermiddle level, and their tourism development may be more or less flawed in some aspects. There are more provinces in the middle level, while the last three provinces of Tibet, Qinghai and Ningxia are at a backward level, and the tourism resources have not been fully developed. Based on the evaluation results of tourism industry competitiveness of 31 provinces, autonomous regions and municipalities, this book uses the method of multivariate statistical analysis to carry out cluster analysis, which can be divided into three types: strong tourism industry competitiveness provinces, medium tourism industry competitiveness provinces and weak tourism industry competitiveness provinces. Table 12.12 shows various industry competitiveness for specific provinces, autonomous regions and municipalities.

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Fig. 12.5 Comprehensive evaluation ranking of tourism industry competitiveness of 31 provinces, autonomous regions and municipalities

Table 12.12 Cluster classification of tourism industry competitiveness of 31 provinces, autonomous regions and municipalities in China Category

Province

Strong competitive region

Beijing, Shanghai, Jiangsu, Zhejiang, Guangdong

Medium competitive region

Hebei, Liaoning, Anhui, Shandong, Henan, Hubei, Hunan, Guangxi, Sichuan, Yunnan

Weak competitive region

Tianjin, Shanxi, Inner Mongolia, Jilin, Heilongjiang, Fujian, Jiangxi, Hainan, Chongqing, Guizhou, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang

12.4.3 Comprehensive Evaluation and Analysis of the Competitiveness of Tourism Industry Factors of 31 Provinces, Autonomous Regions and Municipalities According to our tourism industry competitiveness evaluation system design, it includes six factors, and this part has six major factors to evaluate and analyze the competitiveness of tourism industry of 31 provinces, autonomous regions and municipalities in China.

12.4.3.1

Evaluation and Analysis of International Tourism Competitiveness

From Fig. 12.6, Beijing and Shanghai occupy an absolute competitive advantage in international tourism competitiveness, which is inseparable from the openness, development and international popularity of these two international metropolises.

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Fig. 12.6 Comprehensive evaluation ranking of international tourism competitiveness of 31 provinces, autonomous regions and municipalities

The more open the city is, the more natural attracting foreign tourists and business opportunities it attract. This can be seen from the five provinces of Jiangsu, Zhejiang, Fujian, Liaoning and Guangdong, which are closely related. The five provinces have the commonality: coastal openness and developed economy. Inland provinces such as Inner Mongolia, Henan, Jiangxi, and Gansu have performed poorly in international tourism.

12.4.3.2

Evaluation and Analysis of Domestic Tourism Competitiveness

The results in Fig. 12.7 are unexpected. Xinjiang is at the top of the list and far ahead. The tourist willingness and ability of Xinjiang residents, namely “tourism demand”, are relatively strong. The situation in Tibet, ranked fifth, is similar to that in Xinjiang. The second, third and fourth places in Guangdong, Shanghai and Fujian are another situation. These provinces have relatively developed economy, relatively better service and resources for intra-provincial tourism, relatively more times and time for residents to travel, relatively longer travel distance, and more per capita cost, forming a strong tourism demand market. The same characteristics of the last few provinces such as Hainan, Shanxi and Hebei are that the tourism resources in the province are relatively abundant, resulting in low time and cost for residents to travel outside the province.

12.4.3.3

Market Competitiveness Evaluation and Analysis

Market competitiveness mainly reflects the attraction and reception capacity of the tourism market in the whole province, so as to reflect the competitiveness of the tourism market. As can be seen from Fig. 12.8, the five traditional strong competitive

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Fig. 12.7 Comprehensive evaluation ranking of domestic tourism competitiveness of 31 provinces, autonomous regions and municipalities

Fig. 12.8 Comprehensive evaluation ranking of market competitiveness of tourism industry of 31 provinces, autonomous regions and municipalities

provinces of Jiangsu, Shanghai, Zhejiang, Beijing and Guangdong occupy the top five with obvious advantages. The economic development drives the prosperity of the industry, and the tourism industry is also driven. The number of travel agencies, star-rated hotels and operating income is also high. The occupancy rate of rooms and the evaluation of service quality by tourists are also high. The development of service industry and tertiary industry in these five provinces is also at the leading level in China. Also at the domestic leading level. The provinces that are in the last few places are Gansu, Qinghai and Tibet. The tourism market is relatively backward, and the corresponding tourism services lack market competitiveness. After the opening of the Qinghai-Tibet Railway, the tourism industry in these provinces will get better development opportunities.

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Fig. 12.9 Comprehensive evaluation ranking of the competitiveness of tourism industry enterprises of 31 provinces, autonomous regions and municipalities

12.4.3.4

Evaluation and Analysis of Enterprise Competitiveness

The competitiveness of enterprises is mainly to study the scale, layout, structure and economic benefits of tourism enterprises in various provinces in China. As shown in Fig. 12.9, the top five strong competitive provinces are Shandong, Sichuan, Henan, Liaoning and other medium-competitive provinces. Travel agencies, tourist areas, star-rated hotels and other tourism enterprises in these provinces are relatively developed, correspondingly, the scale, operating income, profits and taxes, labor productivity, assets, and employees of these enterprises have reached a high level. No matter how good the tourism resources are, the lack of competitiveness of enterprises is not enough to attract tourists. Travel safety, food, accommodation and other aspects are very important for tourists, because tourism is to relax and enjoy all kinds of quality services, which is usually the majority. The purpose of tourism is then to visit tourist attractions and increase knowledge.

12.4.3.5

Evaluation and Analysis of Tourism Resources Competitiveness

Tourism resources is a hard index. The inherent tourism resources and natural geographical scenery in each province should be fixed in a certain period of time, but it can also be changed through the construction of tourist areas. The question is how to develop attractiveness for tourists. In addition to the traditional tourism provinces, tourism resources are in the top, as well as Sichuan and Henan (See Fig. 12.10). As is known to all, Sichuan’s Jiuzhaigou, Wolong, Leshan Giant Buddha, Emei Mountain, Henan’s Shaolin Temple, Luoyang Ancient Capital, Kaifeng, etc. are all

12.4 Design, Assessment and Analysis on Tourism Sector’s Competitiveness …

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Fig. 12.10 Comprehensive evaluation ranking of tourism resources competitiveness of tourism industry of 31 provinces, autonomous regions and municipalities

world-famous tourist destinations. These famous scenic spots will indeed give extra points to the province’s tourism resources. Inner Mongolia, Tianjin and Ningxia, the last few places in the list, are the provinces that lack tourism resources or have not been fully developed.

12.4.3.6

Evaluation and Analysis of Tourism Infrastructure Competitiveness

Tourism infrastructure plays a pivotal role in the tourism industry. Without first-class transportation, accommodation, catering, sanitation and safety services, the development of the tourism industry is unlikely to be so smooth. In addition to the traditional strong competitive provinces of Jiangsu, Zhejiang, Guangdong and Beijing, Liaoning ranks in the top five (See Fig. 12.11). Liaoning, as a coastal developed province, the original foundation of the heavy industry base in Northeast China has given Liaoning Province a superior traffic condition and a relatively open economic development environment. With the development of the economy, star-rated hotels, tourism vehicles and shipping enterprises and other related industries, form a relatively benign industrial chain driving cycle mechanism. At the end of the list are still inland provinces with less developed transportation such as Tibet, Qinghai and Ningxia.

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Fig. 12.11 Comprehensive evaluation ranking of tourism infrastructure competitiveness of 31 provinces, autonomous regions and municipalities

12.4.4 Analysis of the Structural Balance of Tourism Industry Competitiveness in 31 Provinces, Autonomous Regions and Municipalities The structural equilibrium degree of the development of the provinces in six aspects is shown in Fig. 12.12. Guangxi, Anhui and Hubei are at a medium level in the comprehensive ranking of tourism competitiveness, but they enjoy a more balanced structure in all aspects. Go hand in hand. The provinces such as Shandong and Guangdong are not only in a strong position in comprehensive tourism competitiveness, but also in a relatively good structural balance, and their comprehensive competitiveness is at the domestic advanced level. Provinces such as Ningxia, Qinghai, and Tibet not only have weak comprehensive competitiveness, but also have relatively unbalanced in development.

12.4.5 Summary of the Competitiveness of Tourism Industry in 31 Provinces, Autonomous Regions and Municipalities To sum up, the results of the evaluation of the competitiveness of tourism industry in various provinces and cities in China show that: (1) the tourism industry of Beijing, Shanghai, Guangdong, Zhejiang and Jiangsu has achieved high speed and high quality development. (2) Shandong, Hainan, Yunnan, Sichuan and other mediumstrong competitive provinces have shown a good development trend. As long as the rich tourism resources are developed and utilized, the tourism industry will be prosperous in the near future. (3) The developing provinces of Guangxi, Anhui,

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Fig. 12.12 Ranking of tourism structure equilibrium of 31 provinces, autonomous regions and municipalities

Hubei and other provinces have balanced development in all aspects, and they have made great progress. (4) Xinjiang, Ningxia, Qinghai, Tibet and other weak competitive provinces have relatively rich tourism resources, but they are not able to keep up with the development of tourism infrastructure and tourism enterprises. Their tourism market needs to be stimulated by the improvement of infrastructure.

Chapter 13

Research on Industrial Competitiveness of China’s Culture Sector

13.1 Background of the Research on Culture Sector’s Competitiveness More than 20 years of international competitiveness research, especially in the past 10 years, shows that a country’s cultural industry competitiveness has an important foundation and impetus for a country’s international competitiveness. The competitiveness of cultural industry with its extension covering cultural origin, ideology, values, organizational cohesion and so on, which has essential influence and binding force on other relevant elements of international competitiveness. In the new round of national competition brought about by the new scientific and technological revolution, people have become more prominent as the key resources and competitive subjects of national competition. Culture maintains people’s mutual relations, provides space for people to communicate with each other, and enables people to gather together to carry out various activities in society. Culture has three major influences on the country’s economic and social development. Firstly, culture is permeable and easy to communicate, learn from, and integrate. Thoughts and ideas are the cells of culture, everywhere, all the time, and often enter other new ingredients. Secondly, culture has the power of integration, using the cultural way of ideological education to regulate individual behaviors, to promote the individual’s mentality to group sharing, adaptability and adjustment, and to achieve cultural “soft” management. Thirdly, culture has the spiritual penetrating power and is easy to shape the human soul, thus guiding people to construct correct behaviors. Because of the cultural ties, the whole nation and the whole country have the collective commonness which is different from other ethnic groups. The ideology and value concept of this kind of precipitation in the members and organizations of the group coordinate and control the behavior of the members of the group at a deep level, making it lasting and inheriting. As a core competitiveness in a certain sense, the competitiveness of cultural industry is not only the most important national competitive soft power, but also has a profound impact on the overall competitiveness of the © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_13

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whole country. American scholar Huntington pointed out that the competition in the twenty-first century would no longer be economic competition, military competition, but cultural competition. Therefore, the evaluation and analysis of China’s current cultural industry competitiveness level has great practical significance to enhance China’s national competitiveness.

13.2 Structural Model of Culture Sector’s Competitiveness The competitiveness of the cultural industry is omnipresent, reflecting and measuring every aspect of our social life. However, from the main fields of the influence of culture to economic society, culture can be divided into five factors of competitiveness: public culture, business culture, corporate culture, humanistic culture and open culture (see Fig. 13.1). In the public domain, the administrative and legal systems are the two most important leading forces. They are the planning and guidance and macro-control of the entire public life, as well as the level of democratization, scientific and standardization. The level of public culture in a country largely explains the public management of the country, which is the scientific level and perfection of the administrative and legal systems. The competitiveness factor of public health culture industry reflected by this is an effective measure of the quality of public life management in a country and an important part of the overall competitiveness of cultural industry.

Fig. 13.1 Diagram of the factors of cultural industry competitiveness

13.3 Assessment Indicator System of Culture Sector’s Competitiveness

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The business environment is the platform for economic development and reflects the actual background of the overall operation of a country’s economy. Business culture reflects the business philosophy embodied in a country’s business activities, and the degree of perfection of software and hardware related to business development. The industrial competitiveness factors of business culture effectively reflect the quality and competitiveness of a country’s economic operating environment. Enterprises are the cells of a country’s economy and the mainstay of national economic development and competition. The influence of corporate culture on the competitiveness of enterprises has been promoted to a considerable height by scholars in various countries. The important role of corporate culture can be summarized as the corporate culture determines the integration ability of the enterprise. A good corporate culture can be a cohesive force and a centripetal force, so that the enterprise becomes a coordinated and unified whole team. The industrial competitiveness of corporate culture reflects the core competitive advantage of a country—the core competitive advantage of a company and the overall economic competitiveness of a country. The degree of understanding and attention to people has become an important yardstick for measuring the degree of social civilization and knowledge economy development in a country. The humanistic culture established on this basis has a good measure of this event. Humanistic research is mainly embodied in the education of people, the popularization of economic knowledge and science education, the respect of society for individuals, the protection of individual rights, and the tolerance of society to different groups. The industrial competitiveness factors of people-oriented culture are generally reflected in the importance and development of people in various countries, as well as the level of human competitiveness. Open culture is a systematic description of a country’s initiative to participate in international exchanges. With globalization as the core, it reflects the attraction and allocation of talents and resources. It is a systematic measure of a country’s participation in and preparation for the integration of global economy.

13.3 Assessment Indicator System of Culture Sector’s Competitiveness 13.3.1 Construction of Competitiveness Index System On the basis of the above-mentioned connotation of cultural industry competitiveness and the characteristics of cultural sub-factors, combined with the international competitiveness yearbook data released by IMD every year, under the guidance of the principles of comprehensiveness, hierarchy and symmetry, an index system composed of the following five sub-factors, 21 sub-factors and 67 indicators is designed (see Table 13.1).

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Table 13.1 Structure of cultural industry competitiveness evaluation index system Public culture

Decree implementation

Development and application of technology: legal environment support (↑) is bound by the legal environment (↓) Legal framework: supporting the development of national competitiveness (↑) damage to the development of national competitiveness (↓) Environmental Act: hinders business development (↓) does not hinder business development (↑)

Policy effectiveness

Your country’s exchange rate policy: supports the company’s competitiveness (↑) hinders the company’s competitiveness (↓) The consistency of the cabinet on policy direction: is very high (↑) is not high (↓) Government decision-making: can be effectively implemented (↑) cannot be effectively implemented (↓)

Government effectiveness

The management of public finances: will improve in the next two years (↑) will be weakened (↓) The central bank: has a positive impact on economic development (↑) has a negative impact on economic development (↓) Social cohesion: is one of the government’s primary goals (↑) is not one of the government’s primary goals (↓)

Government image

Bureaucracy: does not prevent the development of enterprises (↑) to prevent the development of enterprises (↓) Inappropriate behavior (such as bribery or corruption): is not prevalent in the public domain (↑) prevailing in the public domain (↓) Transparency: the government is transparent to the public (↑) and often cannot successfully disclose its intentions (↓)

Business culture Entrepreneurial spirit

Company creation: is common in your country (↑) is not common in your country (↓) Unemployment law: motivates people to find work (↑) does not motivate people to find work (↓) Employment growth: increased percentage

Business culture Sense of competition

Capital cost: does not hinder the development of competitive enterprises (↑) is too high and is not conducive to the development of competitive enterprises (↓) Competition law: preventing unfair competition in your country (↑) does not prevent unfair competition in your country (↓) (continued)

13.3 Assessment Indicator System of Culture Sector’s Competitiveness

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Table 13.1 (continued) Social values: are conducive to the improvement of competitiveness (↑) is not conducive to the improvement of competitiveness (↓) Financial intermediation

Stock market (including secondary market): provide sufficient funds for the company (↑) can not provide sufficient funds for the company (↓) Venture capital: enterprise development can be easily obtained (↑) enterprise development cannot be easily obtained (↓) Credit: can easily flow from banks to businesses (↑) and cannot easily flow from banks to businesses (↓)

Business fair

Tax evasion: is not common in your country (↑) is very common in your country (↓) Intellectual property rights: are well protected in your country (↑) not fully protected in your country (↓) Financial institution transparency: financial institutions provide sufficient information about their activities (↑) without adequate information on their activities (↓)

Open culture

Local protection

Tariff management: does not hinder the effective re-export of goods (↑) hinders the effective re-export of goods (↓) National protectionism: does not hinder the import of foreign goods and services (↑) hinders the import of foreign goods and services (↓) National culture: open to foreign cultures (↑) close to foreign cultures (↓)

Equality

Entering the local capital market: there are no restrictions on foreign companies (↑) restrictions on foreign companies (↓) Public sector contracts: are fully open to foreign bidders (↑) are not fully open to foreign bidders (↓) Foreign investors: are free to gain control of domestic companies (↑) are not free to obtain control of domestic companies (↓)

Attraction

Investment incentives: are sufficient to attract foreign investment (↑) to attract foreign investment (↓) Brain drain: well-educated people stay in the country for employment (↑) well-educated people immigrate to foreign employment (↓) Foreign high-tech labor force: is attracted by the domestic commercial economic environment (↑) is not attracted by the domestic commercial economic environment (↓)

Open attitude

Attitude: towards globalization is negative in your country (↓) is active in your country (↑) (continued)

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Table 13.1 (continued) Reconfiguration of production: the transfer of production to foreign countries has no threat to the future economy of the country (↑) has a real threat to the future economy of the country (↓) R&D resource reconfiguration: does not pose a threat to future economic development (↑) constitutes a threat (↓) Corporate culture

Team pointing

Employment relationship: the relationship between manager and employee is efficient (↑) oppsite (↓) Worker’s motivation: employees are consistent with company goals (↑) are inconsistent with company goals (↓)

Corporate culture

Team pointing

Employee training: the company attaches great importance to training employees (↑) companies to ignore training employees (↓)

Clear authority

The company’s board of directors: guarantees that the company’s reasonable operation (↑) cannot prevent the company from operating unreasonably (↓) The powers and obligations of shareholders: are clearly defined (↑) are not clearly defined (↓) Shareholder value: managers can effectively create value for shareholders (↑) can not effectively create value for shareholders (↓)

Management art

Ethical practices: adopted by the company (↑) do not adopted by the company (↓) Customer satisfaction: is valued in your country (↑) is not valued in your country (↓) Labor management (employment or dismissal practices): is flexible enough (↑) is not flexible enough (↓)

Exchange research and development

Enterprise technology cooperation: is very common among companies (↑) is very lacking among companies (↓) Cooperative research between institutions and enterprises: is sufficient (↑) insufficient (↓) New information technology: to meet the needs of enterprises very well (↑) can not meet the needs of enterprises (↓)

Entrepreneurship

Entrepreneurship: managers have strong entrepreneurship (↑) managers lack entrepreneurial spirit and innovation awareness (↓) Social responsibility: managers pay attention to responsibility to society (↑) managers ignore responsibility for society (↓) Manager’s credibility: gains public trust (↑) fails to gain public trust (↓) (continued)

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Table 13.1 (continued) People-oriented culture

Personal respect

Immigration law: does not prohibit domestic companies from hiring foreign technicians (↑) prohibits domestic companies from hiring foreign technicians (↓) Fairness,: full of confidence in the fair management of social equity (↑), no confidence in the fair management of social equity (↓) Security: people are full of confidence in the protection of personal and property safety (↑) people have no confidence in the protection of personal and property safety (↓) Equal opportunity: regardless of race, gender, family background, there are equal opportunities (↑) race, gender, family background can become a social barrier (↓)

Human resources Skilled labor: skilled labor is easy to obtain (↑) is difficult to obtain (↓) Financial and technical talents: are easily available in your country’s labor market (↑) not available in your country’s labor market (↓) A competent senior manager: is easy to get from the market (↓) is not easy to get from the market (↓) Status of obtaining qualified engineers: there is sufficient qualified engineers in the market (↑) there is a lack of qualified engineers in the market (↓) Popularity

Science and technology: inspire young people’s interest (↑) do not inspire young people’s interest (↓) Flexibility and adaptability: people in your country are fully flexible and adaptable to new challenges (↑) lack of flexibility and adaptability to new challenges (↓) Human Development Index: economic, social and educational composite index

People-oriented culture

Popularity

Alcoholism and drug abuse: have not become serious problems in the workplace (↑) become a serious problem in the workplace (↓)

Quality of education

Education system: adapt to the needs of a competitive society (↑) do not adapt to the needs of a competitive society (↓) University education: meet the requirements of a competitive economy (↑) does not meet the requirements of a competitive economy (↓) Economic knowledge popularization: economic knowledge popularization rate is high (↑) is low (↓) The state of science education: in the stage of compulsory education, science and technology education is in good condition (↑) is not good (↓)

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13.3.2 Validity Test of Competitiveness Index System In theory, we can fully affirm the important influence and role of cultural industry competitiveness and sub-factor competitiveness on national competitiveness and related specific fields. However, from the scientific and rigorous nature of the research, the indicators we selected are based on the soft data obtained through questionnaires in The IMD World Competitiveness Evaluation Yearbook. The data of these indicators were obtained by the respondents through subjective evaluation of individual experience. Although the relevant scientific and objective requirements were followed in the scoring process, the validity of the final scores was not guaranteed. This has always been an insurmountable weakness in the use of soft data. At the same time, considering the correlation between these indicators, the problem of duplicate information is reflected. Therefore, the principal component analysis method is used to extract the factors, and the main information of the indicators contained in each factor is gathered on a few factors to improve the efficiency of the analysis. We use the subordinate indicators of the five cultural sub-elements in the cultural industry competitiveness as a unit to analyze the factors of each sub-factor index. From the results of factor analysis, we found that the factor fitting of the subfactor indicators of each cultural industry competitiveness is relatively successful, and the corresponding simplified common factors are obtained. Then, we will carry out correlation analysis by using these factors and representative development “hard” indicators of each corresponding field for correlation analysis, and the results are shown in Tables 13.2, 13.3, 13.4, 13.5 and 13.6. According to the results of the comprehensive correlation analysis, several common factors of each cultural sub-factor have a strong correlation coefficient with the corresponding representative “hard” indicators of the relevant field, and the highest is above 0.8. From an empirical point of view, it shows that the index system of cultural industry competitiveness we selected does comprehensively summarize the overall information of the corresponding cultural sub-factors. At the same time, Table 13.2 Public culture correlation analysis Public culture sub-factors

Inflation rate (%, predicted value)

Exchange rate stability (2001) Changes in the exchange rate of the local currency relative to the special drawing rights (2001/1999)

Central government budget surplus/deficit accounted for GDP (%)

Real GDP growth rate (%, predicted value)

FAC1_1

−0.517388066

0.500601209

0.693549241

−0.39596

FAC2_1

0.002185813

0.142042233

0.127301171

0.5681

FAC3_1

−0.078033269

−0.119702196

0.747308075

0.283505

13.3 Assessment Indicator System of Culture Sector’s Competitiveness

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Table 13.3 Business culture correlation analysis Business culture sub-factors

Growth rate of export of Stock market goods percentage of financing amount change in US$ (%) accounted for GDP (%)

Investment risk European Currency national credit rating: 0–100

FAC1_1

0.511496842

0.495721723

0.573928064

FAC2_1

−0.242763167

0.106896731

0.501136041

FAC3_1

0.281025732

0.401061338

−0.274977408

Table 13.4 Open cultural correlation analysis Open cultural Foreign trade sub-factors dependence (export + import)/(GDP × 2)

Attracting foreign direct investment as a share of GDP (%)

Investment risk European Currency national credit rating: 0–100

National credit rating (2001) rated on a percentage basis according to Institutional Investor assessment

0.217653906

0.665878586

0.639181438

FAC1_1

0.271099676

FAC2_1

0.668941294

0.593767167

0.235740331

0.245681416

FAC3_1

−0.022278221

0.157364578

−0.470388792

−0.510408115

Table 13.5 Corporate culture correlation analysis Corporate culture sub-factor

Labor productivity (purchasing power parity) Hourly GDP per employee (in purchasing power parity) (US$)

Large enterprises against international standards: is efficient (↑) not efficient (↓)

Small and medium-sized enterprises against international standards: is efficient (↑) not efficient (↓)

Comprehensive productivity growth rate percentage change in real GDP per employed (2001, %)

Number of R&D staff (thousand people of full day equivalent unit)

FAC1_1

0.340445123

0.62135024

0.454536836

−0.34286

0.122007997

FAC2_1

0.658149339

0.469745682

0.762972408

−0.10574

0.439968766

FAC3_1

−0.224354275

0.235449642

0.164835285

0.650753

−0.221073528

Table 13.6 People-oriented culture correlation analysis People-oriented Unemployment Expected as a proportion healthy living culture of labor (%) age (2001, sub-factor estimated average)

Public education expenditure accounted for GDP

Per capita GDP calculated at current price and purchasing power parity (US$)

Number of computers per thousand people

FAC1_1

0.511496842

0.842388868

0.550924305

0.885863725

0.896742725

FAC2_1

−0.242763167

−0.109158694

0.298352095

0.027190183

0.044089065

FAC3_1

0.281025732

−0.14416842

0.107843171

0.143603161

0.173457763

FAC4_1

0.179130119

0.238096688 −0.09219642

−0.047124637 −0.0083227

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it also proves that the cultural sub-factors in different fields do have close connection and strong influence with the economic and social development degree in the same field.

13.4 Overall Assessment and Analysis of International Culture Sector’s Competitiveness Based on the IMD’S Yearbook, each country and region participated in the evaluation as the main body of the analysis, and the competitiveness index value of the cultural industry of the country or region as the data basis, this part analyzes and evaluates the overall and sub-factors of the cultural industry competitiveness of the country (region).

13.4.1 Evaluation and Analysis Ideas First, the indicator data of countries and regions are processed and converted into standardized scores between 0 and 100. This solves the problem that each index has different components and can not be effectively summarized to calculate the score of the upper level competitiveness factors. At the same time, it makes the index data more intuitive and concise. The specific method is to treat the indicator value of each country as a sample of normal distribution in each indicator. The mean μ and standard deviation σ of the sample are calculated. On the basis of assuming that the sample obeys the normal distribution N (μα), the lower cumulative probability value P(X 0.5

Country and region

Singapore

The United States

The United Kingdom

Lombardy, Italy

South Africa

Iceland

Sweden

Belgium

Zhejiang, China

Mexico

Canada

South Korea

Turkey

Brazil

Romania

Australia

Rhone-Alpes, France

India

Slovenia

Italy

Hong Kong, China

Bavaria, Germany

Colombia

Portugal

Poland

Ireland

Catalonia, Spain

Japan

Philippines

China

Austria

Ile-de-France, France

Scotland, the United Kingdom

Russia

Chile

Jordan

Spain

Indonesia

Denmark

New Zealand

Germany

Argentina

Israel

Slovakia

Czech Republic

Switzerland

France

Maharashtra, India

Finland

Luxembourg

Sao Paulo, Brazil

Norway

Malaysia

Greece

Taiwan, China

Hungary

Netherlands

Estonia

Country and region

Thailand

(2) Cluster analysis of sub-factor scores The scores of 21 sub-factors were analyzed by cluster analysis (see Table 13.9). The clustering results show that 60 samples are divided into five echelons according to the overall level and the structural similarity of each sub-factor. Hong Kong, China is located in a strong echelon. Taiwan, China is in a comparatively strong echelon, Zhejiang, China is in the middle echelon. China is in the weak echelon. Although the scores on the individual sub-factors are high, from the overall situation, the cultural industry competitiveness in China is in a weak position among 60 samples. In a certain sense, China’s Zhejiang Province, in terms of economy and culture, is the

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Table 13.9 Participating samples cluster analysis Stronger echelon

Strong echelon Middle echelon

Weak echelon

Weaker echelon

Singapore

Taiwan, China

India

Portugal

Luxembourg

Finland

Sweden

Malaysia

South Korea

China

Hong Kong, China

Bavaria, Germany

Estonia

Catalonia, Spain

Mexico

Iceland

Norway

Thailand

The United Kingdom

Slovenia

Denmark

Israel

Zhejiang, China

France

Italy

Chile

New Zealand

Jordan

Maharashtra, India

Russia

Canada

Hungary

Slovakia

Ile-de-France, France

Romania

Australia

Belgium

Turkey

Colombia

Argentina

Switzerland

Rhone-Alpes, France

Japan

Scotland, the United Kingdom

Indonesia

Austria

Czech Republic

Sao Paulo, Brazil

Poland

Ireland

Germany

South Africa

Venezuela

The United States

Spain

Netherlands

Brazil Philippines Lombardy, Italy Greece

representative of China’s advanced level. Zhejiang Province of China can surpass the UK, France and South Korea, and join in the middle echelon with Japan. It shows that China’s most advanced level has some strength from a world perspective.

13.5 Conclusions and Suggestions Through the above description of the competitiveness of China’s cultural industry, perhaps we have some understanding of China’s current cultural industry competitiveness. With further research, some problems in the current domestic economic development have emerged. This is the lack of competitiveness of China’s cultural industry, but it is also the starting point for us to improve the overall level of cultural industry competitiveness. Therefore, seriously treating and discussing these problems, and trying to analyze the causes and possible solutions of the problems, this is the direction pursued by this research. By comparing the scores and rankings of the competitiveness of cultural industries in China and China’s Zhejiang Province, it reflects the distance between the

13.5 Conclusions and Suggestions

235

advanced regions of China’s economic development and the national average. At the same time, it is not difficult to calculate the huge gap between advanced regions and backward regions. This gap is not only reflected in the level of economic development, but also in the competitiveness of cultural industries. Advanced people-oriented culture cultivates first-class talents and high-quality workers, advanced open culture creates first-class investment environment and international business exchange platform, advanced public culture and business culture provide first-class economic operation environment, advanced corporate culture creates first-class enterprises to produce first-class products, and the integration of many advanced factors makes a strong economic development and cultural synthesis. Therefore, the backwardness of cultural industry competitiveness is more worthy of our attention than the economic backwardness, because cultural soft power is the environment and institutional foundation for creating economic hard power and the source of economic development. The more prominent issue in business fairness is the protection of intellectual property rights, which has always been criticized by the international community. The solution of this problem requires us to introduce a series of systems and measures from legislation to administrative management. In dealing with problems, we should have laws to follow, rules to follow, and strict law enforcement, The establishment of this system needs the accumulation of time and practice, and also needs to cost a lot of manpower and material resources. Therefore, on the one hand, we must see the seriousness and urgency of the problem; on the other hand, it is impossible to do it overnight. The issue of equal treatment in globalization mainly involves the treatment of foreign capital in China, such as whether it can enter China’s capital market, whether it can participate in the bidding of Chinese public projects, and whether it can obtain the controlling interest of domestic companies. We cannot dismiss foreign capital and investors as fierce floods and savage beasts—great scourges and then always deny them, nor can we treat them all the same as nationals and give them full national treatment, because the reopening countries will impose certain restrictions on foreign institutions and funds from the perspective of national security and protection of national industries. As long as the development of enterprises can stimulate the economy and bring taxes, the issue of foreign capital control rights should not be a reason to hinder the entry of foreign funds into China. In companies that do not involve industrial security and national security, we do not absolutely exclude the holding of foreign capital. The issue of human resources, that is, the issue of talent, has attracted the attention of national leaders as early as the 1980s. Now, in the process of development, this problem also reflects structural problems. In particular, senior managers, engineers, financial and technical personnel, skilled technicians and so on are in short supply. On the one hand, it involves the problem that our country is not attractive enough to international talents. On the other hand, it also reflects the problem of talent training mechanism and training mode of higher education in our country. The

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priority problem that can be solved domestically is to strengthen vocational education and training for high-level skilled workers, focus on raising wage levels and welfare levels, and attract overseas high-end talents to serve in China. Based on the above, it is not difficult to judge that there are different degrees of problems in all aspects of cultural industry competitiveness of China. There is still a long way to go for improvement and development. To fully understand the current status of China’s cultural industry competitiveness, to face the gap between China and advanced countries and regions, to analyze the problems of weak links, to find a breakthrough and to explore solutions, is the work we need to do. I hope that we can always adhere to the attitude of seeking truth from facts, face up problems and solve problems. With the pace of the peaceful rise of the Chinese nation, our cultural industry competitiveness will certainly achieve faster and better development.

Chapter 14

Research on Industrial Competitiveness of China’s Environmental Protection Sector

The environmental protection industry is a special kind of industry. As an economic activity occurring within the economic system, it consumes economic resources and provides economic output as well as other economic activities; it will not only directly create employment and added value, which constitutes a part of GDP, but also stimulate or promote the development of other industries and indirectly create employment opportunities and added value. But on another level, these outputs meet the need to maintain environmental quality and avoid environmental degradation; at the same time, through technological innovations, using cleaner technologies or processes to produce, thereby reducing the negative impact on the environment. Gao Minxue (2004) suggested that the environmental protection industry can be regarded as an industry that achieves a “win–win” for the economy and environment. China’s environmental protection industry started in the 1970s. Over the past 40 years, it has experienced a development process from scratch, from small to large. At present, China’s environmental protection industry has formed an environmental industry system including environmental protection products, environmental protection services, resource recycling, natural ecological protection, clean products and other fields. The industry categories are basically complete, and on the whole, it has a certain economic scale, which provides an important material and technical guarantee for the development of China’s environmental undertakings.1 However, in the international competition of environmental protection industry, China has obviously lagged behind developed countries. There are drawbacks such as lack of international comparability and uniformity in the definition of environmental protection activities and environmental protection industries, and insufficient data, and the measurement of environmental protection activities is realistic. And the measurement of environmental protection activities is divided by the actual management system, scattered in 1

For details, see State Environmental Protection Administration: National Environmental Protection Related Industries Status Bulletin 2000 and National Environmental Protection Related Industries Status Bulletin 2004.

© Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_14

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different departments, its content mainly focuses on the physical quantity statistics of environmental conditions, the value accounting is only limited to incomplete expenditure statistics, lack of unified accounting for environmental protection activities, which leads to the accounting of environmental protection industry in China is still in the preliminary stage of exploration. Therefore, it is necessary to grasp the definition of environmental protection industry at home and abroad, clarify the concept and scope of environmental protection industry based on China’s reality, and show the ways and methods of unified accounting of China’s environmental protection industry, so as to grasp the development status and development trend of China’s environmental protection industry; further, the scale of the environmental protection industry is linked with the level of economic development and environmental pressure, and the opportunities and challenges faced by environmental protection industries in various regions of China are evaluated from the perspective of competitiveness. Therefore, it is possible to timely and fully analyze the implementation of environmental protection activities in China and various regions, so as to implement scientific macro-control, formulate reasonable industrial policies, and give full play to the important role of environmental protection industries in the development of national economy.

14.1 Definition of Environmental Protection Sector The environmental protection industry is directly named environmental industry in some literatures, especially in European and American literatures. Some literatures are named eco-industry or environmental goods and services industry. In China, they are called environmental protection related industries. In order to correspond to the entire environmental protection theme, and to take into account the relevant research at home and abroad, this book uses the title of environmental protection industry. At the beginning of the study of environmental protection industry, due to the double restrictions in theory and practice, the definition of environmental protection industry is relatively narrow, mainly focusing on pollution control. For example, in 1992, the OECD2 defined the environmental protection industry as an industry covering a variety of goods and services, but there is no clear statistical classification, and the data is very limited. According to “end use”, environmental protection equipment and related services are subdivided into four categories, namely wastewater treatment, waste management, air quality control and others (mainly soil restoration and noise reduction). Environmental protection technology involved in industrial process is not included in the classification of environmental protection industry. Comprehensive environmental services is usually related to clean technology and listed separately. It can be seen that considering the difficulty of accounting for clean technologies and processes, the early OECD’s definition of the environmental protection industry, although referring to clean technology, has not been integrated 2

OECD, The Global Environmental Goods and Services Industry, 1996.

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into the environmental industry accounting, but is separately listed. Not only that, but the definition does not include general environmental protection activities such as resource management and ecological protection. As the demand for environmental protection activities has gradually widened, people are not only satisfied with “terminal management” for environmental issues, but also require environmental protection activities in a broader sense. The European Commission3 believes that the environmental industry can be described as being composed of such enterprises the goods and services they produce are used for the measurement, prevention, and limitation of water, air and soil environmental damage and problems related to waste, noise and ecosystems. Minimized or corrected. It includes cleaning techniques, goods and services that minimize pollution and resource use. Based on the definition of environmental protection industry in OECD (1992), it further extends the activities of clean technology, goods and services, and ecosystem protection. The environmental protection industry is defined for environmental protection activities, so its coverage is directly dependent on the scope of environmental protection activities, and the two are in the same line. A more detailed definition of environmental protection activities is the classification of environmental protection activities (CEPA)4 developed by Eurostat in 2000. This classification mainly reflects the different fields of environmental protection in a narrow sense, such as the protection of surrounding air and climate, wastewater management, waste management, soil, groundwater and surface water protection and restoration, noise and vibration reduction, biodiversity and landscape protection, radiation prevention, research and development, etc. However, CEPA is designed to classify transactions and activities with the main purpose of environmental protection, that is, environmental protection activities in a narrow sense, which does not include natural resource management (such as water supply) and natural disaster prevention (such as fire, flood and so on), so it is necessary to supplement them. In addition to the gradual development of environmental industry research by international organizations, the developed countries in the world have begun to realize the importance of environmental protection after experiencing rapid economic development and adopted a series of environmental protection measures. Since 1995, in order to understand the development status of environmental protection industry in Canada, Statistics Canada has started to carry out the annual survey of environmental protection industry under the support of the federal government,5 and clearly pointed out that the environmental protection industry in Canada refers to all companies that are engaged in the production of environmental protection products, the provision of environmental protection services and environmental protection related construction activities in Canada. The environmental protection products and services mentioned above refer to the products and services that can be used or potentially 3

European Commission, Environmental Expenditure Statistics: Industry data collection handbook, 2005. 4 UN, Integrated Environmental and Economic Accounting—2003. 5 Canada, Env-industry Survey 1995–2000.

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used to measure, prevent, limit or improve the environmental damage (natural or man-made behavior) to water, air and soil, and the problems related to waste, noise and ecosystem. It also includes technologies for clean or efficient use of resources, products and services for remediation of valuable by-products, reduction of emissions or minimization of waste emissions. Generally speaking, the key to determine environmental protection products lies in the end use of environmental protection products and services, not in their material properties. While maintaining its position as the world’s largest power, the United States is also the world’s largest energy consumer, in recent decades, it has gradually realized the serious harm of high energy consumption and began to formulate and implement many national strategic plans and legal frameworks to reduce energy consumption. In 1995, Environmental Protection Agency (EPA)6 systematically introduced the definition of environmental protection industry, including the following two points: The first is that the foundation of environmental protection industry is environmental protection activities, and the so-called environmental protection activities are mainly limited to the pollutant reduction and prevention activities within the management scope of the US Environmental Protection Agency. Obviously, this is a narrow definition of environmental protection activities; the second is to determine the environmental protection activities and environmental protection industry by tracking the cost, which refers to the industry that has implemented the environmental protection regulations and thus borne the corresponding cost. In the 1990s, Japan put forward the idea of building a recycling-oriented society, and formulated the long-term goal of an economic and social system with less environmental load and based on waste recycling. In 2001, from a broad perspective, the Japanese Environment Agency defined the environmental protection industry7 as a “industrial sector that potentially contributes to reducing environmental stress”. It includes the development and sales of environmental burden reduction devices, the development and sales of products with less environmental burdens, the development and services of environmental services, and the development and sales of technologies, equipment and systems for strengthening public facilities. Japan’s environmental protection industry has shifted from the first specific polluting industry to the general environmental protection industry including clean technology and ecological protection, from the official needs to the needs of the people, from the city to various regions. Since 1993, China has carried out four surveys on the basic situation of environmental protection-related industries nationwide,8 gradually breaking through the 6

United States Environmental Protection Agency, The U.S. Environmental Protection Industry: the Technical Document. EPA 230-R-95-012, September 1995. 7 Environmental protection industry is usually called ecological industry in Japan. For the classification of environmental protection industry, please refer to Wang Jinfeng. Comparative Analysis of Environmental Protection Industry Classification Between China and Japan, Published in China’s Environmental Protection Industry, No. 4, 2002, pp.34–36. 8 For details, see State Environmental Protection Administration: National Environmental Protection Related Industries Status Bulletin 2000 and National Environmental Protection Related Industries Status Bulletin 2004.

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boundaries of narrow-scale environmental protection activities, and paying more and more attention to the control of environmental behavior throughout the product life cycle. In 2004, the environmental protection industry was defined as the industry in the national economic structure for environmental pollution prevention, ecological protection and restoration, effective use of resources, meeting people’s environmental needs, and providing products and services for social and economic sustainable development. It includes not only the narrow connotation of product and technical services in pollution control and emission reduction, pollution cleanup and waste disposal, but also environmentally friendly technologies and products, energy-saving technologies, eco-design and environmental-related services during the product life cycle. However, China’s definition of environmental protection industry still does not include environmental protection activities such as natural resource management and natural disaster protection. The United Nations’ System of Environmental Economic Accounting 2003 (SEEA) manual defines that the so-called environmental industry, the environmental goods and services industry, it consists of such activities: produce goods and services that are used to measure, prevent, limit, minimize or correct environmental damage to water, air and soil, as well as problems related to waste, noise and ecosystems. It includes clean technologies, goods and services that reduce environmental risks and minimize pollution and resource use, as well as activities related to resource management, resource exploitation and natural disasters. The definition covers all the environmental protection activities involved in the current study, and can be regarded as the most complete and detailed definition of environmental protection industry. Summarizing the above applications, we can generalize the different threads of the environmental protection industry: 1. The environmental protection industry covers a range of goods and services of different natures. It includes not only goods and services directly provided for environmental pollution control, but also environmentally-related products such as equipment, special materials, buildings and facilities that are uniquely used for environmental service production. If the boundaries of environmentally friendly products are further extended, environmentally friendly products, ie cleaning products, should also be included throughout the life of the product. 2. Different research focuses on environmental protection industry. Some researches are based on the broad definition of environment, and the research content is relatively broad. They think that environmental protection industry should be environmental protection activities in a broad sense including pollutant prevention and control management, natural resource management and ecological protection construction, while some researches only focus on environmental protection activities in a narrow sense including pollutant prevention and control management and ecological protection construction. 3. There is still no consensus on the connotation of the environmental protection industry. In the narrow sense of the environmental protection industry, the term

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“terminal management” mainly refers to industries that are formed by environmental protection, emission reduction, pollution control, and waste disposal, which are directly affected by environmental protection. However, more and more researches tend to expand the content of the above-mentioned environmental protection industry in a narrow sense, and believe that it should also include comprehensive environmental protection activities, that is, those activities that have environmental protection functions while achieving specific use value of products. Specifically refers to the production and use activities of cleaning products and cleaning technology. This book follows the definition of environmental protection industry in the SEEA manual, but the definition of China’s environmental protection industry has the following aspects: Firstly, the definition of environmental protection industry should be based on general environmental protection activities, including not only the management of pollutants, but also the sustainable management of resources and the construction of ecological protection. Secondly, the environmental protection activities covered by the environmental protection industry mainly refer to environmental protection activities as production activities, excluding income distribution and capital operation around environmental protection activities. Thirdly, according to the way environmental protection activities occur, the environmental protection industry not only includes environmental protection service industries, but also clean products and technology industries that reflect comprehensive environmental protection activities. Fourthly, in theory, the environmental protection service industry should include not only external environmental protection activities completed by independent economic units, but also internal environmental protection activities that occur within the various economic units to assist production activities. However, due to the limitation of the availability of data, the current accounting for China’s environmental protection industry does not consider the internal environmental protection industry for the time being. Fifthly, the environmental protection industry should also include environmental protection related industries, because its output uniquely serves the environmental protection service industry and is in the upstream of the environmental protection industry. From the basic definition, it is not an environmental activity. However, from another perspective, these industrial activities will not occur if it is not for environmental protection.

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14.2 Identification and Classification of Environmental Protection Sector Regardless of the International Standard Industrial Classification (ISIC) framework or China’s National Economic Industry Standards, environmental activities that can be individually identified are very limited. The reason is that the industry classification is based on the principle of homogeneity of economic activities, and it is difficult to meet the requirements of separately observing environmental protection activities. Therefore, it is necessary to break the existing industry classification based on existing industry standards and regroup the relevant categories of the environmental protection industry.

14.2.1 Basic Framework Based on the above discussion, this study defines and classifies the environmental protection industry as follows: the environmental protection industry is composed of activities that provide services for the measurement, prevention and limitation of environmental damage to water, air and soil, as well as problems related to waste, noise and ecosystem, so as to minimize or correct them, as well as the environmental protection service industry related to resource management, resource exploitation and natural disasters, it also includes clean products and technology industries that reduce environmental risks and minimize pollution and resource use, as well as environmental related industries that provide relevant materials and equipment for the above activities. The details are shown in Fig. 14.1. Further, according to the way of environmental protection industry, the environmental protection service industry can be regarded as the core layer of the environmental protection industry, and the cleaning industry and technology industry can be regarded as the expansion layer of the environmental protection industry, and the environmental protection related industry is regarded as the support layer of the environmental protection industry, as shown in Fig. 14.2.

14.2.2 Classification Basis and Industry Identification In theory, it is the most ideal way to identify environmental protection activities according to the Industrial classification for National Economic Activities. However, in practice, it is necessary to have four-level code classification data and such high requirements can only be met in a specific year. Then, the environmental activity is identified by means of a detailed 122 sectors input–output table, but this can only be achieved in the year of compilation. Finally, we hope to seek data about environmental protection activities with the help of regular statistics. The following

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Fig. 14.1 Basic framework of environmental protection industry

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Fig. 14.2 Structure of environmental protection industry

is based on the principle of from coarse to fine, from shallow to deep, first examines the regular statistical level, then examines the 122 sectors input–output table level, and finally identifies the economic activities that belong to the scope of the environmental protection industry in the Industrial Classification for National Economic Activities.

14.2.2.1

Regular Statistical Level

According to the China Statistical Yearbook 2006, China’s regular statistics does not show environmental protection activities from an industrial perspective, but in the environmental protection section, data on natural resources, ecological protection zones and environmental quality are given from the perspective of environmental stocks. As a rough statistics on the status of environmental protection industry, as shown in Table 14.1.

14.2.2.2

Input–Output Table Level

Of the 122 sectors in the input–output table, there are not many categories that can be clearly defined as environmental protection industries. Because some industries only partially contain environmental protection activities, but environmental protection activities occupy a large proportion of the industry, but there is no relevant data to support, so can not simply define the industry as an environmental protection industry. Table 14.2 lists the industry categories that involve environmental activities.

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Table 14.1 Environmental protection data of China Statistical Yearbook 2006 Physical quantity indicator

Environmental stock

Natural resources

Water resource Forest resource Land resource Wetland area

Ecological protection

Nature reserve Ecological demonstration area

Environmental quality Sea water quality Air quality Environmental pressure

Environmental pollution

Waste water disposal Exhaust emission Solid waste generation Environmental noise

Natural disaster

Geological disaster Earthquake disaster Forest fire

Environmental protection activities

Value indicator

14.2.2.3

Environmental expenditure

Environmental pollution treatment and utilization

Waste water treatment

Sustainable forestry

Forest pest control

Natural disaster prevention

Geological disaster prevention

Pollution control investment

Industrial pollution control

Sustainable forestry

Forestry fixed assets investment

Exhaust gas treatment Solid waste treatment and utilization

Industrial Classification for National Economic Activities Level

Obviously, the identification of environmental protection industry through regular statistics and the input–output table of 122 sectors is difficult to reflect the overall picture of environmental protection industry. Therefore, according to the Industrial Classification for National Economic Activities, the economic activities that meet the above definition and scope of environmental protection industry and are listed in sub categories can be classified as environmental protection industry. However, very detailed data on sub-categories must be available in order to aggregate and obtain an overall overview of the environmental industry, which is difficult in practice.

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Table 14.2 Environmental protection industry categories in the input–output table of 122 sectors Industry category

Code

Industry category

Code

Forestry

02002

Electric machinery

39072

Fishery

04005

Other electrical machinery and equipment manufacturing industry

39074

Agriculture, forestry, animal husbandry 05006 and fishery service industry

Instrumentation manufacturing industry

41081

Petroleum and nuclear fuel processing industry

25036

Waste and scrap

43085

Speciality chemical products manufacturing industry

26043

Electricity and heat production and supply industry

44086

Rubber products industry

29047

Water production and supply industry

46088

Nonferrous metal rolling and processing industry

33059

Construction industry

47089

Metal products industry

34060

Wholesale and retail trade industry

63102

Boiler and prime mover manufacturing 35061 industry

Scientific research

75111

Other specialized equipment manufacturing industry

Professional technology and other technology service industry

76112

36065

Automobile manufacturing industry

37067

Geological prospecting industry

78113

Auto parts and accessories manufacturing industry

37068

Water management industry

79114

Environmental resources and public facilities management industry

80115

Ship and floating device manufacturing 37069 industry

According to the above definition and classification of environmental protection industry, and referring to the Industrial Classification for National Economic Activities, the environmental protection industry can be divided into four levels. The first layer is divided into environmental protection service industry, clean product and technology industry and environmental protection related industry according to the occurrence mode of environmental protection activities, which are respectively represented by part I, part II and part III. The second layer is divided into 8 major categories according to the purpose of environmental protection activities, such as pollution management, resource management and scientific research monitoring, which are indicated by the Roman numerals I and II and so on. The third layer is divided into 14 categories, indicated by Arabic numerals, according to the specific environmental areas to be protected. There are 78 sub-categories in the fourth layer, which is the industry category layer included in the third layer and the specific activity category of the environmental protection industry. No serial number is set in this layer, and the code is set on the left side, which is the corresponding “national economy industry code”.

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In order to scientifically, completely and accurately reflect the classification of environmental protection industry, this classification has made special treatment to some contents: 1. In the third layer, filter layers are set under part of the middle classes. There are 12 categories in total, which are represented by Arabic numerals with brackets, which is helpful to further classify similar industry categories. 2. In the fourth layer, some activities of small categories (industry categories) are not pure environmental protection activities, and the corresponding categories are denoted by asterisk “*”. 3. An extension layer is set under the sub-category (industry category) of the fourth layer, with a total of 38 categories. The extension layer does not set the code and serial number, and the corresponding category is indicated by the horizontal line “—”. This is because some industries are divided very roughly, making it difficult to reflect the environmental protection activities that need to be observed separately when the environmental protection industry is divided according to industries. Therefore, an extension layer is added under some small categories, so as to reflect the environmental protection activities described by the industry scientifically, completely and accurately. Table 14.3 shows the environmental protection activities included in the Industrial Classification for National Economic Activities and further classifies them into the classification of environmental protection industries according to the classification methods.

14.3 Analysis of Industrial Competitiveness of China’s Environmental Protection Sector The environmental protection industry is not only an ordinary industry, it has macropositive benefits such as providing employment and promoting economic growth, but also is a special industry, its output has a social value far greater than its market value as a commodity. Therefore, the environmental protection industry also has an additional Social benefits. The Decision of the State Council on Implementing Scientific Outlook on Development and Strengthening Environmental Protection and the Sixth National Environmental Protection Conference clearly pointed that China must realize the importance of shifting from focusing on economic growth to environmental protection and economic growth, and from environmental protection behind economic development to environmental protection and economic development simultaneously. However, the international competitiveness research of environmental protection industry is in the stage of preliminary exploration. In 1998, the US Department of Commerce Office of Technology Policy issued a report entitled The US Environmental Industry, 1998, the competitiveness of environmental industry related technologies in the United States, Germany, Japan, France and the United Kingdom

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Table 14.3 Environmental protection industry classification National economy industry code

Category Part one: Environmental protection service industry I. Pollution management 1. Waste water management Sewage treatment and its recycling

4620

Water pollution control

8023

Municipal public facilities management*

8110

– Urban sewage discharge, dredge, dredging 2. Solid waste management (1) Hazardous waste collection, treatment and disposal Hazardous waste management Nuclear fuel

processing*

8024 2530

– Nuclear waste disposal (2) Waste collection, treatment and disposal Processing of metal scrap and scrap Processing of metal scrap and scrap

4310

Non-metallic scrap and scrap processing

4320

Recycling and wholesale of recycled materials

6391

3. Other pollution management Urban environmental sanitation management

8022

Other environmental governance

8029

II. Resource management 1. Water resources management Production and supply of tap water

4610

Other water treatment, utilization and distribution

4690

Reservoir management

7921

Water diversion and diversion management

7922

Other water resources management

7929

Other water management

7990

2. Recycled material Recycled rubber manufacturing

2940

3. Sustainable forestry (1) Cultivation and planting of trees Breeding and seedling

0211

Afforestation

0212

Tending and management of forests

0213

(2) Forestry service industry

0520 (continued)

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Table 14.3 (continued) National economy industry code

Category 4. Sustainable fisheries (1) Marine fisheries

0411

Mariculture (2) inland fisheries Inland aquiculture

0421

(3) Fishery service industry

0540

5. Sustainable agriculture Irrigation service

0511

Other agricultural services*

0519

– The activity of planting a crop to promote its growth or to prevent pests and diseases 6. Natural disaster management Meteorological services

7610

The earthquake services

7620

Marine services

7630

Flood control management

7910

7. Ecological protection (1) Nature conservation Nature reserve management

8011

Wildlife conservation

8012

Other nature conservation

8019

(2) Urban greening management

8120

(3) Management of tourist attractions

8131

Management of scenic spots Park management

8132

Management of other tourist attractions

8139

III. Scientific research monitoring 1. Environmental monitoring, mapping and surveying (1) Environmental monitoring and mapping Surveying and mapping service

7640

Environmental monitoring

7660

Engineering survey and

design*

7672

– Investigation and design of water conservancy and hydropower projects – Landscape architecture design Planning management*

7673 (continued)

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Table 14.3 (continued) National economy industry code

Category – Planning activities of scenic spots – Planning activities of urban landscape greening – Planning activities in agriculture and forestry (2) Geological prospecting industry Geological exploration of energy minerals

7811

Geological exploration of solid minerals

7812

Geological exploration of other minerals

7819

Basic geological exploration

7820

Technical service of geological exploration

7830

2. Environmental research and development Engineering and technology research and test development*

7520

– Energy science and technology – Water conservancy engineering technology – Environmental science and technology Agricultural scientific research and experimental development*

7530

– Agricultural, forestry and aquaculture research and experimental development activities Part two: Cleaning products and technology industry I. Clean product industry Turbine and auxiliary machinery manufacturing*

3514

– Water turbine, water wheel and its control machinery Other prime mover manufacturing Generator and generator set

manufacturing*

3519 3911

– Water turbine generator, turbine generator – Nuclear power generation equipment – Wind turbine set Appliance manufacturing for gas, solar and similar energy 3961 sources III. Clean technology industry Hydroelectric power

4412

Nuclear power generation

4413

Other energy generation

4419 (continued)

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Table 14.3 (continued) Category

National economy industry code

Part three: Environmental protection related industries I. Related industries of pollution management 1. Pollution management related materials manufacturing Manufacture of special pharmaceutical materials for environmental pollution treatment

2666

Construction ceramics manufacturing*

3132

– Ceramic pipe: drainage ceramic pipe, well ceramic pipe and ceramic pipe fittings Manufactured of heat and sound insulation materials*

3135

– Mineral wool sound absorber – Other sound insulation, sound absorption mineral products 2. Equipment manufacturing for pollution management Boiler and auxiliary equipment manufacturing*

3511

– Soot cleaner and gas collector Ovens, furnaces and electric furnaces manufacturing*

3560

– Incinerators, waste incinerators, radioactive waste incinerators Gas and liquid separation and purification equipment manufacturing*

3572

– Air separation equipment – Gas or liquid filtration, purification and purification equipment – Purification detection equipment and similar devices Manufacturing of special equipment for prevention and control of environmental pollution

3691

Vehicle manufacturing*

3721

– Special operation vehicle: garbage disposal vehicle, mobile environment monitoring vehicle, etc Auto parts and accessories manufacturing*

3725

– Auto parts: muffler, etc Marine environmental protection equipment

3754

Industrial and mining engineering construction*

4723

– Construction of waterworks and sewage treatment plants – Construction of solid waste treatment project Construction of overhead lines and pipelines (including construction of sewage pipes and water pipes)

4724

– Urban sewage, water pipeline construction and transfer station, control station (by) construction (continued)

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253

Table 14.3 (continued) Category

National economy industry code

II. Resource management related industry Water resources special machinery manufacturing

3697

Water conservancy and port engineering construction

4722

Hand tool manufacturing*

3422

– Fire and explosion-proof special hand tools Safety and fire metal products manufacturing*

3453

– Metal products for fire protection: fire ladders, fire boxes, fire hydrants, etc Social public safety equipment and equipment manufacturing*

3695

– Fire fighting equipment and equipment Vehicle-specific lighting and electrical signal equipment installation*

3991

– Fire alarm equipment and similar devices Construction and installation industry*

4800

– Sewage pipe and equipment installation – Sewer and equipment installation – Fire alarm installation III. Related industries of scientific research monitoring Environmental monitoring special instrument manufacturing

4121

Navigation, meteorological and marine special equipment manufacturing

4123

Geological exploration and seismic special instrument manufacturing*

4125

– Seismic instruments, artificial seismic instruments, etc Nuclear and nuclear radiation measuring instrument manufacturing*

4127

– Nuclear radiation dose monitoring and alarm instrument for environmental and personal protection

was compared and analyzed, mainly involving three fields: environmental service industry, environmental equipment industry and environmental resources industry. The conclusion is that each country has different advantages in various fields, but the United States ranks first, followed by Germany, the United Kingdom, France and Japan. Although this research doesn’t focus on the environmental protection industry, it basically covers the main areas of environmental protection technology and several major leaders in the world market of environmental protection industry. Moreover, due to the advantages of environmental protection technology often directly affect the development advantages of environmental protection industry,

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Fig. 14.3 Environmental industry competitiveness research framework

the research conclusion has value for evaluating the competitiveness of environmental protection industry. To a certain extent, that research can be regarded as the beginning of the research on the competitiveness of international environmental protection industry. This book analyzes China’s environmental protection industry competitiveness, based on various regions of the country.

14.3.1 Theoretical Framework Refer to the survey data of environmental protection-related industries9 carried out by the State Environmental Protection Administration in 2001 and 2004, we can obtain scale data of environmental protection industry. Moreover, starting from the relevant factors related to the development of environmental protection industry, and drawing on Porter’s “Diamond theory” and other theories of determinants of industrial competitiveness, the level of environmental protection industry in each region is examined from the perspectives of economic growth, environmental pressure and environmental governance. As shown in Fig. 14.3, the above three related factors constitute an interrelated “pressure-state-response” structure around the environmental protection industry. The rapid development of the national economy will generate a large amount of pollutants and waste, which will affect the environment and constitute pressure. Environmental stress causes individuals and societies to respond to avoid or mitigate these effects, such as environmental governance and emissions reductions. This constitutes the outer ring of the research framework. In addition, they each interact 9

In principle, the data caliber of the current situation of environmental protection industry should be consistent with the scope of environmental protection industry specified in Sect. 14.2. However, due to the limitation of data, it is impossible to obtain the sub category data of Industrial classification for National Economic Activities at present, so the data of national environmental protection related industry bulletin is adopted. However, as mentioned above, the definition of the scope of environmental protection industry is slightly different from that recommended in this book.

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255

with the environmental industry, which constitutes the inner ring of the research framework. The inner and outer rings work together in the form of a complete system for the environmental protection industry. Each factor is analyzed one by one as follows.

14.3.1.1

Economic Growth

Economic growth is the most fundamental and important determinant of the development of environmental protection industry. Without economic prosperity, the development of environmental protection industry will be difficult to sustain. Tom Titanborg (2003) the famous “Kuznets curve” theory in environmental economics pointed out: environmental quality may continue to decline and deteriorate with economic growth, leading to the development of a narrow environmental protection industry based on pollution control in the early stage of economic development. However, when a certain turning point is reached, environmental quality may follow the economy. The further development has gradually improved, the intensity of pollution control has weakened, and resource management, ecological protection, and the clean products and technology industries have flourished, resulting in the changes of internal structure of the environmental protection industry.

14.3.1.2

Environmental Pressure

Environmental pressure comes from human socio-economic activities and various natural phenomena. These are two completely different categories, which should be statistically separate and should be dominated by the former. Behind the rapid growth of the national economy, the massive energy raw materials and other resources consume. The growth of GDP in many provinces is still at the expense of high energy consumption and high pollution, causing greater environmental pressure. If everyone have a strong sense of environmental protection under the pressure of greater environmental pressure, the environmental protection industry will inevitably develop faster than before. On the contrary, the rapid and healthy development of the environmental protection industry will further reduce environmental pressure.

14.3.1.3

Environmental Governance

In view of the current situation of environmental pollution in China, each region adopts environmental protection activities to control the environment, to eliminate possible environmental threats, to resist the negative impacts of the environment, and to deal with the adverse consequences caused by environmental impacts. As a result, it causes the rapid development of the emerging industry—environmental industries. Gao Minxue (2000) according to the function and mode of environmental activities, environmental governance can be divided into two categories: defensive

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or remedial environmental governance and preventive environmental governance. The former mainly refers to the clean-up action against environmental pollution, aiming to eliminate the impact of environmental pollution and avoid the harm caused by environmental degradation. The latter is to change or control human behavior, aiming to eliminate the possibility that the environment has a negative impact on human life. Obviously, the latter is more effective than the latter, but China is in the transforming process of economic growth mode from extensive to intensive, and the remedial environmental governance is still the highlight of the environmental protection industry.

14.3.2 Selection of Indicators According to the above theoretical framework of environmental protection industry competitiveness, we can design the environmental industry competitiveness model in various regions of China. It selects the basic indicators of China’s environmental industry competitiveness analysis, following the principle of availability and rationality of the indicator statistics and combining with the characteristics of China’s development stage. The specific indicators are shown in Table 14.4.

14.3.3 The Practical Analysis of China’s Environmental Protection Industry Competitiveness 14.3.3.1

The Analysis of China’s Environmental Protection Industry Competitiveness

After nearly 30 years of rapid development, China’s environmental protection industry has formed an industrial system with complete industrial categories and a certain economic scale in genera. In order to prevent environmental pollution, protect natural resources, improve the ecological environment, and maintain social sustainable development, the environmental protection industry has become an important part of the national economic structure. In 2000, the total income of the national environmental protection industry was RMB168.99 billion, accounting for 1.89% of the GDP in the same period, and realized a profit of RMB16.67 billion. In 2004, the total income of the environmental protection industry reached RMB457.21 billion.10 In 2004, the total income of the environmental protection industry reached RMB457.21 10

Compared with 2000, the survey scope of environmental protection related industries in 2004 was slightly adjusted. The scope of the survey is reduced from enterprises and institutions in all environmental protection related industries in 31 provinces, autonomous regions and municipalities to non-state-owned enterprises or institutions with annual sales (operation) income of more than RMB2 million in all state-owned and environmental protection related industries.

14.3 Analysis of Industrial Competitiveness of China’s Environmental …

257

Table 14.4 Basic indicator system for analysis of competitiveness of environmental protection industry Variable name

Indicator

The scale of environmental protection industry

Number of companies

(a)

Number of employees

(people)

Total annual income

(RMB100 million)

Economic growth

Environmental pressure

GDP

(RMB100 million)

Per capita GDP

(RMB100 million)

Industrial added value account for a percentage of regional GDP

(%)

Waste water

Total industrial waste water discharge

(10,000 tons)

Domestic sewage discharge

(10,000 tons)

Industrial sulfur dioxide emissions

(10,000 tons)

Living sulfur dioxide emissions

(10,000 tons)

Industrial soot emissions

(10,000 tons)

Domestic soot emissions

(10,000 tons)

Industrial dust emissions

(10,000 tons)

Industrial solid waste production

(10,000 tons)

Domestic garbage removal

(10,000 tons)

Industrial waste water discharge scalar

(10,000 tons)

Waste water treatment facilities

(set)

Number of waste gas treatment facilities

(set)

Industrial sulfur dioxide removal

(10,000 tons)

Waste gas

Solid waste

Environmental governance

Unit

Waste water

Waste gas

Solid waste

Industrial soot removal

(ton)

Industrial dust removal

(ton)

Industrial solid waste disposal

(10,000 tons)

Domestic garbage removal

(10,000 tons)

258

14 Research on Industrial Competitiveness of China’s Environmental …

billion, which was 2.71 times of the total income in 2000, accounting for 3.34% of the GDP in the same period. Table 14.5 lists the basic situation of the national and regional environmental protection industry in 2000 and 2004, and ranks according to the total annual income of environmental protection industry in 2004. Obviously, the total annual income of environmental protection industry in all regions of the country shows a strong momentum of development. Jiangsu Province’s annual revenue increased from RMB 20.99 billion in 2000 to RMB101.65 billion in 2004 in the environmental protection industry. It has a gap of RMB37.25 billion with the second place in Zhejiang Province. The next one is Guangdong Province. The total annual income of the environmental protection industry in these three provinces exceeds RMB50 billion, which can account for about half of China’s total environmental protection industry income. However, the environmental protection industry is mainly concentrated in economically developed areas, such as the eastern coastal areas. As shown in Table 14.5, the total income of 12 provinces exceed RMB10 billion, in addition to the above three provinces, including Shandong, Liaoning, Shanghai, Fujian and other provinces. The total income of these 12 provinces amount RMB375.14 billion, accounting for 82.05% of the total income of the national environmental protection industry. However, in 2004, the total annual income of environmental protection industries did not exceed RMB1 billion in the western provinces of Xinjiang, Ningxia, Qinghai and Tibet. That shows a wide gap in environmental protection income among provinces.

14.3.3.2

Analysis on the Related Factors of Environmental Protection Industry

In the analysis of the influencing factors of the environmental protection industry, the method of standardized score is adopted, and the selected indexes are calculated according to the normal probability distribution respectively, and multiplied by 100 at the same time, so that the probability value is between 0 and 100. Then the arithmetic average of the probability values of multiple indicators is solved respectively, which is the comprehensive score of the variables (see Table 14.6). 1. Environmental protection industry and economic growth. As mentioned earlier, when examining the relationship between the environmental protection industry and economic growth, this study uses the three indicators of the number of employees, the number of employees and the total income of the environmental protection industry to indicate the scale of the environmental protection industry. The proportion of regional gross domestic product, per capita regional gross domestic product and industrial value added to regional gross domestic product is used to express the economic development of each region. As shown in Fig. 14.4, the horizontal axis represents the level of economic development and the vertical axis represents the size of the environmental protection

14.3 Analysis of Industrial Competitiveness of China’s Environmental …

259

Table 14.5 Basic survey of environmental protection industry in China in 2000 and 2004 Regions

Number of employees

Number of employees

Total annual income (RMB100 million)

2000

2004

2000

2004

2000

2004

National

18,144

11,623

3,176,178

1,594,765

1,689.9

4,572.1

Jiangsu

1,711

1,555

163,879

203,913

209.9

1,016.5

Zhejiang

1,967

1,507

159,964

159,719

245.0

644.0

Guangdong

1,564

943

108,690

124,530

143.5

511.0

Shandong

1,071

789

162,392

161,250

187.1

345.3

Liaoning

872

513

156,946

66,463

133.7

246.2

Shanghai

745

353

40,466

32,635

62.7

165.8

Fujian

965

569

48,273

54,368

66.2

163.1

Henan

831

373

820,159

66,160

94.4

160.1

Anhui

387

316

58,425

53,285

20.3

144.4

Sichuan

420

362

32,915

72,185

17.8

129.1

Hubei

381

320

39,293

43,969

32.7

120.9

Guizhou

223

171

17,013

27,974

12.4

105.0

Hebei

994

461

83,740

68,423

59.7

89.9

Shanxi

643

487

104,586

68,714

28.7

88.1

Guangxi

399

288

25,580

41,120

24.1

86.8

Tianjin

313

228

22,926

31,234

20.7

84.4

Chongqing

141

351

10,397

41,663

7.9

83.0

Yunnan

538

481

35,933

59,117

16.2

77.8

Beijing

375

193

31,157

29,787

39.8

71.8

Hunan

1,114

390

77,083

45,727

100.4

60.9

Jilin

393

226

42,182

26,004

24.6

42.0

Jiangxi

321

121

29,269

21,404

22.4

35.6

Shaanxi

559

162

53,382

26,969

43.9

34.2

Heilongjiang

464

151

798,845

18,877

48.1

18.9

Gansu

249

69

17,420

16,778

11.1

18.1

Inner Mongolia

243

74

18,750

17,531

4.4

9.8

Xinjiang

65

69

3,187

6,698

3.8

8.7

Ningxia

74

43

6,811

6,196

2.7

6.8

Hainan

93

38

5,468

1,699

3.1

3.5

Qinghai

28

18

1,019

337

2.7

0.3

Tibet

1

2

28

36

–

0.1

1

10

12

20

14

17

11

16

7

86.75

81.13

80.60

80.05

73.81

68.74

62.16

59.55

57.93

51.69

46.54

43.84

36.91

36.84

36.12

35.22

35.08

Guangdong

Shandong

Liaoning

Fujian

Shanxi

Henan

Hebei

Sichuan

Yunnan

Anhui

Shanghai

Hubei

Hunan

Chongqing

Guangxi

Tianjin

22

19

26

9

4

6

3

5

2

87.04

Zhejiang

39.63

42.13

43.03

44.21

44.66

54.22

59.26

63.72

63.83

66.73

68.18

68.73

75.69

79.11

82.81

85.05

85.85

86.39

7

25

21

16

10

4

17

19

14

8

12

15

11

6

5

2

1

3

35.88

40.55

42.66

43.83

44.45

45.41

48.25

51.53

53.84

53.98

54.61

54.83

58.26

64.56

88.94

93.87

99.11

99.93

Score

Score

Ranking

Score

Environmental protection industry

Ranking

Year 2004 Environmental protection industry

Economic development level

Year 2000

Jiangsu

Regions

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

Ranking

Table 14.6 Ranking of regional economic development level and environmental protection industry scale in 2000 and 2004

37.00

38.30

38.58

39.79

50.79

52.30

52.63

60.19

62.78

62.99

65.36

68.77

70.49

82.96

84.62

87.79

88.10

89.23

Score

Economic development level

(continued)

6

27

23

19

13

5

18

24

16

7

11

14

10

9

4

2

3

1

Ranking

260 14 Research on Industrial Competitiveness of China’s Environmental …

15

8

23

28

27

30

31

33.94

32.12

31.23

27.83

27.48

26.73

24.77

22.91

22.63

22.44

21.59

20.76

Jilin

Shaanxi

Jiangxi

Heilongjiang

Gansu

Inner Mongolia

Xinjiang

Ningxia

Hainan

Qinghai

Tibet

29

25

21

13

18

24

34.07

Beijing

12.18

18.13

22.30

22.83

25.03

26.34

27.98

28.12

30.08

30.92

31.03

32.20

35.11

31

28

30

24

20

22

26

9

27

23

18

13

29

18.69

19.10

19.93

20.98

21.80

24.11

24.24

26.98

27.55

29.95

32.14

33.67

34.51

Score

Score

Score Ranking

Environmental protection industry

Environmental protection industry

Ranking

Year 2004 Economic development level

Year 2000

Guizhou

Regions

Table 14.6 (continued)

31

30

29

28

27

26

25

24

23

22

21

20

19

Ranking

12.83

16.34

24.81

25.29

26.41

27.71

28.93

30.15

30.64

32.34

32.53

32.98

35.47

Score

Economic development level

31

28

30

21

22

17

26

8

25

20

15

12

29

Ranking

14.3 Analysis of Industrial Competitiveness of China’s Environmental … 261

262

14 Research on Industrial Competitiveness of China’s Environmental …

Fig. 14.4 Regression diagram of environmental protection industry and economic growth

industry. It can be seen that the scale of environmental protection industry is positively correlated with the level of economic development. The correlation coefficient is 0.826 in 2000 and 0.789 in 2004, which means that the higher the level of economic development, the larger the scale of environmental protection industry. Or it can be said that the larger the scale of the environmental protection industry, the higher the level of economic development, the two jointly promote and develop together. The auxiliary diagonal line is added in Fig. 14.4 to show the relationship between environmental protection industry and economic development more clearly. If the index value of each region is scattered around the diagonal, it can be regarded as the simultaneous advancement of environmental protection industry and economic development. On the contrary, it shows that there is a gap between environmental protection industry and economic development, which needs to be further adjusted and improved. In 2000, Henan and Hunan provinces stood out above the diagonal, and their environmental protection industries developed faster than the level of economic development. In 2004, the gap between environmental protection industry and economic development in Henan and Hunan provinces improved, but at the expense of the decline in the ranking of environmental protection industry, it fell by 4 places and 8 places, respectively. Far below the diagonal are Shanghai and Tianjin, two municipalities directly under the central government, whose level of economic development is higher than the scale of the environmental protection industry. 2. Environmental protection industry and environmental pressure. According to the calculation idea of standardization and summation, the scores of environmental protection industry and environmental pressure are obtained respectively, and then the comparative analysis between provinces, autonomous regions and municipalities is carried out (see Table 14.7). The scale of environmental protection industry is closely related to its level of economic development. However, from the correlation between environmental pressure and environmental protection industry,

14.3 Analysis of Industrial Competitiveness of China’s Environmental …

263

the correlation coefficient is about 0.5, the correlation is not high. Compared with the data in 2000, this value also decreased in 2004, indicating that the degree of pollution in a certain area is high, and the scale of its environmental protection industry is not necessarily high. It shows that there are still quite a few areas to achieve regional economic growth at the cost of environmental pollution, and the investment in environmental protection activities is not enough. 3. Environmental protection industry and environmental governance. As mentioned above, accompanied by high energy consumption, high pollution of economic growth, will inevitably cause greater environmental pressure, we must cooperate with effective environmental governance in order to gradually get rid of the environmental pressure caused by economic growth. Based on the empirical analysis of the above environmental protection industry and environmental pressure, this paper further examines the relationship between environmental governance and environmental protection industry, and obtains the regional score of environmental governance according to the same calculation method (see Table 14.8). The correlation coefficient between environmental governance and environmental protection industry is about 0.7, the correlation is high, indicating that the stronger the intensity of environmental governance in various regions, the larger the scale of environmental protection industry. Compared with the data in 2000, the correlation between the two decreased in 2004, which indicates to a certain extent that with the strengthening of environmental protection governance in various regions, the environmental quality has improved. The growth of the scale of the environmental protection industry no longer depends on environmental governance to obtain environmental protection income. Increasingly, it is turning to environmental protection income through the development of cleaning products, the use of clean technology and so on. From the annual change of the total annual income score of environmental governance and environmental protection industry, it can better reflect the significant differences in the direction of change in these two areas in different regions. For example, in Jiangsu, Zhejiang, Fujian, Hebei, Yunnan, Jiangxi and Shaanxi, while increasing environmental governance, environmental protection income has maintained a relatively small growth; In Guangdong, Anhui, Sichuan, Hubei, Guizhou, Shanxi, Guangxi, Tianjin, Chongqing, Gansu, Inner Mongolia, Xinjiang, Ningxia, environmental protection income has increased significantly, but the improvement in environmental governance has not been obvious. And most of these provinces are in the western region; in contrast, the rest of the environmental income and environmental governance have weakened, the overall situation is not optimistic. Therefore, on the whole, the environmental governance in most regions of our country needs to be strengthened, and we should start with remedial and defensive environmental governance at the same time, and work together to develop and strengthen the environmental protection industry.

55.99

71.94

29.92

Fujian

88.12

27.82

87.82

Sichuan

40.36

33.95

Chongqing

Yunnan

27.01

22.98

29.32

19.10

Tianjin

33.66

31.13

79.81

65.96

Shanxi

52.05

87.72

Hebei

Guangxi

35.91

25.12

59.57

58.61

Hubei

Guizhou

29.11

82.21

43.40

Henan

Anhui

53.87

82.27

33.76

Liaoning

97.70

91.31

Shandong

Shanghai

99.80

90.83

52.45

67.11

Zhejiang

99.05

68.16

30.89

37.75

15.68

67.54

83.05

89.51

50.47

54.02

81.11

48.16

84.15

34.43

30.19

70.57

83.63

66.66

53.05

73.45

Year 2004 Environmental pressure

Environmental pressure

Environmental protection industry

Year 2000

Guangdong

Jiangsu

Regions

37.42

38.33

38.57

39.00

39.23

39.54

42.24

45.13

46.63

49.43

52.32

52.87

53.36

67.53

81.88

95.29

98.89

100.00

Environmental protection industry

−20.59 −0.51

−11.71 −3.57

9.25 15.34 10.41

−3.42 −2.60 −3.06

5.57 7.86

1.58

3.23

−12.51

9.21 17.12

−5.55 −8.14 1.79

18.81

−6.71

−19.63 20.32

4.76

1.94

−3.12

−15.82

−7.68

4.51

−0.91 4.46

0.60

0.95

(continued)

Environmental protection industry

−0.45

5.29

Environmental pressure

Differences between 2004 and 2000

Table 14.7 Comparison of score value of environmental pressure and environmental protection industry in China in 2000 and 2004

264 14 Research on Industrial Competitiveness of China’s Environmental …

24.49

21.40

24.63

Gansu

42.47

20.65

17.22

Ningxia

20.82

20.65

–

10.63

12.05

–

Hainan

Qinghai

Tibet

21.13

42.16

21.58

Inner Mongolia

Xinjiang

45.00

47.40

42.85

Shaanxi

30.22

45.33

Jiangxi

Heilongjiang

74.94

31.40

66.82

32.18

Hunan

40.04

21.66

Beijing

Jilin

Environmental pressure

Environmental pressure

9.69

13.72

11.25

16.72

27.78

61.91

25.80

40.72

49.15

47.78

29.22

70.90

19.25

Year 2004

Environmental protection industry

Year 2000

Regions

Table 14.7 (continued)

24.87

24.90

25.37

25.86

26.14

26.30

27.57

27.69

30.10

30.32

31.36

34.51

36.37

Environmental protection industry

9.69

1.67

24.87

4.25

4.55

5.21

−0.50 0.62

5.01

4.91

3.07

6.20

19.75

1.17

−12.38 −17.31

1.75

0.10

−2.14

2.45

−40.44 −0.05

4.08

−3.66

−2.41 −2.96

Environmental protection industry

Environmental pressure

Differences between 2004 and 2000

14.3 Analysis of Industrial Competitiveness of China’s Environmental … 265

55.99

71.94

33.03

Fujian

88.12

27.82

50.97

Sichuan

34.62

38.05

Chongqing

Yunnan

27.01

22.98

29.32

23.29

Tianjin

33.66

31.13

63.40

55.67

Shanxi

52.05

72.43

Hebei

Guangxi

35.91

25.12

64.62

30.29

Hubei

Guizhou

29.11

74.78

65.59

Henan

Anhui

53.87

88.88

50.29

Liaoning

97.70

86.32

Shandong

Shanghai

99.80

90.83

59.77

76.28

Zhejiang

99.05

71.43

49.26

35.50

20.55

48.67

60.44

86.57

33.57

53.61

44.79

52.48

69.21

42.44

37.11

79.30

82.08

72.77

61.36

73.68

Year 2004 Environmental governance

Environmental governance

Environmental protection industry

Year 2000

Guangdong

Jiangsu

Regions

37.42

38.33

38.57

39.00

39.23

39.54

42.24

45.13

46.63

49.43

52.32

52.87

53.36

67.53

81.88

95.29

98.89

100.00

Environmental protection industry

−20.59 −0.51

−9.58 −13.18

9.21

−11.01

11.21

10.41

15.34

9.25

−2.75 0.87

5.57 7.86

−2.96 −7.00

−12.51 14.14

17.12

18.81

−6.18 3.27

−19.63 20.32

−5.56 −13.11

−3.12

−15.82

−4.24

9.41

−0.91 4.46

1.58

0.95

(continued)

Environmental protection industry

−3.51

2.25

Environmental governance

Differences between 2004 and 2000

Table 14.8 Comparison of score value of environmental governance and environmental protection industry in China in 2000 and 2004

266 14 Research on Industrial Competitiveness of China’s Environmental …

24.49

21.40

37.71

Gansu

42.47

20.65

20.17

Ningxia

20.82

20.65

–

14.35

14.31

12.62

Hainan

Qinghai

Tibet

21.13

36.03

20.53

Inner Mongolia

Xinjiang

45.00

27.13

51.62

Shaanxi

30.22

47.76

Jiangxi

Heilongjiang

74.94

31.40

58.75

41.58

Hunan

40.04

24.65

Beijing

Jilin

Environmental governance

Environmental governance

14.86

15.87

16.13

21.47

20.35

38.76

37.71

39.54

34.18

65.17

32.56

54.47

23.32

Year 2004

Environmental protection industry

Year 2000

Regions

Table 14.8 (continued)

24.87

24.90

25.37

25.86

26.14

26.30

27.57

27.69

30.10

30.32

31.36

34.51

36.37

Environmental protection industry −40.44 −0.05

−4.28 −9.02

2.24

1.56

1.77

1.31

–

4.25

4.55

5.21

4.91 5.01

2.73

3.07

−0.18

0.00

−12.38 −17.31

7.05 −12.08

0.10

−3.66

−1.33

17.42

Environmental protection industry

Environmental governance

Differences between 2004 and 2000

14.3 Analysis of Industrial Competitiveness of China’s Environmental … 267

268

14.3.3.3

14 Research on Industrial Competitiveness of China’s Environmental …

Correlation Analysis of Related Factors in Environmental Protection Industry

In the view of the above-mentioned content, the inner ring of the research framework is analyzed, and the relationship between environmental protection industry and economic growth, environmental pressure and environmental governance is analyzed and explained. The following is an analysis of the outer ring of the research framework, taking economic growth as a foothold, examining the proportion of industrial pollutant emissions to industrial added value, as well as the proportion of domestic pollutant emissions to total consumption. Evaluate the pressure caused by economic growth on the environment; further investigate the proportion of pollutant treatment and emissions, and evaluate the investment of environmental protection industry. These influencing factors form an interactive transmission mechanism with the environmental protection industry, and together play a vital role in the vigorous development of the environmental protection industry. 1. Economic growth and environmental pressure. The discharge of industrial waste water, waste gas and solid waste divided by the value added of industry, and the discharge of domestic waste gas, sewage and domestic waste divided by the total consumption to examine the different degrees of pressure on the environment caused by economic growth in each region, the comprehensive scores of each region are calculated and compared by using the above method. The smaller the comprehensive score, the less the pressure on the environment caused by economic growth. As shown in Table 14.9, the provinces with high industrial integration scores are mainly concentrated in the western region. In 2004, the top three provinces with the highest industrial integration scores were Guangxi, Ningxia and Guizhou. This is mainly due to the fact that the exhaust gas emitted per unit of industrial value added ranks first in the country, while the industrial score in the eastern region is relatively low. In 2004, the industrial environmental pressure scores of the three municipalities directly under the central government, Tianjin, Beijing, and Shanghai, were the lowest. It shows that the high level of industrial development in the eastern region has not brought greater environmental pressure, reflecting that the eastern region attaches great importance to environmental protection in the process of economic development. There is no strong consistency between the score ranking of life synthesis and the score ranking of industrial synthesis, and the correlation coefficient between them is only 0.281. For example, in 2004, Xinjiang, Ningxia, Shanxi and Guizhou total unit consumption discharged more domestic pollutants. Although according to the industrial comprehensive score, the industrial economic growth mode of Beijing and Shanghai is more reasonable, but the life of the residents of these two provinces has caused greater environmental pressure; In the process of industrial development in Guangxi, great environmental pressure has been caused, but the comprehensive score of life in this province is only at the middle level in the whole country. The combined scores of Tianjin, Zhejiang, Yunnan and Fujian rank at the end of the

14.3 Analysis of Industrial Competitiveness of China’s Environmental …

269

Table 14.9 Relationship between economic growth and environmental pressure in China in 2000 and 2004 Regions

Year 2000

Year 2004

Differences between 2004 and 2000

Industrial score

Life score

Industrial score

Life score

Industrial score

Life score

Guangxi

82.42

44.85

86.73

46.01

−4.31

−1.17

Ningxia

91.59

57.33

80.28

87.52

11.31

−30.20

Guizhou

82.81

70.00

76.09

68.07

6.73

1.93

Jiangxi

75.14

30.85

74.58

31.17

0.56

−0.32

Shanxi

74.71

97.21

70.98

85.45

3.73

11.76

Inner Mongolia

62.98

61.99

69.50

47.32

−6.52

14.67

Sichuan

63.42

38.72

66.25

31.66

−2.84

7.06

Chongqing

69.40

47.16

66.08

44.04

3.32

3.12

Hunan

54.08

34.28

64.99

45.52

−10.90

−11.24

Shaanxi

66.16

35.76

64.78

45.17

1.38

−9.41

Gansu

68.70

40.77

63.48

56.16

5.22

−15.39

Qinghai

56.03

71.76

56.25

65.88

−0.22

5.88

Yunan

48.20

18.68

54.33

21.72

−6.13

−3.04

Hebei

39.39

32.27

52.22

35.25

−12.83

−2.97

Liaoning

41.89

52.10

44.96

50.43

−3.07

1.67

Anhui

38.82

27.75

44.08

25.20

−5.26

2.55

Hainan

49.26

50.11

41.64

55.79

7.61

−5.67

Tibet

45.23

71.61

41.38

47.41

3.85

24.20

Xinjiang

28.24

57.69

36.89

90.83

−8.65

−33.14

Fujian

22.84

20.08

35.98

20.64

−13.15

−0.56

Henan

35.96

37.34

35.24

27.82

0.72

9.52

Hubei

31.64

54.80

35.14

45.54

−3.50

9.25

Jilin

39.47

61.60

34.45

49.51

5.02

12.09

Jiangsu

25.78

28.05

26.17

28.50

−0.38

−0.45

Zhejiang

22.74

21.53

23.46

24.66

−0.73

−3.13

Heilongjiang

22.01

50.69

20.69

52.05

1.31

−1.36

Shandong

23.43

27.31

20.41

30.19

3.02

−2.88

Guangdong

15.87

48.44

17.66

49.92

−1.79

−1.48

Tianjin

17.01

45.31

16.26

25.02

0.75

20.30 (continued)

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Table 14.9 (continued) Regions

Year 2000

Year 2004

Differences between 2004 and 2000

Industrial score

Life score

Industrial score

Life score

Industrial score

Life score

Beijing

21.06

56.42

15.95

63.47

5.10

−7.06

Shanghai

18.20

57.25

15.36

46.89

2.84

10.36

country, meaning that the lives of residents in these four provinces pose less pressure on the environment. In addition to comparing the different levels of pressure on the environment caused by regional economic growth, it is also necessary to pay attention to whether the pressure of regional economic growth on the environment has improved. As shown in the changes in the last two columns of Table 14.9, the score in 2000 is subtracted from the score in 2004, which indicates that if the change in the industrial score and the life score is positive, that is, the combined score of the two is decreasing, The environmental pressure caused by economic growth is gradually improving; on the contrary, the environmental pressure caused by economic growth is gradually deteriorating. It is not optimistic that the comprehensive scores of industry and life in 15 and 17 provinces, respectively, are rising in 2004, and the increase in the scores of nearly half of the provinces reveals that economic growth is accompanied by greater environmental pressure. 2. Environmental pressure and environmental control. Based on the above analysis of the relationship between environmental pressure and environmental protection industry, environmental governance and environmental protection industry, this book examines the relationship between environmental governance and environmental pressure, and analyzes the effect or level of environmental governance in each region. Or it can be said to examine the efficiency of environmental activities in various regions. Similarly, in view of the availability of data, the relationship between environmental pressure and environmental governance is considered from three aspects: industrial wastewater, waste gas and solid waste (hereinafter referred to as the three wastes). Firstly, the removal amount of the “the three wastes” is divided by the discharge amount to obtain the index value of the treatment rate, and secondly, the treatment rate of the “the three wastes” is obtained according to the standardized method mentioned above. Finally, the average value of the three scores is the comprehensive score of environmental governance efficiency. Figure 14.5 shows the comprehensive score of the ratio of environmental management to environmental pressure in China in 2000 and 2004, and illustrates the level of the efficiency of industrial waste treatment in each region, in which the regions are ranked in descending order according to the comprehensive score in 2004. On the whole, from 2000 to 2004, the governance efficiency of 12 regions in China has been greatly improved, but more than half of the areas are declining,

14.3 Analysis of Industrial Competitiveness of China’s Environmental …

271

Fig. 14.5 Comparisons of comprehensive scores of environmental governance and environmental pressure ratio in China

which is mainly affected by the level of wastewater and waste gas treatment. Moreover, most of the regions where the efficiency of governance has improved rapidly are the western regions with beautiful natural scenery. The reason is that their level of industrial development is relatively slow and backward, and the rate of increase in industrial pollutant emissions is lower than the rapid increase in the level of governance. However, the governance efficiency of some industrially developed regions showed a downward trend, such as Zhejiang, Jiangsu and Shandong, which ranked in the last three places in the country in 2004.

14.3.3.4

Main Conclusions

Through the empirical analysis of the relationship between environmental protection industry and economic growth, the relationship between environmental protection industry and environmental pressure, the following main conclusions for the level of competition of environmental protection industry in each region are as follows: 1. China’s environmental protection industry as a whole has made rapid development, but the layout of environmental protection industry is not very reasonable, environmental protection industry is mainly concentrated in the eastern coast and other economically developed regions. In 2004, the income of environmental protection industry in Jiangsu, Zhejiang and Guangdong all exceeded RMB50 billion, far ahead of other provinces. the total income of the three environmental protection industries accounted for about half of the total income of environmental protection industry in China. However, the total annual income of environmental protection industries in Xinjiang, Ningxia, Qinghai and Tibet and

272

2.

3.

4.

5.

6.

14 Research on Industrial Competitiveness of China’s Environmental …

other western provinces has not exceeded RMB1 billion, showing a significant difference between strong in the east and weak in the west. The scale of environmental protection industry in various regions of China is highly consistent with the level of economic development. Jiangsu, Zhejiang, Guangdong, Shandong, Liaoning, while maintaining the status of a strong economic province, strengthen investment in environmental protection industries, the two jointly promote and develop together. There is little correlation between the pressure of “the three wastes” environmental pollution and the scale of environmental protection industry in various regions of China, and there are obvious differences in the governance of environmental pollution and environmental protection among different regions. Some regions are not currently raising the need for environmental protection to its rightful place. Especially some provinces in the midwest. But on the whole, the environmental pollution in various regions of China has been improved to varying degrees, relatively speaking, the degree of waste gas pollution is reduced, and the pollution of wastewater and solid waste should be paid more attention to in the future. There is a high correlation between the intensity of environmental governance and the scale of environmental protection industry in various regions of China, that is, the stronger the intensity of environmental governance, the larger the scale of environmental protection industry. There are significant differences in the intensity of environmental governance and the change direction of the scale of environmental protection industry in different regions. In Jiangsu, Zhejiang, Fujian and other seven regions, while increasing environmental governance, environmental protection income has maintained a relatively small growth; while most of the western region environmental protection income increased significantly, but the improvement of environmental governance is not obvious. On the whole, the environmental governance in most regions of our country needs to be strengthened. At the same time, we should start with remedial and defensive environmental governance, and work together to develop and strengthen the environmental protection industry. The provinces that bring great environmental pressure in the process of industrial development are mainly concentrated in the western region, Guangxi, Ningxia and Guizhou are at the top of the list. Compared with the central and western regions, the higher level of industrial development in the eastern region has not brought greater environmental pressure. However, the ranking of environmental pressure caused by residents’ life and the ranking of environmental pressure caused by industrial development do not reflect a strong consistency. It is not optimistic that economic growth in almost half of the provinces in 2004 was accompanied by greater environmental pressure than that in 2000. On the whole, the governance efficiency of 12 regions in China has been greatly improved, but the governance efficiency of more than half of the regions is declining, which is mainly affected by the level of wastewater and waste gas treatment. Moreover, most of the areas where the efficiency of governance has improved rapidly are in the western region. However, the governance efficiency

14.4 Policy Suggestions

273

of some industrially developed regions shows a downward trend. On the whole, the efficiency of “the three wastes” treatment in most regions of China needs to be improved, especially in the regions where industry is more developed.

14.4 Policy Suggestions Environmental protection industry is an industry with strong vitality, which plays an extremely important role in the implementation of sustainable development strategy, economic growth and strategic adjustment of industrial structure, as well as a harmonious society. The macro background and basic conditions for the development of environmental protection industry in China have been met, but a series of problems make it difficult to give full play to its potential. Based on the results of the above analysis, this book concludes that the environmental protection industry in China should be regulated on a macro level in at least the following aspects.

14.4.1 Establishing a Comprehensive Environmental Industrial Policy System Environmental industry is a policy-oriented industry, which has a strong dependence on national policy. At present, although China pays more and more attention to environmental protection industry, the policy system of environmental protection industry is not perfect and lacks comprehensive policy support and guidance. It has seriously restricted the development of environmental protection industry. Therefore, we should formulate the overall development plan of China’s environmental protection industry, through a comprehensive environmental protection industry policy to strengthen the macro-management role of the entire environmental protection industry, in order to create a healthy macro environment for the development of environmental protection industry.

14.4.2 Vigorously Promote the Market-Oriented Development of Environmental Protection Industry Although the support of public policy plays an important role in promoting the development of environmental protection industry, in the end, the growth of China’s environmental protection industry still needs to strengthen the internal force and take the path of marketization, which is the key to promote the growth of environmental protection industry. The marketization of environmental protection industry requires environmental protection industry to implement market-oriented production, break

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the concept of segmented small-scale production, widely develop specialized division of labor and cooperation, and constantly improve the enterprise and specialized production of environmental protection industry.

14.4.3 Speeding up the Establishment of Technological Innovation System for Promoting Environmental Protection Industry Science and technology is the primary productivity, as a high-tech industry, environmental protection industry has a high dependence on advanced technology. The technological level of China’s environmental protection industry is still quite far from the advanced level of the world, and “borrowlism” will never be able to dominate the world environmental protection market. Therefore, technological innovation is the lifeline of environmental protection industry. The development of new environmental protection technology, new products, new equipment, adjust the structure of environmental protection industry, promote the development of environmental protection industry to a higher level, all need scientific and technological progress to promote.

Chapter 15

Research on Industrial Competitiveness of China’s Agricultural Sector

15.1 Status Quo of the Research on Industrial Competitiveness of China’s Agriculture Sector Since the mid-1990s, China’s agricultural development has entered a new stage, and some new situations and problems have emerged: the total amount of agricultural products has changed from a shortage to a basic balance of the total amount and more than a bumper year. Agricultural production has changed from resource constraint to resource and market constraint, the structural contradiction of agricultural production is becoming more and more prominent, the market competitiveness of agricultural products is not strong, and so on. At a time when China’s agricultural development was confronted with many contradictions, China became a full member of the WTO on December 11, 2001. The accession to WTO means that China is integrated into the trend of world economic integration and trade liberalization and participating in “international competition” will become the main theme of China’s economic development. So, how does Chinese agriculture participate in international competition? How to deal with the challenge of China’s entry into WTO? The limitations of the traditional exogenous comparative advantage theory and the failure in practical application show that China’s agricultural development can not only stay in the existing cost comparative advantage, but need to transform this comparative advantage into a competitive advantage. Therefore, the author believes that the development of China’s agriculture in the twenty-first century should be centered on enhancing competitiveness. At this time, it is undoubtedly of great theoretical and practical significance to probe into the international competitiveness of China’s agriculture. On the whole, scholars at home and abroad have achieved fruitful results in the study of agricultural competitiveness in China. There is no doubt that the existing research results provide a suitable method and research basis for the study of this topic. However, there are also some obvious tendencies or shortcomings in the existing research. © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4_15

275

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Firstly, the theoretical explanation of the influencing factors of agricultural competitiveness in the existing literature is still insufficient. Most of the existing literatures analyze the influencing factors of agricultural competitiveness from the theory of comparative advantage or the theory of competitive advantage (taking the “national diamond” model as the paradigm). However, both the theory of comparative advantage and the theory of competitive advantage focus on the analysis of the “domestic conditions” that affect the formation of agricultural competitiveness. Little attention has been paid to the impact of “foreign conditions” (such as trade barriers in importing countries, strategies of importing companies, strategies of transnational corporations, etc.) on agricultural competitiveness. Secondly, the existing literature focuses on the evaluation of the performance of China’s agricultural competitiveness, but little attention has been paid to the evaluation of the influencing factors behind China’s agricultural competitiveness. Some literatures are involved in the evaluation of the influencing factors of agricultural competitiveness, but most of the literature only do a simple cost comparative analysis, or use a comprehensive evaluation method to evaluate the overall agriculture. Obviously, this kind of analysis is difficult to reveal the influencing factors of agricultural competitiveness in China. Thirdly, there are some technical problems in the empirical analysis of agricultural competitiveness in most existing literatures, such as the inconsistency of the definition of the scope of agricultural products and the non-continuity of the use of statistical data.

15.2 Comparative Advantage Analysis of China’s Agriculture Products 15.2.1 Evaluation Index of Comparative Advantage of Agricultural Products There are two methods to evaluate the comparative advantage and competitiveness of agricultural products: single factor index evaluation and comprehensive evaluation (Chen 2003). We use single factor evaluation method, and select two of the most commonly used evaluation indicators (RCA index and TC index) to evaluate the comparative advantage and competitiveness of China’s agricultural products.

15.2.1.1

Revealed Comparative Advantage Index

Revealed comparative advantage is a method used by Balassa to measure the comparative advantage of some countries in 1965. It was adopted by international organizations such as the World Bank. It refers to the ratio of a country’s products to the total value of its exports and the world’s exports of such products to the world’s exports.

15.2 Comparative Advantage Analysis of China’s Agriculture Products

277

Expressed by the formula is:  X i j X it  RCAi j = X wj X wt

(15.1)

where, RCAi j : comparative advantage index of product j of country i; X i j : exports of product j of country i; X it : total exports of all products in country i; X wj : total exports of product j in the world; X wt : total exports of all products in the world.

15.2.1.2

Trade Competition Index

The trade competition index usually refers to the ratio of a country’s net exports of a products to its total trade in that product. The advantage of the indicator is that it is a relative value and is not affected by fluctuations in macro-volume such as inflation. It is between −1 and +1, so it is comparable between different periods and different countries. Expressed as: T Ci j =

X i j − Mi j X i j + Mi j

(−1 ≤ T Ci j ≤ 1)

(15.2)

where T Ci j : trade competition index; X i j : total export value of product j of country i; Mi j : total imports of product j of country i. If T Ci j > 0, indicates that the production efficiency of the country’s product j is higher than the international level, the net supplier of the country’s product j has a strong export competitiveness for the world market; if T Ci j < 0, shows that the production efficiency of product j is lower than the international level, the export competitiveness is weak; if T Ci j = 0, the production efficiency of product j in the country is comparable to the international level, and its import and export are purely for variety exchange with the international community.

15.2.2 Overall Evaluation of Comparative Advantage of Agricultural Products in China Figure 15.1 shows the changes in China’s agricultural product trade competition index (hereinafter referred to as TC index) and revealed comparative advantage index (hereinafter referred to as RCA index) from 1987 to 2000. It can be seen from Fig. 15.1 that the TC index value of my country’s agricultural products fluctuates

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15 Research on Industrial Competitiveness of China’s Agricultural Sector

Fig. 15.1 Trend of China’s agricultural product comparative advantage

greatly. It dropped significantly in the early part of 1989, but increased significantly in the early 1990s, reaching a peak of 0.3232 in 1993. Since 1993, the TC index value of agricultural products began to show a downward trend. By 2000, the TC value was already negative, which was the lowest point since 1987. On the whole, my country’s agricultural TC index has shown a downward trend, and the TC index value has been negative in several years. The RCA index of China’s agricultural products has also declined significantly since 1987. From a strong comparative advantage (RCA index was 1.45 in 1987) to a weak comparative advantage (RCA index was 0.74 in 2000), which fully indicates that the comparative advantage of China’s agricultural products as a whole shows a downward trend.

15.2.3 Prospect of the Future Development Trend of China’s Agricultural Products Trade The development pattern and comparative advantage of China’s agricultural products trade have the following main characteristics: firstly, from the total amount, the proportion of China’s agricultural products trade in the whole trade has decreased, and the overall comparative advantage of China’s agricultural products has also shown a downward trend; secondly, in terms of the internal structure of agriculture, China’s bulk agricultural products, forest products and most agricultural raw material products no longer have comparative advantages, while aquatic products, vegetables, fruits, livestock products and so on still have certain comparative advantages; thirdly, from the perspective of trade subject structure and trade mode, the pattern of monopoly of agricultural products trade by state-owned enterprises has been gradually broken, and the distribution of agricultural products import and export market is also gradually diversified. Since the reform and opening up, great changes have taken place in the relationship between China’s agriculture and the national economy. the share of agricultural added value in the gross national product has dropped from 30.1% in 1980 to 14.5%

15.2 Comparative Advantage Analysis of China’s Agriculture Products

279

in 2002. Accordingly, the contribution of agriculture to the growth rate of the national economy has also dropped from about 1/4 at the beginning of the reform to less than 1/10 at present. Since the proportion of agricultural output value in the national economy has generally declined, It is logical for the trade status of agricultural products and the decline of the overall comparative advantage of agricultural products, and it is the inevitable manifestation of the regularity of economic development. From the perspective of the technical conditions and actual cost composition of China’s agricultural production at the present stage, the bulk agricultural products basically belong to the land-intensive agricultural products with relatively dense land input. However, horticultural products such as aquatic products and vegetables and fruits are labor-intensive agricultural products with relatively dense labor input. According to the principle of comparative advantage, a country’s trade structure is intrinsically related to its cost structure and factor endowment conditions. A country should export products produced by relatively intensive use of its relatively abundant factors and import products that are produced with the country’s relatively scarce factors. At present and for a long time in the future, the most basic factor structure characteristics of China’s agricultural economic sector are still the relative abundance of labor resources and the relative scarcity of land resources. Therefore, the evolution of the comparative advantage of China’s agricultural products is consistent with the characteristics of China’s resource endowment. With the development of world economic integration and agricultural trade liberalization, the economic cooperation between China and other countries in the world is becoming more and more active. As a developing country with a population of nearly 1.4 billion, China attracts direct investment from foreign agricultural enterprises with capital, technology, market network and quality standards with low-cost labour and broad market capacity. In this context, the production of China’s agricultural products is faced with greater market space and consumer groups at different levels of demand, so that there are more opportunities to achieve economies of scale and product diversification. In turn, it also promotes the diversification of China’s agricultural import and export market. At the same time, foreign-invested enterprises are also playing a more and more important role in China’s agricultural trade. The characteristics of the evolution of China’s agricultural trade are consistent with the internal laws of economic development. The development trend of China’s agricultural trade in the coming period will be as follows: Firstly, China’s agricultural import and export trade is likely to grow in the future. On the one hand, in the coming period, China will continue to fulfill the commitments of the WTO agreement on agriculture, which will make China’s agricultural market more open and conducive to China’s greater participation in world agricultural trade; on the other hand, the adjustment of the domestic production structure of agriculture has brought about changes in the relationship between supply and demand in the domestic agricultural product market, as well as changes in consumer demand and dietary structure as a result of the rapid growth of residents’ income and the improvement of the level of urbanization, which will promote the growth of China’s agricultural import and export trade in the future.

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Secondly, in the long run, China’s land-intensive products are lack of international competitiveness, and it is impossible for China to export a large number of landintensive products. The main reason for this is that Chinese farmers’ land management is too small, with an average of only half a hectare, equivalent to 1/ 40 in the European Union and 1/400 in the United States. China’s current surplus of agricultural commodities is phased. With the development of demand, the relationship between supply and demand will change. Thirdly, with the changes in domestic supply and demand and the change in the relationship between domestic and foreign market prices, China’s imports of agricultural commodities will increase. There are two main reasons. On the one hand, dominated by the principle of comparative advantage, the production of bulk agricultural products that do not have comparative advantage will gradually be replaced by labor-intensive products such as horticultural products and aquatic products with comparative advantage. Some agricultural commodities will be imported from abroad to meet domestic demand; on the other hand, as China’s rapid growth in the manufacturing industry in the coming period will promote the demand for agricultural raw materials (such as cotton, animal fur, rubber, animal feed and so on). Fourthly, due to the role of the great power effect, China’s market and trade situation has a significant impact on the world market. This impact makes the import of China’s bulk agricultural products will increase, but the quantity is unlikely to be particularly large. This is because the import of large countries will lead to an increase in world market prices, thus inhibiting further imports from China. Fifthly, China’s exports of agricultural products, especially labor-intensive agricultural products such as aquatic products, horticultural products and livestock products, are likely to continue to grow in the coming period, as China can produce these products at a relatively low cost. However, the export of China’s agricultural products is also facing animal diseases, excessive chemical residues and other food safety problems. At a time when developed countries are increasingly concerned about food quality and food safety, if China fails to significantly improve the quality competitiveness of agricultural products, prevent and control animal diseases, improve food safety standards and improve the quarantine system as soon as possible, it will not be able to give full play to the cost comparative advantage of these products. In this sense, the future export growth of China’s labor-intensive agricultural products depends to a large extent on the improvement of the non-price competitiveness of these products. Sixthly, under the influence of income growth and the acceleration of urbanization, the consumption demand of Chinese residents for meat and other non-staple foods will continue to increase in the coming period. Per capita consumption demand for sugar, vegetables, fruits, meat and aquatic products will increase by 20 and 40% in both rural and urban areas in 2010 compared with 2001. Under the conditions of lower tariffs and open markets for agricultural products, the import of these consumptionoriented agricultural products will increase.

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281

Seventhly, with the continuous development of world economic integration, China has actively promoted bilateral, multilateral, regional and regional economic cooperation. The deepening of economic cooperation will certainly promote the reintegration of agricultural production resources between China and other countries. As a result, the intra-industry trade of China’s agricultural products will increase in the future. It is worth mentioning that the production and trade of China’s agricultural products are also affected by some uncertain factors, such as the world economic situation, agricultural technological progress, climate, and so on. Just like the Asian financial crisis, foot-and-mouth disease, SAS infectious disease and avian influenza in recent years, these have had a great negative impact on China’s agricultural production and trade. It is true that we need to take a positive attitude and effective measures to prevent and control the occurrence of these incidents. However, under the framework of WTO, the reform and adjustment of domestic agricultural policies to adapt to the inherent laws of economic development will play a more critical role in the future production and trade of China’s agriculture.

15.3 Research on Inner-Sector Trade and Competitiveness of China’s Agriculture Products 15.3.1 The Basic Theory of Intra-industry Trade The theory of intra-industry trade is an international trade theory rising since the middle of 1970s. It mainly includes: the representative demand theory of Linder, the demand overlaps theory of Lassudrie-Duchene, the tariff alliance theory of Balassa and the economies of scale theory of Krugman. The first two are mainly affected by the diversity of demand preferences, while the latter two are mainly based on the expansion of the market and the size of the enterprise. The representative demand theory holds that the average income is the most important factor affecting the demand structure, and the similarity of the average income level leads to the similarity of the demand structure. The differentiation of products forms a situation of mutual competition that can not be completely replaced, and with the improvement of the level of per capita income, the more diversified the choice of consumers. If two countries have the same representative needs, products that meet such common needs can become realistic exports, and intra-industry trade will occur. This theory also has its application requirements, one is that the income level between trading countries should be close, there is overlap in demand; the other is that the theory is mainly applicable to trade in manufactured goods, but not suitable for trade in primary products. Economies of scale are the independent source of international trade. In the case of identical or even identical elements between the two countries, intra-industry trade may also exist because of economies of scale. For countries with similar or similar

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ratios of factor endowments to factors of production, if a country has economies of scale with decreasing costs in the production of a medium product, it is on the same long-term average cost curve. The country’s product will crowd out the same product in another country at a higher output and lower cost in order to gain an advantage, gain trade benefits and shift the elements of another country to other similar products or industries. If one country has the advantage of economies of scale in one product and another country has the advantage of economies of scale in another similar product, intra-industry trade will occur and both sides will benefit from trade. Both theories emphasize the trade premise of product difference. Because only the existence of product differences, enterprises can carry out professional division of labor and achieve economies of scale. Only the existence of product differences, in order to meet the diversity of consumer demand preferences, demand can become another driver of intra-industry trade.

15.3.2 Data and Analytical Method 15.3.2.1

Data Sources and Classifications

This book defines the scope of trade agricultural products according to the Standard International Trade Classification (SITC), which includes “food” and “agricultural raw material”. Food includes: SITC category 0 (food and live animals), SITC category 1 (beverages and tobacco), SITC category 2 chapter 22 (oil seeds and oleaginous fruits) and SITC category 4 (animal and vegetable oils, fats and waxes). Agricultural raw material include: chapter 21 (raw hides and skins), chapter 23 (raw rubber, including synthetic rubber and recycled rubber), chapter 24 (cork and wood), chapter 25 (pulp and waste paper), chapter 26 (textile fibres and their waste, except wool) and chapter 29 (other animal and vegetable raw materials) of SITC category 2 (non-edible raw materials, except fuels). The agricultural products examined are those with the same first three digits in the SITC, covering 64 categories (see Table 15.1), using data on China’s agricultural trade imports and exports from 1983 to 2002, including quantities and amounts, from the China Customs Statistical Yearbook. In order to further investigate the changes in the commodity structure and market structure of China’s agricultural trade, we have further subdivided the trade in agricultural products. It is divided into eight categories: (1) bulk agricultural products; (2) edible animal products; (3) non-edible animal products; (4) aquatic products; (5) horticultural products; (6) beverage and tobacco products; (7) forest products; and (8) other agricultural products. Table 15.2 describes the catalogues contained in the eight categories of agricultural products and their corresponding SITC statistical numbers. While this classification may exaggerate the value of the intra-industry trade index, it

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Table 15.1 Agricultural products with the same first three digits in the SITC (64 categories) 001 Animals for food

091 Compressed food

011 Fresh, frozen meat

098 Other foods

012 Meat dried, cured, smoked

111 Non-alcoholic drinks

014 Other meat products

112 Alcoholic beverage

022 Milk and butter

121 Unprocessed tobacco

023 Butter

122 Processed tobacco

024 Cheese and curd

211 Raw leather

025 Fresh, preserved eggs

212 Raw fur

034 Fresh, frozen fish

222 Soft oil mixture seeds

035 Marinated, sun-dried, smoked fish

223 Other mixed oil seeds

036 Fresh, frozen shellfish and crustaceans

233 Natural rubber, gum

037 Other fish products

233 Artificial and renewable rubber

041 Unground wheat

244 Natural native cork

042 Rice

245 Firewood and charcoal

043 Unground barley

246 Wood pulp and chips

044 Unground corn

247 Other wooden strips

045 Unground other grains

248 Sleepers, wooden railings

046 Powdery wheat

251 Pulp and waste paper

047 Other powdery grains

261 Silk

048 Preprocessed Cereals

263 Cotton

054 Fresh, Simply Preserved Vegetables

264 Jute (red) hemp and its waste

056 Vegetable products

265 Other plant textile fibers and their wastes

057 Fresh, sun-dried fruits and nuts

266 Synthetic fibers for textiles

058 Fruit products

267 Other plant textile fibers and their wastes

061 Sugar and honey

268 Wool and animal hair

062 Non-chocolate sugar products

269 Old clothing and textiles

071 Coffee and its alternatives

291 Other animal raw materials

072 Cocoa

291 Other plant materials

073 Chocolate products

411 Animal oil and fat

074 Tea

423 Mixed vegetable oil

075 Condiment

424 Other vegetable oils

081 Feed

431 Other processed animal and vegetable oils

can be used to compare larger categories and analyse the order of intra-industry trade. In addition to the inclusiveness of products. The products related to the processing and production links are linked into the advantages of intra-industry trade.

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Table 15.2 Catalogues in the eight categories of agricultural products and SITC standard Category

SITC standard

Category

SITC standard

Bulk agricultural products

Chapter 04 Cereals and products

Beverage and tobacco products

Chapter 11 Drinks

Edible animal products

Chapter 06 Sugar, sugar products and honey

Chapter 12 Tobacco and its products

Chapter 22 Oilseeds Forest products and oleaginous fruits

Chapter 23 Rubber

Section 263 Cotton

Chapter 24 Cork and wood

Chapter 42 Vegetable oil

Chapter 25 Pulp and waste paper

Chapter 00 Live animals mainly for food

Other agricultural products

Chapter 08 Feed

Chapter 01 Meat and meat products

Chapter 09 Miscellaneous products

Chapter 02 Dairy products and poultry eggs

Section 264 Jute (red) hemp and its waste

Chapter 41 Animal oils and fats

Section 265 Other plant textile fibers and their wastes

Chapter 21 Raw and unnitrated fur

Section 266 Synthetic fibers for textiles

Section 263 Silk

Section 267 Other plant textile fibers and their wastes

Section 268 Wool and animal hair

Section 269 Old clothes and textiles; textile fibers

Aquatic products

Chapter 03 Fish, crustaceans and molluscs

Chapter 29 Other animal and plant materials

Horticultural products

Chapter 05 Vegetables and fruits

Chapter 43 Animal and vegetable oils and fats

Non-edible animal products

Chapter 07 Coffee, tea, cocoa, condiments

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15.3.2.2

285

Calculation Method

(1) For the calculation of a single product (a single class in the same division as the first three digits of SITC), we can use the G-L exponent formula. (2) For the eight groups of data after classification, we use the formula of GL index of a certain industry to calculate them.

15.3.3 Analysis of Empirical Conclusions By calculation, the G-L indices of the 64 agricultural products observed are shown in Table 15.3. We divide the data, products with G-L value between 0 and 0.25 are classified as strong inter-industry trade products (code ➀), and products between 0.25−0.5 are classified as sub-industry trade products (code ➁). The value between 0.5–0.75 is classified as secondary intra-industry trade products (code ➂) and 0.75–1 as strong intra-industry trade products (code ➃). Put 64 products into their own class, and their G-L value trend is indicated by the ➀➁➂➃ specified above. From Table 15.3, we can see the general trend of the G-L index for each individual product and eight categories over the past 16 years. At the same time, we have also calculated the G-L index for eight categories and total agricultural products, as shown in Fig. 15.2. Through Fig. 15.2, the overall direction and order of each category can be seen more clearly, of course, this method will inevitably exaggerate or offset the phenomenon of intra industry trade. Therefore, the following will combine Fig. 15.2 with Table 15.1 to analyze the overall structure trend of intra industry trade of agricultural products in China.

15.3.4 Analysis on the Trend of Agricultural Products Trade Structure The main results are as follows: (1) On the whole, the trade of agricultural products in China is mainly inter-industry trade, which indicates that China’s agriculture still participates in international trade in accordance with the traditional principle of comparative advantage. The curve trend of horticultural products and forest products in China is smooth and has been below 0.4, and aquatic products have been below 0.5, which means that the trade forms of the three types of products are basically inter-industry trade. (2) The three categories of bulk agricultural products, non-edible animal products and beverages and tobacco all fluctuate greatly, and occupy the middle of the Fig. 15.2 at the same time. Edible animal products showed a greater upward trend. Other agricultural products are at the top of the Fig. 15.2.

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Table 15.3 G-L Index of 64 agricultural products Category

SITC code G-L value

Category 1 Bulk agricultural products

041

Category 2 Edible animal products

➀

042

➀

043

➁

044

➀

Category

SITC code G-L value

Category 5 Horticultural products

054

➀

056

➀

057

➁–➂–➃

058

➀

045

➀

071

➁➂

046

➀

072

➃

047

➀–➁

073

➁–➂

048

➁

074

➀

061

➃

075

➀

062

➃–➁

➁–➀

222

➀–➁

Category 6 Beverage 111 and tobacco products 112

223

➀–➁

121

➂–➃

263

➀–➂–➀–➃

122

➁–➂–➃–➂

423

➁

424

➁–➀

001

➀

Category 7 Forest products

➁–➃

232

➀

233

➀

244

➀–➂

011

➀–➃

245

➃–➀

012

➀

246

➀

014

➀

247

➀

022

➁

248

➃–➁

023

➀

251

➀

024

➀–➁

081

➂➃

Category 8 Other agricultural products

025

➀

091

➀

411

➀

098

➂

➂–➀

264

➀

Category 3 211 Non-edible animal 212 products 261

➂–➁–➀

266

➀

➀

267

➀

268

➂

269

➃

Category 4 Aquatic products

034

➂

291

➀–➁

035

➃–➂–➁

292

➂–➁–➂

036

➀–➁–➂

431

➃–➀

037

➀

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Fig. 15.2 G-L Index diagram of eight categories of products

(3) With the exception of the troughs of bulk agricultural products in 1995 and 1996, the rest basically fluctuated around 0.75, as seen from Table 15.3. In fact, the form of trade in individual products of bulk agricultural products is also mainly inter-industry trade (that is to say, most of them are code ➀), but it contains sugar and honey (061) and cotton (263), which are varieties of strong intra-industry trade. It has played a greater role in the G-L value of the whole category, and it may also be that the cumulative errors we have mentioned exaggerate the intensity of intra-industry trade. (4) Non-edible livestock products were at a low ebb in 1990 and have been on a downward trend in subsequent years, and have been at the dividing line 0.5 between intra-industry trade and inter-industry trade in 2001–2002, as can be seen from Table 15.3, two of the four products in this category have changed from sub-industry intra-industry trade to strong inter-industry trade (➂–➀). Wool and animal hair (268) should be noted that it basically reflects the form of sub-industry intra-industry trade. (5) The situation of tobacco and beverage is the same as that of non-edible animal products, which hovers around 0.5 after the trough. Looking at Table 15.3 and the original data, non-alcoholic beverages (111) account for a large proportion of this category, so they have an impact on the overall G-L value. Individually, alcoholic beverages (112), unprocessed tobacco (121), and processed tobacco (121) are still represented in the form of intra-industry trade. (6) Edible animal products are close to the form of intra-industry trade after the original form of inter-industry trade rose in 1998. As can be seen from Table 15.1, most of the products in this category belong to inter-industry trade. what is worth noting is fresh and frozen meat (011), which has shown strong intraindustry trade in the past four years from 1999 to 2002, which affected the whole category. (7) The G-L value of other agricultural products has been very high. compared with Table 15.1, it can be seen that feed (081), other foods (091), old clothing and old textiles (269) have a greater impact on it and are affected by errors at the same time.

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15.3.5 Basic Policy Recommendations The main contents are as follows: (1) Fully coordinate the two forms of trade, inter-industry trade and intra-industry trade, and give full play to their own advantages. On the basis of making full use of the advantages of China’s resource endowment and strengthening interindustry trade with emphasis, efforts should be made to develop intra-industry trade, and some inter-industry trade based on scarce or non-renewable resources should be transformed into intra-industry trade. (2) Regard differentiated products as the premise of entering the international market, and strive to create their own intra-industry trade advantages. Under the fierce competition of the international agricultural product market, the difference strategy will be an effective means of competition. For agricultural products, which is a regional product, how to make use of its own resource advantages and produce our country’s unique products is the problem that we must pay attention to in the whole agricultural trade. (3) To improve the technical content of agricultural products, increase the added value of products, and fundamentally improve the quality of agricultural products in China. (4) To plan the long-term development of agricultural industry and make full use of intra-industry trade. For some agricultural products that lack or gradually lose their comparative advantage, such as grain, oilseeds, and other large agricultural products characterized by dense land, under the condition of ensuring safe supply, domestic production can be moderately reduced. Effective use of the international market to adjust the gap between supply and demand; for products with comparative advantages, measures should be taken to further exaggerate their advantages and enhance trade competitiveness. Ecological agriculture should be actively developed, various ecological parks should be established, and sustainable roads should be taken.

15.4 Research on Inner-Sector Trade Development and Competitiveness of China’s Food Processing Sector Our research attempts to answer the following two questions: (1) Is intra-industry trade an important part of China’s processed food trade? What is the development trend of intra-industry trade in China’s processed food industry? (2) Will those factors that affect intra-industry trade in other countries have a similar impact on China’s intra-industry trade in processed food?

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15.4.1 Current Situation of Intra-industry Trade of Processed Food in China We use the data of China’s import and export trade of processed food (SITC-4bit code, Rev. 1 version) from 1987 to 2002 provided by COMMTRADE, a trade database created by the United Nations Statistical Office, to calculate. The results are described as follows: Figure 15.3 reports the changing trend of G-L index and share of different trade types of processed food in China from 1987 to 2002. Firstly, from the G-L index, the G-L index of processed food in China shows an overall upward trend, rising from 15% in 1987 to 33% in 2002, which indicates that intra-industry trade model plays an increasingly important role in China’s processed food trade. However, the overall G-L index of processed food in China is still low (the highest year is only 33%), which is different from that of developed countries. Secondly, according to the share of different types of trade in China’s total processed food trade, before 2000, the share of inter-industry trade was the highest, but after 2000, the share of intra-industry trade of vertical differentiated products was the highest. By 2002, the share of intra-industry trade of vertical differentiated products was 58%, and that of intra-industry trade of inter-industry trade and horizontal differentiated products was 39 and 3% respectively. This shows that the growth of intra-industry trade plays a more and more important role in the increase of China’s processed food trade, especially in the intra-industry trade of vertically differentiated products.

Fig. 15.3 G-L Index of intra-industry trade in processed food

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15.4.2 Determinants and Variable Selection of Intra-industry Trade in Processed Food In the existing literature, the selection of determinants and hypothetical variables of intra-industry trade in processed food is based on different intra-industry trade theories or previous empirical studies on other industries (Christodolou 1992; Hirscherg et al. 1994; Pieri et al. 1997; Ferto and Hubbard 2002). These hypothetical variables can be divided into three categories in a broad sense: (1) country-specific variables, mainly including economic development, market size, geographical distance; (2) industry-specific variables including product differences, economies of scale, market structure, product life cycle and the role of transnational corporations; (3) policybased variables, including economic integration and trade barriers. This book mainly selects the variables of “national characteristics” for empirical analysis as follows.

15.4.2.1

Market Size

The theoretical models of Lancaster (1980) and Bergstrand (1990) show that when the average market size between trading partners increases, it also means that the number of consumers and consumption in each country increases, and the more likely it is to achieve differential production in economies of scale. So as to improve intra-industry trade. The average market size between China and its trading partners or regions is to be replaced by an average gross national product, recorded as GDP.

15.4.2.2

Differences in Market Size

Dixit and Norman (1980) and Helpman (1981) argue that the smaller the difference in market size between trading partners, the more able they are to produce differentiated products, and thus the more likely they are to engage in intra-industry trade between them. Assuming that the level of market size difference between China and its trading partner countries or regions has a negative impact on the degree of intra- industry trade of processed food in both vertical and horizontal types. In this book, the level of market size difference between China and trading partner countries or regions is to be replaced by the absolute difference in gross national product between trading countries, recorded as DGDP. The calculation is as follows:   DGDP = GDPc − GDPj 

(15.3)

In the formula, GDPc represents China’s gross national product, GDPj represents the gross national product of China’s trading partner countries.

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15.4.2.3

291

Per Capita Income Level

The level of per capita income has an impact on trade patterns from both supply and demand. On the supply side, if a country has a high level of per capita income, its capital/labour ratio is also high. Therefore, the stronger its ability to innovate and produce differential products. On the demand side, high per capita income creates more differentiated needs that enable a country to create economies of scale on a wider range of different products. The per capita income level in the book was measured by the average per capita income level between China and its selected trading partners, recorded as PCI.

15.4.2.4

Differences in Per Capita Income Levels

The difference of per capita income level has different theoretical implications in different trade models, so the impact on different types of intra-industry trade is not consistent. We believe that the difference in the level of per capita income between China and its trading partners has a positive impact on the degree of intra-industry trade of vertically differentiated products of processed food and a negative impact on the degree of intra-industry trade of horizontally differentiated products. In this book the difference in per capita income between China and its selected trading partners is recorded as the same calculation method as DPCI, and DGDP.

15.4.2.5

Geographical Distance

There are three ways in which the spatial distance between the two countries affects intra-industry trade between the two countries (Andresen 2003): the first is transportation cost. The closer the two countries are geographically to each other, the lower the transportation cost, and the higher the trade intensity between the two countries; the second is that two geographically close countries are more likely to have similar cultural and consumer preferences, which increases the possibility of intra industry trade; the third is that geographically close countries are more likely to have similar resource endowment conditions, so they are more likely to engage in the production of the same industry, which is more conducive to the occurrence of intra- industry trade. The spatial distance between China and its selected trading partner countries or regions will be measured by the spherical distance of the capital city, which is recorded as DIST. We present the above hypothetical variables, their meanings, and theoretical prediction symbols in Table 15.4.

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Table 15.4 Determinants, explanatory variables and theoretical prediction symbols of intraindustry trade Variable name (abbreviation)

Definition

Symbols of theoretical prediction TIIT

VIIT

HIIT

Gross domestic product (GDP)

Average GDP of the two countries

+

+

+

Differences of gross domestic product (DGDP)

The absolute difference of GDP between the two countries

–

–

–

Per capita income level (PCI)

Average per capita income level in the two countries

+

+

+

Differences of Per capita income level (DPCI)

Absolute difference of per capita income between the two countries

–

±

–

Geographical distance (DIST)

Absolute distance between two countries (capital)

–

–

–

Note The theoretical conclusions are shown in the “symbols of theoretical prediction” column. Among them, “+” indicates that intra-industry trade increases with the increase of this factor; “–” indicates that intra-industry trade decreases with the increase of this factor; and “±” indicates that the correlation with this factor may be positive or negative

15.4.3 Econometric Models, Sample Selection and Data Sources Panel Data model is adopted in this book, and linear model is mainly adopted. It is assumed that the parameters of the time series are homogeneous, that is, the parameters satisfy the time consistency, and the parameter values do not change with time. For intercept and slope parameters, it is assumed that the regression slope coefficient is the same (homogeneous) but the intercept is different, that is, the most widely used variable intercept model. Its basic form is: 

yit = αi + β xit + u it i = 1, . . . , N , t = 1, . . . , T

(15.4)

where, X it is the vector that explains the variable, including market scale variables, market scale difference variables, per capita income level variables, per capita income difference variables and geographical distance variables; β n are the parameter vectors to be estimated; αi represents the individual characteristics of the section element, and reflects the influence of the missing individual difference variables in the model; the individual period variables u it represent the influence of the missing factors in the model that change with the cross section and time series at the same time. In this book, 22 trading partner countries or regions of processed food of China were selected: the United States, Japan, Germany, the Netherlands, the United Kingdom, Italy, France, Australia, Canada, Spain, Finland, Denmark, South Korea, Malaysia, Indonesia, Thailand, Brazil, Argentina, Chile, Poland, New Zealand etc. These 22 sample countries or regions accounted for more than 80% of China’s total

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293

processed food trade during the period 1987–2002 (COMMTRADE database). The theoretical observation sample size of this book was 352 observations (22*16 = 352). Data on bilateral trade flows (imports and exports and unit prices of imports and exports) of processed food between China and various countries (regions) from 1987 to 2002 are derived from the United Nations COMTRADE (Commodity Trade Statistics) database. During 1987 and 2002, the GDP and per capita GDP of each sample country or regions were derived from the World Economic Outlook (WEO) database of the International Monetary Fund (IMF); the distance data were from the “distance calculator” on the website: www.indo.com.

15.4.4 Test Results and Analysis We use the TSCSREG module in SAS to establish a variable intercept model of China’s total intra-industry trade (TIIT) index of processed food for five variables: market size, market scale difference, per capita income level difference and geographical distance. The results are as shown in Table 15.5. Table 15.5 shows that the operation results of TIIT’s deterministic effect model are not ideal, the coefficients, degrees of freedom and standard errors of DIS are all 0, while t statistical values are missing. At the same time, deterministic effect models of VIIT and HIIT also encounter the same problems. The main reason for this problem is that the distance between countries or regions does not change greatly with the year. the geographical distance between the two countries or regions uses the same data, which can lead to discontent in the analysis of panel data. This can lead to estimation problems. In view of this, the DIS is eliminated and the four explanatory variables of PCI, DPCI, GDP and DGDP are remodeled. Table 15.5 TIIT test results of deterministic effect model Independent variable

Freedom

Coefficient estimation

Standard error

t value

Pr > |t|

Intercept

1

0.307257

0.2593

1.18

0.237

PCI

1

5.09717

1.1810

4.32

0.0001

DPCI

1

−4.56608

1.1741

−3.89

0.0001

GDP

1

0.284884

0.2685

1.06

0.2895

DGDP

1

−0.18301

0.2182

−0.84

0.4023

DIS

0

0

0

−

–

294

15.4.4.1

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Test Results of Determinants of Total Intra-Industry Trade (TIIT) of Processed Food in China

We first use SAS to test the F test of whether the model adopts the fixed effect model or not: the original hypothesis is that there is no deterministic effect, the alternative hypothesis is the existence of deterministic effect, the value of F statistic is 11.40, and Pr value |t| label

Intercept

1

0.307257

0.2593

1.18

0.237

PCI

1

5.09717

1.1810

4.32

0.0001

DPCI

1

−4.56608

1.1741

−3.89

0.0001

GDP

1

0.284884

0.2685

1.06

0.2895

DGDP

1

−0.18301

0.2182

−0.84

0.4023

Fit statistics SSE

160.6667

DFE

341

MSE

0.4712

Root MSE

0.6864

R2

0.5622

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295

on the overall intra-industry trade of processed food in China. The results of t-value test of market size difference (DGDP) are not significant, which also shows that the difference between China and its trading partners has little effect on the development of intra-industry trade of processed food in China.

15.4.4.2

Test Results of Determinants of Intra-Industry Trade (HIIT) of Products with Different Levels of Processed Food in China

First of all, F test is carried out on the model, the value of F statistic is 3.59 and Pr value |t| label

Intercept

1

0.545253

0.3414

1.60

0.1112

PCI

1

4.385313

1.5548

2.82

0.0051

DPCI

1

−3.92164

1.5457

−2.54

0.0116

GDP

1

0.31466

0.3535

−0.89

0.3741

DGDP

1

−0.04277

0.2873

−0.15

0.8817

Fit statistics SSE

278.4574

DFE

341

MSE

0.8166

Root MSE

0.9037

R2

0.2413

296

15.4.4.3

15 Research on Industrial Competitiveness of China’s Agricultural Sector

Test Results of Intra-industry Trade Determinants of Vertically Differentiated (VIIT) Processed Food Products in China

First of all, F test is carried out on the model. The value of F statistic is 9.96 and Pr value |t| label

Intercept

1

0.125168

0.2690

0.47

0.6420

PCI

1

4.125097

1.2250

3.37

0.0008

DPCI

1

−3.698

1.2178

−3.04

0.0026

GDP

1

0.474604

0.2785

1.70

0.0893

DGDP

1

−0.19707

0.2263

−0.87

0.3845

Fit statistics SSE

172.8410

DFE

341

MSE

0.5069

Root MSE

0.7119

R2

0.5290

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297

and more important role in the development of China’s processed food trade. In the intra-industry trade of processed food, it is not the intra-industry trade of horizontally differentiated products, but the proportion of intra-industry trade of vertically differentiated products with different prices and quality continues to grow. (2) Different types of processed foods have inconsistent trade patterns. The trade of “vegetable products”, “animal oil” and “fruit products” are mainly based on inter-industry trade, and inter-industry trade also occupies a leading position in the trade of “sugar and honey”, “vegetable oil” and “animal feed”. The trade in “margarine and miscellaneous foods”, “meat products”, “dairy products”, “fish products”, “beverages”, “tobacco” and “flour and cereal products” is mainly intra-industry trade. (3) Among the selected explanatory variables, the average level of per capita income and the difference of per capita income are the primary factors affecting the intra-industry trade of China’s processed food industry. The average level of per capita income plays a positive role, while the difference in per capita income has a negative impact. This result is consistent in three cases: the overall intraindustry trade, the intra-industry trade of vertically differentiated products and the intra-industry trade of horizontally differentiated products. (4) The explanatory variables selected in this book are “national characteristics” variables, without taking into account the “industrial characteristics” variables of intra-industry trade (for example, product differentiation, economies of scale, market structure, international direct investment, etc.) and “policy characteristics” variables (such as tariff barriers, non-tariff barriers, degree of economic integration, etc.). These factors need to be further studied.

15.5 Comprehensive Assessment and Analysis of China’s Regional Agriculture Sector’s Competitiveness of Thirty-One Provinces, Autonomous Regions and Municipalities 15.5.1 The Basic Problems of Agricultural Industry Competitiveness Agricultural competitiveness is a very complex phenomenon, from the theoretical point of view, we can do many aspects, many angles of research and analysis. However, when entering the field of practical application, people prefer to be able to use statistical methods to quantify the strength of agricultural competitiveness and its influencing factors. Therefore, the evaluation of agricultural competitiveness has become a special field in the study of agricultural competitiveness, and has been widely concerned.

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As early as 1965, Balassa put forward the “revealed comparative advantage index (RCA)” based on export data to reflect the trade comparative advantage of a country’s products or industries. However, the RCA index only takes into account the relative proportion of exports of the product or industry, and does not take into account the impact of the import factors of the industry or product. In order to measure the competitiveness of a country’s products or industries, Vollrath (1988) and Abbas (1992) have designed “Competitive Advantage Index (CA)” and “Index of Normalized Trade Balance (NTB)”, respectively. the results show that the index of display competitive advantage and the index of comparable net export are used to measure the competitiveness of a country’s products or industries, respectively. These three competitiveness evaluation methods and indicators have been widely used in agricultural competitiveness evaluation since 1980s because of reliable data sources and simple operation. Using import and export data to evaluate agricultural competitiveness can well reflect the performance of agricultural industry in market competition or the results of agricultural competitiveness, but it cannot reveal the causes or determinants of agricultural competitiveness. To this end, a number of analytical indicators have been adopted in recent years. Such as “Domestic Resource Cost (DRC)”, “Net Social Profitability (NSP)”, “Effective Protection Rate (ERP)”, “Total Factor Productivity (TFP)”, they evaluate the competitiveness of agricultural industry from the perspectives of production factor cost, resource allocation efficiency, trade distortion and agricultural technology level. It is true that these aspects will affect the competitiveness of agriculture, but the competitiveness of agriculture is also related to the level of business entities, the size of business scale, the degree of industrial correlation, agricultural system and other factors. It is a pity that there are few studies on the comprehensive evaluation of various determinants of agricultural competitiveness. In view of this, this book attempts to put forward a comprehensive evaluation index system and evaluation method of agricultural competitiveness, and apply it to the evaluation and analysis of agricultural industrial competitiveness of 31 provinces autonomous regions and municipalities in China. It provides an objective basis for understanding the actual level of agricultural development in various provinces autonomous regions and municipalities, and improving their agricultural competitiveness.

15.5.2 Index System, Method and Process of Comprehensive Evaluation of Agricultural Competitiveness 15.5.2.1

Comprehensive Evaluation Index System of Agricultural Competitiveness

The key to the comprehensive evaluation of agricultural competitiveness lies in the scientific selection of indicators and the construction of indicators system. Under the

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299

principles of objectivity, dynamics and operability, 38 indicators are selected from 7 aspects to establish the comprehensive evaluation index system of agricultural competitiveness based on available statistical data (see Table 15.9).

15.5.2.2

The Method and Procedure of Comprehensive Evaluation of Agricultural Competitiveness

Firstly, collecting relevant data. Then the standardized values of each observation on each index were calculated, and the standard deviation method was adopted. the calculation formula was as follows: Xi =

xi − x Q2

(15.5)

−

where, xi is the original data, x is the average, Q 2 is the variance, X i is the standardized value. Secondly, on the basis of standardized value, a comprehensive evaluation model is established to evaluate the competitiveness of each sub-factor and the overall competitiveness of agricultural competitiveness. The expression of the comprehensive evaluation model used in this book is as follows: (1) The evaluation model of sub-elements of competitiveness: Ai =

m 

Bi j

(15.6)

j=1

(2) Comprehensive evaluation model of agricultural competitiveness: F=

7 

Ai

(15.7)

i=1

Ai is the sub-factor competitiveness index, Bi j the standardized value and F is the total score value of agricultural competitiveness. Finally, according to the above calculation results, the analysis is carried out. In the application analysis, we will also use cluster analysis, correlation and other statistical methods to further analyze the agricultural competitiveness of 31 provinces autonomous regions and municipalities in China.

Index name

Effectiveness

(4) Index of relative advantage of gross agricultural output value

= (Agricultural GDP growth rate of each province/GDP growth rate of each province)/(agricultural GDP growth rate of the whole country/GDP growth rate of the whole country) (note: In this book, the calculation of growth rate is based on 1998)

Output of a product/sown area of the product (note: In this book, land productivity is a simple average of land productivity of grain crops, oilseeds, cotton, sugar, vegetables and fruits)

(2) Land productivity

(3) Farmers’ per capita net household income

= Gross agricultural output/value of agricultural labour forces

(1) Labour productivity

(continued)

Reflecting the profit level of agriculture

Input-output benefits reflecting land elements

Reflecting the input-output benefits of agricultural labor factors

Reflecting the level of total fishery output Reflecting the level of the primary industry output

(4) Gross value of fisheries

(5) Gross output value of primary industry

Reflecting the level of total forestry output Reflecting the level of total animal husbandry output

Reflecting the level of total agricultural output

Index meaning

(2) Gross forestry output value

Calculating methods of some indexes

(3) Gross output value of animal husbandry

Industrial scale (1) Gross agricultural output value

Object

Table 15.9 Evaluation index system of agricultural industry competitiveness of 31 provinces autonomous regions and municipalities in China based on available statistics

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Structure

Basics

Basics

Object

(2) Proportion of forest, animal husbandry, fishery and agricultural output value

(1) Diversity index

(continued)

Reflecting the degree of structural optimization within agriculture

Reflecting the comprehensive structure and diversification level of farming, forestry, animal husbandry and fisheries within agriculture

(Note: In this study, the three-year average of Reflecting the state of agricultural disaster-stricken area and disaster-stricken infrastructure area is adopted)

(5) Agricultural natural disasters accounted for the proportion of disaster-stricken areasa

= (Total sown area of crops-sown area of grain)/total sown area of crops

Reflecting the status of investment in agricultural science and technology

= The amount of agricultural science and technology expenses/the proportion of agricultural GDP

(4) Agricultural scientific research intensity

(3) Agricultural investment intensity

Reflecting the status of agricultural capital input

Reflecting the quality of agricultural labor force

(2) Proportion of non-illiterate population in rural families = (Rural credit cooperatives’ agricultural loan amount + farmer’s savings balance + financial fund for agriculture)/ratio of agricultural value added

Reflecting the status of agricultural land elements

(1) Cultivated land area

= (Total agricultural exports of each Reflect the comparative advantage of province/total exports of all products of each agricultural products export in a certain area province)/(Total agricultural exports of the whole country/total exports of all products of the whole country)

(5) Agricultural export advantage index

Index meaning

Calculating methods of some indexes

Index name

Table 15.9 (continued)

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Modernization

Object

Reflecting the development of rural industry

Index meaning

(continued)

Reflecting the level of agricultural irrigation

Reflecting the level of agricultural industrialization

(6) Number of key leading enterprises in agricultural industrialization in different regions

(1) Number of key leading enterprises in agricultural industrialization in areas with effective irrigation in unit cultivated land area

Reflecting the development of related industries in the lower reaches of agriculture

= (industry + construction + transport, Reflecting the structure of rural employment warehousing and post and telecommunications + wholesale catering + other non-agricultural industries)/(industry + construction + transport, warehousing and post and telecommunications + wholesale catering + other non-agricultural industries)/(industry + construction + transport, storage and post and telecommunications + wholesale catering + other non-agricultural industries)/(industry + construction + transport, warehousing and post and telecommunications + wholesale catering + other non-agricultural industries + agriculture + forestry, animal husbandry and fisheries)

Calculating methods of some indexes

(5) Power of agricultural products processing machinery

(4) The proportion of rural non-agricultural workers

(3) Value added of township enterprises

Index name

Table 15.9 (continued)

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Reflecting the growth of agricultural value added Reflecting the growth of agricultural products processing industry

Reflecting the change of agricultural mechanization level

(3) Growth rate of agricultural value added

(4) Gross output growth rate of light industry = (Expenditure on health care + using agricultural products as raw materials Expenditure on cultural, educational and in different regions recreational goods and services)/Total expenditure on farmers’ living expenses

(5) Gross power growth rate of agricultural machinery

(continued)

Reflecting the growth of agricultural investment

Reflecting the level of agricultural chemistry

(6) Pesticide usage per unit sown area

(2) Growth rate of total agricultural investment

Reflecting the level of agricultural mechanization

(5) Use of agricultural diesel oil per unit of seeding area

Reflecting the growth of agricultural human capital investment

Reflecting the level of agricultural chemistry

(4) Fertilizer application rate per unit sown area

(1) The growth rate of the proportion of human capital expenditure in farmers’ life consumption

Reflecting the level of agricultural electrification

(3) Electricity consumption per unit sown area

Growth

Reflecting the level of agricultural mechanization

Index meaning

(2) Agricultural mechanization level of major operating projects of unit sowing area

Calculating methods of some indexes

Index name

Object

Modernization

Table 15.9 (continued)

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(continued)

Reflecting the level of specialization of agricultural production and the comparative advantages of this kind of agricultural products in different provinces and cities in China

(2) Intensity index of land-intensive agricultural products production

Characteristics

Calculating method: (1) first calculate the concentration index of grain crops, oil crops, cotton and sugar respectively, then weighted average, the weight is the sown area of the four products; (2) the concentration index of grain crops, oil crops, cotton and sugar is equal to the national average of the per capita sown area divided by the corresponding indicators

Reflecting the level of specialization of agricultural production and the comparative advantages of this kind of agricultural products in different provinces and cities in China

Calculating method: (1) calculate the concentration index of vegetables, fruits, meat and aquatic products separately, then simply average it; (2) the concentration index of vegetables and fruits is equal to the national average measure of per capita sown area divided by corresponding index; (3) the concentration index of meat and aquatic products is equal to the average measure value of per capita output divided by corresponding index

(1) Labor-intensive agricultural product production concentration index

Index meaning

Characteristics

Calculating methods of some indexes Reflecting the growth of agricultural science and technology investment

Index name

(6) Growth rate of agricultural science and technology expenditure

Object

Table 15.9 (continued)

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= Foreign capital utilization in agriculture in Reflecting the degree of agricultural provinces/total foreign capital utilization in opening to the outside world agriculture in China = (total agricultural products import + total agricultural products export)/gross agricultural output

(4) The proportion of foreign capital used in agriculture in the whole country

(5) Agricultural extroversion index

Reflecting the development level of export-oriented agriculture

= In this study, the commodity rates of Reflecting the level of agricultural grain, cotton, oil, sugar, meat, eggs, dairy and marketization aquatic products were calculated separately, and then* averaged simply. In the average sales volume of main agricultural products per rural household, the calculation methods of meat were pork, beef, beef and aquatic products. The sum of mutton and poultry

(3) Commodity rate of agricultural products

Index meaning

Calculating methods of some indexes

Index name

Asterisk marks indictor is an inverse index Note The ones with a are inverse indicators

*

Object

Table 15.9 (continued)

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15.5.3 Results and Analysis of Comprehensive Evaluation of Agricultural Competitiveness of 31 Provinces Autonomous Regions and Municipalities in China Using the index system and evaluation method composed of the above 38 evaluation indexes, we quantitatively evaluate the agricultural competitiveness of 31 provinces autonomous regions and municipalities in China on the basis of the data in 2003.1 The evaluation results and analysis are as follows:

15.5.3.1

General Evaluation of Agricultural Competitiveness

Figure 15.4 shows the comprehensive ranking of agricultural competitiveness of 31 provinces autonomous regions and municipalities in China in 2003. In 2003, the agricultural competitiveness of Zhejiang, Shandong and Guangdong provinces ranked the top three among 31 provinces autonomous regions and municipalities in China, with scores of 66.60, 66.12 and 64.14, respectively. The comprehensive level of agricultural competitiveness in Qinghai, Guizhou and Tibet is relatively low. Generally speaking, there are two obvious characteristics of the agricultural competitiveness of provinces autonomous regions and municipalities in China: (1) the comprehensive level of agricultural competitiveness of provinces autonomous regions and municipalities is not balanced. The score of strong provinces in agricultural competitiveness is 2.7 times that of weak provinces. The imbalance of agricultural competitiveness is similar to the difference of economic development level (measured by average per capita GDP), and the correlation coefficient between them is 0.82. (2) The comprehensive level of agricultural competitiveness of provinces autonomous regions and municipalities has significant regional characteristics. The top nine provinces are located in the eastern coastal zone, while the bottom nine provinces are in the western region, and the central region is in the middle. In order to observe the characteristics of agricultural comprehensive competitiveness of China’s provinces, autonomous regions and municipalities, we used multivariate statistical clustering method to cluster the scores of agricultural competitiveness indicators of 31 provinces, autonomous regions and municipalities in China. As shown in Table 15.10, China’s agricultural competitiveness can be roughly divided into four types of provinces: the first type is the municipality directly under the central government; the second type of 13 provinces except Sichuan are located in the Central and Eastern region; the third type includes seven provinces; the fourth type of 8 provinces are all in the Western region. We use Fig. 15.5 to express the central value of each sub-factor competitiveness score of the four types of provinces. The difference of the central value of the central 1

The five indexes of the added value of township enterprises, the proportion of foreign investment in agricultural utilization in the whole country, the number of key leading enterprises of agricultural industrialization in each region, the intensity of agricultural investment and the growth rate of total agricultural investment are based on the statistical data of 2002.

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307

Fig. 15.4 Comprehensive ranking of agricultural competitiveness of 31 provinces, autonomous regions and municipalities

Table 15.10 Clustering results of agricultural competitiveness indicators of 31 provinces, autonomous regions and municipalities in China in 2003 Type 1

Tianjin, Beijing, Shanghai

Type 2

Zhejiang, Guangdong, Shandong, Fujian, Jiangsu, Liaoning, Hebei, Hubei, Hunan, Anhui, Henan, Jiangxi, Sichuan

Type 3

Hainan, Xinjiang, Guangxi, Heilongjiang, Inner Mongolia, Jilin, Yunnan

Type 4

Shanxi, Qinghai, Chongqing, Ningxia, Shaanxi, Gansu, Guizhou, Tibet

value reflects the characteristics and differences of agricultural competitiveness of all types of provinces. The structural competitiveness, modernization competitiveness, characteristic competitiveness and basic competitiveness of the first type of provinces have obvious advantages, but the disadvantage lies in the small scale of agriculture. The second type of provinces have the strongest scale competitiveness, and the other

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Fig. 15.5 Radar map of competitiveness differences of agricultural sub-elements in different provinces

Fig. 15.6 Comparisons of correlation coefficients between agricultural sub-factors competitiveness and comprehensive competitiveness

six sub-factors have the strongest competitiveness. The third type of provinces have the strongest benefit competitiveness, but the weakest structural competitiveness, and the other five sub-factors have relatively low competitiveness. The fourth type of provinces have the weakest agricultural competitiveness. In order to further investigate the influence and contribution of agricultural subfactor competitiveness to comprehensive competitiveness, we have calculated the correlation coefficient between the score of each sub-factor competitiveness and the score of comprehensive competitiveness (see Fig. 15.6). The results show that: (1) There is a high positive correlation between the scores of agricultural scale competitiveness, agricultural modernization competitiveness and agricultural characteristic competitiveness and the score of comprehensive competitiveness. The correlation coefficients are 0.8476, 0.7896 and 0.7174, respectively, which

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309

indicates that the competitiveness of modernization, structure and characteristics is the most important factor to determine the level of comprehensive competitiveness of agriculture. (2) There was a moderate positive correlation between the scores of agricultural scale competitiveness, agricultural basic competitiveness and agricultural benefit competitiveness and the score of comprehensive competitiveness. The correlation coefficients are 0.6944, 0.6169 and 0.5361, respectively, which indicates that the strong competitiveness of the three factors of scale, foundation and benefit is also a basic feature of the comprehensive competitiveness of agriculture. (3) It is a matter of concern that there is a very weak negative correlation between the score of agricultural growth competitiveness and the score of comprehensive competitiveness, and the correlation coefficient is −0.0042, which indicates that from a dynamic point of view, at present, some provinces with backward agricultural comprehensive competitiveness are showing a rapid growth trend, while some leading provinces are weak in the development trend. In the future, the pattern of agricultural comprehensive competitiveness of provinces in China will change, the speed of this change will depend on the growth of China’s entire national economy, but also depends on whether the provinces can conform to the inherent laws of economic development to promote the replacement of industrial structure. 15.5.3.2

Evaluation of Seven Agricultural Sub-factors Competitiveness

(1) Agricultural scale competitiveness According to the ranking of agricultural competitiveness scale competitiveness of provinces, the top provinces are Shandong, Henan, Guangdong, Sichuan, Jiangsu, Hunan, Hebei, and their competitiveness scores are more than 70 points. The provinces with low scores are Beijing, Shanghai, Qinghai, Ningxia, Tianjin, Tibet, all of which score less than 20 points. It can be seen that the gap between 31 provinces in the competitiveness of agricultural scale is relatively large. Because these indicators are all total output indicators, the top provinces are the “big agricultural provinces”. However, the comprehensive agricultural competitiveness of some of the major traditional agricultural provinces, such as Henan and Sichuan, all belong to the middle level. There is no sign of a “strong agricultural province”. (2) Competitiveness of agricultural benefits According to the ranking of agricultural basic competitiveness of provinces, Zhejiang, Xinjiang, Hainan, Heilongjiang and Shandong are in the top 5, and the bottom five provinces are Ningxia, Chongqing, Shaanxi, Guizhou and Qinghai in turn. The five specific indicators are positively correlated with the total score of benefit competitiveness, indicating that these five aspects play an important role in improving the competitiveness of agricultural efficiency.

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(3) Agricultural basic competitiveness According to the ranking of agricultural basic competitiveness, Liaoning, Tianjin, Hebei, Chongqing and Heilongjiang are in the top five, followed by Qinghai, Guizhou, Fujian, Hainan and Tibet. From the point of view of the correlation between the score of each index and the total score of basic competitiveness, agricultural human capital and agricultural investment play a key role in the promotion of agricultural basic competitiveness. (4) Competitiveness of agricultural structures The competitiveness of agricultural structure has significant regional differences. The top five provinces are Beijing, Zhejiang, Jiangsu, Shanghai and Guangdong, all of which are in the eastern developed region, while the five provinces with the lowest scores belong to the western region, namely Tibet, Gansu, Yunnan, Shaanxi and Ningxia. From the specific indicators, output value, township enterprises, nonagricultural industrial development, leading enterprises, mechanization and so on are the problems and difficulties that need to be solved urgently in the agricultural economic structure of backward areas. (5) Competitiveness of agricultural modernization The provinces with the highest score of agricultural modernization competitiveness are Beijing, Zhejiang, Shanghai, Fujian and Tianjin; the provinces with low scores, such as Guizhou, Heilongjiang, Chongqing, Inner Mongolia, Gansu etc., all belong to the central and western regions. The correlation between the scores of each index and the total score of modern competitiveness is high, which indicates that backward areas need to improve their modern competitiveness in an all-round way from the aspects of mechanization, electrification, chemistry and water conservancy of agriculture. (6) Competitiveness of agricultural growth According to the ranking of the competitiveness of agricultural growth in various provinces, Tianjin, Qinghai, Zhejiang, Guizhou, Jiangxi, scored high. Among these “leaders” in terms of growth, there are already provinces with the highest comprehensive competitiveness, such as Zhejiang and Tianjin. There are also provinces that lag behind, such as Guizhou, whose comprehensive competitiveness ranks second to last. The provinces with the lowest score of growth competitiveness are Shanghai, Guangxi, Hebei, Jiangsu, Sichuan, Liaoning and Heilongjiang in turn. According to the correlation coefficient between the score of each index and the total score of growth competitiveness shows that the deep processing of agricultural products, the expenditure on science and technology, the expenditure on human capital, mechanization and so on will effectively promote the growth of agriculture. (7) Agricultural characteristic competitiveness The top five provinces in the competitiveness of agricultural characteristics are Tianjin, Hainan, Liaoning, Shandong and Xinjiang, all of which belong to the eastern

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region except Xinjiang, while the five provinces and cities with the lowest scores all belong to the western region. They are Tibet, Chongqing, Guizhou, Sichuan and Qinghai. From the point of view of the correlation between the score of each index and the total score of characteristic competitiveness, the utilization of foreign capital and extroversion of agriculture are most closely related to the characteristic competitiveness.

15.5.4 Main Conclusions and Policy Implications Based on the available statistical data, this book tentatively puts forward the evaluation system of 7 factors and 38 indexes of comprehensive evaluation of China’s agricultural competitiveness, and makes a quantitative evaluation of the agricultural competitiveness of 31 provinces, autonomous regions and municipalities in China in 2003. For the agricultural competitiveness of 31 provinces, autonomous regions and municipalities in China in 2003, we can summarize the main findings of this study as follows: Firstly, the comprehensive level of agricultural competitiveness of 31 provinces, autonomous regions and municipalities in China presents unbalanced development and remarkable regional characteristics. Generally speaking, the comprehensive level of agricultural competitiveness of the eastern coastal provinces is generally higher than that of the central region, and the central region are generally better than the western region, which is very consistent with the gradient difference of China’s national economic development. Secondly, at present, the level of agricultural comprehensive competitiveness mainly depends on the competitiveness of agricultural modernization, the competitiveness of agricultural structure and the competitiveness of agricultural characteristics, which are the three important factors affecting the comprehensive competitiveness. Thirdly, with the improvement of the level of economic development, the growth rate of total agricultural volume and agricultural investment in some economically developed provinces and cities has shown a relatively slow trend, which directly shows the weakness of agricultural growth competitiveness. On the contrary, the competitiveness of agricultural growth in some economically backward areas is strong. Fourthly, the comprehensive competitiveness of agriculture is a complex, including all aspects of agriculture. Some valuable findings include: (1) a large agricultural province is not necessarily a power agricultural province; (2) the level of agricultural human capital and volume of investment in agriculture, which plays a key role in promoting the basic competitiveness of agriculture in various provinces; (3) the regional gradient difference of agricultural structure competitiveness is obvious, and the competitiveness of agricultural structure in western provinces is the weakest; (4) the competitiveness of agricultural modernization also shows a significant gradient difference, which is comprehensive. The backward region needs to enhance their

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competitiveness from the aspects of agricultural mechanization, electricity, chemistry and water conservancy; (5) most of the provinces with weak competitiveness of agricultural growth are located in the eastern and central regions; (6) the gradient difference of agricultural characteristic competitiveness is also obvious. The main reason for the weak characteristic competitiveness of backward provinces is the low degree of agricultural openness and export-oriented. In short, for regions at different levels and stages of development, the focus and direction of agricultural development should not be completely the same. Based on the regional situation, resource characteristics and advantages of each region, according to the level of economic development and industrial development, we should adopt the principle of classification guidance, suit the remedy to the case, formulate feasible key industries and industries, and promote the sustainable improvement of agricultural competitiveness level of each region by developing specific agricultural industries with regional characteristics and comparative advantages.

Postscript

The competitiveness research team of Renmin University of China has developed for 16 years. On the basis of the study of international competitiveness, we are deeply aware of the core and basic position of industrial competitiveness. In our research, we pay special attention to the role of team, among which, we have trained a number of high-level doctoral students. Adhere to the cooperative relationship with government departments, cooperate with the National Bureau of Statistics to ensure the latest and most authoritative enterprise statistics, interact with the Ministry of Commerce and other needs, and effectively ensure the application value of the research results. Pay attention to the renewal and development of database, play the role of statistical model, and pursue the basic construction of long-term research. Play the role of radiation and cultivation of research, absorb external research basis and strength of the research team to participate, such as absorbing Huazhong University of Science and Technology optoelectronic industry competitiveness research team, strengthen the domestic research team. The study of China’s industrial competitiveness is to give full play to the interdisciplinary advantages of Renmin University of China. The main experts on the subject include Professor Zhao Yanyun, Professor Wang Huacheng, Professor Lei Da, Professor Zou Ji, Professor Gao Minxue, Professor Wang Qiyan, Professor Kong Xiangzhi and Professor Lu Dongbin. And Associate Professor Chen Weiping, Associate Professor Jian Ming, Associate Professor Li Jingping, Associate Professor Xue Wei. As an assistant to the chief expert, Dr. Zhen Feng has played an important role in research and organization. The other main researchers are Dr. Zhang Mingqian, Dr. Zhen Feng, Dr. Chen Fang, Dr. Fu Qi, Dr. Tan Yingping, Dr. Li Zhenghui, Dr. Li Yajie, Dr. Wang Zuocheng, Dr. Wang Tao, Dr. Qiao Yunxia, Master Tao Jing, Master Xia Fan, Master Wang Changchun, Master Zhao Changchun, Master Hou Xiaoxia, Master Ma Wentao, Master Wang Feng, Master Yu Wei, Master Cao Qian, Master Yu Yi, Master Li Xiaohu, and doctoral students Guo Danbo, Wang Min, Wu Yilin, Cheng Xiaoyue, Xie Yihui, Cheng Hongli, Xie Leilei, Xing Ruijun and others. Professor Wei Ping of Huazhong University of Science and Technology led his team to participate in this study with the study of the Competitiveness of Optoelectronics Industry. In the process of this research, we have got the strong support of leaders © Economic Science Press and Springer Nature Singapore Pte Ltd. 2023 Y. Zhao, Study on China’s Industrial Competitiveness, https://doi.org/10.1007/978-981-19-9845-4

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and experts from National Bureau of Statistics, Ministry of Commerce, National Development and Reform Commission, ICBC, China Development Bank, China National Tourism Administration etc. We would like to express our heartfelt thanks. We would also like to thank Professor Qiu Dong of the Accreditation Committee of the Ministry of Education and other experts for their affirmation and loving suggestions on our research. There are still aspects of our research results that need to be studied in depth, and individual places may not be entirely appropriate. Therefore, we respectfully ask for your kindly comments. Zhao Yanyun

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