German and Chinese Contributions to Digitalization: Opportunities, Challenges, and Impacts [1st ed.] 9783658293390, 9783658293406

Table of contents :
Front Matter ....Pages i-xvi
Front Matter ....Pages 1-1
Germany’s Industry 4.0 Guiding China’s Development Based on the Perspective of Cyber Physical Systems (Yang Yanhong, Wang Yuzhen)....Pages 3-12
Industry 4.0—Economic Benefits and Challenges, Especially for Small and Medium-Sized Enterprises (Andreas Oberheitmann)....Pages 13-22
Industry 4.0—New Thoughts on Transforming and Upgrading the Traditional Food Manufacturing Industries (Xu Xuanguo)....Pages 23-29
Digital Transformation in SMEs—Lean Management + Industry 4.0 (Rudolf Jerrentrup)....Pages 31-37
Industry 4.0—Flexibility of Technical Infonomics by Knowledge Management (Michael Schaffner)....Pages 39-46
Front Matter ....Pages 47-47
How Industry 4.0 Inspires Chinese Automotive Companies in the Context of Made in China 2025 (Thomas Heupel, Zhang Congying)....Pages 49-73
The Four Waves of Industrialization in China (Zhou Xufeng)....Pages 75-87
An Effective Path to Made in China 2025—Sharing Economy Mode (Zhang Ping, Sun Xi)....Pages 89-97
Front Matter ....Pages 99-99
A Study on the Effect of Basic Public Services in China on the Net Migration Rate of the Provincial Population Based on the Analysis of a Provincial Spatial Panel Model (Zhang Yue, Sun Xiaofang)....Pages 101-118
On the Symbiotic Relationship Between the Equipment Manufacturing Industry and Producer Services of Shanxi Province (Hao Wangli)....Pages 119-137
The Opportunities and Challenges Shanxi’s Industrial Economy Faces in the Age of Industry 4.0 (Chao Tong)....Pages 139-152
A Study on the Interactive Mechanism Between Population Urbanization and Transfer of Labor Force in Shanxi Province—Based on the Perspective of Industrial Agglomeration (Peng Jia, Han Peiyu)....Pages 153-175
Front Matter ....Pages 177-177
How a New Thinking Determines the Future of (Small) Banks (Marcel Seidel)....Pages 179-186
Development Strategy of Coal Science and Technology Financing in Shanxi (Zhang Wenlong)....Pages 187-195
Research on the Refinancing Problem of Shanxi’s Listed Resource Companies (Yuan Gaixia, Zhang Caixia)....Pages 197-214
Research on the Marxist Theory of International Economic Cooperation from the Perspective of Economic Globalization—a Case Study on Regional Energy Cooperation (Kang Xuhua)....Pages 215-239
Designing Trustworthy Smart Contracts in International Trade Blockchains (Roger W. H. Bons)....Pages 241-249
Front Matter ....Pages 251-251
The Changing Role of SMEs in Innovation Activities in Germany–The Example of the Automobile Value-Added Chain (Michael Rothgang, Wolfgang Dürig)....Pages 253-267
A Research on Total Rewards, Labor Productivity and Labor Absorption of Non-State-Owned Manufacturing Enterprises in China (Chen Hong, Yang Junqing)....Pages 269-286

Citation preview

FOM-Edition

Andreas Oberheitmann Thomas Heupel Yang Junqing Wang Zhenlin Editors

German and Chinese Contributions to Digitalization Opportunities, Challenges, and Impacts

FOM-Edition International Series Series Editor FOM Hochschule für Oekonomie & Management Essen, Germany

In the course of its development, the FOM University of Applied Sciences founded a scientific publication series, the FOM-Edition, which is specifically dedicated to the publication projects of its lecturers. The FOM-Edition is divided into the following categories: textbooks, case study books, specialist books, and an international subseries (International Series). This contribution is part of the International Series, which accompanies the FOM strategy of internationalization and enables a unique representation of the productive outcome of international research collaboration and partnership. Through this subseries, FOM University offers its lecturers, researchers, and cooperation partners a platform to share joint projects, methods, and insights internationally.

More information about this subseries at http://www.springer.com/series/15755

Andreas Oberheitmann · Thomas Heupel · Yang Junqing · Wang Zhenlin Editors

German and Chinese Contributions to Digitalization Opportunities, Challenges, and Impacts

Editors Andreas Oberheitmann FOM Hochschule für Oekonomie & Management Essen, Germany Yang Junqing Shanxi University of Finance & Economics (SUFE) Taiyuan City, China

Thomas Heupel FOM Hochschule für Oekonomie & Management Essen, Germany Wang Zhenlin Shandong Agricultural University (SDAU) Shandong, China

ISSN 2625-7114 ISSN 2625-7122  (electronic) FOM-Edition ISSN 2524-6739 ISSN 2524-6747  (electronic) International Series ISBN 978-3-658-29339-0 ISBN 978-3-658-29340-6  (eBook) https://doi.org/10.1007/978-3-658-29340-6 Springer Gabler © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Responsible Editor: Angela Meffert This Springer Gabler imprint is published by the registered company Springer Fachmedien Wiesbaden GmbH part of Springer Nature. The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany

Message of Greeting

Ladies and gentlemen, in view of the great challenges we face in our time, international exchange and cooperation are becoming increasingly important. Climate change, the decline of natural resources, digitalization, and demographic change—none of these challenges are constrained by national borders. National approaches to finding a solution only show little effect. Within science and research, there is a strong network for facilitating international collaboration already. There are over 230 cooperations between universities in North RhineWestphalia and China alone. Photo: Dietmar Wadewitz Aside from student exchange programs and a range of opportunities for knowledge transfer, teaching partnerships are what mainly shape these long-term cooperations—teaching partnerships just like the one the FOM University of Applied Sciences has been successfully conducting for years. The German-Sino School of Business & Technology and its Chinese partner universities provide one of Europe’s most extensive exchange programs for Chinese students. More than 3500 students have graduated since its founding. I am happy to say that this successful form of collaboration is now going to be further expanded into the area of research, especially as the “Travelling Conferences” focus on the digital challenges of Industry 4.0, a topic of key interest to the North ­Rhine-Westphalian government. North Rhine-Westphalia has always been characterized by the high versatility of its industry. We aim to demonstrate this in the realm of digital transformation as well. In this context our scientists certainly have a lot to offer—I am looking forward to the valuable input from your cooperation. I would like to thank all of our partners for their engagement in intensifying the exchange, expanding the network and strengthening the cooperation in science and research and their readiness to learn with and from each other. I would v

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Message of Greeting

particularly like to thank our Chinese partners, the Shandong Agricultural University (SDAU), the Shanxi University of Finance and Economics (SUFE), and the College of Mobile Telecommunications of Chongqing, as well as the University of Posts and Telecommunication, and the College of Information of the Shanxi Agricultural University. February 2017

Svenja Schulze Former Minister of Innovation, Science and Research of North Rhine-Westphalia

Preface by the Editors

Digitalization is providing impact on businesses and economies around the world, and it certainly does in Germany and China not only for large firms, but also for small and medium-sized enterprises (SME). In Germany, the digitalization of the economy is supported by the Federal Government’s high-tech strategy Industry 4.0. Industry 4.0 combines a strong individualization of products with the conditions of an efficient and at the same time highly flexible production. Customers and business partners should be directly involved in business and value-added processes. Intelligent IT-based monitoring and decision-making processes aim at controlling and optimizing companies and entire value-added networks in near-real time. Despite individualized production, the resource efficiency of service provision and the costs of production can be reduced. The digital networking of companies in the value chain enable the optimization not only of the production steps but of the entire value chain. Closely related to this is the concept of the Internet of Things (IoT). The ability to control production processes across companies has great potential for saving resources and energy. In order to realize this potential, valid data for performance measurement and control must be obtained in real time. This requires an intensive examination of the possibilities and challenges of digital transformation. For China, the German concept Industry 4.0 is a strategic source of inspiration. Among other things, it was a model for the current Chinese innovation and industrial policy strategy Made in China 2025. Within the framework of this large-scale reform program, areas have been defined that are to receive special funding in the future. These areas include intelligent production, the interconnection of mobile Internet, cloud computing, Big Data, IoT and modern manufacturing (“Internet +”), as well as increasing energy and resource efficiency. This book is the tangible outcome of the Traveling Conference on “Industry 4.0— Resource Efficiency and Digital Transformation”, supported by the German Federal Ministry of Education and Research (BMBF), and held in February 2017 at four different partner universities of the FOM University of Applied Sciences, namely Shanxi University of Finance and Economics, Shandong Agricultural University, Shanxi Agricultural University and Chongqing University of Posts and Telecommunications. vii

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Preface by the Editors

Inter alia, experts from the University of Duisburg-Essen, the German Chamber of Commerce and the Essen Economic Promotion Organization also joined the conference with valuable presentations. The department of research promotion of the FOM University organized the successful event. From the editors’ point of view, this unique publication can be considered, first and foremost, a symbol of German-Chinese research collaboration and academic friendship. In a particular manner, this book exemplifies the similarities and differences in German and Chinese scientific practices and the productive result of their juncture. The editors of this book would like to thank all participants and hosts of the conference for their valuable contribution. The cooperation of all institutions involved has largely strengthened and deepened through the conference and this tangible outcome. The editors Andreas Oberheitmann Thomas Heupel Yang Junqing Wang Zhenlin

Editors

About the Editors Andreas Oberheitmann  is a professor for business administration and international management at the FOM University of Applied Sciences and the FOM German-Sino School of Business & Technology respectively, and furthermore functions as scientific director of the German-Sino Competence Center of Business & Technology (KCBT). He is a member of the editorial board of the American Journal of Climate Change and was expert reviewer for the fifth and sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), Working Group III. Between 2007 and 2013, he was international director of the Research Center for International Environmental Policy (RCIEP) and visiting professor at the School of Environment of Tsinghua University in Beijing. Between 1993 and 2015, he was senior research fellow at the RWI – Leibniz Institute for Economic Research, Essen. Andreas Oberheitmann conducted various studies and projects on different energy and environmental policy issues in China, including climate change mitigation in the building sector (CDM, P-CDM, sectoral approaches), low carbon economy in cities, sustainable development, post Kyoto issues, climate change adaptation, international trade issues, the introduction of competition in the power sector in China, supply and demand trends of mineral resources, etc.

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Editors

Thomas Heupel studied economics at the University of Siegen and subsequently worked as a research assistant at the IöB (Institut für ökologische Betriebswirtschaft) and managing director of the SMI (Siegener Mittelstandsinstitut) at the University of Siegen, Germany. He is a professor of business administration, with a focus on cost accounting and controlling. Since 2009 he has been vice rector of research at the FOM University of Applied Sciences in Essen, Germany. His research focuses on the fields of behavioral economics, automotive industry management, demographic change, blue ocean strategy, management of SMEs and cost control. He is a member of several scientific institutions’ advisory boards and editor of numerous academic books. Yang Junqing  is a professor of economics and vice-rector at the Shanxi University of Finance & Economics in Shanxi Province, China. His research fields include labor economics, human resources management, labor relation, human capital theory and rural industrialization as well as urbanization in China.

Wang Zhenlin  is a professor of crop science and vice president at the Shandong Agricultural University in Shandong, China. His research fields include, amongst others, nutritional characteristics and physiological and biochemical processes of high-yield and high-quality in crops respectively, the effect mechanism of water utilization rule of high-yielding and high-quality cultivation of crops, the coupling effects of cultivar-fertilizer-water and effects on crop yield and quality, physiological and biochemical processes of organic matter metabolism of crop and regulation, as well as the theoretical and technical approaches of high-yield and highquality cultivation of crops.

Contents

Part I  Industry 4.0 1

Germany’s Industry 4.0 Guiding China’s Development Based on the Perspective of Cyber Physical Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Yang Yanhong and Wang Yuzhen

2

Industry 4.0—Economic Benefits and Challenges, Especially for Small and Medium-Sized Enterprises. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Andreas Oberheitmann

3

Industry 4.0—New Thoughts on Transforming and Upgrading the Traditional Food Manufacturing Industries . . . . . . . . . . . . . . . . . . . . . . . 23 Xu Xuanguo

4

Digital Transformation in SMEs—Lean Management + Industry 4.0. . . . . . 31 Rudolf Jerrentrup

5

Industry 4.0—Flexibility of Technical Infonomics by Knowledge Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Michael Schaffner

Part II  Made in China 2025 6

How Industry 4.0 Inspires Chinese Automotive Companies in the Context of Made in China 2025. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Thomas Heupel and Zhang Congying

7

The Four Waves of Industrialization in China. . . . . . . . . . . . . . . . . . . . . . . . . 75 Zhou Xufeng

8

An Effective Path to Made in China 2025—Sharing Economy Mode. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Zhang Ping and Sun Xi

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Contents

Part III  Digitalization, Big Data, and Regional Aspects 9

A Study on the Effect of Basic Public Services in China on the Net Migration Rate of the Provincial Population Based on the Analysis of a Provincial Spatial Panel Model. . . . . . . . . . . . . . . . . . . . . . . . . . 101 Zhang Yue and Sun Xiaofang

10 On the Symbiotic Relationship Between the Equipment Manufacturing Industry and Producer Services of Shanxi Province . . . . . . 119 Hao Wangli 11 The Opportunities and Challenges Shanxi’s Industrial Economy Faces in the Age of Industry 4.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Chao Tong 12 A Study on the Interactive Mechanism Between Population Urbanization and Transfer of Labor Force in Shanxi Province— Based on the Perspective of Industrial Agglomeration. . . . . . . . . . . . . . . . . . 153 Peng Jia and Han Peiyu Part IV Digitalization, the Financial Sector, and International Trade Cooperation 13 How a New Thinking Determines the Future of (Small) Banks. . . . . . . . . . . 179 Marcel Seidel 14 Development Strategy of Coal Science and Technology Financing in Shanxi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Zhang Wenlong 15 Research on the Refinancing Problem of Shanxi’s Listed Resource Companies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Yuan Gaixia and Zhang Caixia 16 Research on the Marxist Theory of International Economic Cooperation from the Perspective of Economic Globalization—a Case Study on Regional Energy Cooperation . . . . . . . . . . . . . . . . . . . . . . . . . 215 Kang Xuhua 17 Designing Trustworthy Smart Contracts in International Trade Blockchains. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Roger W.H. Bons

Contents

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Part V  Digitalization and Innovation 18 The Changing Role of SMEs in Innovation Activities in Germany–The Example of the Automobile Value-Added Chain. . . . . . . . . . 253 Michael Rothgang and Wolfgang Dürig 19 A Research on Total Rewards, Labor Productivity and Labor Absorption of Non-State-Owned Manufacturing Enterprises in China. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Chen Hong and Yang Junqing

List of Contributors

Roger W. H. Bons  FOM University of Applied Sciences, Essen, Germany Chao Tong  Shanxi University of Finance & Economics, Taiyuan, China Chen Hong  Shanxi University of Finance & Economics, Taiyuan, China Wolfgang Dürig  RWI—Leibniz Institut für Wirtschaftsforschung, Essen, Germany Han Peiyu  Shanxi University of Finance & Economics, Taiyuan, China Hao Wangli  Shanxi University of Finance & Economics, Taiyuan, China Thomas Heupel  FOM University of Applied Sciences, Essen, Germany Rudolf Jerrentrup  FOM University of Applied Sciences, Essen, Germany Kang Xuhua  Shanxi University of Finance & Economics, Taiyuan, China Andreas Oberheitmann  FOM University of Applied Sciences, Essen, Germany Peng Jia  Shanxi University of Finance & Economics, Taiyuan, China Michael Rothgang  RWI—Leibniz Institut für Wirtschaftsforschung, Essen, Germany Michael Schaffner  FOM University of Applied Sciences, Berlin, Germany Marcel Seidel  FOM University of Applied Sciences, Stuttgart, Germany Sun Xi  Chongqing University of Posts and Telecommunications, Chongqing Hechuan, China

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List of Contributors

Sun Xiaofang  Shanxi University of Finance & Economics, Taiyuan, China Wang Yuzhen  Shanxi University of Finance & Economics, Taiyuan, China Xu Xuanguo  Shandong Agricultural University, Taian, China Yang Yanhong  Shanxi University of Finance & Economics, Taiyuan, China Yang Junqing  Shanxi University of Finance & Economics, Taiyuan, China Yuan Gaixia  Shanxi University of Finance & Economics, Taiyuan, China Zhang Caixia  Shanxi University of Finance & Economics, Taiyuan, China Zhang Congying  FOM University of Applied Sciences, Essen, Germany Zhang Ping Chongqing University of Posts and Telecommunications, Chongqing Hechuan, China Zhang Wenlong  Shanxi University of Finance & Economics, Taiyuan, China Zhou Xufeng  Shanxi University of Finance and Economics, Taiyuan, China Zhang Yue  Shanxi University of Finance & Economics, Taiyuan, China

Part I Industry 4.0

1

Germany’s Industry 4.0 Guiding China’s Development Based on the Perspective of Cyber Physical Systems Yang Yanhong and Wang Yuzhen

Contents 1.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 The Comparison Between Made in China 2025 and Germany’s Industry 4.0 . . . . . . . . . . 5 1.2.1 Made in China 2025. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.2 Germany’s Industry 4.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2.3 Comparison of Made in China 2025 and Industry 4.0. . . . . . . . . . . . . . . . . . . . . . . 8 1.3 China’s ‘Enlightenment’: Germany’s Industry 4.0 Emphasis on CPS Construction. . . . . . 10 1.4 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Abstract

The implementation of Germany’s Industry 4.0 strategy policy is well grounded, layer upon layer in domestic industry, market system, the legal system, etc. Germany is fully aware of the economic and social significance of the Cyber Physical System (CPS) and the significance of its support for the full and free development of the people. Hence, the CPS builds the core of Industry 4.0. The content of the Made in China 2025 strategy lacks the overall framework for the implementation of the policies and the understanding of the importance of building CPS. As a guiding strategy for national progress, it is necessary to attach great importance to the development of

Y. Yang (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] Y. Wang  Shanxi University of Finance & Economics, Taiyuan, China © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_1

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CPS, which is of essential significance to China’s economic power, cultural power and the happiness of its citizens.

1.1 Introduction Made in China 2025 and Germany’s Industry 4.0 are the national strategies devised by two of the most important economies in the world in order to achieve the goal of making China and Germany strong manufacturing countries. Made in China 2025 also aims at establishing China as a strong nation.1 The market economy in China has a history of only little more than 30 years. When the 18th National Congress of the Communist Party of China established the centrality of the market system in the distribution of resources, the market system was still underdeveloped. Legal awareness such as social contract awareness, professional ethics ­awareness and the protection of property rights were lacking. Although the manufacturing industry has developed rapidly, there is still a lot of potential. Up to now, it has only a few renowned global manufacturing enterprises and national brands due to the weak foundation. The depth of integration of the finance industry has just begun to kick off. Tackling the problem of financing, the real economy remains to be dealt with. Germany, as an established economic powerhouse, has a well-developed system of personnel training and scientific and technological innovation. Market management systems such as the legal system and the system of property rights protection are also well developed. The finance industry is highly regulated and prudently guarded by the mechanisms of the financial system. More resources can be designated to the real economy rather than excessively being assigned to the finance industry. This not only ensures the stability of the financial system but also provides a steady flow of funds and other resources to the economy and caters towards a sound economic development. Due to the differences between China and Germany regarding the market system, social system, and the technological level, the strategy of Made in China 2025 resides at its early stages and lags behind that of Germany’s Industry 4.0. In order to ensure a competitive advantage in the future, we need to clearly recognize the large gap between the strategic goals of the industrial development in China and Germany. Due to differing national conditions, China cannot simply copy the experience and measures of other countries like, for example, Germany. However, the practices and experience won in the approach to Industry 4.0 are of great reference value for the detailed implementation of the policy measures of Made in China 2025 and for pointing out the direction for the development of the manufacturing industry.

1Notice

No. 28.

of the State Council on Printing and Distributing Made in China 2025; Guo Fa [2015]

1  Germany’s Industry 4.0 Guiding China’s Development Based on the …

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1.2 The Comparison Between Made in China 2025 and Germany’s Industry 4.0 1.2.1 Made in China 2025 1.2.1.1 Policy Background Against the background of Germany’s Industry 4.0, China brought forward Made in China 2025 in 2015 (Li Jinhua 2016). The aim is to create a high-end domestic manufacturing industry, in 10 years time, by driving innovation, promoting smart transformation, strengthening basic and green development, and raising the level of manufacturing in China so as to promote China’s development from a manufacturing country to a manufacturing power. 1.2.1.2 Policy Goals Made in China 2025 is a strategy designed to create a strong nation. First of all, China is striving to become one of the global manufacturing powers by 2025; secondly, by 2035, the overall level of China’s manufacturing industry is intended to reach a medium level in the world’s manufacturing power camp; and finally, by the time a hundred years have past since the founding of the New China, China’s comprehensive strength is planned to be situated at the forefront of the world’s manufacturing powerhouses. The new generation of integrating information technology and manufacturing industry is creating far-reaching changes in the industry. New producers, types of industry, business models, and economic growth points are emerging. Many countries are focused on technological innovation, transformation and upgrading. This is generating a major opportunity for the innovation and development of the manufacturing industry in our country. The industrial sectors all over the world are in a very important period of adjustment. Many Western capitalist countries are also implementing a strategy of ­“re-industrialization” (Ding Chun 2014) using new models and methods in foreign trade and investment, hoping to form a new competitive advantage and to further consolidate or improve their position in the global market. Against this background, some developing countries are also accelerating their strategy, actively participating in the global division of labor, technology and capital transfer, and expanding in the international market. This has caused China’s manufacturing industry to face a ‘double squeeze’ that has formed between ‘Industry 4.0’ in developed economies and emerging economies. Therefore, China must have a global vision, strengthen strategic planning, strive to build a powerful nation and to seize the new round of development opportunities in the manufacturing industry. 1.2.1.3 The Problems Faced China is still in the process of industrialization. It thus remains a rather large gap between China and the developed capitalist countries in the West. First of all, the scope of China’s manufacturing industry as a whole is large in size but not highly developed; it

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currently remains in a state of being ‘big, but not strong’. Second, regarding innovation, Chinese enterprises are facing difficulties to innovate independently, lacking the prerequisite of awareness, motivation and the technological foundation. Core technologies are lacking and there is a tendency to rely on core technologies and high-end devices from other countries. This causes a weak core competitiveness, low international visibility and has great impact on corporate sales and foreign exports. In addition, many small and medium-sized enterprises lack the advanced concept of business management. Enterprises do not use innovative measures to create value and the business models are not changed. All this has set obstacles for the further development of the enterprises. Finally, the production process only focuses on maximizing economic goals while neglecting ecological interests, green production and green development in economy and society. The enterprises are failing to see that a sustainable development links economic, ecological and social development in time and space.

1.2.1.4 Countermeasures 1. Innovation-driven Development To develop the manufacturing industry in China the main focus should be on innovation, using innovative forces to drive the development of knowledge and knowledge transfer and of the manufacturing industries across the municipalities, provinces and country. 2. Quality First Initially, attention should be payed to technology to ensure the development of quality, then on the production to achieve quality excellence. Third, compliance with legislation will ensure the bottom line for quality and, last but not least, there needs to be a change in mindset ensuring a shift in focus from quantity to quality. 3. Green Development The ecological and social development should be prioritized and obtain a binding character. There is a fundamental connection between the ecological balance, the economic development and social progress. Maintaining the ecological balance is a prerequisite for the survival of humankind and a fundamental guarantee for achieving a sustainable use of resources and an environmentally friendly society. 4. Structure Optimization The optimization of the manufacturing structure is the key to developing the manufacturing potential. Efforts should be made to improve the traditional manufacturing structure, to optimize the industrial structure of China’s manufacturing industry and thus to enhance industrial competitiveness. 5. Talent-Based Personnel training, and especially talent building, is fundamental to the development of the manufacturing industry. Therefore, China should be devoted to cultivating a large number of specialized and qualified personnel.

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1.2.2 Germany’s Industry 4.0 1.2.2.1 Policy Background Industry 4.0 is a high-tech strategy launched by Germany in 2013 that aims to encourage and promote the development and innovation of revolutionary new technologies in Germany’s domestic industry and to further improve creativity and the industry’s competitiveness globally. With Industry 4.0 and its strengths in manufacturing and embedded systems, Germany has enabled the Internet of Things (IoT) and Services Internet to expand and grow in the manufacturing sector. Major Industry 4.0 projects can be divided into two broad categories. One is the smart factory and the other is smart production (Hu Jie 2014). Research on smart factories focuses on Cyber Physical Systems (CPS),2 intelligent production processes, intelligent production systems, and networked distributed production facilities. Some examples are the intelligent production in the main business area of production i.e. logistics management, human-computer interaction, 3D technology and its applications. Industry 4.0 has the advantage that it can be customized in some areas to meet the specific needs of its customers. New ways can be developed to create value and new business models to bring new opportunities for the development of enterprises, especially Small and Mediumsized Enterprises (SME). Last but not least, it can contribute to a more productive and efficient utilization of resources and energy in the entire value network of opportunities and further economic development. 1.2.2.2 Policy Goals Germany is carrying out the Fourth Industrial Revolution while maintaining the traditional advantages of the German manufacturing industry. Germany took the initiative in manufacturing development, boosting it to take a leading position in the world. In detail, Germany expects to achieve the following: 1. Become a market leader in machinery and equipment manufacturing. 2. Become the pioneer of innovation in embedded systems and automation projects. 3. Become the provider of an abundance of skilled labor. 4. Become the advanced pioneer in the network and cooperation between suppliers and users.

2CPS

(Cyber Physical Systems), also known as information physics system, or virtual network entity physical system, is a unified information system and physical system. It can be regarded as an upgraded version of the Internet of Things. This system places more emphasis on the digital world's control over the physical world. CPS provides real-time, autonomous control of physical entities and systems over the Internet in a reliable and secure manner. CPS will make the digital world no longer just a virtual image of the physical world, but truly evolve into the new world of human society. In the future, the integration of people, machines and goods brought by CPS will lead to a revolution in productivity in the manufacturing industry and even in all industries, to make human life safer, more efficient, healthier and cleaner.

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1.2.2.3 Policy Measures 1. Standardization and Reference Architecture (He Yiwen 2015) The concept and implementation of standardization should encompass different companies across the entire value network. Among these different actors, a number of supporting tools have been developed and adopted to achieve a single set of standards that apply to all. 2. Safety and Security (He Yiwen 2015) The smart factories and smart production in Industry 4.0 are all based on a concept that ensures safety and security of products and of information related to the production. 3. Organization and Design of Work (He Yiwen 2015) As a result, intelligent production will bring a series of changes. Real-time control in the smart factory will not only change the main content of the work but also the work environment. This requires even more innovation and offers more uses for technology. 4. Resource Utilization Efficiency (He Yiwen 2015) Industry 4.0 helps to improve the efficiency in the utilization of resources and boosts the sustainable development of economy. 5. Managing Complex Systems (He Yiwen 2015) The products and manufacturing systems needed for intelligent production are becoming increasingly complex. Corresponding models are needed to manage these increasingly complex systems. 6. Establishing a Comprehensive Broadband Infrastructure for the Industry. The extensive construction of broadband internet infrastructure has become an urgent need. Reliable, comprehensive, and high quality communication networks are a key requirement of Industry 4.0.

1.2.3 Comparison of Made in China 2025 and Industry 4.0 On the whole, China’s strategy is more macro-oriented. The Made in China 2025 strategy provides mostly descriptive and presumptive statements and requirements. The measures are often not sufficiently specific. Germany’s Industry 4.0 strategy, released by the German Federal Ministry of Education and Research in September 2013, is more specific and detailed, reflecting the rigorous personality and the developed market economy that is oftentimes associated with Germany and its citizens. From the perspective of policy guidance, Made in China 2025 still lags the industrial policy features of the catching-up stage. From top to bottom, those can be defined as the future pillars of economic development: • focusing on a new generation of information technology industry, • high-end Computer Numerical Control (CNC) machine tools and robotics, • aerospace equipment,

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• • • • • • •

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marine engineering equipment and high-tech vessels, advanced rail transportation equipment, energy-saving and new energy vehicles, electric equipment, agricultural machinery and equipment, new materials, biomedicine and high performance medical equipment and ten more fields.

However, if China would be more cautious, it could diminish serious consequences caused by the selection of industrial technology of enterprises. First, in the economic catch-up phase, the industrial policy adopts a large number of selective policy tools. Second, in the rapid economic growth phase, the direction of the industrial policy is to encourage enterprises to do joined research and development. With the exception of a few successful examples, the effect of the policy is not satisfactory, the biggest drawback being technology convergence. Third, when the government formulated and implemented industrial policies, its role was misguided, interfering too much in the market, yet failing to effectively intervene in the real market failure. Fourth, it misled the demand, causing enterprises to make wrong judgments and decisions. A first consequence is the distortion of price signals, leading to the failure to eliminate backward production capacity, as well as causing a great number of enterprises to allocate large amounts of investment. The government wastes social and financial resources, i.e. it undertakes investments, which, in the end, do not pay off. Second, due to excessive government intervention in the economy, the government often creates huge rent seeking areas for enterprises in the formulation of industrial policies. Therefore, one should always be vigilant about the negative effects of these industrial policies. In addition, although China has put forward such strategies as “creating a fair competitive market environment, perfecting financial support policies, strengthening financial and taxation policy support, improving the multi-level personnel training system and perfecting the policy of small and medium-sized enterprises”, the various types of government policies have not formed a concerted effort and policies have not managed to establish an overall framework. Therefore, the government’s leadership over the development of science and technology, especially the high-tech development that is related to the core national interests, has been greatly reduced. When following the German example, China needs to improve standards and legal structures by fostering the needs and financial resources of enterprises and the human resources of schools. The establishment of trade associations with a ‘leader’ nature, the development of social co-management, the relationship between government officials and students, the creation of a national innovation system, and the expansion and improvement of its functions and performance should be encouraged. In contrast to China, Germany as a veteran industrial power, no longer has technology and branding as their goal, but is shifting to the production model, focusing on production management, production safety and other higher-level manufacturing philosophy.

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Pursuing the new industrial revolution mode of production characterized by networking and intelligence, the Germans are acutely aware of the great improvement of infrastructure in the world through the accomplishments of the first three industrial civilizations by mankind and the establishment of a ‘global village’. They integrated intelligent equipment, information engineering and production facilities into the construction of CPS (Virtual Network—Cyber Physical System). Therefore, Germany’s Industry 4.0 is, one might assume, more ambitious than the Made in China 2025 strategy. If Made in China 2025 is to promote the completion of industrialization and information technology, then Germany’s Industry 4.0, to some extent, is a subversion of the existing industrial production mode, rooted in Germany’s globally leading equipment manufacturing industry. These advantages include innovative manufacturing technology, highly specialized and complex industrial process management, robust machinery and equipment manufacturing, information technology capabilities, as well as high technology in embedded systems and automation engineering. It is worth pondering over whether the competitive advantage that China is trying to build will be able to compete with the Industry 4.0 plan of an established industrial power such as Germany.

1.3 China’s ‘Enlightenment’: Germany’s Industry 4.0 Emphasis on CPS Construction The core of Germany’s Industry 4.0 is the realization of CPS by creating enterprises, which establish a production and sales network in the world. Smart sensors are integrated into the manufacturing system, in their storage systems and production facilities, enabling the enterprises to better control the business process, the production system and the automatic exchange of information with each other, independently triggering actions and controls. Therefore, China also needs to focus on CPS construction as this can provide domestic industries the following economic competitive advantages: 1. CPS can facilitate a fundamental improvement in the process of manufacturing, material selection, management, supply chain management and life cycle management. The Smart Factory takes a completely new approach to production: smart products are identified in unique forms that can be located at any time and know their own history, current status, and alternative routes for achieving their target status. The embedded manufacturing system, on the other hand, enables vertical network connections in business processes between factories and businesses. Horizontal connections are created across decentralized value networks, and real-time management, from placing an order all the way to the delivery logistics. In addition, the end-to-end engineering they generate induces demand, which runs through the value chain. 2. Smart factories make the small-batch production still profitable, and thus help to meet the individualized needs of future customers. Due to the transparency, detailedness,

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controllability, dynamic business and engineering processes of the manufacturing process, momentums can also change, helping to generate the right business decisions. 3. Providing development opportunities for start-ups and small businesses is conducive to the public entrepreneurship and the realization of numerous innovations, bringing new ways of creating value and business models. It can expand the area of economic development, extend the value chain of economic development, drive more people to work and create more value. 4. Most importantly, in the long run, the greatest value and significance of Industry 4.0 is not limited to the economic realm. Through the establishment of CPS, the interconnectedness of this world is more and more advanced, which is greatly increasing personal abilities. CPS has an impact on the organization of work, creates demographic changes and influences social factors. The intelligent support system frees workers from performing routine tasks so that human beings can focus on innovative and value-added activities, i.e., save the necessary labor time mentioned in Marx’s political economy to enhance people’s freedom and promote the progress of civilization.

1.4 Conclusion Industry 4.0 is a high-tech strategy launched by Germany in 2013 (Pei Changhong and Yu Yan 2014). It aims at encouraging and promoting the development and innovation of revolutionary new technologies in the domestic industry in Germany. Its aim is to further enhance the creativity and competitiveness of German industry within the global industry. Germany is expected to take the lead and thus gain a dominant position in this new industrial revolution. Under this influence, the development of the Made in China 2025 strategy is geared towards medium and high-end manufacturing in China. On the network basis, the development of Made in China 2025 has a major strategic significance. However, at the same time, we must also recognize that the strategic goals of China are fragmented and the construction of CPS is mainly focused on the economic industry. The understanding of the significance of CPS in reshaping social forms is inadequate and the pre-research on relevant policies is not sufficient. First of all, policy research should be carried out to focus on the impact and leading role of CPS on various aspects of China’s development. Secondly, it should aim to strengthen communication and cooperation with Germany. As a unique and powerful European country with the power to establish a strong national industry, Germany is also based on the principles of the social market economy. Last but not least, we should keep a close eye on other industrialized countries. For example, Japan and the United States also attach great importance to the CPS construction work. In view of this historic prospect, these countries should, with regard to the opinion of this chapter’s authors, seize the opportunities and win the competition.

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Additional Literature 李金华.德国工业4.0背景下中国制造强国的六大行动路径[J].南京社会科学, 2016(29), 8–16 丁纯.德国工业4.0内容动因与前景及其启示[J].德国研究, 2014, 4(29), 46–66. 胡杰.从德国工业4.0看中国未来制造业的发展[J].民营科技, 2014(12), 268–269. 何懿文.工业4.0:中国的机遇与挑战[J].计算机世界, 2015(18), 1–12. 裴长洪,于燕.德国工业4.0与中德制造业合作新发展[J].财经问题研究, 2014 (10), 27–33.

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Industry 4.0—Economic Benefits and Challenges, Especially for Small and Medium-Sized Enterprises Andreas Oberheitmann

Contents 2.1 Background and Rationale of Industry 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2 Economic Benefits of Industry 4.0 Smart Factories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.3 Motivation and Obstacles for the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises (SMEs) in Germany. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Abstract

Industry 4.0 represents the fourth step of the industrial revolution, fully digitalizing the industrial value chain with the Cyber-Physical System, the Internet of Things, and other means. With Industry 4.0, a largely self-organized production can be organized. This will require changes in industrial workers and in management skills as well as huge investments in technology. Different studies, e.g. by the Boston Consulting Group or the German Federal Ministry for Economic Affairs and Energy (BMWi), estimate economic boosts in Germany of about 150 billion Euro in its GDP by 2020, through the use of Industry 4.0. SMEs are rating the lack of available resources, sufficient qualifications, clear transparency of benefits or the handling of systems as bigger challenges for the implementation of Industry 4.0 compared to large-sized companies. On the other hand, SMEs see slightly higher potentials in the implementation of Industry 4.0 than large-sized companies.

A. Oberheitmann (*)  FOM University of Applied Sciences, Essen, Germany e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_2

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2.1 Background and Rationale of Industry 4.0 The term Industry 4.0 was coined by Henning Kagermann, Wolf-Dieter Lukas and Wolfgang Wahlster and was first revealed to the public on the Hanover Fair in 2011 (Kagermann et al. 2011). It was based on the high-tech industry strategy of the German federal government. It also stands for a research platform of the German Federal Ministry of Education and Science (BMBF). It is now also under the auspices of the German Federal Ministry for the Economy and Energy (BMWi) with the aim to closely interlink industrial production with modern information and communication technology. New business models with virtual teams all over the world can be developed (Elstner et al. 2016). Industry 4.0 may be an additional driver of the current fifth Kondratiev cycle or even a catalyst for a sixth new long wave of economic prosperity (Dörre 2016). The theory of cyclic economic development or long waves was introduced in 1926 by the Russian economist Nikolai Kondratiev (Kondratiev 1926). The starting point for the long waves of about 45 to 60 years are paradigm shifts and the associated innovation-induced investments: When new, ground-breaking innovations appear, an economy will massively invest in these new technologies and thus an economic boom will be induced. When an innovation has been generally accepted, the associated investment will be drastically reduced and results in a downturn. However, during that period of the downturn, new paradigms and innovations were already being worked on. At his time, Kondratiev was able to detect two and a half of such long waves, assuming that the third wave would end at the end of the 1920s, which became true with the collapse of the stock market and the global economic crisis. Up to now, five Kondratiev cycles occurred (Grinin et al. 2016): 1st cycle (approx. 1780–1840) Early mechanization: The beginning of industrialization in Germany; Steam Engine Kondratiev. There are conjectures that there was already an earlier cycle in England. 2nd cycle (approx. 1840–1890) Second industrial revolution of railroad Kondratiev (Bessemer steel and steam ships). In Central Europe this era was called “Gründerzeit”. 3rd cycle (approx. 1890–1940) Electrical engineering and heavy machinery Kondratiev (also chemistry). 4th cycle (approx. 1940–1990) Single-purpose automation Kondratiev (basic innovations: integrated circuit, nuclear power, transistor, computers). 5th cycle (since 1990) Information and Communication Development).

Technology

Kondratiev

(Global

Economic

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Similarly, Industry 4.0 represents the fourth step of ground-breaking innovations since the mid/end of the 18th Century (Fig. 2.1). Industry 1.0 stands for the first industrial revolution during the mid/end of the 18th Century characterized by the utilisation of machines for mechanical production fuelled by steam power, e.g. steam pumps for coal mining in Great Britain or steam engines for mechanical weaving looms in Germany. During the second industrial revolution, which took place in the early 20th Century (Industry 2.0), machines for industrial mass production were fuelled by electricity, e.g. conveyor belts in automobile production in the US and Germany. Industry 2.0 marked the era of Taylorism. The third industrial revolution (Industry 3.0), i. e. since the early 1970s, utilized electronics and IT for further automatization in production, e.g. computers and other digital equipment in production and offices around the world. Today, Industry 4.0 is starting to establish smart factories using intelligent and digitally networking systems such as: • Cyber-physical System (CPS): Online networks linking IT with mechanical and electronic components communicating with each other in the network, e.g. radio frequency identification (RFID) technology is a basic CPS used since 1999. • Internet of Things (IoT): “Networked interconnection of everyday objects, which are often equipped with ubiquitous intelligence. IoT will increase the ubiquity of the internet by integrating every object for interaction via embedded systems, which leads to a highly distributed network of devices communicating with human beings as well as other devices.” (Xia et al. 2012)

Industry 4.0

Industry 3.0

Industry 2.0

Industry 1.0

Utilization of cyber physical systems

Utilization of electronics and IT for further automatization in production

Utilization of machines for industrial mass production fuelled by electricity

Utilization of machines for mechanical production fuelled steam power Mid/End 18 th Century

Early 20th Century

Early 1970s

Fig. 2.1  Four stages of the industrial revolution

Today

Time

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• M2M: machine-to-machine, mobile-to-machine, and machine-to-mobile communications. M2M data communication involves one or more entities (machines, mobiles) that do not necessarily require human interaction or intervention in the process of communication. M2M enables a variety of equipment (e.g. home appliances, vehicles, buildings) to communicate with each other in order to create new levels of “smart services” and commerce (The Focal Point Group 2013). • Augmented Reality (AR): Technology, which enables people to perceive completely computational elements and objects within the real world experience and structures (Krevelen and Poelman 2010). AR technology is used in laboratories or now also as virtual reality glasses in combination with smartphones. The aim of Industry 4.0 is to develop a largely self-organized production. People, machines, plants, logistics and products communicate and cooperate directly in Industry 4.0. Through networking, it will be possible to optimize not only one production step but also a whole value chain. The network will cover all phases of the product’s life cycle— from the idea of a product through its development, manufacturing, use and maintenance to its recycling process. Elements of the organizational design concept (Deloitte 2014) are • Networks: Machines, devices, sensors and people can network with one another and can communicate via the Internet of Things. • Big Data: Sensory and big data expand information systems of digital factory models in order to create a virtual image of the real world. • Technical assistance: Assistance systems support people with the help of aggregated, visualized and comprehensible information. In this way, informed decisions can be made and problems can be resolved more quickly. In addition, people are supported physically during strenuous, unpleasant or dangerous work. • Decentralized decisions: Cyber-physical systems are able to make independent decisions and to carry out tasks as autonomously as possible. Only in exceptional cases, for example, in the case of disturbances or conflicts of destination, does it transfer the tasks to a higher authority. Digitalisation of industry is not only a German strategy. Other countries are following similar approaches. In the US, it is called “Industrial Internet”. The Industrial Internet Consortium was founded in March 2014 by the companies AT & T, Cisco, General Electric, IBM and Intel. By the end of July 2017, it had 251 members (Industrial Internet Consortium 2017). In Japan, a similar strategy is implemented called “Industrial Value-Chain Initiative”, which included 138 major industrial companies by the end of July 2017, amongst others Toyota, Toshiba, Nissan and NEC (Industrial Value-Chain Initiative 2017). With Made in China 2025, China took an initiative similar to the German platform Industry 4.0 in the five-year plan of 2015. It was established to play a decisive role in the desired transformation from a low-wage country to a global industrial power by 2049,

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the 100th anniversary of the foundation of the People’s Republic of China (State Council of the People’s Republic of China 2015). South Korea invests in so-called “smart factories”. In April 2017, the South Korean government issued the targeted number of smart factories to be increased to 30,000 by 2025 (Maeil Business News Korea 2017). In France, industrial digitalization is approached by the name of “Industrie du futur”. On 18th of May 2015, in Nantes, the former minister for the economy, Emanuel Macron, gathered the actors mobilized in favour of reindustrialization around the Future Industry project, the new matrix of industrial strategy. The project aims at modernizing the industrial sector and transforming an economic model through digital technology (Economie. gouv.fr 2015). The implementation of Industry 4.0 and similar approaches in the world are expected to bring about considerable economic benefits.

2.2 Economic Benefits of Industry 4.0 Smart Factories According to a study implemented by the Boston Consulting Group (2015), benefits will accrue in four distinct areas: productivity, revenue growth, employment, and investment: On average, productivity gains of 5 to 8 percent could be achieved. In some sectors, such as industrial-component manufacturers (20–30%) and automotive companies (10–20%), the gains will be largely above average. A revenue growth of about 30 billion Euro a year representing about 1% of Germany’s GDP, is expected. The impact on employment is hard to assess. In the future, different skills will be required and workers will be laid-off. However, on average, a 6% growth in employment during the next ten years is estimated. The implementation of Industry 4.0 in Germany will require investments of about 250 billion Euro or about 1.0 to 1.5% of manufacturers’ revenues during the next ten years. The current industry network without Industry 4.0 (Fig.  2.2) has different disadvantages: • Only one principal and agent are connected. • Information is solely exchanged between them. • Large Original Equipment Manufacturers (OEMs) are connected to different small and medium-sized enterprises. • However, their production is not linked, so that communication between these enterprises happens individually. In the future industry network, with Industry 4.0, all companies in the value chain are interconnected (Fig. 2.3) and information can be exchanged between all of them (maximum inter-operationability is reached). Through common norms and standards of

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Fig. 2.2  Current industry network without industry 4.0. (Source Based on BMWi 2015)

Fig. 2.3  Future industry network with industry 4.0. (Source Based on BMWI 2015)

communication and a maximum of inter-operationability, the investment risks can be reduced and maximum economic potential be tapped. In 2015, the German Federal Ministry for Economic Affairs and Energy (BMWi) undertook a study on the economic effects of Industry 4.0. Central sectors to tap the market potential for Industry 4.0 are sensor technology, robotics, innovative production systems, logistics and, ICT. Until 2020, on the national level, total growth effects of about 150 billion Euro p.a. are to be expected, broken down by sector (Fig. 2.4). On the EU level, until 2030, 90 billion Euro p.a. or 1.34 trillion Euro of total GDP growth is estimated. On the international scale, the Internet of Things (29 trillion Euro),

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Fig. 2.4  Economic effects of industry 4.0. (Source Based on BMWI 2015)

digital intelligence (7.2 trillion Euro), robotics (4.8 trillion Euro) and cloud computing (1.4 trillion Euro) will induce considerable economic growth. In each of these sectors, Germany will be a lead market and lead supplier. Thus, Industry 4.0 will help to strengthen Germany’s industrial basis.

2.3 Motivation and Obstacles for the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises (SMEs) in Germany Currently, only 22% of all interviewed companies have a high level of digitalization in their vertical and horizontal value chains. In the next five years, this percentage is supposed to quadruple at about 84%. In principle, the increasing digitalization facilitates the outsourcing of many business processes along the value chains. Increasing productivity, turnover, and production flexibility, while reducing costs at the same time, are the main joint driving forces across all company sizes. The development of new business models and services as well as an increased customer loyalty and satisfaction play a greater role for SMEs than for large enterprises. Especially its thematic complexity, high investment costs and security concerns make all companies hesitate about implementing Industry 4.0 (Fig. 2.5).

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Fig. 2.5  Motivation for the implementation of industry 4.0 in SMEs and large-scale enterprises. (Source Based on BMWI 2015)

Many important challenges, such as available resources, sufficient qualifications, clear transparency of benefits or the handling of systems are a greater problem for SMEs than for large companies (Fig. 2.6).

Fig. 2.6  Obstacles for the implementation of industry 4.0 in SMEs and large-scale enterprises. (Source Based on BMWi 2015)

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Especially the question of economic efficiency of the required investments is turning out to be the greatest obstacle. Most German companies estimate the investment costs to be higher on a mid-term basis than the expected company growth. That many companies, especially in the SME segment, hesitate because of the oftentimes negatively rated relation between the predicted high demand for investments and the resulting sales growth, is rather likely. All in all, it turns out to be apparent that SMEs see slightly higher potentials in the implementation of Industry 4.0 but at the same time face more serious challenges than large enterprises.

2.4 Summary Industry 4.0 represents the current step of the industrial revolution and evolves through the use of cyber-physical systems and other means in production. It aims at developing a largely self-organized production. People, machines, plants, logistics, and products communicate and cooperate directly, and the whole value chain can potentially be optimized. Main elements are networks, information transparency, technical assistance, and decentralized decisions. Not only Germany but also other countries such as the US, China, Japan, South Korea, or France are pursuing similar approaches. In 2015, the German Federal Ministry for the Economy and Energy commenced a study on the economic effects of Industry 4.0 for small and medium-sized as well as large companies (BMWi 2015). Main results of a study were: • In Industry 4.0, through common norms and standards of communication and maximum inter-operationability, the investment risks are reduced and maximum economic potential can be tapped. • Through the implementation of Industry 4.0, a study of the German Federal Ministry for Economic Affairs estimates a possible plus of about 150 billion Euro in GDP by 2020. • Currently, the thematic complexity, high investment costs and security concerns make all companies hesitate about implementing Industry 4.0. • Challenges such as available resources, sufficient qualifications, a clear transparency of benefits or the handling of systems are a greater problem for SMEs than for ­large-sized companies. • However, SMEs see slightly higher potentials in the implementation of Industry 4.0 than large-sized companies. Overall, according to a study of the Boston Consulting Group, published within the same year, considerable benefits will accrue in productivity (5 to 8%), revenue growth (1% of Germany’s GDP), employment (6% growth on average) and investment (250 billion Euro over the next ten years).

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References BMWi (2015). Industrie 4.0 – Volks- und betriebswirtschaftliche Faktoren für den Standort Deutschland. Berlin: Mimeo. Boston Consulting Group (2015). Industry 4.0—The future of productivity and growth in manufacturing industries. https://www.bcgperspectives.com/content/articles/engineered_products_project_business_industry_40_future_productivity_growth_manufacturing_industries/?chapter=3. Accessed 30 July 2017. Dörre, K. (2016). Industrie 4.0 – Neue Prosperität oder Vertiefung gesellschaftlicher Spaltungen? Sechs Thesen zur Diskussion, Working Paper der DFG-KollegforscherInnengruppe Postwachstumsgesellschaften, Nr. 02/2016, Jena, 2016. Deloitte (2014). Industry 4.0—Challenges and solutions for the digital transformation and use of exponential technologies. Zurich: Mimeo. Economie.gouv.fr (2015). Industrie du Futur: transformer le modèle industriel par le numérique. https://www.economie.gouv.fr/lancement-seconde-phase-nouvelle-france-industrielle. Accessed 30 July 2017. Elstner, S., Feld, L. P., & Schmidt, C. M. (2016). Bedingt abwehrbereit: Deutschland im digitalen Wandel. Arbeitspapier 03/2016 des Sachverständigenrates zur Begutachtung der gesamtwirtschaftlichen Entwicklung. Berlin: Mimeo. Grinin, L., Korotayew, A., & Tausch, A. (2016). Economic Cycles, crises, and the global periphery. International perspectives on social policy, administration, and practice. https://doi. org/10.1007/978-3-319-41262-7_2. Industrial Internet Consortium (2017). Members. http://www.iiconsortium.org/members.htm. Accessed 30 July 2017. Industrial Value-Chain Initiative (2017). IVI membership list. https://iv-i.org/wp/en/organization/ membership-list/. Accessed 30 July 2017. Kagermann, H., Lukas, W.-D., & Wahlster, W. (2011). Industrie 4.0 – Mit dem Internet der Dinge auf dem Weg zur 4. Industriellen Revolution. vdi-Nachrichten, 13, 2. Krevelen, D. W. F., & van and Poelman, R. (2010). A survey of augmented reality technologies, applications and limitations. The International Journal of Virtual Reality 9(2):1–20. Kondratiev, Nikolai D. (1926). Die langen Wellen der Konjunktur. Archiv für Sozialwissenschaft und Sozialpolitik, 56, 573–609. Maeil Business News Korea (2017). S. Korean govt raises target number of smart factories to 30,000 by 2025. http://pulsenews.co.kr/view.php?year=2017&no=269532. Pulse by Maeil Business News Korea, 2017–04-20. Accessed 30 July 2017. State Council of the People’s Republic of China (2015). Made in China 2025. Beijing, July 7, 2015. Mimeo. http://www.cittadellascienza.it/cina/wp-content/uploads/2017/02/IoT-ONEMade-in-China-2025.pdf. Accessed 30 July 2017. The Focal Point Group (2013). M2M white paper: The growth of device connectivity. https://www. qualcomm.com/documents/m2m-white-paper-growth-device-connectivity. Accessed 30 July 2017. Xia, F., Yang, L. T., Wang, L., & Vinel, A. (2012). Internet of things. International Journal of Communication Systems, 25, 1101–1102. https://doi.org/10.1002/dac.2417.

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Industry 4.0—New Thoughts on Transforming and Upgrading the Traditional Food Manufacturing Industries Xu Xuanguo

Contents 3.1 Four Themes of the Food Industry 4.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.2 Intelligent Food Factory Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.3 Intelligent Food Production Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.4 Intelligent Logistics System Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.5 Intelligent Information System Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 References and Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Acknowledgements: This topic is just for viewpoint discussion. Most of the contributions are based on ideas by Mr. Ren Zhimeng, executive director of Xiamen Shengzhixiang food company. He is the founder of food Industry 4.0 with Chinese characteristics. More information on this topic can be found freely on the internet. With this publication we intended to share this interesting viewpoint with German researchers and like to express our gratitude to Mr. Ren Zhimeng for his inspirations concerning food Industry 4.0. Abstract

This article explains the “food Industry 4.0 model with Chinese characteristics”. Food Industry 4.0 includes the intelligent factory, intelligent production, intelligent logistics, and intelligent information. The intelligent factory focuses on distributed smart manufacturing systems and processes. Intelligent production itself, inter alia,

X. Xu (*)  Shandong Agricultural University, Taian, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_3

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copes with the entire production logistics management, man-machine interaction, and three-dimensional technology applications in the industrial production and logistics process. Intelligent logistics are mainly implemented through the Internet of Things. The demand side can quickly acquire matching services and logistics support. The intelligent information system mainly offers the information exchange among different systems. Intelligent logistic systems inter alia provide for the final product demand and the service demand of the consumers.

3.1 Four Themes of the Food Industry 4.0 As food industry involves the national economy and people’s livelihood, Industry 4.0 will play an important role in the visual trace of the food industry’s whole process. In our opinion, the food Industry 4.0 should not only include Smart Factory (intelligent factory) and intelligent production, but also include the intelligent information system, which is an auditory and visual system, and offer all information from the very beginning, the seed, to the end-consumers. The intelligent information system should run through the whole cycle chain, as an independent system. Hence, food Industry 4.0 should be divided into Smart Factory (intelligent factory), intelligent production, intelligent logistics, and intelligent information – four big systems (see Fig. 3.1). The ‘Smart Factory’, or intelligent factory, focuses on intelligent manufacturing systems and processes, as well as the realization of the network of distributed manufacturing facilities. ‘Intelligent production’ mainly relates to the entire enterprise production logistics management, human-computer interaction, and three-dimensional technology applications in the industrial production and logistics process, etc. ‘Intelligent logistics’ are mainly implemented through the Internet, the Internet of Things, business networking and the integration of logistics resources. They are furthermore giving full play to the efficiency of the existing logistics resources. The demand side can quickly get matching services and logistics support. The ‘Intelligent information system’ mainly offers the information exchange among different systems, including the Smart Factory (intelligent factory), intelligent production, and the intelligent logistics system. The Intelligent logistics system is able to anticipate and respond to the final consumers’ product and service demand [3]. Fig. 3.1   Food industry 4.0 composition

intelligent factory food industry 4.0

intelligent production intelligent logistics intelligent information

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These four parts respectively encompass enterprises and departments across the industry. All Smart Factories, intelligent production, and intelligent logistics need to be supported by an intelligent information system. It is a three-dimensional space, audible, and visual cross-boundary industry collaboration system providing for more transparent and more direct access to information systems and finally, to more efficient and convenient products and services.

3.2 Intelligent Food Factory Model An intelligent food factory may associate with more than seven units (see Fig. 3.2). With advanced communication technology, the different units collaborate to provide the products and services in the virtual network space environment and meet the demand across time and space. The intelligent food factory receives information about purchasing orders from the intelligent transportation tool factory, the food machinery factory, the food auxiliary material supply, the intelligent farm, the logistics enterprises, the food technical school as well as the food research institute and then offers a system audit. If the demand can be met, it accepts the order and the order enters into the production stage. If not, the order needs to be modified or re-negotiated. The customer will be asked to make an amendment and the next step is initiated automatically after receiving the reply. The food research institute is in charge of the production process design. In an intelligent factory, product spare parts, tools, carrying cases and machines are equipped with sensors and equipment for business communication and other data exchange. This scale of comprehensive information flow is enabled by the currently most advanced manufacturing automation level. To further optimize production, enterprises should be improved in the following order of industrial processes: product design, production planning, production engineering, production and production services. These services include product repair and maintenance as well as energy conservation and environmental protection services, amongst others. Food production process design should first consider the different Fig. 3.2   Seven units of an intelligent food factory

food research institute

intelligent transportation tool factory

food machinery factory

food technical school

intelligent food factory

food auxiliary material supply

logistics enterprises

intelligent farm

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characteristics of the food varieties, and physical and chemical changes in every process. Food scraps, scrap and waste processing should be affiliated with achieving energy conservation and respecting environmental protection regulations, etc. All of the above processes require the monitoring and implementation of intelligent equipment. Food vocational technical training system (food technical schools) should be integrated into the food production process. The system should be implemented on the basis of fully considering the food process needs to be equipped with all required kinds of technical personnel. In the logistics supply system, it is necessary to meet the needs at each link of intelligent equipment, supplies and product delivery. The intelligent farm and food auxiliary material supply chain should be supported by the software analysis of the production cycle of food, food raw materials, packaging materials, agricultural production cycle etc. The intelligent food machinery factory should be able to automatically correct parameters. Monitoring and controlling the system, it should detect if the system does not automatically correct its parameters. It should then instantly send an alarm and request the staff to launch remote correction technology parameters. If it cannot be corrected remotely, instructions should be given to the nearest production equipment technical personnel. This would maximize the guaranteed equipment capacity in all modes of operation. In cases in which the equipment malfunctions, this process could also reduce the costs and losses to a minimum. All farm and food processing plants, vocational food technical schools, institutes, logistics enterprises, transport manufacturing, as well as food trade of online and offline sales enterprises, are in an information sharing platform. They can reach all kinds of enterprises through the information platform and receive instant information. Instant communication can also help the enterprises to coordinate the supply and demand side of the cooperation more closely and make it more efficient. Food research institutes may require information from food machinery factories, farms, material suppliers, etc. In this way, it is possible to design more scientific, more reasonable and more intelligent food production facilities. The information system can overcome the boundaries of the industry and aid the collaboration between industries. This chain is already no longer a mere internal data exchange, but rather a cross-industry data exchange.

3.3 Intelligent Food Production Model Compared with the advanced products of the intelligent food production, the products produced with low technology context are of far less value (Fig. 3.3). Transportation still creates a considerable proportion of the total cost of the end product. Assuming that producers will set up their production sites close to the raw material source, they reduce transportation costs and not only expand production but also increase the complexity of the production. Automation equipment, advanced communications

3  Industry 4.0—New Thoughts on Transforming and Upgrading … Fig. 3.3   Intelligent food production composition

food production technology monitoring food operator training

order delivery system

intelligent food production

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intelligent food inspection system

raw material inventory system logistics distribution system

product research and development

technology, and a network virtual space system can reduce the complexity of the production process. Vocational food technical schools can monitor the production process, especially the requirements of the technical parameters. The order delivery system can ensure a minimum quantity in stock and can automatically issue orders to a food factory. Logistic distribution systems can receive input from various industries about companies’ logistics requirements. The food research institute, inter alia, collects data on the customer service system and other systems of customer demand, as well as the market, the competition situation, and the market potential, etc. It forecasts the future market information automatically generated by the computer system.

3.4 Intelligent Logistics System Model As already mentioned, in order to establish a logistics system, the supply is required to meet the needs of each link of the intelligent equipment. A supply transportation process as shown below is low in cost, intelligent and automated (Fig. 3.4).

Fig. 3.4   Intelligent logistics composition

vehicles parameter monitoring

driving personnel positioning

intelligent logistics system

transportation equipment maintenance system

vehicles positioning

job training system

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Logistic distribution systems can receive input from various industries about companies’ logistics requirements. The system automatically distributes logistics personnel. If mobile terminals and PCs are connected to the Internet, the system can monitor the ­progress of the tasks. This includes • • • • • •

the location, whether transportation is normal, the performance of the transport equipment, the intelligent recognition system, the main components and the overall performance and conditions of the operation.

This ensures the safest and most efficient execution of the process. Logistics tools of intelligent monitoring can greatly reduce accidents and heavy losses caused by equipment failures, as for example by flat tires, speeding or running red lights. If a device failure or personnel irregularities occur, intelligent systems signal an alarm and report to the police after a short time. In case of a power failure, the energy system issues a warning for a short period of time, and then the revised system will automatically restart.

3.5 Intelligent Information System Model The digital world seamlessly integrates with the physical world in the systems of the intelligent food factory, the intelligent food production and the intelligent logistics ­system (Fig.  3.5).

food research institute food technical school food operator training intelligent food production food inspection

intelligent farm

food maschine factory

food materials supply chain

intelligent factory

transportation tool factory job training system

intelligent information system

……..

Fig. 3.5  Intelligent information composition

intelligent logistics system

……..

vehicles positioning system

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These systems incorporate all the necessary elements and the information about the finished product. Through the physical system of integrating information, the enterprise cannot only clearly identify the product and product positioning, but also get a comprehensive grasp of the following steps in the production and of alternative paths to create the final product. In the era of Industry 4.0, machinery, storage systems and production methods constitute an interwoven network. In this network, information can interact in real-time. At the same time, the physical information integration system can also provide for a feasibility plan and based on preset optimization criteria select the best path. Both can guarantee product standards and are countless times faster than the human ­decision-making process.

References and Additional Literature 中国特色食品工业4.0模型描述. http://www.hfgj.gov.cn/10741/10751/10759/201510/t20151020_ 1894041.html. 吴智慧 (2015) 工业传统制造业转型升级的新思维与新模式. 家具, 2015, 36(1), 1–7. 德国联邦教育研究部工业4.0工作组(康金城,译. 把握德国制造业的未来, 实施工业4.0攻略的 建议[R]. 北京: 中国工程院咨询服务中心, 2013. 食品产业升级与工业4.0研讨会在京召开. http://www.buhaoting.com/zixun/yingyang/huaiyunmeishi/140461.html. Gerbert, P. et al. (2015). Industry 4.0—The future of productivity and growth in manufacturing industries. https://www.bcg.com/publications/2015/engineered_products_project_business_industry_4_ future_productivity_growth_manufacturing_industries.aspx. Pathak, S. D., Wu, Z., & Johnston, D. (2014). Toward a structural view of co-opetition in supply networks. Journal of Operations Management 2014(32), 254–267.

4

Digital Transformation in SMEs—Lean Management + Industry 4.0 Rudolf Jerrentrup

Contents 4.1 Introduction: Current Status of Industry 4.0 Within German Industry . . . . . . . . . . . . . . . . 32 4.2 Challenges and Implementation Requirements for SMEs. . . . . . . . . . . . . . . . . . . . . . . . . . 33 4.3 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Abstract

Digital transformation will considerably change the technical production environment and the way of working in the industry. This change will take place primarily in the larger conglomerates, but will soon affect small and medium-sized enterprises (SMEs). In Germany, particularly SMEs are of high importance, as they constitute a substantial part of the overall firm population. The initiative Industry 4.0, based on the high-tech strategy of the German federal government, is also a research platform focused on driving the digital transformation process in the German industry. As digital transformation is not only a technical but also a managerial and cultural challenge, many companies have already formulated some strategic digital transformation ideas. In practice, however, only selected and very innovative (often larger companies) have

First, I would like to thank my former student Christoph Wunderlich who gave generous support by conducting several interviews with selected companies and putting the respective results into the right display format. R. Jerrentrup (*)  FOM University of Applied Sciences, Essen, Germany e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_4

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implemented first solutions. These solutions often concentrate on production improvement as cost reduction, flexibility, and quality. The creation of new products and particularly new business models is still a distant prospect. Due to the specific cultural and managerial framework, most SMEs are especially challenged. The digital transformation process in these companies requires substantial changes in leadership and management behavior as well as conduct. Hence, a structured holistic change project, using established methods of the Lean Management Approach, is a prerequisite for a successful digital transformation process. Lean management and Industry 4.0 form a compulsory symbiosis.

4.1 Introduction: Current Status of Industry 4.0 Within German Industry The term Industry 4.0 is a research platform established by the German government and first mentioned publicly on the Hannover fair in 2011. It mainly comprises: • • • •

Men-machine communication by IoT Generation and Transparency of information Virtual reality Decision support and autonomous decision-making systems

Various studies have evaluated the current situation of Industry 4.0 initiatives. They show that particularly in small and medium-sized enterprises (SMEs) in Germany these initiatives often concentrate on cost reduction, flexibility enhancement, and quality improvement in production. To enhance productivity and to improve the competitor position has already been the focus of the companies in recent years. In the 90s, most companies made use of the project-oriented methodology of Six Sigma. Later the more holistic approach of lean six sigma or lean management was preferred. Therefore, empirical studies show the predominance of investments into initiatives to increase production efficiency. In Fig. 4.1 it becomes obvious, that about 90% of the current initiatives concentrate on production and related functions like production planning and internal logistics. Maintenance services and R&D still play a minor role, although Industry 4.0 offers huge potential based on predictive maintenance, predictive analytics, or asset life cycle management. Product life cycle management (PLM) tools can increase the efficiency in R&D. The time to market can be enhanced by 3D simulations, virtual and augmented reality, as well as virtual prototyping. Currently, manufacturers of intelligent hard- and software solutions are pushing the Industry 4.0 applications. They offer solutions for communication between machines, machine and product as well as men-machine interfaces. A prerequisite for these offerings are intelligent algorithms and big data analysis. In practice, many companies still do not have the capability to generate such an amount of data because the existing machine structure and established MIS are limited with respect to data quality and volume.

4  Digital Transformation in SMEs—Lean Management + Industry 4.0 Fig. 4.1   Functional focus of industry 4.0 investments. (Source Based on Horvath & Partner 2015)

33

70 60 50 40 30 20 10 0

Figure 4.2 shows that projects that generate real value, based on new services and business which enhance revenue, are still very limited. Hence, particularly in SMEs, the transformation process proceeds slowly. In addition to the above mentioned major obstacles, this poses security issues. Enterprise as well as private data protection and intellectual property are restricting the penetration of Industry 4.0 applications. Furthermore, a substantial cultural challenge of the organization is required to accept the changes of the digital transformation process in the industry.

4.2 Challenges and Implementation Requirements for SMEs To evaluate the changes and risks of the digital transformation process in SMEs an empirical study was conducted by Christoph Wunderlich in the context of his Master thesis “Chancen und Risiken der digitalen Transformation der Organisationen kleiner und mittlerer Unternehmen in Deutschland” based on selected explorative interviews

Fig. 4.2   Benefits of industry 4.0 investments. (Source Based on Horvath & Partner 2015)

80 70 60 50 40 30 20 10 0

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with senior and top managers in different industry segments. Referring to the organizational Management Model of St. Gallen (Rüegg-Stürm, J. 2005) different aspects of the digital transformation process were mirrored against the organizational framework. This framework comprises five aspects, the organizational structure, the supporting systems required, the resources (primarily personnel), the culture within the company, and finally the strategic orientation of the management. The Digitalization aspects include based on the above-mentioned concept (Fig. 4.3): • connect: connectivity between machines, machines, and product as well as ­man-machine interfaces • analysis: big data analysis and interpretation as well as simulations • automate: self-learning and autonomous decision making • mobilize: organizational and cultural change, advanced leadership characteristics • secure: enterprise and private data security Figure 4.4 shows that the organizational structure of SMEs is characterized by flat hierarchies, often limited management resources and a concentration of power e.g. with the owner. Limited IT infrastructure poses restrictions regarding controlling processes and

Fig. 4.3  Concept for evaluating digital transformation impacts on SMEs. (Source Own adapted figure. Kind usage permission by Christoph Wunderlich)

4  Digital Transformation in SMEs—Lean Management + Industry 4.0

Systems Strong functional focus functions Limited IT infrastructure Low level of controlling processes and systems ….

Structure Concentration of power Flat hierarchies Few specialized functions Limited management resources …

Environment Independence

Orientation Entrepreneur‘s personal vision High dependency on founder‘ sense of intuition Often limited corporate strategic planning organizational development …

Entrepreneurs personally represent their company

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Culture Determined by entrepreneur’s values and vision Closeness between management and employees Pragmatism, improvisation and intuition … Resources Close connection between ownership and leadership Dependency on entrepreneur (know how and financial potential) Limited specialization in administration …

Personal relationship between entrepreneur and market environment

Fig. 4.4  SME organizational model. (Source Own adapted figure. Kind usage permission by Christoph Wunderlich)

systems. The culture is dominated by values and vision of the entrepreneur. Pragmatism, improvisation, and intuition are more relevant than in larger companies. Know-how and financial potential of the company is dependent on the standing of the entrepreneur or owner. Leadership and ownership are closely related. The study indicates that digital transformation will enhance productivity and flexibility of production. The collaboration among employees will increase. The externalization of implicit knowledge will be pushed. Employer attractiveness will alleviate the recruitment of employees. Corporate culture will be determined by the ability to change. Competences, particularly in transformation management, become more important than expertise. Figure 4.5 illustrates the challenges of the digitalization process in SMEs. Digital transformation enhances collaboration between employees and pro-active knowledge exchange but requires a transformation manager who can counter-balance the claim for leadership of the entrepreneur. Charisma and know-how can strengthen his or her position. Digital transformation skills of employees will outrank long experience in the company. This could lead to considerable frictions within the company. The change in values could lead to misplaced gratitude and threaten organizational peace. The higher complexity will challenge the knowledge of the management and require resources. Considerable investments will be needed in IT infrastructure and thus respective trainings of employees.

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Systems Higher requirements for system integration Higher expenses for IT security Higher requirements and complexity in knowledge management

Structure Transformation manager counter balances entrepreneur More Evolution versus revolution (rapid transformational change) …

Environment Increasing competition

Orientation Insufficient change through lack of strategic vision High dependency on the entrepreneur's personal willingness and ability to change …

Culture Management Overload Threat of “organizational peace” through value change Misplaced “gratitude” for employees threatens changeability …

Resources Risks through deficits in transformation management knowhow Insufficient management capacities and knowledge Increasing dependency on specific employee knowhow

Increasing complexity of supply chain

Fig. 4.5  Challenges of the digitalization process in SMEs. (Source Own adapted figure. Kind usage permission by Christoph Wunderlich)

4.3 Conclusions Only with clear and active support of the top management, the digital transformation process will be successful. Similar to Six Sigma or Lean Management projects, rigid project management is essential. Openness for external knowledge and the usage of benchmarks of other successful transformed companies will facilitate the required change (Fig. 4.6).

Transformation Manger defined Top Management actively supports the transformation process

Success Factors

External knowledge actively involved / Benchmarks Rigid Project Management …

Fig. 4.6  Success factors of a digital transformation process. (Source Own adapted figure. Kind usage permission by Christoph Wunderlich)

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While large companies are, to a considerable extent, already investing in digitalization projects and respective transformation requirements, SMEs are still at an early stage respectively. The overall focus is currently very much efficiency oriented; technical aspects and IT structures predominate the mutual understanding. Nevertheless, ecosystems based on platform technologies generating new business concepts and opportunities are the future, for larger companies as well as SMEs. These will lead to even greater challenges within the organizations regarding leadership, management, and corporate culture change.

References Rüegg-Stürm, J. (Organisationsmodell, 2005). Das neue St. Galler Management-Modell (2. Aufl.). Bern: Haupt.

Additional Literature Schlund, S., Hämmerle, M., & Strölin, T. (2016). Industrie 4.0 – Wo steht die Revolution der Arbeitsgestaltung. Ingenetics und Fraunhofer IAO. Sauter, R., Bode, M., & Kittelberger, D. (2015). Wie Industrie 4.0 die Steuerung der Wertschöpfung verändert. Horvath & Partner. Bundesverband der deutschen Industrie e. V., PricewaterhouseCoopers AG (ed.) (Digitalisierung, 2015). Mittelstandspanel: Die Digitalisierung im Mittelstand. Berlin. Bullinger, H.-J. et al. (Organisation, 2009). Handbuch Unternehmensorganisation (3. Aufl.). Berlin: Springer. Heidbrink, M., & Jenewein, W. (2011). High-Performance-Organisationen. Stuttgart: Schäffer-Poeschel. Wimmer, R. (Familienunternehmen, 2009). Familienunternehmen. In A. von Schlippe (Eds.), Beiträge zur Theorie des Familienunternehmens (S. 1–16). Lohmar: Eul. Höttges, T. (Digitalisierung, 2015). Vernetzung ist unser Geschäft. In C. Knop & T. Becker (eds.), Digitales Neuland. Warum Deutschlands Manager jetzt Revolutionäre werden (S. 167–179). Wiesbaden: Springer Gabler.

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Industry 4.0—Flexibility of Technical Infonomics by Knowledge Management Michael Schaffner

Contents 5.1 Technical Infonomics Today . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 5.2 New Production Structures Are Created by Industry 4.0. . . . . . . . . . . . . . . . . . . . . . . . . . . 40 5.3 Technical Communication in Industry 4.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Abstract

Within industrial environments, digital transformation is combined with the term “smart factory” and in Germany, in particular, with the term Industry 4.0. A humanfree and robot-based production, machine control via digital terminals or data glasses as well as continuous and high actual data transparency in the horizontal and vertical value chains, are fictional images of the future based on pilot environments. However, the current reality looks different; especially in technical operation and machine maintenance. Dirty hands, outdated and unclear operating- and ­maintenance-instructions and just little digitalization. How do we reach the future? For the industrial service, “technical communication” is currently paid insufficient attention to, which results in a research gap in this scientific area. The contemporary findings are based primarily on research results in ongoing projects. They are, however, only interim results. One result relates, for example, to the completely changed

M. Schaffner (*)  FOM University of Applied Sciences, Berlin, Germany e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_5

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view of technical editors. Editors no longer think into possible action state of affairs and write rigid instructions, but manage metadata so that content can be context-sensitively linked to the time of use. So far, technical editors have been pure information managers and are now becoming knowledge managers or knowledge architects. Consistent digitization, semantic content structures and reformations in the occupational profile of technical writers are some of the basic conditions for flexible infonomics of the future, which are briefly discussed here.

5.1 Technical Infonomics Today Production structures in Industry 4.0 are often described as making use of high industrial automation in almost deserted factories, multimedia support in machine operation or in service processes (such as data goggles, augmented reality) and as being supported by service robots and artificial intelligence. But the reality is often different nowadays. Operating and service environments are rather often handcrafted. Information for operation, repair and maintenance (technical information) are seldom on the most up-to-date state of the list of components or service experience. Often, this information is hidden in unmanageable document structures (printed manuals, PDFs) and can only be found with considerable search effort. Digitization also results in a new operating and malfunctioning situation, which is not yet known or can be surpassed when the production machines are delivered (Schaffner 2017a). In addition to known material causes of malfunction (broken lever, cracked belt) or data flow errors (incorrect synchronizations, data signal errors), software problems occur, whose effects are revealed only in networked systems (viruses, trojans, software errors). New production structures lead to the need for a new, flexible information economy for technical information and reorganization in technical communication and technical editing.

5.2 New Production Structures Are Created by Industry 4.0 From the point of view of industrial production, Industry 4.0 is mainly characterized by the smart (“intelligent”) factory, which is based on the fractal factory in Warnecke (Warnecke 1995). The organization of classical factories is predominantly ­vertical-hierarchically structured. If the performance complexity increases, this leads to a strong horizontal decomposition, high coordination costs, and costs in general. Nature, on the other hand, has a fractal structure. It consists of self-similar structures (repetitions of a particular structure in itself). Examples of such a self-similarity are crystals,

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snowflakes, coastal lines, branches of a tree, the leaf structure of ferns or the surface of a Romanesco broccoli. According to Warnecke, a fractal factory consists of decentralized structures with small control circuits (fractals), which enable an intense communication between all subsystems of a factory. The fractals act as autonomous, dynamic and self-similar units and stand in a relationship of service to each other. Like this, the systems in a fractal factory itself organize and optimize themselves. A smart factory is created by the fact that these fractals with the new I4.0 technologies become so-called agents. Agents are programs that act independently as a component of a distributed system and can communicate with other agents of the system. Embedded systems and agents make so-called Cyber-Physical Systems (CPS) from physical production systems, which can be linked and interacted via data networks. The data from I4.0 components (in general: devices, objects, items) are organized in so-called administration shells (ZVEI 2016), which represent the component virtually and thus represent the interface between the real component and the virtual I4.0 world. The administration shell is an information package stored in a repository (e.g. cloud) and is linked to the item via unique ID. The information package contains all the relevant data of the object collected and updated over the complete life cycle of a product. This is the time of obsolete manuals or faulty replacement parts, if the information is always ­up-to-date in the required language. All states and services are standardized for Industry 4.0 and are supported via ­I4.0-compliant semantics. Information can be exchanged via I4.0-compliant communication. Devices are referred to as assets in Industry 4.0 and may comprise organic and inorganic objects. Not only machines and components but also factories are an object (Internet of Things), have an administrative shell, and are accessible for identification via ID. Also, a person is a device, has an administration shell (with e.g. personnel data, certificates deposited, information about professional experiences) and can be addressed by ID. Identifiable items are e.g. via RFID chip. Smart devices can be processed in a smart factory, which, by means of embedded systems, can communicate with machines, components and other systems via radio technology (information is located in the administration shell). For example, configuration data can be stored on a component, so that the commissioning of a machine is faster and manual configuration steps are no longer necessary. Another example would be that wear data can be collected in order to trigger a service in the case of tolerance deviations and to reveal hitherto unknown error causes in a statistical evaluation (Big Data Analytics). The Cyber-Physical Systems in administration and production are linked vertically within companies via business processes and distributed horizontally, linked in ­real-time controllable value-added networks—from the order to the output logistics (Acatech 2013, p. 89 ff.).

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Description of Vertical Digitization

• Integration of the IT systems on the different hierarchical levels of a company (e.g., planning, control, production) • Digital modeling of production • Agent structures in a smart factory allow a variable and automatically configurable production structure • Freely configurable products determine the production process using ­information-based configuration rules • Production lines are thus no longer rigid, but can be dynamically retrofitted, therefore they are enabling a high-level variant production as well as rapid conversion (e.g. in case of system failures or logistical bottlenecks)

Description of Horizontal Digitization

• Integration of different IT systems along enterprise boundaries (value creation networks) • Digital consistency of engineering over the entire product life cycle • Engineering information is dynamically carried over the entire product life cycle (for example, always current maintenance plans and plant documentation via the management boards) • Case study “predictive maintenance”: – The status data of all machine components are continuously recorded and collected via the embedded system (condition monitoring) – Deviations from the tolerance give indications about possible machine errors and the maintenance can be planned in advance – In a service portal, the central monitoring is performed – From here, actions are automatically triggered (e.g.: order of suitable spare parts and necessary tools via the merchandise management, search and booking of experienced specialists via the Skill and Workforce Management database, coordinated ordering of all assets at a specific date)

With Industry 4.0, technical communication is thus gaining a new understanding (see Fig. 5.1). Technical information is not only needed for self-made goods and services, but also for your own smart factory. And users of technical information are no longer just people, but people and machines (Schaffner 2017b).

5  Industry 4.0—Flexibility of Technical …

43

Technical Communication (advanced understanding) Technical Communication

Technical Documentation Dokumentation documentation for products (goods, services) in need of explanation

• product-related • few media • unidirectional

supply of information all persons involved in the manufacture or modification of a product

Industry 4.0

intelligent information for „smart applications“ in Factory 4.0, where humans and machines can be users • value chain • machine readability • ECO system

• company-wide • media plurality • multidirectional

for produced goods and services

for own factory

Fig. 5.1  Advanced understanding of technical communication. (Source Schaffner 2017b)

5.3 Technical Communication in Industry 4.0 Today’s technical documents are addressed to people who evaluate this technical information, link it with personal experiences, draw conclusions and assess the success of action results in advance. Within the concept of Industry 4.0, these cognitive processes must now be codified in the business processes. We speak of “intelligent information” when behavior-controlling systems (such as humans, but also an I4.0 component) are supported in their decision-making by cognitive-structured information. This assumes that data is structured and interpreted using metadata. In addition, the action context (knowledge domain) must be represented by a semantic model (ontology). In the future, an I4.0 device from an operating, maintenance or malfunction situation will formulate the need for a—and indeed the latest—technical information. Technical communication is therefore intrinsically stimulated (from the situation). On the other hand, today’s service literature is anticipated by the technical editor for certain action scenarios and is therefore stimulated extrinsically (from the outside) (see Fig. 5.2). Technical product literature is now written in a user-oriented manner. In the future, information fragments will be compiled in a user-centric manner (Schaffner 2017c, p. 119). Only a specific demand (request) triggers the compilation of technical information, for example, a maintenance manual, which is then dynamically generated and provided on the basis of most recent data (delivery). In technical communication 4.0, these semantic relationships between knowledge topics (e.g. situation, instruction, tool, spare part, operator’s qualification etc.) have to

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extrinsic stimulated technical writers (engineers) analyzing realistic situations of action and writing suitable instructions (service documentation) (static documents: usually based on status of delivery, BOM as delivered)

Information 3.0

intrinsic stimulated as a coming out from the situation, a dynamic, individual and context-sensitive representation of information from different sources is requested (dynamic information: based on BOM as built, live and wear data)

Information 4.0

from user-oriented manner

to user-centric manner

Not the „product“ of the service is in focus

but the effect and benefits of the „product“.

„documentation“ is valuable

„information“ solves a problem

Fig. 5.2  Paradigm change in creation of technical literature. (Source Schaffner 2017b)

be modeled. It is also necessary to ensure that the most up-to-date information (e.g. the latest piece of material, the latest maintenance information, wear data, etc.) is provided in the administration shells of all the assets involved in the action context (people, machines, components, tools, spare parts, etc.). The shift of cognition into the business processes leads to a greater understanding in the knowledge work of the technical editors. Today’s service literature spreads in particular situational knowledge (correct classification and interpretation of the application context, for example operation, maintenance, and disturbance) and conceptual knowledge (factual knowledge about what is to be done in a specific situation, for example, a machine downturn). The cognitive abilities of the operator or the service technician are used to map the procedural knowledge (knowledge extension and individual learning curves) and the strategic knowledge (problem solving strategies for problems for which there are no general solution strategies, such as previously unknown disturbances or solution procedures) (see Fig. 5.3). In today’s information management, flexibility is thus ensured by human beings. Within Industry 4.0, this must be done via “intelligent information”. The fact that the information in the administration shell is continually expanded and updated during the product life-cycle, is a necessary but not sufficient operation. In the future, technical editors will have to penetrate the complex logical relationships of components, model them and maintain them continuously along the product life (Schaffner 2019).

Infonomics in technical communication 4.0

Infonomics in technical communication 3.0

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knowledge class

definition

description

situational knowledge

knowledge of typical, domainspecific situations

correct classification and interpretation of the application context (e. g. operation, maintenance, jam-up)

conceptual knowledge

static knowledge about facts, concepts and principles

facts about what is to be done in a specific situation

procedural knowledge

acquired through practice

extension of factual knowledge through experience (learning curves)

strategic knowledge

metacognitive knowledge about an optimal structuring of the problem-solving behavior

problem-solving strategies for problems for which there are no general solution strategies

Fig. 5.3  Knowledge as a process of convenient interconnection of information. (Source Based on Lehner 2015, p. 58 ff.)

The editors in a technical communication 4.0 are, therefore, less guided by expert editorial questions, but rather by questions of industry-conception such as: • Which sensor values, status messages, assistance data (for example, linked components) etc. can be unambiguously identified? (situational knowledge) • How can the relationships with all relevant resources (spare parts, tools, technicians, linked components, etc.) be clearly identified? (conceptual knowledge) • What are the prerequisites for creating a digital CV for objects? (procedural knowledge) • Which data is still hidden (dark data), but essential for the identification of hitherto unknown errors, errors or problem-solving strategies (for example using Big Data Analysis)? (strategic knowledge) For industrial communication, Industry 4.0 offers an opportunity for strategic positioning within the company. Knowledge management will thus become a new task for technical editors (Schaffner 2011).

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References Acatech (2013). Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0 – Abschlussbericht des Arbeitskreises Industrie 4.0. Frankfurt a. M.: Plattform Industrie 4.0. Lehner, F. (2015). Wissensmanagement – Grundlagen, Methoden und technische Unterstützung (5th ed.). München: Hanser. Schaffner, M. (2011). Change-Management – erfolgreiche Projektarbeit in der Technischen Dokumentation: Wissensmanagement – Veränderungen gestalten. tekom Frühjahrstagung, 15.04.2011, Potsdam. Schaffner, M. (2017a). Flexibility of Infonomics in the Industrial Production of Machines and Plants—Knowledge Management in the Industry 4.0. BMBF-Projekt DigiTrans CD, Shandong Agricultural University, 26.02.2017, Taian (China). Schaffner, M. (2017b). Technische Kommunikation in der Industrie 4.0 – Forderung nach einer Flexibilisierung der Informationswirtschaft. Regionalkonferenz „Technische Redaktion im Umfeld von Industrie 4.0“, tekom RG Bodenseeraum und Alb-Donau und tecom Schweiz, 28.06.2017, Konstanz. Schaffner, M. (2017c). Industrie 4.0 als Motor für „intelligente Information“. In J. Hennig & M. Tjarks-Sobhani (Eds.), Intelligente Information; tekom-Schriften zur Technischen Kommunikation (Vol. 22). Lübeck: Schmidt-Römhild. Schaffner, M. (2019). Industrie 4.0 – Technische Redakteure werden zu Semantik-modellierern. In B. Hermeier, T. Heupel, & S. Fichtner-Rosada (Eds.), Arbeitswelten der Zukunft – Wie die Digitalisierung unsere Arbeitsplätze und Arbeitsweisen verändert (pp. 107–129). Wiesbaden: Springer Gabler. Warnecke, H.-J. (Ed.). (1995). Aufbruch zum Fraktalen Unternehmen: Praxisbeispiele für neues Denken und Handeln. Berlin: Springer. ZVEI. (2016). Beispiele zur Verwaltungsschale der Industrie 4.0-Komponente (Whitepaper). Frankfurt a. M.: Zentralverband Elektrotechnik und Elektronikindustrie e. V.

Part II Made in China 2025

6

How Industry 4.0 Inspires Chinese Automotive Companies in the Context of Made in China 2025 Thomas Heupel and Zhang Congying

Contents 6.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 6.2 Comparison Between Made in China 2025 and Industry 4.0 . . . . . . . . . . . . . . . . . . . . . . . 50 6.3 Automotive Industry in Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 6.3.1 Significance of Automotive Industry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 6.3.2 SWOT-Analysis for the German Automotive Industry . . . . . . . . . . . . . . . . . . . . . . 53 6.4 Automotive Industry in China. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 6.5 Case Studies of German and Chinese Automotive Companies. . . . . . . . . . . . . . . . . . . . . . 58 6.5.1 Volkswagen AG. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 6.5.2 Zhejiang Geely Holding Group. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 6.5.3 SAIC Motor Corporation Limited. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 6.6 Comparison of the Cases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 6.7 Inspiration for Chinese Automotive Companies—10 Recommendations. . . . . . . . . . . . . . 67 6.8 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Abstract

This chapter investigates digitalization as a significant economical trend within the manufacturing industry and the automotive industry in particular, whilst examining and contrasting Germany’s Industry 4.0 and China’s Made in China 2025 strategy. The chapter is specifically dedicated to the discussion of how and to what extent

T. Heupel (*) · C. Zhang  FOM University of Applied Sciences, Essen, Germany e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_6

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Industry 4.0 might function as a particular point of reference for the development of the Chinese automotive industry.

6.1 Introduction Digitalization, as one of the most significant trends in the economy of the 21st century, is changing the daily lives of people as well as businesses in all sectors of the economy. The fourth Industrial Revolution refers to a fusion of emerging technology breakthroughs in many fields such as the Internet of Things (IoT), robotics, 3D-printing and intelligent car manufacturing based on full interconnection and interaction (cf. Schwab 2016, p. 12). In this context, many countries introduced new policies and strategies to accelerate the transformation and upgrading of their manufacturing industry, for example, the “Industrial Internet” in the United States, the “Robot Revolution” in Japan, the Industry 4.0 in Germany and the Made in China 2025 in China (cf. Zhang 2017a, p. 50). Compared to Germany, China is perceived as “The World’s Factory” with its ­labor-intensive mass production. Although it was the largest automobile manufacturing country worldwide with a total of approximately 28 million manufactured vehicles in 2016, China is still situated at the end of the value chain including low profitability (cf. Statista (ed.) 2018d, online). In order to launch an industrial transformation from ­labor-intensive production to knowledge-intensive production and increase the profitability for the whole manufacturing industry, the Chinese government published the Made in China 2025 plan in 2015 (cf. State Council of the People’s Republic of China 2015, online). It is referred to as the Chinese version of German Industry 4.0 because of its similar high-tech strategy and core. Nevertheless, the Chinese Made in China 2025 plan is significantly different from the German Industry 4.0 in many aspects such as their widely divergent backgrounds. Consequently, one might ask to what extent Chinese automotive companies can learn from the German automotive industry. For a better understanding of the German and Chinese automotive industry, this article introduces three different automotive manufacturing companies: a German auto manufacturer (Volkswagen), a privately owned Chinese auto manufacturer (Geely) and a state-owned Chinese auto manufacturer (SAIC). However, through these three specific cases, this paper is not aimed to give a particular solution for a specific problem, but rather to understand the trends for the whole Chinese automotive industry in the changing environment. This article thereby figures out possible adaptive approaches for Chinese automotive companies.

6.2 Comparison Between Made in China 2025 and Industry 4.0 The term Industry 4.0 represents an abrupt and radical change. So far we have experienced three industrial revolutions. The first industrial revolution began in the late 18th century with the invention of the steam engine. It is characterized by mechanization,

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i. e. the replacement of muscle power by hydropower and steam energy (cf. Obermaier 2017, p. 3). The second industrial revolution, which started in the early 20th century, triggered by electricity and the construction of the assembly line, ushered in the age of mass production. The third industrial revolution, which lasted from the late 20th century to the 21st, is usually called the “computer or digital revolution” as it was catalyzed by the development of semiconductors, mainframe computing (1960s), personal computing (1970s and 1980s) and the internet (1990s). The ongoing fourth industrial revolution is based on the previous digital revolution. Different from the digital technologies of the third industrial revolution, the advanced technologies in the fourth industrial revolution are more sophisticated and integrated (cf. Schwab 2016, pp. 11–12). The Internet of Things is possible to be realized with ubiquitous sensors and mobile internet. Therefore, the term Industry 4.0 is understood to be digitalization and networking of industrial infrastructure, including machinery, materials, people, products, and factories, using the emerging digital breakthroughs (cf. Ludwig et al. 2016, p. 73). However, Industry 4.0 was originally derived from a national strategic initiative by the German government in 2012, which is identified as part of the German government’s High Tech 2020 Strategy. Its aim is to enable German industry to be prepared for the fourth industrial age and to consolidate their position as a leader in mechanical engineering by driving smart manufacturing and production forward (cf. BMBF 2012, p. 24). During the government consultation in October 2014, the German and Chinese government agreed on a framework for Sino-German cooperation with a particular focus on Industry 4.0, to further intensify long-term strategic partnership (cf. BMWi 2014, online). This action also illustrates that Industry 4.0 has a profound strategic and historical significance. China has become “the workshop of the world” and the world’s export engine, while Germany has managed to maintain Europe’s industrial powerhouse and technological power status. To enable China to reinvent itself from a world manufacturing workshop into a world-class industrial power with the high level of technology, the Chinese government published the Made in China 2025 plan in 2015. According to the State Council document, “Made-in-China 2025” is the first decade of a ­“three-phases” grand plan, which outlines plans to comprehensively upgrade Chinese industry and enable China to occupy the highest parts of global production chains (cf. State Council of the People’s Republic of China 2015, online). Drawing direct inspiration from Germany’s Industry 4.0 plan, Made in China 2025 has always been parallelized with Germany’s Industry 4.0 strategy by researchers. The most striking common ground is that both of them attach great importance to the manufacturing industry. The manufacturing industry has been one of the critical drivers of a country’s economy since the beginning of industrial civilization after the first industrial revolution. Germany is an industrial nation, with a substantial production share. The statistics of the World Bank show that the manufacturing industry takes up around 27% of Germany’s gross domestic product (GDP) across economic sectors from 2007 to 2017 (cf. Statista 2017, p. 9). Thus, it has become the most important in Germany after the service sector. Compared to other EU-countries, but also to the US, this share is unusually high. It is

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also cited as one of the reasons why Germany, unlike other countries, has overcome the economic crisis of 2009 very quickly (cf. Huber 2016, p. 2). Among the whole manufacturing industry, the automotive industry is of considerable importance to Germany. Total revenue generated by German automobile manufacturers in 2016 amounted to 464.69 billion euros, and the automotive industry accounted for about 20% of the GDP in Germany (cf. Statista (ed.) 2018a, p. 13). As a result, the automotive industry is regarded as a critical focus area in the future project Industry 4.0. In the same way, China emphasizes manufacturing as well as the automotive industry in her industrial masterplan Made in China 2025. With a GDP of 11937.56 billion US$, China is the second largest economy following after the United States and obtains increasing importance in the world. According to IMF, it is also estimated that China will replace the United States at the top in 2030 (cf. International Monetary Fund (BMF) 2018, online). The Made-in-China products range from high-tech goods such as computers and mobile phones to consumer goods such as air conditioners. It is reported that China produced and/or assembled more than 80% of the world’s computers, 90% of mobile phones, 80% of air-conditioners, and 28% of vehicles (cf. European Chamber (ed.) 2017, p. 2). However, large manufacturing production amount and GDP are not able to the sole standards to measure a country’s economic success. Although China is well-known as the workshop of the world and is famous for its “Made in China” products, China’s manufacturing industry is big, but not strong. China therefore seeks to use “intelligent manufacturing” to turn the country from the world’s factory into a leading manufacturing power over the coming decades (cf. State Council of the People’s Republic of China (ed.) 2015, online).

6.3 Automotive Industry in Germany 6.3.1 Significance of Automotive Industry Germany’s automotive industry dates back to the 19th century and is now in a high reputation worldwide. It is the largest industry sector with a cumulated turnover of 404 billion Euros—around one-fifth of total industrial revenue in Germany (cf. GTAI 2017, p. 3). It has been one of the largest employers in the industrial sector over the last few years, with a workforce of around 819.996 in 2017, a continuous increase from the nadir (701.585) since the global economic crisis in 2009. A particularly remarkable aspect is that the total number of employees accounts for up to 1.5 million when the indirect employees in upstream or downstream industries are taken into consideration (cf. Bormann et al. 2018, p. 9). The German automotive industry stands for over 63% of Germany’s exports since 2010 (cf. Statista 2018a, p. 23). Thus, it is clear from these data that the automotive industry plays a distinctive role for prosperity and employment in Germany.

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6.3.2 SWOT-Analysis for the German Automotive Industry Strengths:  Germany is regarded as “the world’s automotive innovation hub.” (GTAI 2017, p. 2). “Made in Germany” automobiles are considered as a coalition of top design, advanced technology as well as high functionality and quality. These valuable qualities make German autos dominate the upper end of the auto market. “Made in Germany” and “German Engines” are always considered as the basis for the worldwide success of German OEMs. The three group companies, Volkswagen, Daimler, and BMW, are the largest auto manufacturers in Germany and own the most popular brands that include BMW, Volkswagen, Mercedes-Benz, and Audi (cf. Wagner 2015, p. 1). As you can see, most of them are the top of the line luxury cars of high prestige for their precision and craftsmanship. Besides the world-class OEMs, there are also world leading tier suppliers like Robert Bosch, Continental, and ZF Friedrichshafen, to ensure the top-class performances of German automobiles (cf. GTAI 2017, pp. 8–9). The worldwide reputation of German automobiles benefits primarily from the high Research and Development (R&D) investment. According to Germany Trade & Invest (GTAI), one-third of global R&D expenditure in the automotive industry is spent by German OEMs. In terms of R&D expenditure in the automotive industry, Germany ranks first among the large automotive manufacturing countries, with a total amount of around 39 billion Euro. This means that in effect Germany even beats its main competitors, which is the United States and Japan. It is worth noting that 40% of the R&D budget was spent in Germany instead of in overseas locations while 60% of the automobile production occurs abroad (Cf. Bormann et al. 2018, p. 9). In this way, Germany managed to keep the advanced technologies and patents at home. Weaknesses:  The automotive industry is now undergoing a rapid transformation. However, the problems of German industry appear in the fast-changing environment. As an old industrial country, Germany has developed its traditional auto industry with the fossil fuel combustion engines. Historically speaking, the conventional automotive culture, which represents the traditional internal combustion engines, the private ownership of autos and driving by human drivers, has been formed for almost 100 years since the first industrial revolution. The obsolete usage of automotive culture remains firmly rooted in this country. It can be a hindrance for it to promote the transformation. The formula—“product competence, plus production competence, plus high-quality standardized mass production” has supported the German automotive industry for a long time (Bormann et al. 2018, p. 21). Thus, a purely product-technological innovation approach was designed to meet the new demands within the given structures and requirements. However, compared to the emerging new automotive culture and its new business models, this approach is not scientific in this age of digitalization and transformation. Conventional notions need to be changed on a deeper level. The other problem is that the reputation of German automotive industry, and even the core brand “Made in Germany”, has been badly tarnished by a destructive scandal over the past Volkswagen’s diesel

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emissions and the present antitrust issues. Germany’s “Spiegel” magazine reported that Volkswagen, Daimler, and BMW had been colluding illegally on price-fixing, technology, and even the emissions, for decades (cf. Dohmen and Hawranek 2017, online). The successive exposure of scandals reveals the potential problems in the enterprise operation and management. Meanwhile, growing awareness of the harmful effects of ­diesel-powered cars has led the diesel-engine under sharp criticism (cf. Bormann et al. 2018, p. 5). In this context, it is necessary to restructure the automotive industry. Opportunities:  Germany is the largest automotive market in Europe, with total sales of 3.8 million in 2017 (cf. OICA 2018, online). Moreover, Germany has overtaken Norway as Europe’s biggest market for electric cars. According to the European Automobile Manufacturers’ Association (ACEA), sales of electric automobiles has surged 70% in the first quarter in 2018 (cf. Palazzo et al. 2018). Besides, German cars are competitive in the international market. Around 79% of German cars are exported to various countries all over the world (Cf. GTAI 2017, p. 3). All these data indicate the great growth potential of the German automotive industry. In the meantime, the national and government policies provide strong backup and reliable support to its pillar industry. On the one hand, the German government has already realized the significance of sustainability and adopted the government program “Electromobility” in 2011 so that Germany can play a pioneering role in the development of promising technologies in new energy automobiles field (cf. BMWi 2011, online). Furthermore, sustainable mobility has been set as one of the future projects in the “Hightech-Strategie 2020”. Its central aim is to look out for solutions for innovative, ecological and sustainable mobility. It covers many areas, ranging from vehicle concepts, traditional energy and driving-technologies to the whole transport system as such. The change in social mobility behavior is also inclusive. On the other hand, the heavy investment into industry 4.0 technologies has created great potential for German conventional auto industry. The German OEMs can use the advanced technologies to retool their assembly lines and build the smart factory. Threats:  Data from the World Bank shows that in 2017 54.74% of the population worldwide live in urban areas (cf. The World Bank Group 2014, online). For the automotive industry, this circumstance is problematic due to insufficient available space in densely populated urban areas. Additionally, consumers begin to reject to pay for the conventional vehicles because of its harmful effects on the environment. Instead of standardization, they are pursuing individual characters of the products. The mass production with technical orientation does no longer meet the current requirements and urgently needs to be combined with customization (cf. Ebel et al. 2004, pp. 4–5). Along with the exponential development of digital networking, new business models within the digital platform economy have been formed (cf. Bormann et al. 2018, p. 11). Nowadays, consumers attach more importance to the utilization of the vehicles instead of the ownership. Confronted with these megatrends, the auto manufacturers are required to develop more flexible and useful products and services to satisfy the increasing customer demands.

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The new automotive culture, which includes new energy autos, autonomous driving, and automobile usage concepts, is forming eventually. There is no future for the pure production of automobiles. Not only are the automakers in severe industrial competition, but they are also facing the challenges of non-industry players. As can be noticed, US Californian and Chinese IT companies, such as Didi Chuxing and Uber, have been crossing industry boundaries over the past years (cf. Bormann et al. 2018, p. 20). They are attacking the established automotive industry with new ideas for driving and using automobiles in a direct, visionary, well-financed, and aggressive manner, based on digital capability. In this context, the German automotive industry needs to set itself free from its established structure and must figure out a new way. Figure 6.1 concisely illustrates the key aspects of the SWOT-Analysis of the German automotive industry.

6.4 Automotive Industry in China Made in China 2025 has proposed clear and specific requirements for the automobile industry. On the one hand, it is forced to promote the industrial restructuring and upgrading of conventional vehicles industry and to promote intelligent manufacturing. On the other hand, it is necessary to develop energy saving, new energy vehicles and intelligent connected vehicles (ICVs). In addition, Made in China 2025 calls for increased efforts in the area of energy conservation and emission reduction of traditional internal combustion engine vehicles (ICEVs). The core idea is to build a globally competitive automotive industry by integration of low-carbon, digitalization, and automation (cf. CATARC and CAAM 2016, pp. 15–16). The automotive industry is one of 10 key sectors in Made in China 2025. It makes a significant contribution to the Chinese national economy. China’s share in global vehicle production has continually increased from 13.15% to 29.82% over the past ten years (cf. Statista 2018b, p. 13). According to the China Association of Automobile Manufacturers (CAAM), the retail trade revenue generated by the national Strengths • innovation hub worldwide • top brands • largest producer in EU

Opportunities • largest market • policy support • digitalization

Weaknesses • conventional automotive culture • reputation damage German automotive industry

Threats

• new requests from megatrends • squeezed by USA and China • increasing labor cost

Fig. 6.1  SWOT-analysis of the German automotive industry

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automobile industry in 2015 amounted to 27.32 trillion yuan, which has increased 70.2% compared with the revenue in 2010. The average annual growth rate during the 12th Five-Year-Plan period (2011–2015) was 11.2%. The tax revenue in the automotive industry accounted for over 9% of the total national tax revenue (cf. CATARC and CAAM 2016, pp. 12–13). These data all indicate that the automotive industry occupies a vital position in the national economy. SWOT-Analysis for Chinese Automotive Industry Strengths:  The automotive industry is a pillar industry that not only concerns a country’s economy but also affects people’s livelihood. It is one of the most significant drivers to stimulate employment in China. The Annual Report on The Development of China Automotive Industry (2018) shows that the number of employed people in the ­automobile-related industries has exceeded 1/6 of the total number of social employment. Additional employment in automobile production can increase the employment of 10 related personnel (cf. Lin 2018, online). The Chinese automotive industry has grown exponentially regarding production. Data shows that annual output has trebled in the past decade, from 9.5 million in 2008 to 27.5 million in 2017 (cf. Statista 2018b, p. 19). China is now the largest automobile manufacturing country, producing 29.82% of automobiles worldwide. Comparatively, China produced more than 27.5 million vehicles in 2017, the equivalent of the total amount of the other three leading car manufacturing countries: the United States (12 million), Japan (9.5 million) and Germany (6 million) (cf. Statista 2018d, online). Weaknesses:  A great majority of the key components need to be imported from countries like Germany, the United States, and Japan. According to CAAM, the automotive components imports in 2015 reached 336.76 billion dollars. The demand for the key components including starter motors, automatic transmissions is increasing continually (cf. CATARC and CAAM 2016, p. 207). Some large groups have relied too much on their joint-venture technology. Foreign auto parts enterprises have already moved their production to China, but the corresponding intellectual property rights and talents of key components are still controlled by themselves. In a way one might assume that China will remain mostly an assembly workshop for auto powers and world auto giants if it cannot master core technology and improve innovation ability. Although Chinese automotive brands such as Geely, Great Wall, and BYD have experienced remarkable growth in the domestic market and have achieved a market share of 43.24% in 2016, they remain largely unknown outside the country. In addition, the quality gap between Chinese domestic auto brands and international brands still exists, which was 13 PP (problems per 100 vehicles) in 2017. Among the eight problem categories, the gap in engine and transmission was the biggest with 5.8 PP100 (cf. J.D. Power 2017, online). Among the self-owned brand automobile enterprises, the enterprises that produce the

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whole vehicles are far stronger than components enterprises. At present, the Chinese automakers still mainly reply on foreign components suppliers (cf. Lin et al. 2018, p. 51). To build the internationally renowned brands, Chinese domestic automakers still have a long way to go. Opportunities:  One of the biggest opportunities for Chinese automotive industry is that China has outstripped the United States and become the world’s largest vehicle market in 2010 and has remained the largest ever since. In 2017, automakers sold 24.72 million passenger vehicles and 4.16 million commercial vehicles in China, up 3.1% from 2016. The number of passenger cars sold in China is estimated to reach 27.6 million (cf. Statista 2018c, p. 9). Meanwhile, the motor vehicles per 1000 people in China in 2014 was accounted to only 83, far below those in other countries such as 797 in the United States and 572 in Germany (cf. NationMaster 2014, online). Along with the rapid and steady growth of the Chinese economy and accelerated process of urbanization in China, the demand for automobiles is likely to keep growing in a relatively long period. The low penetration rate in China provides the great market potential for the future, while the car markets in developing countries have been saturated for years (cf. Ebel et al. 2004, pp. 15–16). Moreover, the Chinese government has introduced a series of policies and measures to promote the automotive industry in China. These policies cover a large industrial chain centered on new or used automobiles, including maintenance, fittings, remodeling, beauty, finance, insurance, leasing, automobile culture, and scrap recycling (cf. CATARC and CAAM 2016, pp. 75–99). For example, “the Measures for the Administration of Automobile Sales” adopted in 2017 by the Ministry of Commerce, aims to maintain the fair and impartial market order and to promote the sound development of the automobile market in China (cf. Ministry of Commerce of the People’s Republic of China 2017, online). Made in China 2025, combined with the era background of the fourth industrial revolution, can be a guideline to promote the upgrading of the whole automotive industry. Threats:  China’s automotive industry faces a series of problems such as the disappearance of demographic dividends, rising manufacturing costs, and the loss of resource advantages (cf. Lin et al. 2018, p. 49). The labor cost in China is predicted to rise the fastest to 6.5 US$ per hour in five years, more than double of the labor cost in Vietnam (cf. Statista 2018e, online). The labor-intensive manufacturing western companies are always seeking lower-cost production locations. As a study by Deloitte shows, built on the global cost competitiveness, the “Mighty 5”—Malaysia, India, Thailand, Indonesia, and Vietnam—are turning to be the emerging manufacturing power as China used to be (cf. Deloitte 2016, p. 15). Figure 6.2 concisely illustrates the key aspects of the SWOT-Analysis of the Chinese automotive industry.

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Weaknesses

• largest producer • development of new energy vehicles Opportunities • largest market • policy support

Chinese automotive industry

• lack of core technologies • lack of top-brands • import of core automobile components Threats • increasing labor cost • squeezed by manufacturing power & emerging producer

Fig. 6.2  SWOT-analysis of the chinese automotive industry

6.5 Case Studies of German and Chinese Automotive Companies 6.5.1 Volkswagen AG The Volkswagen Group (VW), originally founded by the German government in 1937, is now one of the world’s leading automobile manufacturers and the largest automaker in Europe. With its headquarters in Wolfsburg, the VW Group has established its own global production and sales network. The Group operates 122 production plants and sells its automobiles in 153 countries throughout the world (cf. Volkswagen AG 2018c, online). It set a new sales record of 10.74 million vehicles in 2017, which surpassed Renault-Nissan-Mitsubishi and Toyota to become the largest carmaker worldwide (cf. Volkswagen AG 2017, p. 22). Strategy:  With the grand vision to be “a globally leading provider of sustainable ­mobility,” the VW Group is launching its future program “TOGETHER-Strategy 2025” (Volkswagen AG 2018e, online). This strategy stresses the collaboration and solidarity across the entire value chain. The mission of “TOGETHER 2025” is to achieve sustainable growth by the synergy of four target dimensions: Excited customers, excellent employers, role model for the environment, safety and integrity as well as competitive profitability (cf. ibidem). It is a sensible strategy that complies with the trend of digitalization, individualization, and sustainability. “TOGETHER 2025” consists of four key building blocks and each block comprises its own group initiatives, as can be seen in Fig. 6.3. Most striking is that three of these key building blocks are directly and closely linked with the increasing digitalization: Transform core business, build mobility solutions business and strengthen innovation power. The secure funding is aimed to make VW effectively use all conceivable advantages, especially the capital advantage, so that it can achieve to be a final sound leading mobility provider (cf. Volkswagen AG 2018d, online).

Fig. 6.3  Group initiatives—overview. (Source Volkswagen AG 2018d)

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The block “strengthen innovation” is paving the way to usher a digital transformation at VW and further to push the transformation of core business and expansion to mobility service—the other two key blocks of “TOGETHER 2025”. Implementation in Practice: VW is planning to drive the digital transformation in two dimensions simultaneously: the transformation of existing core business, and the development of new mobility solutions business. The core business comprises the R&D, production, and sales of both conventional and new energy vehicles, especially electric vehicles. Correspondingly, the new mobility solutions business refers to mobility services such as car-sharing service and ride-hailing service (cf. Volkswagen AG 2018e, online). Thus, an important question arises: how can the VW Group leverage the power of industry 4.0 to accelerate the change in these two areas? • The Smart Factory (SF): VW has been using digital manufacturing solutions based on Tecnomatix from Siemens for more than ten years. Above all, they are applicated in assembly planning and validation, as well as the stamping shop and plant planning and optimization. Another area of application is logistics planning (including packaging). • Radio Frequency Identification (RFID) makes it possible to identify and track the tags of objects in real-time through the electromagnetic wave (cf. Baltes 2015, p. 54). VW launched the program “Transparent Prototype” to track and trace test vehicles and prototype parts via RFID in 2011. It is currently the largest cross-company RFID project in the automotive industry. Therefore, VW cooperates with more than 280 suppliers who offer the prototype components with radio chips. In addition, VW implements RFID technology in the body construction, paint shop and internal shipping to identify the parts and products. • Like many other manufacturers, VW uses sensitive robots to enhance the level of automation in the production plant. Besides, the employees can be released from an unfavorable work position such as high-temperature operation and aerial work. Also, the high work accuracy can be guaranteed, and a cost reduction would be possible (cf. Huber 2016, p. 162). • 3D-Printers are also special kinds of industrial robots, which can add materials layer after layer successively and build them into a three-dimensional object according to the computer-aided design (CAD) model (cf. ibidem, p. 32). The VW Group has introduced 3D-printers at 26 different production locations over the world. 3D-Printing has already revolutionized the production of prototypes and changed the spare parts management in a significant way. • The intelligent assistance systems based on Augmented Reality (AR) and Virtual Reality (VR) are playing a growing role in Smart Factory. While VR is utterly ­computer-generated within a simulated environment, AR describes the visual overlay of the real world with additional virtual information and is regarded as an interface between the real and digital world. Data-glasses are a typical application of AR technology (cf. ibidem, p. 160).

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• VW is currently focusing not exclusively on e-mobility—including ordinary hybrid, pure electric and plug-in hybrids—but on high-efficiency and environmentally friendly diesel, gasoline and natural gas engines. VW is now able to produce synthetic natural gas from sustainable sources, for example, convert wind power into synthetic methane in Audi plant (cf. Volkswagen AG 2018b, pp. 8–9). VW launched the “Roadmap E” project to accelerate the electrification in 2017. By 2025, about a quarter of the group’s new cars will be pure electric vehicles (EVs). • Concerning the ICVs, VW’s Car-Net App-Connect has already been available on all car models produced since 2017, including Passat, Tiguan, Jetta, Golf Sportwagen, etc. App-Connect is now compatible with Apple CarPlay, MirrorLink, and Android Auto platforms. It transforms the car into a smart mobile travel space that integrates entertainment, communication, navigation and other functions. In 2016, VW cooperated with DoorBird and realized the interconnection between the car and the user’s house. • VW also established a new mobility services company MOIA in December 2016. It focuses on intelligent on-demand mobility services such as App-based ride-hailing and ride-pooling services. MOIA began to offer its mobile service in 2017 and plans to extend its business in other cities from 2018 successively. Besides, MOIA is trying to figure out future mobility business models such as the on-demand operation of driverless cars (cf. Volkswagen AG 2018a, online).

6.5.2 Zhejiang Geely Holding Group The Zhejiang Geely Holding Group (ZGH or Geely), based in Hangzhou in south-east China’s Zhejiang province, was the first Chinese privately owned auto manufacturer. It was originally established in 1986 and entered the automotive industry in 1997. Just like many other Chinese companies, ZGH has achieved an impressive elevation through cross-border mergers and acquisitions. In 2010, it completed the acquisition of the entire share capital of Volvo Car Corporation from Ford Motor (cf. ZGH Group 2018, online). Recently, ZGH has acquired 9.69% of Daimler with 9 billion dollars, which means it has become the largest shareholder of the Daimler Group (cf. Daimler AG 2018, p. 15). The acquisitions make synergy effects of technology and brand possible. In this way, ZGH consists of both, the Chinese independent brands, and well-known international automotive brands. Over the past two decades, the group has experienced rapid growth and has ranked on the Fortune Global 500 list for seven consecutive years. Strategy:  Compared to VW, Geely has not come up with a systematic strategy against the digitalization trend. Nevertheless, Mr. Ding Guoxiang, the Chief Information Officer (CIO), raised the digitalization concept of Geely Group at the Computing Conference in 2017. Geely is promoting its digital transformation in an all-around-way including manufacturing, marketing, and R&D. Besides, Geely will take full advantage of

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digitalization to support business operations, enterprise innovation and business transformation. In addition, Geely considers that the digitalization of a company cannot be carried out only within the company, but rather in the whole society. Therefore, Geely is seeking the collaboration opportunities with advanced IT-companies such as Alibaba so that it can make use of the existing resources to realize its transformation smoothly (cf. Ding 2017, pp. 24–26). With the awareness of digitalization and sustainability trend, Geely has announced the “Blue Geely Initiative” in 2015 and “20200 Strategy” in 2016. The core idea of them is to concentrate entirely on new energy vehicles (NEVs) market and make Geely a market leader in this field. The “Blue Geely Initiative” aims at overhauling the Group’s entire product portfolio with the mass introduction of NEVs including pure electric, hybrid electric and plug-in hybrid vehicles (cf. Geely Auto Group 2015, online). The objective of “20200 Strategy” is to bring 30 NEV models to market and sell 2.000.000 vehicles by 2020 (cf. ZGH Group 2016, online). Moreover, Geely addresses the significance of brand strategy based on the current needs of customers and emerging technologies. The iNTEC technologies consist of five core modules: Efficient Powertrain (G-Power), Humanistic Safety (G-Safety), Autonomous Drive (G-Pilot), Health Ecological Interior-Environment (G-Blue), Intelligent Net-link (G-Netlink) (cf. ZGH Group 2017, p. 17). Implementation in Practice: Geely is unfolding the digital transformation in manufacturing, marketing, and R&D. In terms of manufacturing, Geely is engaged in digital assembly, process simulation, online simulation, and offline manufacturing through the establishment of a digital factory. • The simulation is based on the “Digital Twins (DTs)” technology designed by Siemens. Deloitte (2017) defines a digital twin as “an evolving digital profile of the historical and current behavior of a physical object or process that helps optimize business performance.” The real power of DTs is “the near-real-time comprehensive linkage between the digital and physical worlds.” (Deloitte 2017, p. 3). Since DTs can completely and truly represent the product and production process in the digital world, manufacturers can simulate, test and optimize in the virtual world before they do so in the physical world. The simulation technology is widely used in the Geely plant: verification in stamping shops or welding shop, painting simulation in painting shops, assembly and ergonomics verification in assembly shops. An example would be that after two years of exploration, the gap between the simulation results and actual results in Geely Digital Factory has been shortened to 3 mm, which means “what you see is what you get.” (cf. Zhang 2017b, online). • Furthermore, based on the 3D visualization of the entire plant, the gridding monitoring and management in Geely Digital Factory can be realized. Similar to Google Street View, a roaming system for the factory is formed by use of the AR and VR technology. In this way, the full range of activities made by machines, robots or workers is observable at any time. For example, the information of production drawings,

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production status, or process steps will be displayed only with one click on a certain button of corresponding production equipment. • Geely has built cross-industry cooperative relationships with Siemens, Alibaba, Baidu, and Intel to jointly explore an effective way to make better use of industrial Big Data. As for the marketing field, Geely utilizes the emerging information technology, including cloud computing, IoTs, and Big Data, to promote business innovation and transformation. In 2016, Geely began to build a new marketing IT system for the new vehicle models, which covers three core business modules—sales, after-sales and customer relationship management. Adopting Alibaba’s data technology concept, the entire system is fully built on Aliyun—the cloud platform of Alibaba. • R&D is another key area to promote the digitalization transformation. Today, R&D is one of the biggest drivers of digitalization. With four R&D centers located in China, England, and Sweden, Geely has created a global R&D network. Over 10.000 technology-focused engineers work together to ensure the Group’s technological ­ competitiveness (cf. Geely Auto Group 2018a, online). • Following its “Blue Geely Initiative” and “20200 Strategy”, Geely is dedicated to figuring out diversified new energy mobility solutions. On the one hand, Geely promotes the use of alternative clean fuels such as methanol. It builds a partnership with the Carbon Recycling International in Iceland—the world leader in producing renewable methanol technology—to make a joint effort in developing and promoting the 100% methanol fuel vehicles (cf. ZGH Group 2015, online). On the other hand, Geely is hastening the adoption of pure electric, hybrid and plug-in hybrid technologies. • Via V2X links vehicles, drivers or passengers, mobile devices, and infrastructure are connected with each other through cloud services and Big Data, forming a so-called Internet of Vehicles (IoV). This combines three essential technologies: vehicle connectivity, artificial intelligence and automatic driving. • As for the independent Chinese brand Geely Auto, the Group updated the model Bo Yue SUV with the new Geely Smart Ecosystem GKUI in 2018. GKUI is an open, shared and connected in-car user interface platform that aims to change the car into a comfortable and intelligent mobility solution through a comprehensive application ecosystem (cf. Geely Auto Group 2018b, online). At present, it supports a variety of apps including Alibaba’s AutoNavi navigation, iFlytek voice recognition, ZTE connectivity to 4/5G networks, Ximalaya Radio, Tencent social network, JD Smart Home, Guahao WeDoctor medical support, and Babytree child education.

6.5.3 SAIC Motor Corporation Limited The Shanghai-headquartered automaker SAIC Motor Corporation Limited (SAIC) has a long history which can be traced back to the early 20th century. In October 1984, the first 50/50 joint venture since reform and opening up in the automotive industry—Shanghai Volkswagen Automotive Co., Ltd. (SAIC Volkswagen)—was established. After that,

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SAIC successively formed joint ventures with some foreign companies such as General Motors of the United States (SAIC-GM) and Volvo of Sweden (SUNWIN) (cf. SAIC Motor 2018b, online). SAIC Group’s annual sales in 2017 reached 6.93 million units. In addition, with its annual revenue of $128.819 billion, it ranked first and 7th among Chinese and global automobile companies respectively in 2017 (cf. SAIC Motor 2018c, online). Strategy:  According to the Chief Engineer at SAIC Group Mr. Cheng Jinglei, digital transformation should be involved in four aspects: R&D process, product, manufacturing process, and service sector. The intelligence is not a simple combination through an embedded communication chip, but a smartly connected ecosystem, which combines the user date and covers the entire automobile industry chain. In respect of intelligence and connection, SAIC has cooperated with the Chinese e-commerce and internet giant Alibaba Group to build “cars on the internet”. Furthermore, it aims to develop the V2X (vehicle-to-everything communication) and to form an ecosystem integrated with vehicles and other services. Regarding the aspect of sharing, the objective is to build the world’s largest platform that offers timeshare leasing services with NEVs. The sharing service is expected to involve 300.000 NEVs and cover more than 100 cities nationwide (cf. SAIC Motor 2017c, online). Implementation in Practice: SAIC introduces advanced technologies through the establishment of joint venture groups and the acquisition of foreign companies. These newly established or acquired companies can significantly promote the transformation to the intelligent manufacturing of the entire group. Among them, the most eye-catching is the industry 4.0 plant of SAIC Volkswagen and C2B mass customization of SAIC Maxus. The SAIC-Volkswagen Ningbo Plant, completed and put into production in 2017, is the first industry 4.0 plant which refers to the digital plant of the German Volkswagen Group. Currently, the annual production capacity is scheduled to be 600.000 units. • With the large-scale use of highly intelligent robots, the production automation rate of the whole plant has reached 86%. On average, there is one new car completely assembled every 51 s. • SAIC Maxus is taking the lead in the transformation from Business to Customer (B2C) to user-centered Customer to Business (C2B). To implement the C2B strategy, SAIC Maxus released the “Woxing@MAXUS” (“我行@MAXUS”) platform and its pioneer C2B customized product SUV D90 in 2016. The platform is the first digital interactive platform which allows users to participate in the entire car manufacturing process. That means the users are now able to define, design, configure, test and improve their cars as well as fix car prices. Data shows that in the definition phase of SUV D90, SAIC Maxus focused on 18 definition points, conducted offline surveys on 1119 target users, interacted with 31.125 users in the test driving via its online platforms, invited 25 SUV professionals to take a test drive and collected more than

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30.000 suggestions in total. With a better understanding of customers’ needs, SAIC Maxus can customize car products for thousands of customers (cf. SAIC Motor 2016, online). • As the only auto manufacturer in China that comprehensively promotes plug-in hybrid electric, pure electric and fuel cell technologies, SAIC attaches great importance to the development of new energy vehicles. By the end of 2017, SAIC has invested more than 10 billion RMB in this field and formed a new energy R&D team of nearly 1000 people. By 2020, it will continue to invest 10 billion RMB in research on related technologies and products of NEVs (cf. SAIC Motor 2017a, p. 58). • SAIC has mastered the core technologies of “three powers” (plug-in hybrid, pure electric and fuel cell) and has developed its self-owned battery management system (BMS) as well as energy storage system. While expanding its market and adhering to R&D, SAIC has cooperated with the leading companies specializing in the core components such as batteries and BMS such as Contemporary Amperex Technology Co. Limited (CATL) and Infineon Technologies Co., Ltd. (cf. SAIC Motor 2017b, p. 9). • Driven by the trend of intelligence and connection, SAIC officially released the world’s first mass-produced intelligent connected vehicle (ICV)—Roewe RX5 SUV in 2016. Based on the mobile operating system AliOS from Alibaba Group, this software is designed for the owners to remotely control the car, inquire about the car state information, and acquire the connected car services such as Alipay and Taobao (cf. Banma 2018, online). • SAIC has the complete independent intellectual property rights of the core technology of the second-generation intelligent driving platform and has achieved the level 4 (L4) of the driving automation—high-level automatic driving (cf. SAIC Motor 2018a, online). According to the Society of Automotive Engineers (SAE) International, there are five classifications for the driving automation. The L4 vehicles with Automated Driving System (ADS) can intervene themselves without any human intervention when a failure occurs (cf. Auto Alliance 2018, online). • In September 2018, the Roewe MARVEL X equipped with self-parking function will be officially launched. Other functions such as self-driving at high-speed and ­self-driving in urban areas will also be put into commercial application in the next year. • SAIC considers multiple cooperation necessary for the development of ICVs. For this reason, SAIC and Tongji University have jointly established the “ICVs Evaluation Base,” which is the first public R&D platform in China that integrates technologies of ICVs R&D, testing, and evaluation. In the Mobile World Congress in June 2017, SAIC has developed a tripartite cooperation partnership with China Mobile and Huawei to make the SAIC-Tongji “ICVs Evaluation Base” the first 5G test site in Asia. • In terms of car sharing, SAIC has merged its EVCARD and E-sharing Car and founded Global Car Sharing and Rental Co., Ltd to provide the time-share leasing service of NEVs. Different from the traditional car sharing and rental, the Global Car Sharing is a new car-sharing mode consisting of various leasing stations and mobile terminals thereby achieving entire self-service.

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6.6 Comparison of the Cases Through the case study, the conclusion that both German and Chinese companies are promoting the intelligent manufacturing in the existing automobile production can be drawn (Fig. 6.4). Meanwhile, they pay the same attention to the development of NEVs, ICVs and smart mobile travel services. On the whole, VW has a comprehensive, structured and specific strategy with concrete action plans for Industry 4.0 implementation. Compared to VW, Geely and SAIC have proposed their understanding of intelligence, digitalization, and electrification and formulated relative development strategies as well as goals. But unlike VW, their strategies appear much more like business guidelines rather than implementation plans. 1. (+) Regardless of the Industry 4.0 technical maturity or the breadth and depth of its application, VW is far ahead of Geely and SAIC in developing smart factories. Regarding modular platforms, VW has independently developed the MEB while Geely has developed its own modular platform system with CMA, AMA, BMA, DMA, and PMA. 2. (0) In the new field of NEVs and ICVs, the three companies are neck-and-neck. But in providing intelligent mobile travel service, Geely and SAIC have developed distinctive mobile travel services with NEVs that have been popularized in China. However, the mobility service of VW’s MOIA was officially launched in 2017 and have not been widely used. 3. (−) China has a tremendous speed of development and has thus reached a very good position in the new digital technologies within a few years. The automotive industry

criterions

VW

Geely

brand awareness clear and specific strategy industry 4.0 technology maturity intelligent manufacturing modularplatform NEVs

ICVs mobile travelservice independent R&D multiple cooperation annotations: high level

middle level

low level

Fig. 6.4  Cases comparison based on ten criterions

SAIC

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is related closely to various branches and leading companies like Alibaba, Baidu, Intel etc. The employees are open-minded with reference to new technologies, while German workers have a strong inertia. The political background and power is much more dominant in socialistic systems than in the German political system. It is worth noting that all three companies consider technology as core comparativeness. All of them focus on independent research and development and cross-industry multiple cooperation.

6.7 Inspiration for Chinese Automotive Companies—10 Recommendations 1. Mr. Zhu Kongyuan, the deputy director of the China Association of Automobile Manufacturers, pointed out six significant problems in the informatization and digitalization of Chinese companies. Most companies fail to recognize the significance of digit technology so that their strategic orientation is unclear. Most of them regard the emerging technology only as a new tool but not as a signal of the coming industrial revolution. How to overcome these problems has become a significant problem for Chinese auto companies. Here, the German “Industry 4.0” and its implementation of the German automotive industry provides a reference for Chinese automotive companies (cf. Bai 2011, p. 18). 2. After the announcement of the “Industry 4.0” strategy in Germany, VW has developed the “TOGETHER 2025” strategy to promote the group’s digital transformation. In this strategy, each key building block is also subdivided into different initiatives for better implementation in practice. What can be observed is that a detailed and feasible strategy that conforms to the megatrends and to the current situation is crucial for company change. 3. After the “12th Five-Year Plan (2011–2015)” proposed to promote the in-depth integration of informatization and industrialization, China and Germany announced that they will carry out Industry 4.0 cooperation. While China’s 12th Five-Year Plan was aiming to comprehensively enhance the intelligent level of R&D, production, management, and service, its successor, the Made in China 2025 initiative, now additionally focuses on digital, networked and intelligent manufacturing. All these policies have shown that the Chinese government is providing substantial support to digital and intelligent transformation (cf. Dong et al. 2017, p. 6). 4. China’s large-scale state-owned automotive groups represented by SAIC, have primarily established a series of information systems with PLM/PDM, ERP, MES, and BOM, covering all aspects including product design and development, prototype production, material procurement, manufacturing, sales, etc. Like VW, these automakers with a long history are paving the way for digital and intelligent change

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for their existing business and factories. At the same time, they are expected to develop new vehicle types and business models. 5. Small and medium-sized automobile companies in China are often private-owned companies with self-owned brands. They are the later starters in conventional ­auto-manufacturing. Like Geely, if these companies concentrate on R&D and innovation, they will have great potential to take the lead in the field of NEVs and ICVs (cf. ibidem, pp. 6–8). Therefore, Chinese auto companies should proceed to form the current situation and grasp the policy advantages to formulate the most appropriate strategy for themselves. 6. At the same time, consumers focus not only on the product quality and price but on the excellent pre-sales and after-sales services. Therefore, it is also essential to develop a professional service plan for the customer during the customer life cycle, from the beginning of a customer relationship to its maintenance. The service plan should run through the entire customer lifecycle, including scheduling pre-sale test drives, detailed vehicle descriptions, regular return visits to customers, a­ fter-sales inspection and maintenance, system upgrades, etc. (cf. Xin and Zheng 2014, pp. 72–77). 7. For the new generation, the usage right of the car is more economical than the possession of the car. Along with the development of advanced technologies, the application of big data analysis and the increasingly fierce market competition, the new business model of sharing economy has gradually emerged. Therefore, auto companies should also develop corresponding mobile travel services in accordance with their own situations to satisfy consumer demands. As in the cases of VW, Geely, and SAIC: they have founded MOIA, CaoCao, Global Car Sharing respectively to expand their business. 8. Intelligent manufacturing: VW is holding a leading position in Smart Factory development. The digital factory of SAIC-Volkswagen has been put to use for two years. Geely has also established a highly intelligent digital plant for production of LYNK&CO vehicles. The most crucial factor for a smart factory is to form the Internet of Things through CPS, which achieves full traceability of manufacturing by associating with devices, orders, processes, and personnel. With the help of sensors, numerical control systems or RFID, all data such as production, quality, energy consumption and equipment performance can be generated and displayed on electronic boards. The real-time production status is under control, thereby preventing errors. According to this, auto companies should establish a unified data standard and carry out data format specification so that it can be transported and used more widely and conveniently (cf. Yu et al. 2017, p. 230). 9. Big Data: With the rapid development of digit technology and the popularization of multimedia and personal mobile devices, the amount of data in the world is growing exponentially. These enormous volumes of data generated from heterogeneous sources have various types. It leads to the new requirements for data collection, storage, screening, and analysis. Big Data opens up new possibilities for auto companies

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to obtain a more complete and accurate understanding of products, customer behavior, and future industry trends (cf. Xin and Zheng 2014, pp. 71–72). 10. Multiple cooperation: As shown in the cases described, digital transformation is hard to be realized only by auto manufacturers alone. The cooperation and support from all forces of society are necessary. The German and Chinese government has established a bilateral cooperative partnership in terms of Industry 4.0. Domestic companies such as SAIC and Geely have also introduced advanced foreign technology through joint ventures or acquisitions of leading international companies. These days, domestic leading automakers such as SAIC, Geely, Great Wall, FAW, and BAIC have already applied their technical achievements such as self-driving technology to production. IT companies such as Baidu, Alibaba, and Huawei are also actively participating in this transformation. Baidu is developing high-precision maps. Alibaba is cooperating with SAIC to create connected platforms for ICVs. Huawei invests heavily in R&D of V2X technology and Internet of Vehicles (IoV) (cf. Feng 2018, pp. 66–70). In a word, Chinese automakers should follow the example of VW, SAIC, and Geely and develop multi-party partnerships with vehicle and component companies, upstream suppliers, downstream dealers, emerge IT companies, governments, and associations. Through cooperation, it is also possible to solve the problem of overlapping investments and information islands in the process of informatization.

6.8 Conclusion German automotive industry functions as a particular point of reference for the development of the Chinese automobile industry. At present, Germany is implementing the Industry 4.0 strategy to comprehensively promote the digital, intelligent and sustainable transformation of the entire manufacturing industry. China and Germany are jointly strengthening the cooperation in Industry 4.0-applications. The Chinese government has proposed the Made in China 2025 strategy according to their national conditions to make China a world-leading manufacturing power. The Chinese government has provided strong policy support for smart manufacturing, NEVs, and ICVs, which is also an advantage that Chinese auto companies should firmly grasp. The German auto companies represented by VW have more than ten years of experience in Industry 4.0 technologies. They use innovative techniques such as industrial robots, 3D printing, and AR/VR technology to actively promote the intelligent transformation of traditional automobile production and occupy a world-leading position in the field of intelligent manufacturing. Chinese automakers are intensifying their efforts in independent R&D. Besides, they enhance their competitiveness in the field of intelligent manufacturing by acquiring ­well-known foreign auto companies. After the reform and opening up, Chinese

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state-owned auto companies represented by SAIC have mainly established joint ventures with other world-leading automakers. Since 2015, smart factories have gradually been formed and put into use. Emerging technologies have not only brought about changes in conventional automobile manufacturing, but also created new automobile products and new business models such as NEVs, ICVs and intelligent mobile travel services. Unlike automobile manufacturing, these fields are newly emerging in recent years. In a sense, Chinese auto companies and foreign leading auto companies are almost at the same starting line. With cross-industry cooperation and support from national policies, Chinese auto companies have made tremendous progress in the development of new energy and IoV. Therefore, NEVs and ICVs are expected to be the breakthrough for Chinese auto companies to increase their international influence (cf. Cao 2017, p. 53). In summary, Industry 4.0 offers a wide range of possibilities and improvements. In the era of changes, the Chinese automotive companies must be far-sighted so that they can play a leading role in global automobile manufacturing and enhance the international influence of Chinese auto brands. They must use advanced technology as their core competitiveness, develop optimal innovation-driven strategy and achieve the digital and intelligent transformation of the entire Chinese automotive industry.

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7

The Four Waves of Industrialization in China Zhou Xufeng

Contents 7.1 Three Waves of Industrialization Before Liberation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 7.1.1 Prelude of Industrialization—Westernization Movement (1861–1894) . . . . . . . . . 76 7.1.2 The First Wave of Industrialization in the Late Qing Dynasty (1895–1911). . . . . . 77 7.1.3 The Second Wave of Industrialization in the Beiyang Period (1914–1922). . . . . . 78 7.1.4 The Third Wave of Industrialization During the Kuomintang Period. . . . . . . . . . . 79 7.2 New Concept of Industrialization After the Foundation of the P.R.C. . . . . . . . . . . . . . . . . 80 7.2.1 The Ups and Downs of Industrialization Before the Reform and Opening Up (1949–1978). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 7.2.2 The Reform and Opening Up Ushered in the Spring of Industrialization (After 1979). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 7.3 Some Thoughts Triggered by China’s Four Waves of Industrialization . . . . . . . . . . . . . . . 84 7.3.1 Common Law of Industrialization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 7.3.2 Three Modes of Industrialization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 7.3.3 Industrialization Before and After World War II. . . . . . . . . . . . . . . . . . . . . . . . . . . 85 7.3.4 The Reasons for the Extensive Use of Financial Leaders After World War II. . . . . 86 7.4 The Historical Choice of China’s Road to Industrialization. . . . . . . . . . . . . . . . . . . . . . . . 86 References and Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Abstract

This chapter summarizes the process of industrialization in China, which includes the Westernization Movement and three waves of industrialization from late Qing Dynasty to the Republic of China. After the Liberation, with help of the former Soviet X. Zhou (*)  University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_7

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Union, China began to industrialize in the catch-up mode, and acquired extraordinary achievements. However, under the error command of “catch up with the United States and surpass Britain”, Chinese industrialization suffered a great setback. After the Reform and Opening, industrialization of financial pilot modes had begun in China. Financial reforms provided a steady stream of financial support for the new industrialization climax, and brought strong growth in China’s economy for more than 30 years.

7.1 Three Waves of Industrialization Before Liberation 7.1.1 Prelude of Industrialization—Westernization Movement (1861–1894) Around the middle of the 20th century, the Industrial Revolution in Great Britain has ended. The outcomes of this revolution—advanced technology e.g.—were spread around the whole globe ever since, and China also got its share. The Westernization Movement, which began in the 1960s, became the beginning of China’s industrialization. From 1842 on, when the Qing government was forced to sign the “Nanjing Treaty”, China has entered the semi-colonial society. Different from the Japanese government of that time, the Chinese government acted ignorant and refused to push forward the industrial revolution of the country. However, the painful lessons of the failure of the two Opium Wars, and the hardships of the suppression of the Taiping Heavenly Kingdom made the Qing government realize the great power of the advanced weapons of the Western world. Therefore, in 1861, Tseng Kuo-fan founded China’s first modern industrial institution, Anqing Ordnance, whose mission was to duplicate and manufacture Western weapons. Since then, the vigorous Westernization Movement began, which featured copying Western industrial systems. At first, the Westernization Movement was dominated by military industry. Westernization officials set up a number of government-run military enterprises under the slogan of “self-reliance”. From 1861 to 1890, a total of 24 arms factories and shipyards was created, featured by Li Hongzhang’s Jiangnan Manufacturing General Administration and Zuo Zongtang’s Fuzhou Shipbuilding Bureau. In the 1870s, due to the deterioration of the financial situation of the Qing government and the needs of military enterprises supporting services, the Westernization Movement expanded from the military industry to the civilian industry. the mode of operation gradually changed from purely official to official business, private investment and other forms. Before 1894, nearly 200 civil enterprises had been set up, and the total number of employed workers can be said to have been about 90,000. These enterprises were involved in mining, metallurgy, transportation, textile and other industries, 27 of which were state owned (including being governmentally supervised). The government investment was about 29.64 million yuan with 25.500 to 29.500 employees; 171 private enterprises, and the

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investment amount was about 12.358 million yuan with 62.604 workers. One of the most successful civil enterprises was the Hanyang Iron Factory, which was founded by Zhang Zhidong with a capital of 5.56 million yuan. The Hanyang Iron Factory was the largest iron and steel enterprise in the eastern hemisphere. Kaiping Coal Mine, founded by Li Hongzhang, was a state supervised civil enterprise, with a daily coal production of 500 tons from 1882 to over 900 tons in 1884. Its stock value increased from 100 Liang when it started to 237 Liang in 1882. The Merchants Steamship Navigation Company, founded by Li Hongzhang in 1872, was the first form of joint-stock company in modern China. It marks the beginning of the modern enterprise system. State owned enterprises mainly focused on the transportation industry, accounting for 46% of the total investment amount, followed by metallurgy and mining. Private investment enterprises evolved slightly later than state-owned enterprises. Its emergence can be traced to three main reasons. First reason being the low efficiency of state owned enterprises. The second reason is its originality of workshop handicraft industry. One example would be the Fachang Machinery Company, whose founder Fang Zanju was a blacksmith who owned a small co-organized iron shop. The capital of that iron shop in 1866 was only 200 yuan. After starting to make iron for the British ship building company, they introduced the lathe in 1869, and his small workshop turned into a large machine industry, which was able to manufacture fairly modern small fire wheels at that time. The third reason is the investment of overseas Chinese, domestic businessmen and early banks, which formed, for example, the first silk-filature factory. Jichanglong Silk-filature Factory was founded by the Chinese-Indonesian Chen Qiyuan. Private enterprises, mainly in the manufacturing sector, account for 85% of the total number of factories, accounting for 60% of the total investment, mainly manufacturing light industrial products such as reeling, cotton, printing, matches, rice, grinding and so on. As a result of weak funds, feudal oppression, government officials’ pressure and foreign invasion, many private factories closed down soon after the start of the business. The Jichanglong Silk-filature Factory, for example, was forced to move to Macau due to some arbitrary reason. From the point of view of capital comparison, the Westernization Movement was dominated by government-run enterprises. Government investment was one of the main approaches of the original accumulation of industrialization in China. Industrial layout was mainly concentrated in the southeast coast and the Yangtze River area, forming three industrial centers: Guangzhou, Shanghai and Wuhan.

7.1.2 The First Wave of Industrialization in the Late Qing Dynasty (1895–1911) The Westernization Movement, the main purpose of which was to strengthen the military, declared its failure in the rumbling of the Sino-Japanese War. The signing of the Treaty of Shimonoseki in 1895 and the Treaty of Xinchou in 1901 made China subject to semi-colonialism. China’s small-scale peasant economy was quickly disintegrated.

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The high quality yet inexpensive rice, flour, cloth, wax, lime, fire etc. from the Western world broke down the natural economy based on farming in China, and the domestic market was expanded. Peasants did not own much at that time, so they had to serve as constant and cheap working force of the industrial development. At the same time, Western knowledge of science began to prevail in China. In order to sustain its ruling, the Qing government was forced to set up Daxuetang (predecessors of modern universities) in every capital city of each province. Therefore, many Daxuetang and Zhongxuetang (predecessors of modern middle schools) like Jingshi Daxuetang (currently Peking University), Beiyang Daxuetang (currently Tianjin University), Shanxi Daxuetang (currently Shanxi University) and Shanxi Gongli Zhongxuetang (currently Taiyuan No. 5 middle school) were established. One of the most famous modern Chinese authors and revolutionary, Lu Xun, entered Jiangnan Shuishixuetang in 1898. Modern scientists like Zhan Tianyou have returned from overseas to China and became the inner circle of China’s industrialization process. The disintegration of the natural economy and the introduction of Western technology led to the emergence of the first wave of industrialization between 1895 and 1911. During these 17 years, the number of newly opened factories and mines (with a capital of more than 10 k) was 549, which is 2.7 times the number in comparison to the Westernization Movement. The new total investment amount was 120 million yuan. The number of newly opened factories and mines invested by foreigners (with a capital of more than 100 k) was 136. Its new total investment amount was 100 million yuan. In 1894, modern industrial capital amounted to 77.45 million yuan, and increased to 666.22 million yuan in 1913, which was about 7.6 times higher than before. The average annual growth rate amounted to 14.44%. Mining and metallurgical industry capital increased by 9.3 times, manufacturing capital increased by 5.7 times. By 1911, the new industrial output value was about 348 million yuan, but the proportion of the national economy is still very low, accounting for only 1.8% of industrial and agricultural output value.

7.1.3 The Second Wave of Industrialization in the Beiyang Period (1914–1922) The Revolution of 1911, the Second Revolution and the assassination of Song Jiaoren and other unstable factors, as well as the early years of the political chaos, led to a slowdown in industrial investment growth, and the first wave of industrialization went into a trough. In 1914 the First World War started. Western powers had no time to take care of any businesses other than war, so China had a chance to “breathe” temporarily. During that period of time, its national industry had a significant development. The time period between 1915 and 1922 is known as the “golden age” of Chinese industry. In 1920, the capital expenditure of modern industry increased by 60% in comparison to 1913;

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mining and metallurgical industry increased by 47%, manufacturing by 67%. In 1920, the ­proportion of industrial output value accounted for 5.03% of the total industrial and agricultural output value. Shortly after the end of the First World War, the imperial powers returned to the Chinese market, bringing large numbers of cheap goods back to further squeeze the naive Chinese national industry. Coupled with successive years of warlord melee, the second wave of industrialization encountered a major setback.

7.1.4 The Third Wave of Industrialization During the Kuomintang Period After the victory of the Northern Expedition in 1928, especially after the Central Plains war, the domestic political atmosphere was relatively stable as it enabled a suitable environment for industrial development. Between 1928 and 1936, China has set off a third wave of industrialization, which reached its peak in 1936. In that year, the capital of modern industry doubled compared to 1920, of which mining and metallurgy increased 53%, while the manufacturing industry soared 2.4 times. In 1936, the new industrial output value accounted for 23.69% of the total industrial output value—compared with 1920 it increased by 12.91 percentage points. The total industrial and agricultural output value also reached 11.35%—compared with 1920, it increased 6.32 percentage points. An important feature of the third wave of industrialization is that the degree of mechanization was greatly improved. In 1936, the proportion of machinery production in the five major sectors of coal, iron, iron ore, cotton weaving and cotton spinning was 84.7%, 82.7%, 87%, 83%, and 39% respectively. During this period, the average annual growth rate of China’s mining industry reached 7.7 to 8.1%. The average per capita production of steel, pig iron and coal reached 0.88 kg, 1.725 kg and 84.96 kg respectively in 1936, compared with 0.06 kg, 0.004 kg and 0.099 kg in 1912. It seems that the figure multiplied 10 times, or even hundreds of times during these 24 years. However, compared horizontally, steel per capita production in Great Britain in 1936 was 253.2 kg, 376.3 kg in the United States and 95.3 kg in the former Soviet Union. Judging from per capita cotton production, in 1936, the figure was 7.34 m for China. In the United Kingdom, in direct comparison, it was 70.38 m; 61.42 m in the United States and 20.28 m in the former Soviet Union. Thus, China was lagging far behind. In 1937 China’s third wave of industrialization was ruthlessly destroyed by Japanese invaders. The eastern coastal industrial areas were all subject to the Japanese occupation, and the industrialization was unprecedentedly destroyed. After the victory of the AntiJapanese War, with the start of the three-year civil war, the price soared, people were destitute, the national economy was on the verge of collapse, and industrialization was nowhere to be expected. By 1949, industrial output in China was only 14 billion yuan (only 30% of total industrial and agricultural output value) and industrial net output accounted for only 12.6% of national income. China’s industrial road was still long and tough.

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7.2 New Concept of Industrialization After the Foundation of the P.R.C 7.2.1 The Ups and Downs of Industrialization Before the Reform and Opening Up (1949–1978) In 1949 the new P.R. China was established, and the country started its way to socialist industrialization. Mao Zedong (in his article on the coalition government, on people’s democratic dictatorship and other articles) repeatedly pointed out that the construction of new China must take the road of industrialization. After three years of national economic recovery, the financial situation fundamentally improved, the industrial indicators reached, or rather exceeded, the best level before the war. In 1952, China’s industrial output value increased by 144.9% to over 1949, with an average annual increase of 34.8%. The recovery of major industrial production is shown in Table 7.1. As shown in Table 7.1, the industrial indicators in 1952 were not only significantly higher than in 1949, but also chemical fertilizers reached the best level in ­pre-liberation history, indicating that by the end of 1952, the national economy had largely recovered. Due to the rapid industrial rehabilitation, the share of industrial output in the gross industrial and agricultural output jumped from 30% in 1949 to 41.5% in 1952. After the liberation, workers made improvements to the original technological process and the technology for industrial production greatly improved. For example, old Chinese rails and high-quality steel products all had to be imported from abroad. However, by 1952, China had been able to produce a wide range of ordinary steel plates, sheet steel, silicon steel sheets, some special steel and seamless steel pipes, etc. The new Chengdu-Chongqing Railroad started to use domestic made rails for the first time. ­ Another example is that the machinery industry in the old China could only engage in general decoration, accessories, etc. However, in 1952, China was able to produce complete sets of textile machinery and a variety of work machine, mining equipment, and 3000 kW generating units. In those three years, the means of production increased by 227% with an average annual increase of 48.5%; the consumption data increased by 114.8% with an average annual increase of 29%. The proportion of light and heavy industries grew from 73:27 in 1949 to 64:36 in 1952. The status of heavy industry has been markedly strengthened, laying a solid foundation for the rapid growth during the “First Five-Year Plan”. In 1953, China began implementing the First Five-Year Plan and focused on industrial construction consisting of 156 construction projects, aided by the former Soviet Union, and 694 construction units above the designated size. China mainly studied the experience of the former Soviet Union and adopted the principle of giving priority to the development of heavy industry. In accordance with this guideline, the capital construction investment in the industrial sector was 24.85 billion yuan, accounting for 58.2% of the total investment, of which heavy industry accounted for 88.8% of the industrial sector. As a result of the implementation of the first five-year plan, more than 10.000

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Table 7.1  Contents of recovery of production of major industrial products in early liberation (in: 10 kt). (Source Following the Chinese academy of social sciences, central archives. economic archives of the people’s republic of China selected: Comprehensive co-volume, Beijing: China City Economic Society Press 1990, p. 932–933) Item

Production in 1952

Ratio/1949 (%)

Ratio/Max production before liberation (%)

Steel

134.9

853.8

146.2

Raw iron

192.9

765.5

107.1

Coal

6649.0

205.0

107.4

Electricity

72.6 (100 million kWh)

168.4

121.8

Oil

43.6

360.3

135.8

Cement

286.0

433.3

124.9

Sulfuric acid

19.0

475.0

105.6

Soda ash

19.2

218.2

186.4

Caustic soda

7.9

526.7

658.3

Fertilizers

18.1

670.4

79.7

Metal cutting machine tools

1.37 (10 k)

868.1

Cotton yarn

362 (10 k)

201.1

147.8

Cotton

38.3 100 million meters) 202.6

137.3

Cigarettes

265.0 (10k)

165.6

112.3

Sugar

45.1

226.6

108.9

Salt

494.5

165.7

126.2

industrial construction units were started, of which 921 were above the limit, 227 more than planned, and 537 units were put into production in whole or in part. By 1957, the industrial output value reached 78.39 billion yuan, with an increase of 128.3% over 1952 and an average annual increase of 18%. The share of industrial output in the total industrial and agricultural output increased from 43.1% in 1952 to 56.7% in 1957. In terms of industry, the production rate of means of production increased 2.1 times from 1952, with an average annual increase of 25.4%. The share of industrial output increased from 35.6% in 1952 to 48.3% in 1957 accordingly (Table 7.2). Through the implementation of the “First Five-Year Plan”, China’s manufacturing industries such as aircraft, automobiles, heavy machinery, precision instruments, power generation equipment, metallurgical equipment, mining equipment, advanced alloy steel and non-ferrous metal smelting industries have all developed out of nothing, established a more complete industrial system and initially laid the industrial foundation of China. The achievements made in in the sector of industrial production during these five years have greatly exceeded the level that could have been achieved in one hundred years in old China.

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Table 7.2  Industrial and capital construction during the first five-year-plan period (in 100 million yuan, %). (Source Based on the China statistical yearbook: 1984. Beijing: China Statistics Press 1984, p. 23, 301, 417) Item

1953

1954

1955

1956

1957

Industrial output vs. previous year (%)

450 30.3

515 14.4

534 3.7

642 20.2

704 9.7

Infrastructure investment vs. previous year (%)

90.44 107.6

99.07 9.5

100.36 155.28 1.3 54.7

Revenue vs. previous year (%)

222.9 21.3

262.4 17.7

272.0 3.7

287.4 5.7

143.32 −7.7 310.2 7.9

Since 1958, due to the influence of the extremely “leftist” ideology, China’s industrialization began a period of 20 years of wandering, undergoing chaos, adjustment, ­re-chaos and readjustment. The economy fluctuated greatly. In the meantime, there was an absolute egalitarianism and proneness to boasting and exaggeration, so the statistics lost their meaning. In short, by 1976, the profit rate of funds for industrial enterprises in the country was only half of its value in 1965; with more than one-third of loss-making enterprises and losses of up to 7.3 billion yuan. The national income growth rate was 2.7%. There were serious disorders in the proportion of agriculture, and the national economy was once again situated on the brink of collapse.

7.2.2 The Reform and Opening Up Ushered in the Spring of Industrialization (After 1979) After the Third Plenary Session of the 11th Central Government, China began to carry out the reform and opening up; thus, industrialization took the right track. At first, the financial sector took the lead in the reform. In March, August and October 1979, it successively resumed the Agricultural Bank of China, set up People’s Construction Bank of China, the Bank of China, China International Trust and Investment Corporation, resumed People’s Insurance Company of China, and provided financial support for the steady stream of new industrialization. Then it continued to adapt to market economy reforms, making tremendous contributions to China’s rapid industrial growth for more than 30 years. In a second step, industrialization shifted from giving priority to the development of heavy industry to a more balanced industrialization of heavy industry and light industry. The ratio of heavy industry to light industry was adjusted from 56.9:43.1 in 1978 to 50.7:49.3 in 1998, and the coordinated development of both was initially realized. In a third step, with the deepening of the reform and the opening up, the old industrialization of “large in size and collective in nature”, which solely relies on the state, has changed to the industrialization of “public ownership dominance with different economic sectors existing side by side”. This maximized the mobilization of resources

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from all sectors of society. The share of state-owned and state-controlled industrial ­output within the total industrial output dropped from 77.6% in 1978 to 31.95% in 2011. The share of other types of ownership within the industrial output rose from 22.4% in 1978 to 68.05% in 2011. The vast majority of non-state-owned enterprises in 1978 were collectively owned and have now been transformed into private, as well as private and foreign-funded enterprises. The shift in this model has fully mobilized all parties’ enthusiasm and greatly accelerated the process of industrialization in China. As a fourth point, it seems recommendable to shift from industrialization characterized by high accumulation and high investment to industrialization focusing mainly on science and technology as well as on efficiency. Before the reform and the opening up, although the pace of industrial growth was not low, extensive and inefficient management led to a decline in people’s living standards. After the reform and the opening up, China introduced a large number of advanced foreign production technologies and accelerated technological innovation, which greatly improved the efficiency of enterprises. Fifth, from the industrialization of import substitution to the export-oriented industrialization. China’s industrialization started from the import substitution. At the beginning of the reform and the opening up, China continued to learn from advanced foreign technologies and import substitution. However, due to the abundant labor resources and the relative lack of other natural resources, the traditional import substitution model cannot fully benefit from the international division of labor. Therefore, with the consolidation of the opening up, China has gradually shifted from an export-oriented model to a strategy of using foreign investment, thereby expanding foreign trade actively. By the end of last century, China’s dependence on foreign trade has reached about 45%. Its foreign trade volume has risen 372 times from 9.75 billion US$ in 1978 to 3.6 trillion US$ in 2011. Through the above-mentioned transformation, China’s industrialization has made remarkable achievements both in scale and in efficiency. The rapid growth of industrial output has enabled the sustained and rapid development of industrialization. The output of various industrial products increased sharply. The net fixed assets of state-owned and state-controlled industrial enterprises increased more than 50 times from 211.45 billion yuan in 1978 to 11,188.889 billion yuan in 2011. As for per capita output, compared with 1978, coal production increased more than 12 times; crude steel more than 15 times; and cement 20 times. With the strengthening of industrial production capacity, China is gradually becoming a large industrial producer. The industrial structure is becoming more and more balanced. Since the reform and opening-up, China has successively carried out industrial restructuring four times. The first restructuring process began in the late 1970s and early 1980s. It changed the long-term imbalance of agriculture, light and heavy industry, and initially realized the coordinated development of all three. The second process started in the second half of the 1980s. The rapid development of new home appliances industry has achieved the import substitution and upgrading of home appliances. The third process was in the 90s. The basic industries were given priority to development, easing the “bottleneck”

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constraints of industrialization. Since the fourth restructuring process at the end of the last century, the status of high-tech industries has risen markedly. Industries that are ­technology-intensive and have high added-value products have developed rapidly. China has become one of the top 10 global electronics producers. The growth rate of communications equipment, network equipment, electronic computers and other electronic products has risen 2 to 4 times as much as the average rate of industrial growth and has become an engine driver of industrial growth. Labor productivity has risen dramatically. Since 1978, China has changed its reputation of being far behind in technology through technology introduction and independent innovation. The gap between developed countries in key enterprises in major industrial production departments and the technological level has narrowed from more than 20 years to less than 10 years. In a few areas, on a technical level, China has been close to, or even exceeded, the level of developed countries. The traditional industries such as machinery, metallurgy, coal, chemical industry and building materials have made significant improvements in their major economic and technological indicators through technological transformation. Compared with 1978, the coal production efficiency increased by 70% and the standard coal consumption for power generation dropped from 521.76 g/ kWh in 1980 to 463.82 g/kWh in 2011. The export competitiveness greatly enhanced. In 2012, China’s total export volume was 2.0489 trillion US$, 209 times more than the U.S.; $ 9.75 billion in 1978. In the export structure, primary products accounted for more than 50% in 1978; industrial products accounted for more than 90% in 2012; and the export of electromechanical products in manufactured products was 1.1794 trillion US$, accounting for 57.56% of total exports, becoming China’s largest export commodities. Above all, China has become a veritable “world factory”.

7.3 Some Thoughts Triggered by China’s Four Waves of Industrialization 7.3.1 Common Law of Industrialization All countries in the world need capital, technology and labor for industrialization. Therefore, general laws of industrialization could be summarized as follows: • Primitive accumulation in advance, • Industrialization begins with the accumulation of capital, • Industrialization begins to emerge due to fierce competition and the continuous introduction of technology or innovation in various industrialized enterprises; and the fruits of industrialization are applied to agriculture, which led to the mechanization of agriculture and an increase of labor productivity of agriculture. It excludes a large surplus of labor from agriculture and provides a steady stream of cheap labor for

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industry. Industrialization has begun to accelerate. Large amounts of capital have been accumulated, industrial output gradually surpasses that of agriculture, and the urban population gradually surpasses the rural population. The market economy gradually replaced the natural economy, and the agricultural society gradually stepped into the industrial society. After the “bonus” of new technology was completely absorbed by the industry, a temporary technological stagnation appeared and the industrialization ended.

7.3.2 Three Modes of Industrialization As mentioned earlier, industrialization includes three modes: natural evolution, catch-up and financial leading. Natural evolution model: adopting a natural evolution model of the successful industrialized countries, mainly the United Kingdom and some small European countries adjacent to the United Kingdom. Their main features are as follows: the time of occurrence, the long period of experience, the colonial aggression, the unstable frequency of the economic crisis, the minor role of the government and that technology depends entirely on independent innovation. The catching up mode: countries that gained their success using the catching up model are countries like the United States, Germany, France, Russia and other major capitalist countries. The main features of the model are: the occurrence of time and time span are between the natural evolutionary model and the financial precursor model (approximately 10 years), and often spread to other countries to form a global economic crisis. The colonial aggression became more and more rampant and eventually evolved into a world war. Government intervention was intensified. Technology mainly relied on the introduction and trade protection measures. Financial Leading Model: This model is a new variant of the catching up model. Most countries adopted this model after World War II. Successful countries include emerging economies such as Japan, South Korea, Hong Kong, Taiwan, and Singapore. The characteristics of this model are as follows: the latest occurrence time, the shortest experience period, the primitive accumulation depends on finance, the government’s role greatly enhanced, non-tariff barriers become the main form of trade protection, the financial regulation and control is greatly strengthened, the economic crisis in the process of industrialization eases and the financial crisis, economic stagnation or lack of growth and other phenomena occurred shortly after the industrialization.

7.3.3 Industrialization Before and After World War II The biggest difference between the first two industrializations and the latter industrialization is the different forms of economic crisis. The success of the first two models

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occurred before World War II, the success of the latter model mostly occurred after World War II. Therefore, the first two models can be combined, called pre-World War II industrialization; the latter is called post-World War II industrialization. Upon the outbreak of the industrial revolution, the economic crisis followed and brought cyclical negative growth. The frequency of the industrial revolution rising the damage was more and more serious, and the world war was finally triggered. In the capitalist world, the economic crisis has gone hand in hand and became irremediable cancer. As a result, in 1916, Lenin asserted that imperialism was decadent and that dying capitalism was about to transition to socialism. However, since the end of World War II, the economic crisis seems to have softened a lot. The worst oil crisis in 1973 was only a trigger for “stagflation”. There was no such radical retrogression as in the years between 1929 and 1933.

7.3.4 The Reasons for the Extensive Use of Financial Leaders After World War II From the above analysis, we can draw the conclusion that there must be advanced technology, cheap labor force and sufficient capital for industrialization. Advanced technology can be imported from abroad. Cheap labor can be released from agriculture. But what about sufficient capital? Prior to World War II, countries that succeeded in industrialization tended to make up for lack of capital through the colonial plunder and the war of aggression. After World War II, the colonies and semi-colonies were independent, and it was these former colonies or semi-colonies that needed industrialization. They could no longer be allowed to carry out colonial plunder. However, “when one door shuts, another opens”. After the Second World War, the system of paper currency established its dominance in all countries of the world. The last gold of the gold standard was also dimmed with the collapse of the Bretton Woods system. After the establishment of the management of the currency system, the money supply is no longer an endogenous variable of the economy, but becomes a symbiotic variable both inside and outside. The monetary authority of a country can adjust the money supply through the monetary policy so that the capital chain of the enterprise can be connected, thus making up for the industrialized capital. However, huge financial fluctuations have been brought about.

7.4 The Historical Choice of China’s Road to Industrialization Before the liberation of the Westernization Movement and the three waves of industrialization, China made only small achievements. The most fundamental reason is that the colonial and national exploitation by the powers of the empire, especially the war of aggression against China, launched by the Japanese imperialists, interrupted China’s industrialization for eight years. “The imperialist aggression shattered the dream of the

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Chinese people to learn from the West” (United States Department of State 1949). After the liberation, with the aid of the former Soviet Union, China started its attempt to catch up and overtake the industrialization in the early days of the founding of the People’s Republic of China and made extraordinary achievements. However, with Mao’s wrong command of chasing the United States and overtaking the United Kingdom, industrialization suffered a great setback. After the deterioration of Sino-Soviet relations, the gap between China and the world widened even further. Reform and opening up played an important role in the industrialization of the financial lead model. Since the restoration of the Agricultural Bank of China in early 1979, the leading financial reform and economic reform competed with and complemented each other, which formed the achievements of China’s 30-year high growth in economy. Continuing to head along this path of success, China will be able to achieve industrialization in 2025.

References and Additional Literature 赵德馨. 中国近现代经济史[M]. 郑州:河南人民出版社, 2003. pp. 141,146–149,155–156,187–188, 207–208. 王珏. 世界经济通史. 中卷[M]. 北京:高等教育出版社, 2005. p. 374. 毛泽东. 论联合政府. 毛泽东选集:第三卷[M]. 北京:人民出版社,1966. pp. 1029–1031. 毛泽东. 论人民民主专政. 毛泽东选集:第四卷[M]. 北京:人民出版社,1966. p. 1407,1414. 苏星. 新中国经济史[M]. 北京:中共中央党校出版社,1999. p. 184. 高德步、王珏. 世界经济史[M]. 北京:中国人民大学出版社, 2001. p. 216. 孙健. 中国经济通史. 下卷[M]. 北京:中国人民大学出版社, 2000. p. 1818 ,2338. 刘明康. 中国银行业改革开放30年[M]. 北京:中国金融出版社, 2009. p. 6–10. 高德步. 世界经济通史. 下卷[M]. 北京:高等教育出版社. 2005. p. 389–390. 本书编写组. 十八大报告学习辅导百问[M]. 北京:学习出版社、党建读物出版社, 2012. p. 10. 列宁. 帝国主义是资本主义的最高阶段. 列宁全集:第27卷[M]. 第二版. 北京:人民出版社,1990. p. 411,437. 胡锦涛. 坚定不移沿着中国特色社会主义道路前进为全面建成小康社会而奋斗:在中国共产 党第十八次全国代表大会上的报告[R]. 北京:人民出版社, 2012. p. 17. 各年度《中国统计年鉴》. United States Department of State. (1949). United States Relations with China: With Special Reference to the Period 1940–1949. Department of State Publication 3573. Washington D.C.

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An Effective Path to Made in China 2025—Sharing Economy Mode Zhang Ping and Sun Xi

Contents 8.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 8.2 The Current Development Situation of China’s Manufacturing and Sharing Economy. . . 90 8.2.1 The Development of China’s Manufacturing Industry . . . . . . . . . . . . . . . . . . . . . . 90 8.2.2 The Development of Chinese Sharing Economy. . . . . . . . . . . . . . . . . . . . . . . . . . . 91 8.3 The Basis and Necessity of China’s Manufacturing Participation in Sharing Economy. . . 92 8.3.1 Macro Policy Level: The Government’s Vigorous Promotion Becomes Normality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 8.3.2 Technology Promotes a Comprehensive Upgrade of the Manufacturing Sector: “Manufacturing Industry & Internet” Develops Rapidly . . . . . . . . . . . . . . 92 8.3.3 Changes in Market Demand: The Era of Personalized Consumption—Internal and External “Customers”. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 8.4 The Effective Path of Made in China 2025: Sharing Economy Mode Based on the Core Competence of Enterprises. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 8.4.1 Innovation Sector in Manufacturing Industry: Internal and External Resources Sharing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 8.4.2 Production Sector of Manufacturing Industry: Mutually Shared Benefits of Spare Capacity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 8.4.3 Market Operation of the Manufacturing Industry: Business Mode for Mutually Creating and Sharing Value. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 8.5 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 References and Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

P. Zhang (*) · X. Sun  Chongqing University of Posts and Telecommunications, Chongqing Hechuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_8

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P. Zhang and X. Sun Abstract

Based on the change of international industry trends, the Chinese government has made a major strategic plan to comprehensively improve the quality of the Chinese manufacturing industry. China’s manufacturing industry is the main body of Chinese national economy. In the process of stepping into manufacturing power, this article recommends the government to stick to the Internet Plus plan, to introduce sharing economy and to develop the principal enterprises’ leadership and core competence in order to achieve rapid progress in innovation, production and business mode as well as to achieve participation of many parties in the creation of value.

8.1 Introduction The concept Made in China 2025 was first mentioned in China in December 2014. In 2016, Premier Li Keqiang proposed the project Made in China 2025 in the 2016 Annual Government Work Report during the National People’s Congress of the People’s Republic of China (NPC) and Chinese People’s Political Consultative Conference (CPPCC). Made in China 2025 is the first “Ten-year Guideline” to implement the strategy of “Manufacturing Power” by the Chinese government; it focuses on improving innovation ability, basic ability of the manufacturing industry, and it promotes deep integration of information technology and manufacturing technology; it is one of the most important fields for China to advance supply-side structural reform. It is also significant for economic transition, industrial development and social progress of China. “Sharing Economy” is also called “Collaborative Consumption” or “Peer-to-Peer Economy”. This term was first used in American economist Weitzman’s work: the Sharing Economy: Conquering Stagflation, Income, Wealth, and the Maximum Principle. As the Airbnb CEO Brian Chesky said: “access but not ownership”. It is a social economic ecosystem based on sharing data and materials and its guiding principle is “All for One, One for All”. The public shares idle resources with others through social platforms, and obtains income. Globally, new business modes such as Uber, Airbnb and car2go have changed the traditional industrial structure, and have promoted economic and social development. Based on the resource sharing, this new mode has achieved the optimal allocation of resources with the help of technology and has reduced energy consumption. Furthermore, it has rapidly occupied fields such as the manufacturing industry.

8.2 The Current Development Situation of China’s Manufacturing and Sharing Economy 8.2.1 The Development of China’s Manufacturing Industry China is a manufacturing country. Out of more than 500 kinds of industrial products in the world, China produced more than 200 kinds, which makes China rank first. However,

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the manufacturing industry is big but still weak. Although in some fields Chinese manufacturing industry has taken the lead in the world, the problem still exists. For example, the development of the industries is not balanced; there are gaps between large and small enterprises; independent innovation ability is weak; the quality of some products is poor; and there is low efficiency of resource utilization and irrational industry structures. Compared with developed countries, Chinese manufacturing industry still has a long way to go. However, Chinese manufacturing advantages are mainly reflected in the modular products such as the engineering machinery, household appliances, consumer electronic products and large complex equipment: communication equipment, high-speed railway, nuclear power equipment. At the same time, the field of core components in need of ­cutting-edge technology support lacks advantages. Most of Chinese manufacturing supply can only meet the demand of low quality and low prices, the supply structure cannot adapt to the new changes of the demand. The whole industry is still at the bottom of the global value chain.

8.2.2 The Development of Chinese Sharing Economy In March 2016, during the national NPC and CPPCC, “Sharing Economy” was first written into the Annual Government Work Report, and then quickly became the most active innovation field of Chinese economy. As the State Information Center’s report with the title “China’s Share Economic Development Report 2017” shows, the market turnover of China’s sharing economy in 2016 is 3 trillion and 500 billion Yuan, an increase of 103% compared with the year before. There are over 600 million people involved in it, which represents an increase of 100 million over the last year; the size of the financing scale is about 171 billion Yuan, an increase of 130% in relation to the last year. “Knowledge Payment”, “Webcast”, and “Bike Sharing”, which usher in the first year of development, gain explosive growth. Public entrepreneurship with sharing genes come out. Public entrepreneurship spaces registered by government make up more than 4000. Sharing economy means to establish a link from consumption data to production data, links from consumption to production, links from providing services for consumers to enterprises continuously improving the trading efficiency and production efficiency. Traffic, short rental housing, and intelligent manufacturing platforms have emerged, such as Didi, Xiaozhu short rent, Haier Idea, Shenyang Machine Tool i5 and other wellknown brands. It is predicted that in the future, China’s sharing economy will still maintain an average annual growth of about 40%. Till 2020, sharing economic transactions will account for more than 10% of the proportion of Chinese GDP.

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8.3 The Basis and Necessity of China’s Manufacturing Participation in Sharing Economy 8.3.1 Macro Policy Level: The Government’s Vigorous Promotion Becomes Normality The waste of resources, environmental pollution and extensive efficiency have plagued the healthy development of China’s manufacturing industry for a long time. “Sharing Economy”, the efficient use of idle resources in the field of R & D, production and other areas, has gradually been recognized. In March 2016, the Chinese Annual Government Work Report first proposed the “13th Five-year” period to facilitate the development of sharing economy, and to expand the new industrial clusters. In May 2016, the State Council issued the guidance on deepening the integrated development of manufacturing and Internet. It promotes manufacturing resources and production ability of small and medium-sized enterprises to fully dock with the internet platforms; so that they are able to release, coordinate and trade online. This has laid the foundation for the “mobile Internet + Internet + cloud computing + big data technology” and the deep integration of the Internet and manufacturing industry. This also provides a policy basis for platform interaction and resource sharing. In March 2017, the country has just concluded the two sessions (NPC and CPPCC). Premier Li Keqiang stressed again that the government supports and guides the development of “Sharing Economy” and improves the efficiency of social resources. The government needs to accelerate the development of new technologies, new industries and new formats. Furthermore, it needs to promote the development of “Sharing Economy” by institutional innovation, to build sharing platforms, to make the high-tech industry, modern services industry, and other emerging industrial clusters strong, and to build a new powerful engine.

8.3.2 Technology Promotes a Comprehensive Upgrade of the Manufacturing Sector: “Manufacturing Industry & Internet” Develops Rapidly American futurist Nicholas Negroponte boldly predicted that “digitization” is the source of social change in the 21st Century in his book Being Digital (Negroponte 1996). The manufacturing industry is the main battlefield of internet integration and digital construction. Made in China 2025 and Internet Plus are closely combined, which represents an important feature of development of Chinese manufacturing industry. China is trying to join together the power of the manufacturing industry and the internet. The innovation factor and innovation function of cloud computing, Big Data, Internet of Things and mobile internet constantly ingrates into the whole cycle of research and development, production, purchase, manufacture, logistics, delivery services of manufacturing industry, and continuously improves allocation efficiency of production factors in each link by integration, sensation, connection, optimization and control. Meanwhile,

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absorbing genes of sharing economy, using the Internet platform to achieve resource sharing, and the comprehensive upgrade of manufacturing industry will be promoted. “Internet + advanced manufacturing industry” will become the new engine of the Chinese economy’s development, and will bring forward the emergence of new techniques, new industries and new patterns.

8.3.3 Changes in Market Demand: The Era of Personalized Consumption—Internal and External “Customers” In China, the era of mass entrepreneurship and innovation is coming. During the Summer Davos Forum in September 2014, Premier Li Keqiang first called on mass entrepreneurship and innovation, which set off a wave of public entrepreneurship and “grassroots entrepreneurship” in China, and formed a “new situation” of “public innovation”. Since then, he frequently explained these key words in the first World Internet Conference, the executive meetings of the State Council and at a variety of other occasions. Driven by macro-economic policies and entrepreneurial culture, the entrepreneurial enthusiasm of the Chinese has been ignited. At the same time, the traditional “company + employee” mode was facing challenges; the creativity of employees also needed to be released, the new “platform + entrepreneur” mode was becoming an effective choice. In 2016, Chinese free worker participation in sharing platforms reached 60 million, and the employment trend also extended to the manufacturing sector. In addition, it is more and more difficult for the core competence of manufacturing enterprises to deal with the change of external customer demands. There are multilevel demands in China’s manufacturing market. With the economic development and the increasing demands for quality, service and experience, China’s manufacturing industry (which relies on low cost of demographic dividend) has gradually lost competitiveness. At the same time, intensified market segments, and the pursuit of personality value have become the new market demand, and it prompts the manufacturing enterprises to integrate internal and external resources in the design, to include research and development, to improve the whole services value chain and to change “single core competitiveness” to “ecological synergy competitiveness”. Furthermore, the manufacturing industry has to adopt “crowd-funding”, “crowd-sourcing” and “flexible production” in order to efficiently meet customer needs.

8.4 The Effective Path of Made in China 2025: Sharing Economy Mode Based on the Core Competence of Enterprises Jeremy Rifkin, an American economist, said that “the sharing economy has brought about a resources revolution which can change human’s life style, it brings about a new way of economic life, which will surpass the traditional market mode”. Sharing economy

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emphasizes mutual creation, mutual ownership, mutual sharing and mutual benefit. It is based on the core competitiveness of enterprises, forms the ecological system, enforces the enterprise’s leadership in its industry, continues to seek sources of value which are different from the traditional industry structure, or competitive position. It attracts heterogeneity of relevant interest parties, and increases complementarities and reciprocity so that the manufacturing industry can get rid of the traditional single, closed core competitiveness. It can enlarge adaptability and form cooperative competitive advantages. The mode of production and manufacturing in the global manufacturing industry is at the junction of the old modes of production transforming to new ones. The core of manufacturing change is from exclusiveness to sharing, and the modes are transforming from the large-scale, centralized, homogeneous and one-way traditional production mode to small batch, decentralized, personalized, participatory modes; in this process, many business opportunities and innovative modes are going to arise.

8.4.1 Innovation Sector in Manufacturing Industry: Internal and External Resources Sharing With the development of Sharing Economy, support platforms of mass entrepreneurship and innovation are increasing; the modes of public entrepreneurship, crowd-sourcing, collective support and crowd-funding emerge in an endless stream. The government can take a lead to establish new sharing modes of new scientific instruments, such as scientific instrument sharing, scientific talents and service sharing, scientific consulting and cooperative research. To expand and deepen cooperation with domestic and foreign scientific and technological resource sharing platforms (and to establish science and technology resources sharing network service systems) manufacturing enterprises can integrate internal and external resources, absorb the innovation power, build resource pools, patent pools, and standard pools across departments, fields and regions of government enterprises, school enterprises, companies and individuality, in order to form new R&D modes of network crowd-sourcing, cloud design, collaborative design and costumers’ participation in design which integrates industry-university-research. Meanwhile, in a market-oriented manner, the government encourages high-tech enterprises, characteristic industrial parks and research institutes to share the hardware and software resources, such as large-scale scientific instruments, laboratory environment, inspection and testing capabilities through “scientific and technological innovation coupons” and other modes. Through integration, the innovation task can be designed and completed by the traditional manufacturing industry, which is open to the external resources and public. Enterprises can reduce R&D costs, shorten the development cycle and improve R&D productivity. Thus, customers can also get more satisfactory products. So, e.g., the Haier Group of China, who adheres to the idea that “the world is our R&D center” and takes the HOPE innovation platform to stimulate the “maker” vitality inside and outside of the

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enterprises, and closely interacts with the customers, in order to develop a large number of innovative products favored by the market.

8.4.2 Production Sector of Manufacturing Industry: Mutually Shared Benefits of Spare Capacity Through the internet, manufacturing enterprises fully combine their advantages and weaknesses; especially through equipment capability sharing platforms, such as ­self-production and third parties, they can optimize their capacity; enterprises can rent equipment on demand; by renting instead of purchasing, payment is based on time consumption. It forms the new manufacturing mode of equipment leasing and plant sharing. In this mode, small and medium-sized enterprises do not need to invest high expenditures to buy equipment, the idle time of the factories can also be used effectively in order to achieve the optimal combination of production factors and production conditions. Due to its late start, the sharing economy in China’s manufacturing sector has not yet formed the market scale. However, representative platforms such as the “i5 Intelligent Machine Tool Control System” of Shenyang Machine tool plant, and “Tao factory” of the Alibaba group have already lead the small and medium-sized enterprises and entrepreneurs upstream and downstream to enjoy the sharing economy bonus. The “i platform” made by Shenyang Machine tool plant (which is based on the i5 intelligent machine tool control system) can be paid according to the products and working time. It carries out machine leasing and recycling re-manufacturing business, which has realized the transformation from the purchase of machine tools to the purchase of machine tool processing capacity, i.e. from the “ownership of machine tools” to the “right to use the machine tools”. In addition, according to the efficiency of the machine tools used by the costumers, the idle time of machine tools can be shared as well.

8.4.3 Market Operation of the Manufacturing Industry: Business Mode for Mutually Creating and Sharing Value From the point of view of the “new normal” of China’s economy, China’s manufacturing industry is facing a difficult transition. Thus, it is steadily advancing. The main tasks are to cut excessive industrial capacity, to cut storage, to leverage, to reduce the cost and to improve weak links. Innovations of the business mode can bring forward new economic growth for China’s manufacturing industry; this mode adheres to ­“customer-centered thinking”, transforms the traditional supply and marketing relationship into a business mode of platform; it transforms from “stand-alone” to “a complete set” and provides customers with a system solution integrated with R&D, design, production and ­after-sales service; it exchanges the sale of products with the sale of services. Thus, it

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provides opportunities to enhance the brand value and interests of enterprises, and it also improves the comprehensive management level. The authors of this chapter suggest the government to support the establishment of third-party manufacturing network sharing platforms for small and medium-sized enterprises (such as B2B, C2B). In addition, they suggest to promote full docking of small and medium-sized enterprises manufacturing resources and the internet platform. To implement the off-line execution of professional service search, supply and demand docking, and outsourcing service of the design for manufacturing enterprises, manufacture test, experiment, maintenance, simulation, certification in order to realize the industrial service sharing by O2O mode, supply capacity of small and medium-sized enterprises will be enhanced flexibly and efficiently and their responses to the market are quickened.

8.5 Conclusion Made in China 2025 is a unique product of China’s national conditions. The rapid development of Sharing Economy is an effective way to realize the coordinated development of China’s economy and society. Although there are many problems, such as imperfect credit mechanism, imperfect legal system, and imperfect regulatory measures, it is without doubt that “Chinese manufacturing + Sharing Economy” will be a new strategic opportunity. At present, China is the world’s largest manufacturing country with the largest amount of internet users. It will be a feasible path for the healthy and sustainable development of the economy and society in the future: • to organically combine mass production with personalized needs, • to take the lead in realizing the transformation of production mode, • to create a new space for development and new mode for development of the manufacturing industry, • to develop the enterprises’ unique “leadership and competence” and • to promote the development of sharing economy in the manufacturing sector; then, mutual benefits of interest parties can be achieved.

References and Additional Literature China’s Sharing Economy Working Committee. (2017). China’s sharing economy development report. National Information Center, 2017, 4–12. Li Keqiang, Annual Government Work Report 2016 (2016). Beijing: National People’s Congress of the People’s Republic of China (NPC). Negroponte, N. (1996). Being digital. London: Hodder & Stoughton.

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Rifkin, J. (2014). The zero marginal cost society: The internet of things, the collaborative commons, and the eclipse of capitalism (Chinese version), China Critic Press. Tencent Research Institute. (2015). Internet plus report: The manufacturing industry, tisi net. The State Council of the PRC. (2015a). Made in China 2025, China Xinhua Net. The State Council of the PRC. (2015b). Suggestions on policies and measures to vigorously promote the mass entrepreneurship and innovation. Xinhua Net. The State Council of the PRC. (2016). Guidance on deepening the integrated development of manufacturing and internet, China Xinhua Net. Weitzman, M. L. (1986). The share economy: Conquering stagflation, income, wealth, and the maximum principle (Chinese Version), China economic publishing house.

Part III Digitalization, Big Data, and Regional Aspects

9

A Study on the Effect of Basic Public Services in China on the Net Migration Rate of the Provincial Population Based on the Analysis of a Provincial Spatial Panel Model Zhang Yue and Sun Xiaofang

Contents 9.1 Problem Statement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 9.2 Rationale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 9.3 Analysis of the Spatial Pattern and Development Characteristics of Migration and Basic Public Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 9.3.1 The Spatial Distribution of Migration and Basic Public Services. . . . . . . . . . . . . . 104 9.3.2 Spatial Autocorrelation Analysis of the Net Migration Rate of the Inter-Province Population and Basic Public Services. . . . . . . . . . . . . . . . . . . . . . . 107 9.4 Influencing Factors of Spatial Development of Population Net Migration. . . . . . . . . . . . . 113 9.4.1 Variable Selection and Preliminary Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 9.4.2 Model Establishment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 9.4.3 Model Estimation and Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 9.5 Conclusion and Policy Recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 9.5.1 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 9.5.2 Policy Recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Abstract

This chapter introduces the Spatial Econometric Model (OpenGeoDa). The OpenGeoDa is applied to the analysis of the spatial distribution and evolution Y. Zhang (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] X. Sun (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_9

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mechanism of net migration and how this is linked to the education and medical care level in a specific region. In this research a pooled panel regression is carried out based on the collected panel data from 2000 to 2011. The research shows that the development of the basic public services has a significant impact on the net migration rate of the inter provincial population, and the trend is gradually increasing. However, the effect of per capita GDP and other economic factors on migration in China is declining. In China, more attention should be paid to the non-economic factors, such as the basic public service, to direct the rationale of the population for migrating.

9.1 Problem Statement Since the financial crisis in 2008, the problem of “labor shortage” in China, especially in the Eastern coastal cities, has become increasingly prominent. In a survey on the choice of university students’ employment, the most attractive provinces and municipalities are the coastal regions like Guangdong, Zhejiang and Jiangsu, but Xinjiang, Inner Mongolia, Jiangxi and Henan also rank among the top ten. Beijing, Tianjin and Shanghai, on the other hand, have become the cities with the lowest migration rates (Cebula and Alexander 2006). The first-tier cities in the north of the country are shifting towards becoming second-tier cities due to the pressure of rising housing prices, rising prices of consumer products, and rising living costs for instance for medical care and education. In addition, migration in China has shown the obvious ‘family-related’ characteristics. In 60% of families, spouses and children move along with them. In the married new-generation floating population, the proportion of spouses migrating together accounts for nearly 90%. The number of elderly migrants has also increased gradually. It has exceeded 10 million and there is still a growing trend (Florida et al. 2011). There is an increased demand for public services such as medical care and education and at the same time a motivation to change employment with ‘family-related’ migration. This makes it necessary to study the mechanism and evolution of the impact of basic public services on population migration.

9.2 Rationale The current research on population migration mainly focusses on numbers of migrating people and the development of spatial patterns as well as their influencing factors. However, among the influencing factors of population migration, most of the early research analyses focus on inter-regional economic factors. As Tiebout (1956) put forward a “vote by foot” argument on population migration and the supply of public goods, there is a growing amount of literature on public services and their link to population migration. Tiebout pointed out that when employment opportunities are equal, people are

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more likely to migrate to areas which provide their preferred public services in order to maximize utility. The American scholar Richard Florida (2011) conducted a “Survey on the Degree of Dwelling Place and Happiness” in his country to show that Americans regard the basic services (education, medical care, housing and road traffic) and the aesthetics (physical environment, public facilities and other cultural facilities) as very important. Of course, this is not the case with other economic factors. Studies by Cebula and Alexander (2006) show that the net immigration rate in a region is positively correlated with the per student expenditure on primary and middle school education in this region. John et al. (1995) conducted a microcosmic investigation of the relocation of residents in London, England, and found that public services will, to a certain extent, affect the relocation behavior. Its importance however is lower than the purchase of the first real estate and other factors. Research on the influence of public service on population migration started later in China. Luo (2009) finds that the role of the survival instinct in human migration has decreased, while the equalization of public service space that the immigrants can enjoy has become a crucial motivation for relocation. The inequality of public services is the financial reason of population migration. If a society achieves the equalization of public services, the quantity and order of population migration will be controlled to a certain extent. Tang and Liang (2009) studied the relationship between inter-provincial migration and local public expenditure by establishing a gravity model. The results show that local public expenditure had no significant effect on population migration before 2000 but show an effect between 2000 and 2005. Before 2000 migration was predominantly affected by the pull-in force, but after 2000, it was mainly driven by thrust. Zhang et al. (2013) took Anhui Province as the research object and constructed a net population migration index, establishing a multiple regression model to study the factors of population migration. The results show that the main push-pull factors affecting population migration in the Anhui Province are the proportion of urban employees, the distribution of labor force in the three sectors and the number of urban parks. Ma et al. (2012) studied the impact of the transport infrastructure, based on a gravity model on population migration using 1987, 1995 and 2005 population migration panel data. The results show that the level of traffic development has a positive effect on the free flow. Furthermore, the results reveal that the rational allocation of population has a significant role in promoting migration. From the review of the above literature, we can deduct that the current research on public services and population migration are still relatively diverse in focus. There is no final conclusion on the choice of public service variables. This chapter thus uses the basic public services as a starting point and introduces the spatial measurement model. The impact of education and medical treatment on population migration provides reference for the government to formulate basic public service policies to guide the population to flow reasonably.

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9.3 Analysis of the Spatial Pattern and Development Characteristics of Migration and Basic Public Services 9.3.1 The Spatial Distribution of Migration and Basic Public Services In this chapter, the net migration rate of inter-provincial population is chosen as the index of population migration. The net migration rate of the inter-provincial population is calculated in proportion to the resident population in the province (unit: ‰). It is the difference between the number of people moving in and out of a province in a specific period within a certain timeframe. We selected education funding and number of beds per thousand medical institutions as a measure for basic indicators of public services. The quartiles of the above three indicators in 2000 and 2011, respectively, are calculated in OpenGeoDa as follows.1 The quartile maps (Fig. 9.1, 9.2, 9.3, 9.4, 9.5 and 9.6) show the differences in the spatial distribution and the evolution of these differences between migration and basic public services. In 2000, the only provinces with a high net migration rate were Beijing, Guangdong, Shanghai and Xinjiang. In 2011, in addition to Beijing, Guangdong, Shanghai and Xinjiang, some central provinces such as Ningxia, Chongqing and Guizhou provinces also had high net migration rates. Qinghai was the only province with a relatively low net migration rate of the inter-provincial population in 2000, whereas the

Quantile: JQ2000 [-2:-2] (1) [-1:-1] (6) [0:0] (17) [1:1] (3) [3:7] (4)

Fig. 9.1  Distribution of net migration rate of the provincial population in 2000

1The

net migration rate of inter-provincial population is calculated based on data provided by “Population and Population Statistics of Sub-districts and Cities of the People’s Republic of China” (2000 and 2011); education expenditure and number of beds per 1000 medical institutions are calculated based on data provided by the China Statistical Yearbook (2001, 2012).

9  A Study on the Effect of Basic Public Services in China … Quantile: JQ2011 [-5:-2] (4)

[-1:-1] (0) [-1:0] (15) [1:2] (6)

[3:10] (6)

Fig. 9.2  Distribution of net migration rate of the provincial population in 2011

Quantile: EDU2000 [8.16:53.53] (6) [58.09:79.46] (6) [90.29:122.6] (7) [146.3:170.9] (6) [200.9:361] (6)

Fig. 9.3  Distribution of educational funds by province in 2000

Quantile: EDU2011 [82.61:413.6] (6) [429.4:504] (6) [549.5:684.4] (7) [710.6:844.8] (6) [1024:1885] (6)

Fig. 9.4  Distribution of educational funds by province in 2011

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Distribution of beds per thousand medical institutions in various provinces in 2011 Quantile: MED2011 [3:3] (0) [3:3] (9) [3:3] (17) [4:4] (0) [5:8] (5)

Fig. 9.5  Distribution of number of beds per thousand medical institutions in various provinces in 2000

Distribution of beds per thousand medical institutions in various provinces in 2000 Quantile: MED2000 [1.57:2.18] (6) [2.19:2.32] (6) [2.36:2.64] (7) [2.66:3.39] (6) [3.45:5.67] (6)

Fig. 9.6  Distribution of number of beds per thousand medical institutions in various provinces in 2000

net migration rate of Qinghai Province significantly increased in 2011. Gansu, Shanxi, Heilongjiang and Jilin were the provinces with relatively low net migration rates. In 2000, the regions with higher education funds were mainly concentrated in the provinces of eastern China, such as Liaoning, Beijing, Shandong, Jiangsu, Zhejiang and Guangdong. In 2011, the regions with relatively higher education funds gradually spread to central China. Henan, Hunan, Sichuan and Anhui provinces have also entered the ranks of higher education funding. In 2000 and 2011, the Western regions of Tibet, Qinghai and Gansu provinces were among the provinces with the lowest education funds. In 2000, the

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distribution of the number of beds per thousand medical institutions in various provinces in China was significantly different, among them, Xinjiang, Shanxi, Beijing, Tianjin, Jilin and Shanghai rating at the top. However, by 2011, the distribution gap between the number of beds was obviously reduced. Except in Jilin, Beijing, Tianjin, Shanghai and Xinjiang, the number of beds per one thousand medical institutions had risen, while in the other provinces it was evenly distributed ranking them third and fourth. Overall, the level of development of education and medical care in China is comparable to the development of the population migration, all of which have spread from a few developed cities to the central provinces. Provinces with higher levels of education and medical care often correspond with higher net migration rates of the inter-provincial population.

9.3.2 Spatial Autocorrelation Analysis of the Net Migration Rate of the Inter-Province Population and Basic Public Services Spatial autocorrelation analysis examines whether there is an agglomeration or contiguity of population migration and basic public services in a specific area, which is the prerequisite for establishing a spatial econometric model. To study the spatial autocorrelation of variables, we first need to establish the spatial weights. In this chapter, a new spatial adjacency weight matrix is created under OpenGeoDa. When two regions have a common boundary, the spatial weight matrix factor is defined, otherwise, the spatial weight matrix factor value is defined. After building the spatial weights, the space lag index needs to be established in OpenGeoDa, that is, the weight matrix is multiplied with this index. This chapter analyzes the spatial autocorrelation from the perspectives of the spatial agglomeration effect of the population net migration and the basic public services, as well as for the degree of local relevance. Analysis of the Spatial Agglomeration Effect of the Net Population Migration and Basic Public Services Moran’s I is a commonly used measure for global spatial autocorrelation. It is used to test the correlation between adjacent regions throughout the study area, calculated as:

I=

n

n n



¯ ) xj − x¯ i=1 j=1 wij (xi − x n n n ¯ )2 i=1 (xi − x i=1 j=1 wij



=

n n i=1



¯ ) xj i� =1 wij (xi − x n n 2 S i=1 j=1 wij

− x¯



(n is the number of spatial units in the study area; xi and xj are the value of a property in the region; wij is the spatial weight matrix; n  x = n1 xi is the average of the property value;

x=

1 n

i=1 n  i=1

xi is the variance of the property value)

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Figure 9.7, 9.8, 9.9, 9.10, 9.11 and 9.12 show the scatter plots of Moran’s I and Moran, calculated by OpenGeoDa and plotted by Moran’s I and Moran for three indicators in 2000 and 2011: the provincial net migration rate, education expenditure and number of beds per thousand medical institutions. This shows that there is a certain spatial autocorrelation among all the variables. Among them, the Moran’s I of the net migration rate of inter-provincial population is significantly higher than that of 2000 and 2011. The spatial autocorrelation shows a tendency to increase, indicating that the large-scale direction mobility feature of the Chinese population is becoming more and more prominent. The Moran’s I value of education expenditure has a small variation, basically maintained at about 0.2. The Moran’s I value of the number of beds per one thousand medical institutions is lower than that of 2000 and 2011. This may be due to the equalization policy of medical and health services implemented in China. The spatial randomness of the

Fig. 9.7   Moran’s I and Moran scatter plots of net migration of the provincial population in 2000

Fig. 9.8   Moran’s I and Moran scatter plots of net migration of the provincial population in 2011

9  A Study on the Effect of Basic Public Services in China … Fig. 9.9   Moran’s I and Moran scatter plot for the educational expenditure 2000

Fig. 9.10   Moran’s I and Moran scatter plot for the educational expenditure 2011

Fig. 9.11   Moran’s I and Moran scatter plots per 1000 hospital beds in 2000

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Fig. 9.12   Moran’s I and Moran scatter plots per 1000 hospital beds in 2011

medical level becomes apparent. The results of the global spatial autocorrelation show that there are spatial agglomeration effects in China’s population migration and basic public services. Local Correlation Analysis Between Migration and Basic Public Service Local spatial autocorrelation analysis is the spatial distribution of an attribute value. It is usually measured by the Local Moran’s I, which indicates the local correlation between a region and its surrounding. The local Moran’s I (LISA) formula for the region is:

Ii =

(xi − x¯ )  Wij (xj − x¯ ) S2 i�=j

(n is the number of spatial units in the study area; xi and xj are the value of a property n  in the region; wij is the spatial weight matrix; x¯ = n1 xi is the average of the property n i=1 1  2 2 value; S = n (xi − x¯ ) is the variance of the property value). i=1

Figure 9.13, 9.14, 9.15, 9.16, 9.17 and 9.18 show LISA plots of local spatial autocorrelations between the three variables in 2000 and 2011. We can thus deduct, that all three variables show a certain degree of agglomeration and correlation. At the 0.05 level of significance, only Xinjiang and its surrounding areas showed a high-low concentration in 2000, while Shaanxi Province and its surrounding areas showed low-low concentrations. In 2011, the spatial agglomeration of the net migration of inter-provincial population further highlights that the provinces of Inner Mongolia, Shaanxi and Henan showed low-low agglomeration along with the surrounding areas, high-high agglomerations of Tianjin and the surrounding areas, and no more high-low agglomeration for Xinjiang. In 2000, the distribution of educational expenditure in Xinjiang, Qinghai and Gansu provinces showed a pattern of low-low agglomeration. Sichuan and its surrounding areas

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LISA cluster map: not significant high-high (0) low-low (1) low-high (0) high-low (1) neighborless (1) Fig. 9.13  LISA aggregation map of interim provincial population net movement rate in 2000

LISA cluster map: not significant high-high (0) low-low (1) low-high (0) high-low (1) neighborless (1) Fig. 9.14  LISA aggregation map of interim provincial population net movement rate in 2011

LISA cluster map: not significant high-high (0) low-low (1) low-high (0) high-low (1) neighborless (1) Fig. 9.15  LISA aggregation map of education expenditure in 2000

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LISA cluster map: not significant high-high (0) low-low (1) low-high (0) high-low (1) neighborless (1) Fig. 9.16  LISA aggregation map of education expenditure in 2011

LISA cluster map: not significant high-high (0) low-low (1) low-high (0) high-low (1) neighborless (1) Fig. 9.17  LISA aggregation Map of the number of beds per thousand medical institutions in 2000

LISA cluster map: not significant high-high (0) low-low (1) low-high (0) high-low (1) neighborless (1) Fig. 9.18  LISA aggregation Map of the number of beds per thousand medical institutions in 2011

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showed high-low agglomeration while Shanghai and Jiangsu showed ­high-high agglomeration patterns. Anhui, Jiangxi, Fujian and their surrounding areas showed a low-high agglomeration mode. In 2011, the local spatial distribution pattern of educational funds in Xinjiang, Gansu, Sichuan, Jiangxi and Fujian did not change, except for Jiangsu and Shanghai. Shandong, Anhui and their surrounding areas also showed ­high-high concentration. As for the provinces with high net migration rate, the basic areas of education and high funding coincide. The LISA chart of the number of beds per one thousand medical institutions in 2000 shows, that except for Hebei and its surrounding areas with lowhigh concentration, a large area of Hubei, Chongqing, Jiangxi, Hunan, Yunnan, Guizhou and Guangxi showed other forms of concentration. In 2011, the spatial distribution of medical care improved. Sichuan became a low-low agglomeration province. However, Chongqing, Guizhou, Guangxi and Jiangxi are no longer low-low agglomeration patterns. Xinjiang and its surrounding areas showed a high-low concentration of the distribution, which is consistent with Xinjiang being a large province of population migration.

9.4 Influencing Factors of Spatial Development of Population Net Migration The third part of this chapter visualized the spatial distribution of the net migration of the inter-provincial population and basic public services in China in 2000 and 2011. The following part will continue to investigate in depth the extent to which the basic public services affect the population migration. The collected data is divided into two time periods (2000–2005 and 2006–2011) and is then respectively regressed to compare whether the mechanism of the impact of basic public services on population migration has changed over time.

9.4.1 Variable Selection and Preliminary Analysis The purpose of this chapter is to examine the mechanism behind the impact of basic public services on population migration and to question whether this impact has changed as time progresses. This chapter also seeks to investigate the differences concerning the level of development in all regions. Based on this, the author uses the above-mentioned provincial net population migration rate as an explanatory variable of the two indicators of basic public services: the education expenditure and the number of beds per thousand medical institutions. In addition, the per capita GDP, urbanization level (urban), ­non-economic factors of traffic density (traf, which is calculated by dividing the total number of miles of highways, railways and inland waterways in all provinces by the size of the area), and the local general budget expenditure (fe) are also used as control variables for regression analysis.

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As economic development and people’s awareness increase, individual d­ ecision-making begins to focus on the pursuit of quality of life. Therefore, it is expected that the two indicators of basic public services, namely education and medical care, will both have a positive impact on population migration. Among other control variables, per capita GDP and the urbanization rate can measure the level of economic development in a region. A high level of the two indicators, the prosperity of a region and the state of public infrastructure, are expected to play a positive role in population migration. A high density of traffic network, enabling more developed traffic in the region, provides a favorable precondition for population migration. It is also assumed that the density of the traffic network increases to the same extent as the population mobility. Where the general budget expenditures of the local governments are high, the project funds benefiting the relocated population, may also be relatively increased. Therefore, the preliminary assessment of the expenditures on local general budgets will also have a positive impact on the population migration. In addition, we believe that individuals will pay more and more attention to the quality of life and children’s education. In the course of time, the impact of basic public services will gradually increase in population migration ­decision-making. However, the impact of economic factors such as per capita GDP will decline correspondingly.

9.4.2 Model Establishment Three different models are chosen in this chapter to examine the impact of public social services on population movements in detail. 1. Common Space Hybrid Panel Model (OLS):

yit = xit β + ε

y is the dependend variable, x is the independent variable, β is the explanatory variable coefficient, ε is the random error vector and obeys the standard normal distribution, i represents each province and t represents the year.

2. Mixed effects of space lag model (SLM):

yit = ρwyit + xit β + ε

y is the explanatory variable, w is the spatial weight matrix, wy is the explanatory variable of space lag, ρ is the spatial regression coefficient, x is the explanatory variable, β is the explanatory variable coefficient and ε is the random error vector. The model mainly explains whether the variables have Spillover Effect.

3. Spatial Error Model (SEM) for Mixed Effects:

εit = W εit = µit

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ε is the random error vector,  is the spatial error coefficient of the vector of explanatory variables, and µ is the random error vector of the normal distribution. This model mainly explains the degree of influence of the error impact of the explanatory variables on the observed values in the area.

9.4.3 Model Estimation and Analysis Based on the above three models, the data obtained in this chapter is regressed in Matlab. Table 9.1 shows the regression results after finishing. The regression results in Table 9.1 show that in all three models, the indicators of public social services, education and medical coefficients are positive. In the SLM model, the coefficients all pass the significance test of 1%, which is in line with the expectation. A sound education and the level of medical care will have a positive effect on individuals’ migration decisions. Among other control variables, GDP per capita,

Table 9.1  2000–2011 mixed panel regression results Variable

2000–2011 OLS

SLM

SEM

lnedu

2.0097c

0.3713c

0.1269

med

0.9726c

0.7906c

0.8169c

GDP

0.5990c

0.4178c

0.4736c

urban

0.0119

0.0281b

0.0329c

traf

0.7143c

1.0968c

0.6691a

lnfe

−3.0592c

−1.5009c

−0.9833c

ρ

0.1010a

0.3120c



R2 LogL a, b, c

0.6346

0.6086

0.5882

−68

−679.8

refer to the 10%, 5%, 1% significance test respectively Due to the intercept of the regression results, the space model is omitted in this article, and the results of the intercepts in the OLS are not listed in this table. The data of net migration rate of interprovincial population come from “Sub-counties and Municipal Population Data” (2000–2011) (State Statistical Bureau of China (diff. issues)); the data of other independent variables are respectively from China Statistical Yearbook 2001–2012, Data compilation (State Statistical Bureau of China (diff. issues)), the official website of the National Bureau of Statistics collected directly or calculated. In order to avoid any large discrepancy between the numerical values caused by the existing numerical values (such as education expenditure) and the ratio values (such as the rate of urbanization) in the data used, this chapter made logarithmic treatment to education expenditure and public budget expenditure indicators

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urbanization rate and traffic developed level also have a positive impact on population migration, but the coefficient of local general budget expenditure is negative. Contrary to the expectation stated previously, this shows, to a certain extent, that, in the provinces’ yearly budget distribution, migrants are not benefitting enough to attract more people to move to the area. On the other hand, local budgets are not an important factor to be considered by individuals in making relocation decisions. The regression results of the SLM and the SEM models show that SLM had a large R2 and all the coefficients passed the significance test. Therefore, the SLM model was preliminarily judged to be superior. That is to say, the spatial spillover mechanism affected the net population migration with the effect coefficient of 0.10.

9.5 Conclusion and Policy Recommendations 9.5.1 Conclusion As a spatial phenomenon, population migration is assumed to follow certain spatial patterns. In this chapter, conclusions are drawn through spatial visualization analysis and spatial panel model analysis of population migration and basic public services, with the following results: 1. The distribution of the basic public services education and medical care in a region is basically the same as that of the inter-provincial population. Educational funds and the number of beds per 1000 medical institutions are at a high level in China’s eastern coastal cities and in Xinjiang. Correspondingly, they have also become areas with high inter-provincial population migration rates. Nevertheless, provinces such as Inner Mongolia and Gansu have lower medical expenditures and a lower level of education and hence also have become areas with a low net migration rate of population. When comparing the data of 2000 and 2010, the northeastern provinces of Heilongjiang and Liaoning may have relatively lower levels of education and medical care because of heavy industry restructuring and other factors, and their net population migration rate declined, corresponding to that of the whole country. In addition, some central provinces, such as Sichuan and Hunan, have also become areas with a high net migration rate of population. 2. Basic public services mainly affect the population migration through the mechanism of spillover. Regarding the regression results, both, the education and the medical level, have a positive impact on the inter-provincial population net migration rate and passed the test of significance. Therefore, the improvement of basic public services, such as regional medical care and the education level, can form an incentive for population migration. 3. The positive effect of basic public services on population migration has tended to be stronger. From the regression results of sub-time periods, the impact of basic public

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services on the population net migration increased while the impact of per capita GDP on population net migration decreased, indicating that among the factors affecting migration decision-making, the impact of the factors such as basic public services is on the rise.

9.5.2 Policy Recommendations Based on the conclusion of the study, this chapter argues that appropriate countermeasures in the following two aspects can be taken to guide the reasonable flow of population: First, we will continue to promote the equalization of basic public services. The government should reverse the past situation of passive provision of public services to address population agglomeration and increase education and medical investment in provinces with high population displacements in the central and western regions, as a policy for retaining qualified personnel and developing the economy. The same can also alleviate the imminent shortage of public services in metropolitan cities caused by too many people moving into big cities. Second, the authors of this chapter consider it as advisable to formulate preferential public service policies to attract talented people. In response to the current situation of family relocation in our country, enterprises may cooperate with the local government or apply for financial appropriation to attract talents through the provision of family-owned apartments, providing work for spouses and education for the children of workers and employees, as well as building schools. The above research confirms that the improvement of basic public services affects the population net migration rate in the specific region and that this effect has a tendency of further enhancement. It is of some reference significance to optimize the urban construction to guide the population to flow reasonably. However, this research still has some limitations: Due to limited data, this chapter only studies the mechanism of basic public services and population migration of 2000 and 2011, and it is difficult to examine the role of renewal between the two. In addition, only education and medical indicators were chosen in terms of basic public services. For further research in this area, and to draw more encompassing conclusions, it seems advisable to examine whether these public services can be distributed fairly between the local population and the immigrating population.

References Cebula, R. J., & Alexander, G. M. (2006). Determinants of Net Interstate Migration. 2000–2004 Armstrong Atlantic State University-USA. Special Section on Migration-JRAP, 36 (2), 116–123. Florida R., Mellander C., & Rentfrow P. J. (2011). The happiness of cities. Regional Studies, 2011 (4), 1–15. https://doi.org/10.1080/00343404.2011.589830.

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John, P., Dowding, K., & Biggs, S. (1995). Residential mobility in London: A micro-level test of the behavioral assumptions of the tiebout model. British Journal of Political Science, 25(3), 379–397. Luo 2009: 罗鸣令.公共服务非均等化_人口迁移的财政制度原因[J].经济论坛, 2009(16), 14–18. Ma et al. 2012: 马伟,王亚华等.交通基础设施与中国人口迁移:基于引力模型分析[J].中国软 科学, 2012 (3), 69–77. State Statistical Bureau of China. (diff. issues from various years). China statistical yearbook 2001–2012. Beijing: China Statistics Press. Tang and Liang 2009: 汤韵,梁若冰.中国省际居民迁移与地方公共支出—基于引力模型的经验 研究[J].财经研究, 2009 (11), 16–25. Tiebout, C. (1956). A pure theory of local expenditures. Journal of Political Economics, 64(5), 416–424. Zhang et  al. 2013: 张苏北,朱宇.安徽省内人口迁移的空间特征及其影响因素[J].经济地理, 2013 (5), 24–30.

Additional Literature 中金网.人口迁移 中国硬伤[EB/OL]. http://gold.hexun.com/2015-10-26/180120408.html. Accessed 26 Oct 2015 相惠莲.财政已成人口发展主导因素 流动人口公共服务却处境尴尬[J].财经, 2015年11月4日. 理查德·弗罗里达.你属哪座城[M]. 北京:北京大学出版社, 2009.

On the Symbiotic Relationship Between the Equipment Manufacturing Industry and Producer Services of Shanxi Province

10

Hao Wangli

Contents 10.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 10.2 Theoretical Analysis and Hypothesis Presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 10.2.1 Literature Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 10.2.2 Analysis and Hypothesis of The Industrial Symbiosis Mechanism. . . . . . . . . . . 122 10.3 Empirical Analysis of The Symbiosis Between The Equipment Manufacturing Industry and The Producer Service Industry in Shanxi Province . . . . . . . . . . . . . . . . . . . 124 10.4 The Symbiotic Development Relationship Between The Equipment Manufacturing Industry and The Producer Service Industry. . . . . . . . . . . . . . . . . . . . . . . 127 10.4.1 Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 10.4.2 Interactive Property: Analysis of The Coefficient of Influence and Induction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 10.4.3 Analysis of the Coordination Degree. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 10.5 Policy Suggestion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 10.5.1 Constructing The Ecological Industry Chain of Equipment Manufacturing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 10.5.2 Strengthen The Ability of Innovation and Vigorously Develop The Emerging Productive Services. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

Abstract

To support building a symbiotic relationship assessing system, this chapter analyses the integration and interactivity between the equipment manufacturing industry and producer services of Shanxi Province using the input-output approach. Employing W. Hao (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_10

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the coupling function, a coupling coordination model is constructed to assess the coupling co-ordination between the industries. The evaluation of the symbiotic relationship is then used as reference to make suggestions for the equipment transformation and upgrading in Shanxi province.

10.1 Introduction Since 2013, a time of slow national economic growth, Shanxi’s economy has experienced a sharp slowdown. Shanxi Province is a typical resource-based economy, and its manufacturing industry, the basis of the economy, reflects its productive level. However, in 2014, the manufacturing industry solely accounted for 34% of its added industrial value. To fundamentally change the dependency of the industry’s development on resources, we must choose industries for promotion and development, that cater toward innovation and have a motivating effect on a large scale. The equipment manufacturing industry features characteristics of a strong industrial correlation, great motivation and capital-intensive technology and is therefore undoubtedly the engine to improve Shanxi’s comprehensive strength and to advance the industrialization process. German manufacturing and its equipment manufacturing industry rank first in worldwide comparison. The essence of Germany’s Industry 4.0 is the intelligent manufacturing production and the extension of the value chain upstream and downstream. It combines Germany’s powerful equipment manufacturing with information technology as well as scientific and technological research and development. It rearranges the original industry value chain. This requires linking manufacturing, especially the equipment manufacturing industry, with the production services industry, and importing human capital and intellectual capital in producer services to upgrade and further develop the manufacturing and equipment manufacturing industry. Shanxi is the old industrial base of China. The equipment manufacturing industry has always been its pillar industry, so Shanxi has a certain industrial foundation. An upgrading and development of Shanxi’s manufacturing industry could become a model for an upgrading and development of the industrial structure in other regions. We need a breakthrough in Shanxi’s resource development path, starting with the equipment manufacturing industry, supporting the development of the service industry, and building a well-coordinated symbiotic system with the equipment manufacturing industry and the production service industry. But there are no ready-made development paths to be followed in our province for the equipment manufacturing industry’s development and the symbiotic development with the productive service industry. There is also no similar development model of the resource economy to draw upon. Therefore, we must firstly analyze these two industrial symbioses and then present feasible and effective countermeasures. That is this chapter’s practical significance. At the same time this chapter is a study of a typical resource-based economy. It adds value by offering a theoretical analysis of a regional case of the interactive and integrated development of

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the equipment manufacturing industry and productive service industry, and by providing a theoretical reference for the transformation and upgrading of the resource economy.

10.2 Theoretical Analysis and Hypothesis Presentation 10.2.1 Literature Review The development level of the fundamental and strategic equipment manufacturing industry often determines the competitive level and the industrialization process of the national or regional industry. The equipment manufacturing industry features high industrial correlativeness, great motivation for development, intensive use of technology and capital, among other factors, and is a powerful driving force for other industries. As a result, recent research focusses more on the interactive and integrated development of the equipment manufacturing industry and other industries, especially the productive service industry. Foreign scholars have analyzed the link between equipment manufacturing and product-oriented services from the viewpoint of expansion of, and interaction between, the two. Guerrieri and Meliciani (2003) argue that the latter is the expansion of equipment manufacturing, whose expanded demands and division promote the growth of ­product-oriented services. Eswarran and Kotwal (2002) claim that equipment manufacturing relies more and more on product-targeted services, such as division and professionalism development. Scholars, including Baines et al. (2007) point out that, as the two types of industries integrate and interact more, a symbiotic relationship seems to develop. In reality, product-oriented services and equipment manufacturing develop as a whole, and this reflects that manufacturing is becoming more service-oriented. Sturgeon et al. (2008), guided by the global value-chain theory, states that the expansion of equipment manufacturing has enhanced the interaction with product-oriented services. Mani (2012) also conducted research on this interaction in developing countries. Publications on this topic in China are mainly based on empirical research. Liu Hao (2010), after the determination and differentiation of their symbiotic behavior and regional differences, points out that the two industries are asymmetrically ­mutually-symbiotic. Liu Mingyu (2010) discovered that the coordination between these two industries has efficiently improved the performance of the value chain in productoriented services. Chu Mingqin (2013), whose research is based on analyzing input-output tables, points out the strong forward and backward linkage effect in the equipment manufacturing of our country, and that a forward linkage in the product-oriented service sector is more noticeable. Chen Xiaofeng discovered from the co-aggregation index for the two industries that both the aggregations accordingly show a remarkable pathdependency. Wang Chengdong (2015), using SFA and Cobb-Douglas analysis, built a model for evaluating factors that influence the merger of equipment manufacturing and product-oriented services, and analyzed relative statistics of about 30 provinces and

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cities. Qi Liangqun (2015) applied UDA to perform analysis on the performance, characters and routines of the interaction between the two industries. Apart from analyzing the equipment manufacturing industry and the producer services industry from an overseas and a domestic perspective, Chinese scholars have begun to focus on the interactive development of these two industries in particular areas in recent years, especially in regions where the manufacturing industry is more developed, such as in Liaoning (Qiu Ailian 2014), Jiangsu (Joe equal 2012), the Yangtze River Delta region (Chu Mingqin 2016), Tianjin (Liu Xia 2011), and Chongqing (Liu Junyue et al. 2012, pp. 12–16). The above literature focusses on empirical research of the development of the interaction between the producer services industry and the manufacturing industry, especially the equipment manufacturing industry, in developed areas. As the development of the two industries includes integration, interaction and coordination, it is not enough to solely draw conclusions for the present situation from one of the above three elements. Therefore, this research borrows from the industrial symbiosis theory to make an empirical analysis of the present situation of the industrial symbiosis in Shanxi province—including the three dimensions integration, interaction and coordination—to provide theory references for the upgrading of Shanxi’s manufacturing industry, especially for the equipment manufacturing industry.

10.2.2 Analysis and Hypothesis of the Industrial Symbiosis Mechanism The theory of symbiosis appeared for the first time in the field of biology, referring to the tropism relationship between living bodies. Later it was expanded to the field of economics. Hu Xiaopeng (2009) defines the theoretical connotation and the inherent mechanism of industrial symbiosis. The industrial symbiosis, in the broadest sense, refers to the integrated (merged), interactive and coordinating relations between different business units of the same industry or between business units that are from different types of industries but are related economically. In the narrow sense, industrial symbiosis is the integrated or merged, interactive and coordinated development of business units of same industries or similar industries. 1. Merger: The process by which branches of one or more industries mutually coordinate and cooperate in the fulfilment of shared values, and then gradually merge into a new industry. Symbiotic mergers emphasize on the exchange of materials and service resources, based on which symbiotic industries can develop. Rates of intermediate input and added value can gauge the performance of the merging process. 2. Interactivity: The interaction of business units in the symbiosis system leads to the common development of industries. The producer services industry supports manufacturers with specialized services and benefits from the specialized activity of the

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manufacturing industry’s concentrating on a specific production and the operational sectors. For example, the constant innovation of Apple’s R&D design can support the manufacturing industry’s competitive advantage in the market of smart mobile phones. At the same time, the rising productivity of manufacturing links of Foxconn and other companies can also give Apple a competitive edge in production costs. Both provide an external economic environment for each other, and thus increase the rewards of the industry and economy. Under the framework of symbiosis, the interaction of industries must bring benefits, but the sharing of interests may be balanced or unbalanced. For example, in an agricultural society, the influence of agriculture on other industries must be greater than that of manufacturing. Measurement methods for the interactivity of the producer services industry and the manufacturing industry, such as the induction coefficient and the influence coefficient, reflect the industrial association. 3. Coordination: The connotation of industry coordination includes quantity and quality coordination. Coordination and interactivity can be measured by means of input and output, both of which to a certain extent reflect the quantity coordination degree of “supply demand” between industries. However, the quality coordination emphasizes the coordination of efficiency and it measures the degree of systematic coordination between the two major industries. Therefore, this chapter evaluates the development status of respective industries from multiple dimensions and indices, and then draws on the empirical analysis of the coordination between these industries by using the coordination model of physics. Industrial symbiosis is the economic phenomenon of the system. At the micro level, the industry system’s internal substantial symbiosis is different or has the same exchange within the industrial organization or organization departments through the material or service in the market. They form a value chain based on their respective interests and a complex value exchange network is arranged in a crisscross pattern. Specific transactions will determine the specific contract governance structure according to the transaction frequency, asset specificity, uncertainty and after several market games, forming a stable trading system, thus reducing the transaction costs. At the macro level, by expanding market capacity and promoting the deepening of the circuitous inter-industry-division of labor and production, new industries have been produced to improve production efficiency and to achieve economies of scale. The symbiotic system’s internal integration, interaction, and coordination continue to improve, in order to achieve increasing returns and economic progress, to thus further expand the market capacity (Fig. 10.1). According to Smith’s and Young’s “Theory of Division of Labor”, the division of labor depends on the size of the market, and the market size depends on the division of labor, namely generally depends on the division of labor division. Division of labor can produce efficiency. The inter-industry-division of labor makes the rising industry production more efficient. New industries continue to produce market capacity expansion and further promote the degree of division of labor, so as to achieve economic progress and economies of scale.

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market capacity expansion

industrial division of labour

convergence interactivity manufacturing specialization

economies of scale

coordination

manufacturing specialization

external economy

economies of scale

symbiotic system

increase in returns, improvement of the economy

Fig. 10.1  Industrial symbiosis

On this basis, the performance can be augmented: • Proposition 1: With the consolidation of industrialization, the degree of specialization will also be improved. Then, the degree of specialization of the manufacturing industry in Shanxi, especially the equipment manufacturing industry with the economic engine, will increase with the industrial level. • Proposition 2: The symbiotic relationship between the equipment manufacturing and the producer services in Shanxi will be optimized with the development of the economy.

10.3 Empirical Analysis of the Symbiosis Between the Equipment Manufacturing Industry and the Producer Service Industry in Shanxi Province Basic Determination of The Degree of Industrialization in Shanxi Province 1. Hoffman Coefficient to Determine the Degree of Industrialization in Shanxi (Table 10.1).

2000

0.20

Year

Hoffman coefficient

0.12

2001 0.11

2002 0.09

2003 0.07

2004 0.06

2005 0.05

2006 0.05

2007 0.04

2008

0.05

2009

Table 10.1  Hoffman coefficient of Shanxi. (Data sources calculated from the Shanxi statistical yearbook) 0.05

2010

0.0

2011

0.06

2012

0.06

2013

0.072

2014

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The Hoffman coefficients of the four stages are 5 (+1), 2.5 (+1), 1 (+0.5), and 1 below four stages. The Hoffman index in Shanxi in the years 2000–2014 is below 1, which indicates that Shanxi has entered the late stage of industrialization, and the scale of capital goods is larger than that of consumer goods. 2. Location Quotient Decision of Industrial Subdivision Industries (Table 10.2). Within the industrial structure, the manufacturing industry, especially the equipment manufacturing industry, is in the central position of industrialization. The degree of development of the manufacturing industry is an important indicator to measure the industrialization of a region. This chapter uses the location quotient index to further determine the degree of development of Shanxi’s manufacturing industry and equipment manufacturing industry, and analyzes the degree of specialization of major industries in Shanxi. Its calculation formula is: Q = S/P, whereby Q is the location quotient, S means that the industrial output value of an industry in Shanxi accounts for the proportion of the total industrial output value, and P is the proportion of the same industrial output value in the total industrial output value of the country. If Q > 1, it shows that the development level of this industry is higher. The calculation results show that the location quotient for the manufacturing, mining and power industries in Shanxi since 2004 is at an average annual rate of 1. However, in 2014, the quotient for the manufacturing industry dropped to 0.57, and the mining and power industry still maintained a strong position. The location quotient of the equipment manufacturing industry was only 0.32 in 2014, and its subdivision industry was less than 1. Regarding the Hoffman coefficient, Shanxi has entered the late stage of industrialization, but from the location of business results, the degree of specialization and the later stages of industrialization of Shanxi’s manufacturing industry and equipment manufacturing industry do not match, so proposition 1 is not true. Table 10.2  Location quotient of industrial subdivision industries in Shanxi. (Data sources Shanxi statistical yearbook, diff. years) Mining industry

2000

2014

5.57

4.99

Manufacturing industry

1.17

0.57

Equipment manufacturing industry

0.43

0.32

Metalware

0.79

0.23

General equipment manufacturing industry

0.70

0.29

Special equipment manufacturing industry

1.27

0.68

Transportation equipment manufacturing industry

0.44

0.20

Electrical and mechanical equipment manufacturing industry

0.33

0.19

Electronic communication equipment manufacturing industry

0.05

0.50

Instrumentation, office supplies manufacturing industry

0.17

0.22

Electricity, gas and heat supply

1.13

2.05

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This does not contest Smith and Young’s “Division of Labor Theory”, but the degree of industrialization of Shanxi is shrinking behind the seemingly higher manufacturing and equipment manufacturing. This is due to the Shanxi mining industry and electric power industry boom, caused by the extrusion of the manufacturing industry. The industrial structure of Shanxi is still too resource-based. This is not conducive to the development and upgrading of the manufacturing and equipment manufacturing industry.

10.4 The Symbiotic Development Relationship Between the Equipment Manufacturing Industry and the Producer Service Industry 10.4.1 Integration Analysis of the Intermediate Demand Rate of the Equipment Manufacturing Industry to the Producer Service Industry The producer service industry and the manufacturing industry are in a development process. The division of labor and specialization gradually separated from manufacturing. The function of the independent development of the industry is to provide intermediate products for the manufacturing industry in order to save social transaction costs, promote industrial upgrading and to improve the social and economic efficiency. Therefore, the equipment manufacturing industry is the intermediate consumer of the producer service industry. The demand rate index shows the stimulating effect of the equipment manufacturing for the producer services and the degree to which the producer services promote the development of the equipment manufacturing industry (Table 10.3).

Table 10.3  Analysis of the intermediate demand rate of producer services in producer services. (Data sources calculation of Shanxi input output table based on data from the Shanxi statistical yearbook, diff. years) Particular year

2002 (%)

2007 (%)

2012 (%)

Transportation and warehousing industry

6.50

8.34

0.94

Information transmission, computer services and software industry

1.52

0.93

0.99

Wholesale and retail trade

0.77

1.69

0.87

Finance and insurance industry

8.90

6.36

3.35

Real estate

0.39

0.01

0.19

Leasing and business services

2.49

1.54

5.38

Scientific research and technology service industry

1.12

0.51

0.90

The demand rate of equipment manufacturing industry to the 2.80 whole producer service industry

2.57

1.54

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Regarding the overall manufacturing equipment industry, the intermediate demand rate for producer services has decreased from 2.8% in 2002 to 2.57% in 2007, although the overall rate had increased in 2002 and 2005 and it decreased further to 1.54% in 2012. The value of the equipment manufacturing industry had been increasing, but its industrial added value accounted for the proportion of GDP and has been in a state of decline. During the period of 2006–2012 the proportion gradually began to rise, but in 2012 it was still 1 percentage point lower than in 2002. Therefore, the declining demand rate for producer services is basically consistent with the development trend of the equipment manufacturing industry in Shanxi. In terms of each industrial subdivision, the demand structure has not changed significantly in 2007 compared to 2002. In 2007, the demands of transportation, postal warehouses and the retail industry have improved, but the two industries belong to the traditional labor-intensive producer service industry. The demand for other sectors has declined, for instance for information and software services, leasing and business services, scientific research and in the technology industry. On the one hand, it fully shows that knowledge and technology intensive industries are not closely related to the equipment manufacturing industry, and the development lags behind. Therefore, the service industry with the system of equipment manufacturing has not been formed. On the other hand, it shows that the equipment manufacturing industries in Shanxi are mostly low value-added and there is no sufficient amount of high technology content. That leads to less attraction of producer services and to a low demand for research of science and technology services. The demand remains located in the traditional labor-intensive industries. In 2012, the overall demand continued to decline, but the internal demand structure has changed. The proportion of demand for scientific research in the science and technology service industry began to rise, and the leasing service demand rate reached 5.38%. The traditional service industry demand rate began to decrease significantly, which is because in recent years Shanxi began to adjust the industrial structure and readjust the industrial layout. The tertiary industry continued to expand in 2014, thus reaching the same proportion as the secondary industry. The equipment manufacturing industry is constantly upgrading, requiring an adjustment of the internal structure of the productive service industry. Though decreasing, the demand rate of the financial industry has been relatively high. Proportionally, it is still relatively large, because the equipment manufacturing industry is a technology and capital intensive industry. Input Rate Analysis of Producer Services to Equipment Manufacturing Industry The average input rate of producer services to the equipment manufacturing industry is the ratio of the average input of producer services to the total investment in the production process. The equipment manufacturing industry’s investment in the equipment manufacturing industry, in the production process, comes from the proportion of its own investment. Table 10.4 shows that the producer service industry input rate and the equipment manufacturing industry input rate in 2007 are lower than in 2002, which corresponds

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Table 10.4  The input rate of producer services to equipment manufacturing industry. (Data sources calculation of Shanxi input output table based on data from the Shanxi statistical yearbook, diff. years) Year Metalwork

2002 (%) 9.12

2007 (%) 7.02

2012 (%) 7.51

General and special equipment

8.51

6.07

9.53

Transportation equipment

6.67

3.98

5.85

Electrical machinery and equipment

9.84

3.69

5.45

Communication equipment, computers and other electronic equipment

5.35

11.09

3.89

13.91

15.09

5.29

8.64

6.10

5.00

19.37

14.44

44.68

Instruments and Apparatuses The input rate of producer services to equipment manufacturing industry Investment rate of equipment manufacturing industry in equipment manufacturing industry

with the Shanxi equipment manufacturing industry’s development slowing trend. In 2012, the production service industry investment rate continued to decrease, but the equipment manufacturing industry input rate rose from 14.44% in 2007 to 44.68% in 2012, suggesting that between 2007 and 2012 the equipment manufacturing industry added value and the proportion is rising, but this is not due to an increased development of the equipment manufacturing industry. This is not the result of a growth of the productive service industry investment, but rather a result of the equipment manufacturing industry’s update with advanced equipment, renovation of fixed assets, and the circuitous way of manufacturing machines with machines to improve productivity, which leads to the production of services for the equipment manufacturing industry investment. This shows that the equipment manufacturing in Shanxi is not very dependent on producer services, and the promotion mechanism of producer services for the equipment manufacturing industry is not established.

10.4.2 Interactive Property: Analysis of the Coefficient of Influence and Induction From Table 10.5 one can observe that the main industries in Shanxi province—coal, electric power and equipment manufacturing—have a coefficient of influence higher than 1. This is comparable to the pillar statuses enjoyed by the coal and electricity industries in Shanxi. However, although the equipment manufacturing industry has been well positioned to become a pillar industry, given its high influence and high external demand towards and by other industries, it has a relatively low added value compared to other sectors. The year 2012 has witnessed a great slowdown of economic development.

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Table 10.5  Coefficients of influence and induction. (Data sources calculation based on the input and output table of Shanxi province, Shanxi statistical yearbook, diff. years) Coefficient of Influence 2002

2012

Coefficient of Induction 2002

2012

Equipment manufacturing

1.19

1.13

1.60

1.36

Coal

1.22

1.06

1.02

0.88

Electric power

1.60

1.15

1.30

1.35

Transport & Warehousing industry

1.03

0.94

1.83

1.22

Information transmission, 1.12 computer service, software industry

1.23

0.31

0.51

Wholesale and retail trade

0.85

1.09

1.57

1.72

Financial insurance industry

0.75

0.87

0.58

0.78

Real estate

0.78

0.75

0.32

0.53

Rental and business services industry

0.80

0.97

0.31

0.58

Scientific research and technological services industry

0.66

0.69

0.18

0.31

Despite the decline of the coefficient of influence and the induction of the coal and power industries, the coefficients of the equipment manufacturing industry remained stable. This is because in recent years, Shanxi has gradually adjusted its industrial structure, increasing its support for the equipment manufacturing industry. From the viewpoint of the producer services, the overall coefficients of influence and induction are basically smaller than 1. Therefore, in Shanxi’s industrial structure, the secondary sector of the economy remains to be dominant and the producer services remain subordinate. This basically conforms with the “two, three, one” industrial structure in Shanxi. However, compared to 2002, niche businesses in producer services have an enhanced coefficient of influence and induction. This indicates that with the incessant development of the tertiary industry, the influence and degree of external need of productive services has increased by various degrees. From the perspective of the coefficient of influence, producer services play a bigger role in propelling other industries. From the viewpoint of the coefficient of induction, producer services enjoy a boosted demand from other industries, indicating that its function of providing semi-finished products for the manufacturing industry is taking form. Noteworthy in particular is the growing demand for leasing business in research and technology services, indicating that the producer services act as a driver for the development of other sectors as well as the industrial upgrading. However, much leaves to be desired in the area of the producer services.

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Therefore, in its supply side reform and industrial restructuring, Shanxi must vigorously develop producer services, thus promoting manufacturing and the equipment manufacturing industry to complete the structural reform.

10.4.3 Analysis of the Coordination Degree 1. Building a Coordination Model of Coupling Degree: Make the variable ui (i = 1, 2 . . . n) synthesis and parameter of the first subsystem in coupled system. xij (j = 1, 2 . . . n) the number j index value of the first parameter mij , nij the maxima and minima of order parameter. Among

uij =

xij −nij  uij with positive effect) mij −nij

uij =

mij −nij  uij with negative effect) mij −nij



uij indicate the contribution of variable towards system efficiency xij, ranging from 0 to 1. The contribution of subsystem towards the order degree of the whole system can be achieved through integration:

uij =

s  i=1

ij uij ,

t 

  ij = 1 ij indicating the weights of index

j=1

2. Constructing the Evaluation System of Indicators Based on Coupling Coordination: In order to fully reveal the dependence and coordination relationship between producer services and the equipment manufacturing industry (Table 10.6), and to follow the development characteristics of the two industries and the development characteristics of Shanxi province, we established four primary indicators and 3 or 4 secondary indicators for the two major industrial subsystems respectively from the industrial scale, structure, growth and efficiency aspects, based on the principle of combining the scientific and practical factor, and the systematic and hierarchical factor (Table 10.7). The objective evaluation method of extreme entropy weighting is used to empower different indices. The coordination formula is as follows:  D = c∗ T )θ,

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Table 10.6  Comparison of industry coordination Coordination degree

Coordination level

Coordination degree

Coordination level

0–0.09

Extreme disorder

0.50–0.59

Reluctantly coordinated

0.10–0.19

Serious disorder

0.60–-0.69

Primary coordination

0.20–0.29

Moderate disorder

0.70–0.79

Intermediate coordination

0.30–0.39

Mild disorder

0.80–0.89

Good coordination

0.40–0.49

On the verge of imbalance

0.9–1.0

Quality coordination



c=

2(u1 u2 ) 0,5 u1 + u2

T = au1 + bu2

3. Evaluation Results and Analysis: • The overall development trend shows a gradual increase in the process of the development of the equipment manufacturing and production services and the degree of coordination. Prior to 2006, coordination was largely reluctant. Between 2006 and 2009 there is a primary level of coordination. The years 2009 to 2014 reluctantly entered the intermediate level of coordination, with a short rise in coordination in 2012. The reason for this rise lies in the beginning of 2011. Energy prices were kept low, the Shanxi government began to adjust the industrial structure, and more and more production services and equipment manufacturing industry were supported by investment. During that year the development of the two major industries had a more substantial increase. But in 2013 it returned to normal levels (Fig. 10.2). • From the industry’s development point of view, the development of the productive services is strong, while the equipment manufacturing industry development rate is relatively weak. In the coordinated development, the producer services industry began to exceed the equipment manufacturing industry after 2009, which also confirms the shrinking status of Shanxi’s manufacturing industry (Fig. 10.2). • Combined with the results of integration, interactivity and coordination, the development of producer services is relatively healthy, but the equipment manufacturing industry is relatively slow. In integration, the producer services for the equipment manufacturing industry investment rate changes with the development of the equipment manufacturing industry. The emerging producer services have increased the influence and inductance co-efficiency but are still lower than 1 with weak interaction. The status quo is in the equipment manufacturing industry-led non-equilibrium situation. In conclusion, this basically confirms the correctness of proposition 2, but overall, the symbiotic relationship between the two major industries in Shanxi is still at the initial stage (Fig. 10.2).

10  On the Symbiotic Relationship Between …

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Table 10.7  Cooperative evaluation system of producer services and equipment manufacturing industry Equipment manufacturing Primary Secondary indicators indicators Scale indicators

Structural indicators

Productive services Primary Secondary indicators indicators

Weights

Scale indicators

Increased value of producer services

0.0705

Equipment manu- 0.0642 facturing industry employment

Number of employed persons

0.0637

0.0692 Taxes of equipment manufacturing industry’s total profits

Tax

0.0715

Equipment manu- 0.0698 facturing industry added value

Industrial added value accounted for GDP

0.0651

Structural indicators

The tertiary 0.0655 industry accounts for GDP

Equipment manu- 0.0690 facturing industry accounted for the proportion of industrial added value

Producer services 0.0714 accounted for the tertiary industry

Equipment manu- 0.0732 facturing industry profits and taxes accounted for industrial proportion

Employment accounted for the proportion of tertiary industry

The proportion of employment in the equipment manufacturing industry Growth indicators

Weights

0.0646

Equipment manu- 0.0670 facturing industry added value growth rate Employment growth rate

0.0645

0.0621

Tax accounted for 0.0675 the proportion of tertiary industry

Growth indicators

Growth rate of 0.0678 added value of producer services Employment growth rate

0.0621 (continued)

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Table 10.7   (continued) Equipment manufacturing Primary Secondary indicators indicators

Weights

Productive services Primary Secondary indicators indicators

Weights

Profit and tax rate 0.0634 of growth

Tax revenue growth rate

0.0662

Fixed asset growth rate

Fixed asset growth rate

0.0712

Labor productivity

0.0722

0.0680

Benefit Indicators Yield tax rate

0.0719

Benefit Indicators

Hedging growth rate

0.0628

Taxation accounted for the proportion of added value

0.0617

debt ratio

0.0645

Investment coefficient of fixed assets

0.0653

Employment con- 0.0628 tribution rate

Employment con- 0.0614 tribution rate

condition of the Shanxi province industrial symbiosis

1 0.9 0.8 0.7 0.6 0.5 0.4

0.3 0.2 0.1 0 2004

2005 degree of coordination

2006

2007

2008

2009

equipment manufacturing development level

2010

2011

2012

2013

2014

production service industry development level

Fig. 10.2  The present situation of Shanxi equipment manufacturing and production service industry

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10.5 Policy Suggestion With Shanxi’s economic slowdown, at present only through the supply side reform, ­de-capacity and industrial structure adjustment can get rid of the Shanxi “coal charcoal” traditional industrial pattern to revitalize the equipment manufacturing industry as the starting point. At the same time, productive services should be vigorously supported to promote the upgrading of equipment manufacturing and to promote the industrial upgrading of manufacturing. Therefore, for the equipment manufacturing and productive services, we must take this support into account.

10.5.1 Constructing The Ecological Industry Chain of Equipment Manufacturing According to the basic characteristics of Shanxi’s equipment manufacturing, we should vigorously develop advanced equipment manufacturing. It can focus on strengthening the sectors of coal mining machines, automobiles, railway equipment, heavy machinery and other products to construct the country’s main modern manufacturing base. 1. Construction of an industry chain for coal machine manufacturing: Coal machine manufacturing is the traditional “strength” of Shanxi’s equipment manufacturing industry. In the construction of the industry chain, industrial organizations should fully participate and effectively integrate organizational resources. Thus, the Shanxi Taiyuan Heavy Machinery Group Co., Ltd. as a leader, integrated Taiyuan Mining Machinery Co., Ltd, Shanxi Coal Mine Manufacturing Co., Ltd. and other strong traditional coal mining machine manufacturing enterprises and formed joint efforts among enterprises to build coal mining machine sets of equipment manufacturing base. 2. Research on the construction of an industry chain for railway transportation equipment: Traditional enterprises, such as CRRC Datong Elective Locomotive Co., Ltd. and Yongji Tram may serve as leaders and enterprises providing ancillary products, creating the industrial cluster model “sun + stars”. 3. Construction of an industrial chain for the emerging equipment manufacturing: Relying on Taiyuan Foxconn and other enterprises to mainly develop consumer electronic products. Relying on Changzhi Gaoke, Shanxi Feihong, Shanxi Guangyu power and other enterprises to develop R&D and production of LED epitaxial wafers, chip and expand lighting-based end product industry scale. Relying on China Electronics Technology Group Corporation research institute, to mainly develop liquid crystal display devices, microelectronics assembly equipment, vacuum equipment, electronic plating equipment. Relying on Taiyuan Polytechnic Tiancheng, Rock Jiahua and other enterprises, to accelerate the development of embedded software, e-government, e-commerce, Internet of Things and other applications.

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10.5.2 Strengthen The Ability of Innovation and Vigorously Develop The Emerging Productive Services While continuing to maintain the status of the traditional service industry, the emerging service industry should be provided with industrial policy support and financial support. Shanxi’s capital investment in scientific research and technology has been low, but the development of scientific and technological services determines the development height and direction of productive services. Therefore, we must focus on supporting ­knowledge-intensive services, while maintaining the achievements of the traditional services. It should form a model of integration of production and research to enhance innovation capability and to provide support for the industrial upgrading of equipment manufacturing and manufacturing in general.

References Baines, T. S., et al. (2007). State-of-the-art in product-service systems. Proceedings of the institution of mechanical engineers. Journal of Engineering Manufacture, 221(10), 1543–1552. Eswarran, M., & Kotwal, A. (2002). The role of the service sector in the process of industrialization. Journal of Development Economics, 68(2), 401–420. Guerrieri, P., & Meliciani, V. (2003). International competitiveness in produces services. Paper Presented at the SETI Meeting in Rome, 2003. Mani, S. (2012). The mobile communication services industry in India: Has it Led to India becoming a manufacturing hub for telecommunication equipment? Pacific Affairs,85(3), 511–530. Sturgeon, T., Van Biesebroeck, J., & Gereffi, G. (2008). Value chains, networks and clusters: Reframing the global automotive industry. Journal of Economic Geography, 8(3), 297–321.

Additional Literature 刘浩、原毅军. 中国生产性服务业与制造业的共生行为模式检验[J].财贸研究, 2010 (3). 刘明宇、芮明杰、姚凯.生产性服务价值链嵌入与制造业升级的协同演进关系研究[J].中国工 业经济, 2010 (8). 楚明钦.装备制造业与生产性服务业产业关联研究——基于中国投入产出表的比较分析[J].中 国经济问题, 2013 (3). 陈晓峰、陈昭峰.生产性服务业与制造业协同集聚的水平及效应——来自中国东部沿海地区 的经验证据[J].财贸研究, 2014 (2). 王成东、綦良群.中国装备制造业与生产性服务业融合研究[J].学术交流, 2015 (3). 綦良群、蔡渊渊、王成东.我国装备制造业与生产性服务业互动作用及效率评价研究[J].中国 科技论坛, 2015 (1). 李兵、朱天星.辽宁生产性服务业与装备制造业互动发展研究[J].辽宁经济, 2012 (1). 乔均、金汉信、陶经辉.生产性服务业与制造业互动发展研究——1997–2007年江苏省投入 产出表的实证分析[J].南京社会科学, 2012 (3).

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楚明钦.长三角产业区域分工与合作——基于生产性服务业与装备制造业融合的研究[J].云南 财经大学学报, 2016 (1). 刘军跃、万侃、钟升、王敏.重庆生产服务业与装备制造业耦合协调度分析[J].武汉理工大学 学报, 2012 (4). 刘立霞.天津生产性服务业与制造业的互动关系研究[J].哈尔滨商业大学学报, 2011 (5). 胡晓鹏,李庆科.生产性服务业与制造业共生关系研究[J].数量经济技术经济研究, 2009.

The Opportunities and Challenges Shanxi’s Industrial Economy Faces in the Age of Industry 4.0

11

Chao Tong

Contents 11.1 The Opportunities for Shanxi’s Industrial Economy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 11.1.1 Made in China 2025 Rises to a National Strategy. . . . . . . . . . . . . . . . . . . . . . . . 140 11.1.2 Big Changes in Market Conditions Provide New Opportunities for Shanxi’s Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 11.2 Improvements of the Industrial Management in Shanxi Province. . . . . . . . . . . . . . . . . . . 141 11.3 Challenges Faced by Shanxi’s Industrial Economy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 11.3.1 There Is a Downward Pressure on the Industry. . . . . . . . . . . . . . . . . . . . . . . . . . 142 11.3.2 The Main Benefit Index Falls, or Continues to Fall. . . . . . . . . . . . . . . . . . . . . . . 143 11.4 Policy Suggestions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 References and Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152

Abstract

In recent years, the economic situation at home and abroad has become increasingly complex and is facing a big downward pressure. As a result, the external conditions of Shanxi’s industrial economy have changed. Shanxi’s industrial economy will be facing a long-term downturn and will enter the trend of the “New Normal”. In this situation, the transformation of the driving force and the development mode have become important tasks for Shanxi’s industry. This chapter summarizes the positive changes in Shanxi’s industry since the implementation of the Made in China 2025 strategy. It analyzes the problems in the area of investment, the industrial growth trend and efficiency, prices of dominant industrial products, and the coal industry growth trend in T. Chao (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_11

139

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T. Chao

Shanxi and discusses the proper direction, momentum and pattern for the transformation and upgrading of Shanxi’s industry. In its conclusion, this chapter will give policy suggestions on approaches to strengthening the new industrial driving force and the propulsion of new projects. At present, the industrial growth is declining in Shanxi province, whose industrial development has entered the period of deep adjustment. Structural adjustment, transformation and upgrading are becoming a primary task for the industry. Currently, the industrial growth and production organization pattern in Shanxi province, and even the whole country’s and the world’s industrial development trend, are undergoing profound changes. Information technology is highly integrated within industrial technology. The internet, computer technology and information technology, as well as software and automation technology are interwoven. Made in China 2025 and Germany’s Industry 4.0 are actively carrying out strategic docking. We need to further analyze Shanxi’s industrial opportunities and challenges under the new situation, and to explore the countermeasures taken by Shanxi’s industry to seize opportunities of achieving transformation and upgrading.

11.1 The Opportunities for Shanxi’s Industrial Economy 11.1.1 Made in China 2025 Rises to a National Strategy After April 2013, when the German government launched the Industry 4.0 strategy, the concept of Made in China 2025 has been put forward for the first time in December 2014. In March 2015, premier Li Keqiang put forward and implored to speed up the Made in China 2025 strategy, at the Chinese People’s Political Consultative Conference (CPPCC) and the State Council executive meeting. In May 2015, the State Council officially issued Made in China 2025, which is the program of action for the first decade of building a powerful China strategy (Guo Fa [2015] no. 28, 2015). In October 2015, China and Germany announced that they would advance Made in China 2025 and Germany’s Industry 4.0 strategic docking to jointly promote the new industrial revolution and formats. On December 23, 2016, premier Li Keqiang put forward important instructions on Made in China 2025 working site at the fourth meeting of the leading group of national manufacturing powerhouse construction. He also gave full affirmation to the achievements and presented new requirements.

11.1.2 Big Changes in Market Conditions Provide New Opportunities for Shanxi’s Industry Our country has entered the late industrialization where the consumer’s needs can be met with basic food and clothing, and commodity demand presents multi-level

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141

characteristics. Service consumption is rising gradually, and the emerging industries are in the incubation stage. The investment opportunities of new technologies, new products, new conditions and new business models are emerging in large numbers. Individual and diversified consumption is gradually becoming mainstream and the importance of activating supply and demand through innovation is rising significantly. Market competition is turning into a competition of quality and technology brand service. Emerging industries, service industries and small micro enterprises are playing a more and more obvious role. The main factors supporting economic growth have been driven to innovation by mass high intensity input factors of production, but the quality of economic growth will rely more on human capital and technological progress. As the working age population decreases, the population dependency ratio as well as the aging population gradually increase. The savings rate and investment rate are gradually decreasing. Labor and capital investment growth are slowing down and the potential growth rate has a tendency to decline. The main factors supporting economic growth have changed from the production of high and large-scale intensity input to innovation. The economic growth will rely more on human capital quality and technological progress.

11.2 Improvements of the Industrial Management in Shanxi Province The restructuring of the light and heavy industries has made progress. In 2016, the ratio of light industry to heavy industry was 7.3:92.6, which implies an increase of 2.6 percentage points since 2011 for the light industry. Across all industries in Shanxi, the added value for the coal industry accounted for 46.8% of Shanxi’s total industrial ­added-value, and for non-coal industries for 53.2%, which was 12.1% higher than in 2011. (Shanxi Provincial Bureau of Statistics 2015). Both, industrial restructuring and diversified development, have proven effective. Flagship industries changed greatly and were significantly upgraded to mid- and ­high-end ones. In 2011, the added value of industries in the following fields ranked at the top six: coal (58.7%), metallurgy (13.5%), coke (6.8%), equipment (5.4%), electricity (5.3%) and chemistry (3.2%). Yet, in 2015, the ranking was as follows: coal (46.8), electricity (12%), metallurgy (11.8%), equipment (10.4%), chemistry (4.8%) and food (4.3%). Investments were gradually optimized and grew faster in non-coal industries. From 2011 to 2015, investments in Shanxi’s industries were ¥333.9b, ¥412.97b, ¥472.49b, ¥505.4b and ¥528.31b, respectively, an increase of 21.4% year after year. During the twelfth five-year-plan period, the fixed asset investments in coal and non-coal industries were ¥587.67b and ¥1.6628t, with an annual increase of 10.2% and 26.6%, accounting for 26.1% and 73.9% of total investment in Shanxi, respectively. Compared to 2010, investment in coal industry grew slower, and went down by 40.8%, which equals a 9.8% reduction in the ratio; yet non-coal industries performed the opposite, with 16.9% growth in investment, which equals an increase of 9.8% in the ratio.

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Table 11.1  Financial performance of industries in Shanxi province in 2011 and 2015. (Source Shanxi provincial bureau of statistics 2015) Industry

Overall Revenue 2011 2015

Total profit 2011

Sum

16893.4

14393.7

1200.6

Coal

7260.1

5759.7

996.9

Coke

1774.3

776.9

Metallurgy

3407.4

2713.8

89.8

Electricity

1231.7

1458.7

−23.5

−12.8

2015 −68.1

−152.3

−80.9

−68.5

121.7

Profit and taxes 2011

2015

2268.2

631.8

1733.4

265.1

48.4 185.9 34.6

−61.7

−22.6

208.8

Chemistry

729.1

740.5

24.6

38.4

2.1

Building material

328.9

310.2

9.7

−11.8

24.4

−0.3

Electromechanic

1336.6

1479.4

46.8

60.9

82.7

99.2

Food

531.2

648.6

48.9

33

88.7

82.3

−11.4

Medicine

96.2

171.2

10.1

17

16

26.7

Textile

54.5

59.6

1.7

1.2

2.9

2.3

Others

198

275.1

10.1

23

15.8

29.9

The profit structure changed massively. The coal industry, which had been the most profitable, lost most. Yet, the electric power industry performed oppositely. In 2011, coal industry was in the leading role with a profit of ¥99.69b, accounting for 83.7% of the total industrial profit in Shanxi. In the same year, the electric power industry lost ¥2.35b. In 2015, however, the former driving force suffered a hefty loss of ¥15.23b and the electric power industry performed best, achieving a profit of ¥121.7b (see Table 11.1).

11.3 Challenges Faced by Shanxi’s Industrial Economy 11.3.1 There Is a Downward Pressure on the Industry Under the interactive influence of cyclical and structural factors, the external environment of the industrial development in Shanxi has changed periodically. In recent years, Shanxi’s industrial growth rate has decreased from double digits to single digits, and from the mid-high speed to the mid-low pattern. It appears that the economic growth has been slowing down and shifting to another gear, but essentially the economy of Shanxi, affected by the macro market environment and policy incentives, has been restructured and driving forces rebuilt. With the whole society’s growing awareness of the environment, resources and environmental constraints will be further strengthened. The industrial economy must be promoted to restructure into a green low-carbon and recycling

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143

mode. The problem of capacity structural surplus is prominent all over the country, and prices of products remain low. There is a high pressure on the industrial economic growth in Shanxi. The main problem of Shanxi’s industry lies in the structure of the driving forces. Industries with a low growth rate represent a small part of the entire nation, while industries with a high growth rate account for a large proportion. However, in Shanxi province, industries with a low growth rate account for a large proportion, and industries with high growth rate account for a small proportion. Under the effects of slack market demand, declining prices and other factors, coals, metallurgy, coke, and power industries have been slowing down. Especially the growth rate of the coal industry production, which accounts for a large proportion of Shanxi’s economy, has been shifting significantly into another gear. The main manufacturing industries have adjusted their production structure and gone through the throes of growth. The driving force structure tends to be optimized. (Shanxi Provincial Bureau of statistics 2015). The proportion of industrial added value, taking up in GDP, declined. During the 12th five-year-plan period, the industrial added value of Shanxi amounted to 6047 trillion yuan, 6.23 trillion yuan, 6281 trillion yuan, 5.3625 trillion yuan and 4.2295 ­ ­trillion yuan respectively, accounting for 53.6%, 53%, 49.8%, 42%, and 33% of the GDP respectively. The growth rate of the industrial added value continued to fall. During the 12th ­five-year plan period, the average industry growth rate of Shanxi was 7.9%, but Shanxi’s industrial growth rate kept decreasing year by year, and gradually fell from double digits to negative digits. From 2011 to 2015, Shanxi’s industrial growth rate was 17.9%, 11.9%, 10.5%, 3%, and −2.8% respectively. From September 2014 to December 2015, during these 16 months, the growth rate of Shanxi’s industry’s added value ranged within negative growth for 15 months, and only for once in a single month positive growth showed (growth of 0.1% in November 2015). From 2011 to 2015, Shanxi’s industrial growth continued to decline, and it was thus lagging behind 2011’s figures and the 11th five-year-plan. In 2011, Shanxi ranked 17th out of 31 provinces (cities, districts) of the whole country, and ranked 30th out of 31 provinces (cities, districts) in 2015, as shown in Table 11.2. In the external environment, due to a lack of power and pressure in the background, Shanxi’s industrial growth rate dropped significantly between 2013 and 2015. During these years, Shanxi’s industrial growth was 10.5%, 3%, −2.8%, among these rates, the coal industry growth rate was 10.5%, 3.4%, 2.8% and the non-coal industry growth rate was 10.5%, 2.4% and −6.2%.

11.3.2 The Main Benefit Index Falls, or Continues to Fall The number of industrial enterprises and the main business revenue increased year by year before 2013 and fell year by year since peaking in 2013. The number of enterprise units reached 3.946 in 2013 and decreased to 3.720 businesses and 3.731 businesses in

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Table 11.2  The industrial growth rate of six provinces in central China and surrounding provinces during “The 12th Five-Year-Plan” (in %). (Source Shanxi provincial bureau of statistics, diff. volumes)

Districts

2011

2012

2013

2014

2015

China

13.9

10

9.7

8.3

6.1

Shanxi

17.9

11.9

10.5

3

Anhui

21.1

16.2

13.7

11.2

−2.8

Jiangxi

19.1

14.7

12.4

11.8

9.2

Henan

19.6

14.6

11.8

11.2

8.6

Hubei

20.5

14.6

11.8

10.8

8.6

Hunan

20.1

14.6

11.6

9.6

7.8

Inner Mongolia Mon

19

14.8

12

10

8.6

Shanxi

17.9

16.6

13.1

11.3

7

8.6

2014 and 2015. The main business income of Shanxi reached its peak in 2013 (1 trillion and 840 billion 470 million yuan) and decreased year by year in 2014 and 2015. It dropped to 1 trillion and 439 billion 370 million yuan in 2015. Profits decreased year after year. From 2011 to 2015, the industrial profits in Shanxi dropped successively, from 120 billion 60 million yuan to 6 billion 810 million yuan; the industrial profits and taxes in Shanxi decreased likewise, from 226 billion 820 million yuan to 63 billion 180 million yuan, as shown in Table 11.3. Profit growth and profit margins continue to decline. From 2012 to 2015, the industrial profit margins in Shanxi were 4.53%, 2.98%, 1.23% and −0.47%. Since May 2012, Shanxi’s industrial profit growth has entered a downward spiral. Between 2012 and 2014, Shanxi’s industrial profits declined by 30%, 31.4% and 61.4%. In 2015, profit growth declined in an even more obvious manner. The Growth of Traditional Pillar Industries is Limited Shanxi province is a typical coal-based energy economy province. The share of the energy industry accounts for about 60%, the main products being coal (3/4), coke (2/3)

Table 11.3  Main indicators of Shanxi industry during the period of the 12th Five-Year-Plan (Household, billion Yuan). (Source Shanxi provincial statistical yearbook, diff. volumes) Year

Number Of Businesses

The profits of the Total profits main business

Total Pre-tax Profits

Industrial added value

2011

3532

16893.4

1200.6

2268.2

6047

2012

3716

17788.4

806.5

1770.7

6230

2013

3946

18404.7

547.9

1445.8

2014

3720

17119.9

210.6

973.4

5362.5

6281

2015

3731

14393.7

−68.1

631.8

4229.5

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145

and regionally sourced power (1/3). They make a great contribution to the national economic development. In addition to the energy industry, Shanxi’s metallurgical ­industry ranks third in Shanxi’s industrial economy. The metallurgical industry accounts for 1/6 of the industrial economy. In 2008, before the financial crisis, the gap between the heavy and the light industry grew increasingly wider with the accelerated process of industrialization and Shanxi province increased investment in the energy and metallurgical industry. The added value of the light industry has been less than 5% of the industry in Shanxi, with the four traditional heavy industries: coal, coke, electrics and metallurgy, to support the rapid development in recent years in the province. In 2009, the industrial added value reached historic lows of 2.5%, making the high degree of economic dependence of Shanxi’s industry, and the impact of the financial crisis, particularly evident. The long-term trend of oversupply of major industrial products, such as coal, has been established. The national coal consumption growth rate has declined significantly since 2012, with an average growth rate of 6.1% from 2007 to 2011, to less than 1% in 2014. At the same time, the GDP growth slowed from only 10.6% to 7.8%. In 2014, the national coal consumption fell by 2.9% and thermal power generation decreased by 0.3%. In the same year China’s GDP growth rate reached 7.4% under the condition of a negative growth of the coal consumption, further decoupling economic growth and coal consumption growth. As the peak of coal is coming and the long-term trend of oversupply is basically established, coal companies should reduce investment or be prudent with investment to avoid aggravating pile up in excess. At the same time coal enterprises should prepare for the transformation of development, cultivate new economic growth points, in response to a drop of demand after the peak of coal. Many coal enterprises have turned their attention to new growth points, such as the coal chemical industry. This pattern will not change much in the short term. Over the past 10 years, Shanxi's coal industry accounted for 50% of the industrial added value above the regulation, but in the past two years, Shanxi’s industrial growth dropped significantly. The main reason is that the coal industry is affected by both, policy reduction and market squeeze. Shanxi’s government put forward that the target of controlling coal output in 2020 is to not exceed 10 tons. In 2014, the coal output of Shanxi was 9.6 tons. The space for growth of Shanxi’s coal industry is very limited in the next 5 years. Coke, steel and other industries’ overcapacity phenomenon is highlighted. Coke, iron and steel are the pillar industries of Shanxi province, and their demand conditions have undergone profound changes. They are characterized by overcapacity, oversupply, a narrowed expansion of investment space and a significant slowdown of investment growth. Continued Negative Growth of the Producer Price Index, Buying and Selling Prices for a Long-Time Upside Down As of the end of 2015, Shanxi’s industrial Producer Price Index (PPI) denoted 46 consecutive months of negative growth (since March 2012). The industrial producer price was in the range of negative growth, but the decline was less than the PPI. The purchase

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Fig. 11.1  Comparison of factory price and purchase price of industrial producers in the same month since 2011

and sale prices were “upside down” for 58 months (since March 2011). Figure 1 shows a comparison of factory price and purchase price of industrial producers in the same month since 2011 (see Fig. 11.1). The PPI maintains a negative growth and the purchase price outweighs the sales price, gravely thwarting industrial profits. From 2011 to 2015, the industrial profits of Shanxi province experienced a year-on-year decline. March of 2015 witnessed, for the first time in Shanxi industry’s history, an accumulated net loss of almost 6.81 billion yuan. The sustained negative growth of the PPI dampened the investment willingness of many companies. The year-on-year decline of the investment growth rate in industrial fixed assets was witnessed, with 23.9%, 14.4%, 7.5% and 4.6% in a row. This was below the same period growth rate of the fixed assets investment with an increase of 0.6%, 7.7%, 4% and 10.2%. Pressure is Felt in De-leveraging and De-stocking The asset liability ratio is an important index to reflect the long-term solvency of enterprises with the normal ratio ranging from 40% to 60% and the warning line at 70%. By the end of 2015, Shanxi’s industrial asset liability ratio had been above the alert line for 32 months. There are 6 industries which have asset liabilities above the warning line: the coke industry (debt ratio 89%), coal industry (debt ratio 78%), chemical industry (debt ratio 79.3%), building materials industry (76.6% debt ratio), the electric power industry (debt ratio 73.9%), and the metallurgical industry (debt ratio 72.6%). Affected by the higher debt ratio, in 2015, the interest expense of Shanxi was 54 billion 960 million yuan, accounting for 3.8% of the main business income.

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Fig. 11.2  1991 Shanxi’s total fixed asset delivery rate in %. (Source Shanxi provincial statistical yearbook, diff. volumes)

There was a mismatch between products and marketing adds to pressure destocking. From 2011 to 2015, Shanxi’s industrial sales rate continued to run low, floating around 95%, and thus occupying a low position across the nation. From 2012 to 2015, the production and marketing rates were 95.2%, 95.3%, 94.9% and 94.4% respectively, ranking 28th among 31 provinces in 2015. While inventories are high, Shanxi’s PPI continues to decline, and enterprises face greater inventory losses. Decreasing Investment and Benefits of Fixed Assets In recent years, the delivery efficiency and the investment effect coefficient of the fixed assets investment in Shanxi all continued to decline, showing a low investment benefit, further increasing the economic risk. The rate of fixed assets delivery refers to the ratio of newly fixed assets and investment during the same period. It is the index that reflects the completion of investment in fixed assets. From 1991 to 2013, the average utilization rate of new fixed assets in Shanxi was about 67.6% (Dong 2015). Since 2007, the utilization rate of fixed assets in Shanxi has been running at a low level (see Fig. 11.2; Table 11.4). The investment rate of fixed assets and the coefficient of investment reflect the effect of investment. Since 1991, the investment effect coefficient trend of Shanxi is basically equivalent to the nation’s trend. The trend of Shanxi fluctuates. Since 2007, the investment effect coefficient of Shanxi showed a downward trend, dropping to 0.01 in 2009, then remaining low, and continuing to return to 0.1 in 2014. If the investment effect is too low, more attention should be paid to the economic operation (see Fig. 11.3; Table 11.5).

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Table 11.4  1991 Shanxi fixed assets delivery rate (100 million Yuan, %). (Source Shanxi provincial statistical yearbook, diff. volumes) Year

Investment in fixed assets in the whole society

Newly added fixed assets

Application rate of fixed assets

1991

149.5

133.2

89.1

1992

172.8

126.1

73

1993

251.3

146.3

58.2

1994

290.9

200.9

69.1

1995

295.6

227.1

76.8

1996

333.5

238.7

71.6

1997

398.4

329.1

82.6

1998

534.7

384

71.8

1999

575.4

390.5

67.9

2000

625.2

489.1

78.2

2001

708.3

458.5

64.7

2002

838.3

841

100.3

2003

1116.3

708

63.4

2004

1477.7

878.6

59.5

2005

1859.4

1027.7

55.3

2006

2321.5

1484.6

64

2007

2927.2

2008.2

68.6

2008

3635.1

2028.9

55.8

2009

5033.5

2801.2

55.7

2010

6352.6

3377.5

53.2

2011

7373.1

4319

58.6

2012

9176.3

5504.1

60

2013

11200.2

6508.3

58.1

2014

12354.5

8464.4

68.5

11.4 Policy Suggestions We should accurately grasp the law of economic development and analyze in depth the new trend and competition features of the current world industry development. We suggest to be fully aware of the development potential, opportunities, difficulties and challenges of the manufacturing industry in Shanxi Province, with the new development

11  The Opportunities and Challenges Shanxi’s …

Shanxi

149

China

Fig. 11.3  The investment effect coefficient of Shanxi and China since 1991. (Source Shanxi provincial statistical yearbook, diff. volumes)

concept as a guide to promote the supply side’s structural reform as the main line. Apart from this, we should focus on market demand, learn from international experience to create a good environment for the market access, factor allocation, costs reduction and so on, along with the development of an advanced manufacturing industry. Made in China 2025, Internet Plus and public entrepreneurship innovation should be closely combined to form a mutual virtuous circle between a new kinetic energy cultivation and the traditional one, and to strengthen the new development momentum. 1. Further Cultivating New Industries, New Kinetic Energy and a Profit Growth Point The single industry structure and the lack of growth should be improved. While stabilizing the growth of leading industries, we must speed up the cultivation and support of new sources of profits to enhance the industrial development potential. Food, medicine, high-end materials industry and equipment manufacturing production have been gradually accelerated and now establish a new industrial growth point in Shanxi Province. We should increase support in the policy, strengthen the new economy, cultivate new kinetic energy, transform and enhance the traditional kinetic energy to increase the growth potential of Shanxi’s industrial economy. An upgrade should be promoted through main industry development. First, through the equipment manufacturing industry, new materials and other industrial technology innovation. To drive the structural changes of the traditional competitive industry, we should establish technological innovation heights, create a first-class manufacturing supply chain, and further the competitive industrial development of Industry 4.0.

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Table 11.5  Shanxi and the national investment efficiency index since 1991 (100 million Yuan, %). (Source Shanxi provincial statistical yearbook, diff. volumes) Year

GDP

Investment in fixed assets in the whole society

Coefficient of investment effect in Shanxi

National investment effect coefficient

1991

468.5

149.5

0.26

0.56

1992

551.1

172.8

0.48

0.64

1993

680.4

251.3

0.51

0.64

1994

826.7

290.9

0.5

0.75

1995

1076

295.6

0.84

0.63

1996

1292.1

333.5

0.65

0.45

1997

1476

398.4

0.46

0.31

1998

1611.1

534.7

0.25

0.19

1999

1667.1

575.4

0.1

0.18

2000

1845.7

625.2

0.29

0.29

2001

2029.5

708.3

0.26

0.28

2002

2324.8

838.3

0.35

0.25

2003

2855.2

1116.3

0.48

0.28

2004

3571.4

1477.7

0.48

0.34

2005

4230.5

1859.4

0.35

0.28

2006

4878.6

2321.5

0.28

0.29

2007

6024.5

2927.2

0.39

0.36

2008

7315.4

3635.1

0.36

0.28

2009

7358.3

5033.5

0.01

0.12

2010

9200.9

6352.6

0.29

0.24

2011

11237.6

7373.1

0.28

0.23

2012

12112.8

9176.3

0.1

0.12

2013

12602.2

11200.2

0.04

0.11

2014

12759.4

12354.5

0.01

0.13

2. Continuing to Optimize the Investment Structure Endogenous energy and vitality of investment should further be stimulated. Adhering to increasing effective investments and structure optimizing simultaneously, paying attention to the quality of investment and efficiency enhancing, we should speed up the pace of industrial restructuring and upgrading and give full play to the pilot role of strategic adjustment of the economic structure prompted by the investment structure adjustment. Apart from this, attention should be geared towards the growth momentum of industrial investment, increasing investment in new industrial areas, maintaining steady growth

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in industrial investment, especially increasing investment in manufacturing, developing the new technology industry and furthering technological transformation. We should improve the investment proportion of new leading industries, such as the food industry, the coal chemical industry, medicine, equipment manufacturing, and the high-end materials industry to accelerate the new industrialization and enhance endogenous power of the growth of real economy investment. 3. Optimizing the Individual Structure and Product Structure, Increasing Product Added Value and Competitiveness The Made in China 2025 initiative urges to improve the quality and level of ‘made in China’ in all sectors. On the one hand, we need to transfer from ‘made in China’ to ‘created in China’, from quickly made products to excellent-made products, and from Chinese products to Chinese brand name products. On the other hand, China should be aiming at becoming a country that is strong in key areas and key projects. Technology should be playing a supportive and leading role in changing the growth mode of the economic development and adjusting economic structure to promote green recycling and low-carbon development. Adhering to the principle of clean, safe low-carbon and efficient use of black coal, major technological breakthroughs are ­ needed to be made in key aspects like coal mining methods, product development, industrial chain development, as well as the restoration and treatment of the ecological environment of the coal mines, thus advancing the transformation of the coal industry. China needs to pay close attention to enterprises for their constructive role in increasing market activity and strengthening innovation ability. Enterprises’ positiveness is needed to be stimulated through different channels. We must continue to develop the preponderant industry, establish multi-pillar industry systems, accelerate the process of new industrialization, and construct new energy and an industrial base. We need to promote the implementation of Internet Plus and Made in China 2025, speed up the deeper combination of industrialization and informatization, and develop the non-traditional industry. 4. Promoting the Production of Key Industrial Products New Enterprises, as a new growth point, are vital to the growth of industry. We need to clear up planning-to-commissioning-projects and provide counterpart assistance to them one by one. During the process, the schedule should be clear enough to make sure production is being conducted timely and efficiently, to form a new growth point. We need to facilitate the project completion and then start the implementation to form a new growth point as soon as possible. Relying on reinforcement through a project coordination service, dispatching assessment, and precision assistance, together with adhering to a schedule, inverted working period and tracking service, industrial transformation and upgrading, should be accelerated. Hence, China can accomplish the completion and production of the project ahead of time and thus make a contribution to the economy.

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5. Enhancing Deleveraging and Avoiding Business- and Financial Risks Keep away from operational risks. Attention should be payed to the monitoring and takeover of accounts. We need to be careful with sales on loan and be strict with the implementation of the credit system to safeguard the capital. We should enhance the central management of capital and strive for a shorter cycle period, to accelerate the capital turnover and improve capital utilization. We need to prevent financial risks, optimize capital structure and improve the quality of capital operation. Key industries and enterprises should not only focus on capital management under the help of relief policy, such as national cost reduction, but also set the frontier of assets and liabilities, as well as control the scale of capital expenditure and the financial cost reduction.

References and Additional Literature 国发〔2015〕28号.国务院关于印发《中国制造2025》的通知[S].北京:国务院. 山西省统计局. 山西工业能源发展报告[M]. 山西:山西省统计局,2016, pp. 87–93. 山西省统计局. 转型2010–2013 [M].山西:山西省统计局,2014, pp. 77–99. 董晓玲.转型发展新阶段中的山西经济增长动力转变[C].山西省经济普查论文集.山西:山西省 统计局,2015, pp. 319–330. Dong 2015: 董晓玲.转型发展新阶段中的山西经济增长动力转变[C].山西省经济普查论文集.山 西:山西省统计局,2015, pp. 319–330. 童超.煤炭大省正经历寒冬[N].中国信息报,2016.6.23 (8). Shanxi Provincial Bureau of Statistics (2015). Shanxi statistical yearbook 2015. Taiyuan.

A Study on the Interactive Mechanism Between Population Urbanization and Transfer of Labor Force in Shanxi Province—Based on the Perspective of Industrial Agglomeration

12

Peng Jia and Han Peiyu

Contents 12.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 12.2 The Basic Theories of Industrial Agglomeration, Urbanization and Labor Force. . . . . . . 155 12.3 Empirical Analyses of the Urbanization and Labor Transformation in Shanxi Province. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 12.3.1 Analysis of the Characteristics of Urbanization, The Shift of Labor in  Rural Areas and Industrial Agglomeration in Shanxi Province. . . . . . . . . . . . . . 155 12.3.2 Evaluation of the Compatibility Between Urbanization and Rural Labor Transfer in Shanxi Province: Measurement of Coordination Degree. . . . . . . . . 165 12.3.3 Interactive Study of Urbanization and Transfer of Labor Force in Shanxi Province—The Analysis of Relevant Factors and Empirical Tests. . . . . . . . . . . 169 12.4 Research Conclusions and Policy Suggestions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 12.4.1 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 12.4.2 Policy Suggestion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Abstract

This chapter analyzes the development status of the rural surplus labor transfer and the urbanization dynamic mechanism, based on the theory of urbanization, labor transfer and industrial agglomeration correlation analysis. Shanxi Province is taken as J. Peng (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] P. Han (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_12

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J. Peng and P. Han

a case study. The interaction and mutual tolerance development are explored in order to make suggestions for the transfer of rural labor and for the harmonious development of the population urbanization policy for the region.

12.1 Introduction It goes without saying that urbanization and transfer of rural labor are closely related. They can promote and restrict each other. In the process of urbanization, a large number of rural surplus labor force migrates into cities and towns, which has an impact on the local labor market. However, the ever-lasting employment pressure, plus the population transfer caused by urbanization, intensify the conflict of the oversupply of urban labor force, and thus influence the urban labor market to a great extent. As for the rural labor transfer and urbanization, the more classical research models include Lewis’ Dual Economy, the Fei-Ranis model, the Jorgenson model and Darrow’s population flow model. These models explain the power, characteristics and mechanism of rural labor transfer in developing countries. The Lewis model holds that urban and rural income differences and the transfer of accessibility as well as the accumulation of capital expansion cause the transformation of the surplus of labor force flowing. The Fei-Ranis model considers the growth of agricultural productivity, but still believes that there is no unemployment in the industrial department as long as the industrial sector wages are higher than those of the agricultural sector and the recessive rural surplus labor will continue to flow to the cities. The Jorgenson model holds that the reason for transfer and urbanization lies in the change of the demand and consumption structure. Joe Darrow considers urban unemployment in the industrial sector, but he believes that the surplus labor of the rural-urban movement will continue because of the existence of the expected income. These three models mainly study the transfer of rural surplus labor to the ­non-agricultural industries. They implicitly assume that the industrial transfer and the township transfer, and the labor transfer from rural to urban areas, i.e. population urbanization, are synchronous. Darrow’s population flow model mainly focusses on Latin American and some developing countries whose urbanization development is more advanced than that of other countries. These patterns cannot be simply transferred to China’s national conditions or the conditions in most other areas. The transfer of the rural labor force to the non-agricultural industries is a fundamental constituent of the industrialization process. Population urbanization is the main characteristic of urbanization. Moreover, industrialization and urbanization are related and influence each other. Thus, the rural labor transfer needs to be developed along with the population urbanization, whose development scale and speed depend on the evolution and coordination of the relationship between industrialization and urbanization. The study of the coordinated development of rural labor transfer and of the dynamic mechanism of population urbanization can help us understand the law of development and grasp the basic characteristics of most of China’s regional rural labor transfer and urbanization development.

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155

12.2 The Basic Theories of Industrial Agglomeration, Urbanization and Labor Force Industrial agglomeration is the basic power to promote the process of transfer of labor and transformation of cities. The agglomeration effect promotes aggregation in urban spaces and increases the quantity and quality of labor transfer. Industrial agglomeration and urban spatial agglomeration are different representations of homogeneous changes. Relying on the industrially agglomerating city, we should pay attention to encouraging the same or related industrial agglomeration, and to giving full play to the cumulative effect and diffusion effect of industrial agglomeration. We also need to deepen specialization and enhance the innovation capability and competitiveness of cities. 1. The revenue generated by the difference of industrial agglomeration attracts rural surplus labor transfer to non-agricultural industries. 2. The transfer of rural surplus labor forces provides essential conditions for industrial agglomeration. 3. Urbanization agglomeration demands new requirements and promotes the process of urbanization. 4. Urbanization and industrial agglomeration provide the external conditions and environment for the transfer of the rural surplus labor. 5. The transfer of the rural surplus labor force is an important part of urbanization. 6. Urbanization provides the external conditions and environment for the transfer of the rural surplus labor from towns. This chapter focusses on the relationship between the transfer of rural surplus labor, urbanization and industrial agglomeration (Fig. 12.1). Using the data of Shanxi province for theoretical and empirical analysis, it analyzes the main factors affecting the coordinated development of Shanxi province, the transfer of rural surplus labor and urbanization. Examples and data analysis are used to find solutions to problems associated with the topic.

12.3 Empirical Analyses of the Urbanization and Labor Transformation in Shanxi Province 12.3.1 Analysis of the Characteristics of Urbanization, The Shift of Labor in Rural Areas and Industrial Agglomeration in Shanxi Province Analysis of Urbanization in Shanxi Province The process of urbanization: As a traditional energy-focused province, Shanxi, due to its special location and unique developing methods, is common, yet somewhat special, in its

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J. Peng and P. Han Industrial Agglomeration

1

3

2

4

5

Transfer of Rural Surplus Labor

Urbanization 6

Fig. 12.1  The relationship between industrial agglomeration, urbanization and transfer of rural surplus labor

Fig. 12.2  Ratio of population in urban areas in the New China. (Source Shanxi statistical yearbook)

economic development and urbanization compared to other provinces in China. We can see that since the beginning of the New China, its urbanization, despite occasional fluctuations, has been stable and continuous (Fig. 12.2). The analysis of data comparing the urbanization of Shanxi province with the national average, roughly shows the following five phases (see Table 12.1).

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157

Table 12.1  Comparison of the urbanization level between Shanxi province and the national average (in %). (Data source: 2006–2014 China statistical yearbook) Year

2005

2006

2007

2008

2009

2010

2011

2012

Nationwide 42.99

44.34

45.89

46.99

48.34 49.95

51.27

52.57 53.73 54.77

Shanxi

42.11

43.01

44.03

45.11

45.99 47.00

49.68

51.26 52.56 53.79

Difference

0.88

1.33

1.86

1.88

2.35

1.59

1.33

2.95

2013

1.17

2014

0.98

a) Beginning of Urbanization, From 1949 to 1957 At the beginning of the New China, the whole country was in the process of resuming production and recovering from the damage caused by war. In the first five-year-plan, Shanxi, as one of the major regions to be reconstructed and developed, made a largescale infrastructure and economic advancement effort towards a multitude of large and middle-sized industrial projects. This caused the population in cities, towns, and places near to industrial and mining enterprises to develop rapidly. This phase saw the ratio of population in urban areas to rural areas increase from 7.9% in 1949 to 15.9% in 1957, a 7.9 percent rise in eight years, and far beyond the country’s average pace. In this phase, the joint development of urbanization and industrialization in the country promoted the urbanization in Shanxi province. Yet, in general, this process was at a beginning stage and thus very premature. b) Fluctuation of Urbanization, From 1958 to 1965 The obvious impact of national policies and the deviation from the macro-policy caused the process of urbanization to experience huge fluctuation, including urban development and the population. Specifically, policies such as those concerning steel making in the Great Leap Forward between 1958 and 1960 led to a huge increase in urban population, skyrocketing to 19.8%. However, such high-level urbanization was inconsistent with the economic development and left an immediate hazardous impact on the development of later phases. During the three years of hardship, the national economy was experiencing a slump, and as domestic economic policies were adjusted, a state of what could be called anti-urbanization emerged. In 1961, the level of urbanization reached its lowest point, with a population in cities and towns of 2934 million, only accounting for 16.1% of the total population. In conclusion, the development of urbanization was fluctuating in this phase as the national economy kept going up and down. Policies on urban establishment varied between being loosened and tightened and the registration system underwent changes. c) Phase, in Which Urbanization Stagnated, From 1966 to 1982 The ten years of the Cultural Revolution, which lasted from 1966 to 1976, seriously damaged China’s national economy and caused a stagnation in industrialization and urbanization. Until 1976, the urban population had increased by only 1.39 million, 2.7% higher than before. As the implementation of reform and opening up policy in 1977 began, Shanxi’s urban population grew slowly, yet only accounted for 21.01% in 1982. Under the policy of the land allocation reform and the opening up policy, the

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economy grew rapidly in rural areas and the momentum to realize urbanization from head to toe increased. In this phase however, the strict rural-urban dual household registration system hindered an increase of the urban population, obstructing the process of urbanization. d) Expansion of Urbanization, From 1983 to 2000 From 1983 onwards, reform and opening up brought efficient economic growth to Shanxi province. As the policy remained in force, both its economy and industry grew rapidly. As a result, its urbanization continued. Firstly, during the establishment of an energy and heavy-industry base, a large group of industrial and mining enterprises that relied on the abundant coal chemical industries, emerged and developed rapidly, which led to the rise of industrial cities. Secondly, both economy and enterprises in rural areas expanded, and more and more surplus rural labor rushed to non-agricultural industries, all of which prompted the development of small cities and towns. By 2000, the urban population had reached 8618 million, accounting for 35.2% of the total population. The expansion of urbanization in this phase is mainly developed from the stronghold of the local resources. e) Since 2001, Urbanization Has Entered a Rapid Development In the 21st century, due to multiple favorable circumstances such as good domestic macroeconomic policies and a soaring domestic and international energy demand, among others, the economic development of Shanxi province has made a big stride towards the stage of development and prosperity. The entire province, under the guidance of the multi-angle policy, which sees energy as the base, has been promoting the economic restructuring unremittingly. This has improved the level of agricultural industrialization significantly, industrial modernization progressed further, emerging and high-tech industries have been developed rapidly, and the emerging service industry has become an important economic sector. Therefore, Shanxi province is now in its best and fastest development period. The rapid development of industry, agriculture and economy has injected a strong impetus into urbanization. Since the beginning of this period, there has been a growing awareness and validation of urbanization by the government. To implement an urbanization strategy and promote the common development of urban and rural areas is one of the important tasks for China’s “fifteenth” period, as stated in the “fifteenth” plan of China’s national economic and social development. Shanxi’s provincial party committee and government compiled the “Urban System Planning of Shanxi Province” and issued a series of supporting documents, which provided a strong support for the policy. Policies restricting urbanization are gradually being differentiated. Generally speaking, Shanxi is a mountainous plateau, but it has a variety of topographies, such as mountains, hills, and basins. From a geographical point of view, there are mostly basins in the center and in most parts of the East and the West there are mainly hills, which creates economic differences among the regions. More active policies are to replace the original ones in 22 new cities so the level of urbanization can enter into a new stage.

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Characteristics of Urbanization in Shanxi Through the analysis and research on the urbanization in Shanxi province since the founding of the People’s Republic of China, the development of Shanxi province, affected by the national economy, macro policies and other aspects, has steadily gained momentum. In the 21st century, influenced by the government’s developing urbanization policy, a favorable environment and the rapid economic development, the urbanization of Shanxi province has entered a new stage. According to the survey on the urbanization rate of Shanxi Province in 2013, conducted by the Shanxi Provincial Bureau of Statistics, the population living in cities was 18.5108 million, accounting for 53.79% of the provincial resident population, and representing 2.34% more than in the previous year. From the current situation of urbanization of Shanxi province, we can find that the urbanization of Shanxi province has the following characteristics: a) Urbanization is Closely Linked to the Regional Economic Development After the founding of the People’s Republic of China, whether it is before the reform and opening up or after, it is clear that the urbanization of Shanxi province has been developing continuously, as has the national economy. Only with the consistent development of the national economy, urbanization in Shanxi province can be continuously promoted. Owing to a strong demand for energy, from both the domestic and the international market, Shanxi, as a major traditional energy providing province in China, has ushered in the golden stage of development in the first decade of the 21st century. During this period, Shanxi’s economic indicators have improved significantly, and the urbanization of Shanxi province has entered into its golden age as well. The urbanization rate has grown from 35.2% in 2000 to 49.68% in 2011, and in 2012 it surpassed 50% for the first time. In 2014, the urbanization rate reached 53.79%. It is developing fast. b) There is Still a Big Gap Between Shanxi Province and the Rest of the Country Regarding the Urbanization Process and Quality. As Table 12.1 shows, the gap between the urbanization level of Shanxi province and the national average has increased from 0.88% in 2005 to 2% in 2010, and then sank to 0.98%. In the recent decade, the national urbanization average has increased by 1.18% annually, and that of Shanxi has grown by 1.17% annually. Its speed is slightly lower than the national average. Although Shanxi continues to accelerate its speed and nearly reaches the national average, there is still a gap in the urbanization process and quality, compared to the eastern region. c) The Spatial Distribution of the Urban Population is Relatively Concentrated, and the Regional Development of Urbanization Shows Differences and is Imbalanced Obviously, the regional economic development is connected to the natural conditions in Shanxi province. In the center of the province there are more than 16 cities; in the East, there are 5 cities; in the West, there is only one city. Accordingly, 71% of the urban population are located in the center where the urbanization level is 9% higher than the provincial average. Apart from this, there are obvious gaps in

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Table 12.2  Urbanization level of 11 prefecture level cities in Shanxi province in 2013 (in %). (Source Shanxi statistical yearbook 2014) Region

Taiyuan Datong Yang­ Changzhi Jin­ Shuozhou Jin­ quan cheng zhong

Yuncheng

Xin­ zhou

Linfen Lvliang

Urbani­ zation rate

84.12

59.03

64.01

46.87

55.52

51.09

48.87

43.06

43.04 45.67

43.11

Rank

1

3

2

7

4

5

6

10

11

9

8

urban development among the 11 cities. The urbanization rate of Taiyuan, the core city in the central zone, reached 84.12%, while the urbanization level of Lvliang in the western region is only at 43.11%. From Table 12.2 we can deduct that in 2013 the cities in Shanxi province with the top three urbanization levels are Taiyuan, Yangquan and Datong. Those with the lowest urbanization levels are Lvliang and Yuncheng. There is a gap of 41.08 percentage points between the highest level of urbanization in Taiyuan city and the lowest level in Yuncheng city. Taiyuan city has entered the “S” curve, being in the third stage, while the other is still in the second stage. The differences in the development of urbanization in the Shanxi province area are significant and the urbanization development is not balanced. d) The Distribution of the Urban Population is Relatively Dispersed and the Degree of Concentration is Declining The distribution of the urban population size reflects the distribution structure of cities with different scales and levels. The forms and distribution characteristics are closely related to the regional economic structure and the stage of regional economic development. Based on the calculation of urban non-agricultural population, the quantitative structure ratio of mega cities, big cities, medium-sized cities and small cities in Shanxi province is 4.5:4.5:22.7:68.3. At the same time, the quantitative structure ratio of the whole country is 6.2:9.2:32.8:51.8. By comparison, the proportion of big cities and medium-sized cities is 6.4 and 10.1 percentage points lower than the national level, respectively. The smaller size cities reflect the situation best. The reason for the great development of towns in the period after the 90s lies in the level of urbanization in Shanxi Province. This improved urban population increase is linked to the forming of new small cities and towns with a trend of a regional expansion. There is a connection between the mode of development and the relatively advanced development with a relatively high level of slow urban population growth pattern. Analysis of the Current Situation and Characteristics of Labor Transfer in Shanxi Province Calculation method of labor transfer rate The secondary and tertiary industries are basically in the town. CCLi represents the migration from rural areas to cities. The actual (i.e. the primary industry) number of migrant workers is the difference between the actual quantity of labor and the quantity

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of labor a year before. Ri is the growth rate of labor transfer from one year to the next. Based on this theory, the formula of rural labor transfer rate is obtained as:

CCLi = CLi − ALi TRLi = CCLi − CCLi−1 Ri =

TRLi − TRLi−1 TRLi−1

According to the calculation method, combined with relevant data, the trend of the rural labor transfer rate in Shanxi Province in recent years is shown in Fig. 12.3. Analysis of the current situation of the rural surplus labor transfer in Shanxi Shanxi is located in the Loess Plateau. The terrain is complex, dominated by mountains, hills, basins and plateaus. The geographical environment and climate of Shanxi province are rather unfavorable to the development of agriculture. With the continuous development of productive forces, the continuous improvement of science and technology, and the increase of population, the rural surplus labor force with its large number of people in Shanxi province can be described as a vast market. After the reform and opening up, due to the implementation of the household contract responsibility system and farmers’ freedom of choice in employment, a large number of rural surplus labor force shifted into the city. According to the data of the Shanxi Provincial Agricultural Department, the surplus of agricultural labor force transferring in Shanxi was 5640 million people in 2006, accounting for 24.6% of the total rural labor force in the province, which is a remarkable amount.

Fig. 12.3  The transfer of rural labor force trends in Shanxi province in recent years. (Source Shanxi statistical yearbook)

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a) Regional Characteristics and Industrial Distribution Characteristics of Rural Surplus Labor Transfer The main direction of labor transfer shows a shift from the secondary to the tertiary industry. Because of the limitation of the quality of the rural labor force and the internal and external objective conditions, the employment level of migrant workers in Shanxi province is relatively low, and the labor force engaged in the secondary industry accounts for more than 50%. Its industry analysis focuses on mining, manufacturing and construction. In recent years, with the increasing proportion of the tertiary industry in the national economy, the ability to absorb labor force has significantly improved and reached more than 46%, also due to low requirements in knowledge, skills and other aspects. b) Characteristics of Labor The rural labor force in Shanxi province is mainly young and middle-aged, and the majority of these people are male. According to data from 2006, the labor force between the 21 to 40 years old people accounted for more than 60% of the total, 75% of which are male. In addition, the education level of the transferred labor force in Shanxi is mainly junior middle school. The slow economic development, keeping the rural areas backward with economic difficulties, leads to a large number of rural people only having finished the nine year compulsory education, losing the opportunity of further education, directly leading to the mostly low quality of the rural labor transfer. c) Features of Rural Surplus Labor Transfer Generally speaking, the labor transfer of rural migrant workers in Shanxi province is mostly spontaneous, organized, with workers being trained but having rarely studied. Most of the migrant workers rely on traditional geographical and interpersonal networks. To a certain extent, it spawned a series of regional characteristics with brands such as the masons in Wutai Mountain, the cake makers in Linyi, and waterproofing engineers in Yuncheng and Wanrong etc. But on the other hand, this directly reflects the influence of geographical features. On the whole, the transfer of labor force in Shanxi is characterized by a large number of unorganized and spontaneous, relatively backward development, and little training. Analysis of Industrial Agglomeration Degree in Shanxi Measurement Index of Industrial Agglomeration Level There are many ways to measure the level of industrial agglomeration. Many studies calculate the level of industrial agglomeration by using a single index method, such as location entropy, the Beh Finn Dahl index, the geographic concentration index, or the dynamic clustering index. The level of industrial agglomeration has complex characteristics, so this chapter adopts the multi index comprehensive evaluation method, a multi factor measure, to calculate the degree of industrial agglomeration. Using multiple indices to evaluate multiple participating units is called the multi index comprehensive evaluation method. The basic idea is to transform a number of indicators into an index which can reflect the comprehensive situation and deal with the evaluation problem of a multi

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factor complex system well. In recent years, this method has become the most widely used evaluation method of economic development, regional competitiveness, industrial agglomeration and so on. Construction of the Index System This chapter takes the independent and operable to establish the principle of the index system, the quantitative evaluation index system, 1 from the market, the factors of production, development and competitiveness, and institutional support aspects. It establishes a comprehensive evaluation index system including 4 first level indicators and 10 level two indices of the country to compare the regional industrial agglomeration level. In this chapter, the expert scoring method is used as corresponding formula for the first level index and the level two index and weight (see Table 12.3). Table 12.3  Evaluation index system of industrial agglomeration level Evaluation index system of industrial agglomeration level

Primary Index and Weight

Secondary Index and Weight

Index Interpretation

Market Concentration Index (30)

Domestic Market Share (35)

Retail sales of social consumer goods/Total retail sales of consumer goods in China

Consumer Market Share (35)

Sales value of industrial enterprises above designated size/National gross sales

Export Agglomeration Degree (30)

The export amount of the business unit/National total exports

Asset Concentration (35)

Total investment in fixed assets/ Total national fixed assets

Agglomeration Index of Production Factors (25)

Employment Number of employed people/The Agglomeration Degree export amount of the business unit (35) Agglomeration Degree Number of scientific and technical practitioners/Number of scientists of Scientific and and technicians in China Technical Personnel (30)

Scale Agglomeration Index (25)

Value Added Agglomeration (50)

Index of Agglomeration Degree of Supporting institution (20)

Financial Institution Support (60)

Loan amount of financial institutions/Loan amount of financial institutions in China

Support Degree of Science and Technology Institution (40)

Local fiscal expenditure on science and technology/National total expenditure on science and technology

Added value/National added value

Enterprise Number of industrial enterprises Agglomeration Degree above designated Size/Total number (50) of enterprises in China

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Calculation of Industrial Agglomeration Degree According to the preliminary processing formula of the two indicators of the original data, the two indicators of the value weighted index system, corresponding to the two level index, calculate an index value, by which the agglomeration degree of Shanxi province from 2003 to 2014 is obtained as calculation according to the weight index of the industry (Table 12.4; Fig. 12.4). Table 12.4  Comprehensive score of industrial agglomeration degree in Shanxi province from 2003 to 2012. (Data sources: national statistical yearbook, China financial yearbook, China industrial economic statistical yearbook, Chinese Urban statistical yearbook: employment population data from 2004 to 2014 based on information obtained from http://tongji.cnki.net/kns55/Dig/dig.aspx) Industry agglomeration degree comprehensive score

2003

2004

2005

Shanxi 174.28 181.96 182.50 Province

2006

2007

2008

2009

2010

2011

2012

2013

2014

183.29 182.22 178.85 169.56 186.62 194.91 193.72 193.82 192.43

Fig. 12.4  2003–2014 Industry agglomeration degree score chart of Shanxi province. (Source Shanxi statistical yearbook)

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12.3.2 Evaluation of the Compatibility Between Urbanization and Rural Labor Transfer in Shanxi Province: Measurement of Coordination Degree Calculation Method of Coordination Degree Based on the previous theoretical analysis, this chapter constructs the coordination degree calculation model between city urbanization and rural labor transfer as follows:  i 2 cxy = (xi + a yi ) / xi2 + (a yi ) 2 i cxy represents the coordination degree between urbanization and rural labor transfer in Shanxi city during No. i year; xi represents the urbanization rate of Shanxi province in No. i year; yi represents the rate of rural labor transfer in No. i year; a is a set of equivalent coefficients to stabilize the magnitude difference between xi and yi. To achieve this goal, we take the mean difference between xi and yi for. n

a=

1  xi n i=1 yi

From the model itself, we can see that c belongs to the range of [−1.414, 1.414], which is determined by urbanization xi rate and rural labor transfer rate yi rate. When xi and yi are positive and equal, the maximum value of c is 1.414. When xi and yi were negative and equal, the minimum value of c is −1.414. Combining the model with the actual situation of Shanxi province, according to the changes of xi and yi, the coordination degree of urbanization and rural labor transfer in Shanxi city is divided into four types, as shown in Table 12.5. Calculation Results of Coordination Degree The coordination degree between urbanization and the transfer of Shanxi’s rural labor force is calculated according to the above proposed coordination degree calculation model, based on the analysis of data from 1998 to 2014. The results are shown in Table 12.6, and the trend of change is shown in Fig. 12.5. Table 12.6 shows that the overall coordination of the degree of urbanization and transfer of rural labor in Shanxi province is relatively high, but also that there are fluctuations in some individual years. Therefore, it is necessary to analyze the specific situation of some years or stages in-depth, and to understand the result of the urbanization process as it is particularly important for the coordinated development of the city, the town, and the rural labor force transfer in Shanxi. Phase Analysis of Coordination Degree If we carefully study the coordination changes of urbanization and rural labor transfer in Shanxi province during the past 14 years, we can find that they have certain stages. This chapter roughly divides into four stages.

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Table 12.5  Classification of coordination degree between urbanization and rural labor transfer C

xi ayi

Types

Features

1.414

xi = ayi

Coordinating

The level of urbanization and rural labor transfer is completely balanced, which shows the overall optimal state in interactive and mutual capacity situations

xi > 0, 1.0 ≤ c 0

Basic coordination

The level of urbanization is basically consistent with the level of rural labor transfer, and both are in a virtuous cycle. Urbanization promotes the transfer of labor force, and the transfer of labor promotes urbanization

c 0, yi > 0 Uncoordinated There is a deviation between the level of urbanization or yi ≤ 0 and the level of rural labor transfer, and the rural labor transfer is seriously lagging behind. A phenomenon of excessive urbanization, which is not conducive to the overall progress of society, has appeared

Table 12.6  Coordination between urbanization and rural labor transfer in Shanxi from 1998 to 2014

Year

Coordination degree

Year

Coordination degree

1998

1.28

2007

1.31

1999

−0.29

2008

1.31

2009

−0.13

2001

1.29

2010

1.4

2002

1.36

2011

1.37

2003

1.14

2012

1.34

2004

1.34

2013

1.28

2005

1.17

2014

1.12

2006

1.3

2000

Fig. 12.5  Coordination degree of urbanization and rural labor transfer in Shanxi

1.38

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a) Period of Extraordinary Change of Coordination Degree (1998 to 2000) On the one hand, from the late 1980s on, the guidance of the market lead to ­high-speed transfer of rural labor. However, because of market defects and an imperfect mechanism, labor mobility was in disorder and lacking awareness, leading to the attention of government in all aspects. In 1995, the central office issued the “Opinions on Strengthening the Management of Floating Population”, beginning to implement the floating population employment certificate and temporary residence permit system. To some extent, it regulated the transfer of rural labor force. In 1997, the central government issued the “Township Enterprise Law”, which promoted the implementation of township enterprises’ fundamental change, and part of the township enterprises began to scale operations. ‘Leaving the land but not one’s hometown and entering the factory but not the city’ has become a new mode of labor transfer. In addition, affected by the Asian financial crisis, after the second half of 1997, the national coal situation needed urgent attention. As a large province of coal mining and electricity generation, Shanxi suffered from the strong economic impact on the industry, which led to a reduced transfer of agricultural labor force. On the other hand, due to the overall planning of the household registration system and Shanxi province cancelling out county cities, the total urban population may not be reduced in a short period of time. Until 2000, the administrative regionalization of the Shanxi province reform was basically completed, except for the establishment of the prefecture level cities of Yuncheng, Linfen City, Xinzhou city and Lvliang city by means of revocation of Yuncheng area and Linfen area, Xinzhou area and Lvliang area in 2003. Other counties have not changed. Under the premise of the steady development of urbanization, the number of labor transfer is not rising or falling, which makes the coordination degree very unstable. Thus, the economic impact of the labor force transfer is direct and obvious, while the influence of urbanization is relatively indirect. These main factors influence the urbanization policy adjustments. b) Orderly Fluctuation of Coordination Degree (2000 to 2005) At the end of the twentieth century, the imbalance of the industrial structure has become the main factor hindering Shanxi’s economy and the development of other sectors. The “two three one” pattern formed since the 1960s, tends to intensify with the secondary industry, taking a tight grip of Shanxi’s economy. In 2000, the proportion of the three sectors of economy was 9.7:46.5:43.7. It later changed to 4.7:60:35.3 in the year 2006. The shrinking agriculture has aggravated the pressure of transferring rural surplus labor force. At the same time, the diminished proportion of the tertiary industry undermines the urban areas’ ability to absorb and incorporate these laborers. According to a compilation of statistics with data of 60 years of China, there are several reasons that contribute to a degree of instability in coordination. These reasons are: the production is too elementary and far from diverse; industrial clusters are not competitive; there is much room for improvement in the personnel development system and it is difficult for migrant workers to integrate into the urban society.

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1998 marked the third plenary session of the 15th Communist Party of China (CPC) Central Committee where the Central Committee’s decision on major issues concerning agriculture and rural work was deliberated and approved. The document points out that developing small towns is a major strategy to propel rural economy and social development. It can accelerate the transfer of rural surplus labor force and is an important way to enhance agricultural labor productivity generating comprehensive economic benefit. Developing small towns can also promote the proper concentration and restructuring of township and village enterprises. The booming development of the rural tertiary industry, as well as more new jobs for farmers can be achieved. After this plenary session, rural labor transfer has entered a new stage of development. Labor transfer to township and village enterprises, coupled with the acceleration of urbanization construction, signifies a big step forward in the integration of the urban and the rural labor market. During this period, the Shanxi Provincial Party Committee and provincial government put forward a series of policies to counterbalance the increasing number of rural surplus labor. The macro control target of national economic and social development in 2003 has explicitly included enhancing employment and re-employment, accelerating labor transfer through various channels. c) Constant Decline of Coordination Degree (2005 to 2008) This period witnessed a constant slump of the coordination degree between Shanxi’s urbanization and rural lobar transfer. Influenced by the gloomy coal mining outlook across the country, Shanxi’s economic development in this period took a slower step. A decline of the economic-driven employment absorptive capacity became evident. From 2005 to 2007, the coal, coke and iron market was nearly saturated but rife with uncertain factors. The industry development encountered many difficulties and there was a big fluctuation in the economic operation. With eliminating backward production capacity as the overall strategy, some traditional sectors diminished, bringing some temporal barrier to the economic development. At the same time, Beijing winged the bid for the 2008 Olympic Games, as good news cannot be ignored. Large scale infrastructure construction being a driving force for the great leap forward in the bedrock sectors, urbanization forged ahead steadily. Overall, the constant drop in the coordination degree during this period can be attributed to slower economic operation. A series of preferential policy towards farmers makes rural labor transfer lag behind urbanization. d) Coordination Degree Approaching Stability (2008 to 2014) Since 2008, the Shanxi Provincial Party Committee and the provincial government governed and optimized the industrial structure and integrated coal resources. At the same time, a wave of practicing scientific outlook on development took hold across the country. Under the guidance of this strategy, Shanxi province had a stable economic and social development, social contradictions being highlighted. Human resources and material resources have been used more efficiently.

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This period was characterized by a stable development in Shanxi’s urbanization and rural labor transfer with a high coordination degree. It indicated that the transfer of rural labor met the demand of human capital used by urbanization. While the Southern coastal cities suffered from labor shortage, Shanxi province was able to provide sufficient labor to urban areas. In addition, the level of urbanization could provide a sufficient amount of jobs for rural surplus workers, solving one of the three rural issues concerning the increasing income of farmers. The social problems generated by the cluster of the rural idle population were greatly reduced.

12.3.3 Interactive Study of Urbanization and Transfer of Labor Force in Shanxi Province—The Analysis of Relevant Factors and Empirical Tests An advanced coordination of urbanization and the rural labor transfer can promote the politically orderly transfer of rural forces, as well as a steady urbanization. This requires an analysis of the related factors that are linked to these two areas. To discuss their mechanism of actions towards urbanization, rural labor transfer and the coordination degree of economic development and the social environment, system and policy have been chosen in this chapter. Model Construction and Data Source In this chapter, the following model and related data were used for empirical test:

COR = C + a1 RGDP + a2 RNAG + a3 RALS + a4 RINC + a5 RIA + a6 DVP COR represents the coordination degree RGDP represents the regional GDP growth rate RNAG represents the growth rate of the second and tertiary industries proportion RALS represents the farmland non-agri-use ratio (Cultivable area reduction ratio) RINC represents the per capita income ratio of urban and rural areas RIA represents the Industry Agglomeration Score DVP represents the policy reform dummy variable C represents the constant term; a1 , a2 , a3 , a4 , a5 , a6 are the coefficients of each variable. The data sources for each variable are as follows: a) For the coordinate data sources see Table 12.6 b) Regional GDP growth rate = (regional growth rate of the respective year) / regional growth rate of the respective year)/regional growth rate of the respective year X 100%; c) Growth rate of the second and tertiary industries proportion = (growth rate of the respective year—growth rate of last year) / growth rate of the year before X 100%;

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d) Farmland non-agri-use ratio = (cultivable land area of this year’s end—cultivable land area of the respective year’s beginning) / cultivable land area of this year’s beginning X 100%; e) Per capita income ratio of urban and rural areas = urban per capita disposable income of the respective year/rural areas per capita net income; f) Policy reform dummy variable. Since the beginning of the 21st century, the urbanization of Shanxi province has entered a period of rapid development. The provincial and municipal governments have always been committed to improving the quality and efficiency of urbanization and to the optimization of urban functions. After several years of research, demonstration and consultation, Shanxi’s Provincial People’s Government promulgated the Shanxi Province Town System Planning in 2006, to prevent an overheated development of urbanization. It emphasized the coordinated development of urbanization and industrialization, regional economy, resources and environment. In the same year, the Shanxi provincial government issued ‘Views on how to further accelerate the rural labor transfer’. It required the formation of a multi-channel, multi-level, multi-form transfer of the rural labor force and an establishment of a unified urban and rural labor market, as well as the promotion of the rapid development of the labor economy and thus the realization of economic and social progress. As a result, the institutional environment after 2006 has undergone a major and significant change. This study chooses 2006 as the starting point for the policy reform. An empirical test of the policy reform, the relationship between urbanization and the transfer of rural labor force is conducted. For the main indicators of the required data, see Table 12.7. Estimated Results By using the statistical data between 2003 and 2014, an empirical test was made by applying the metrological analysis software SPSS to analyze the factors affecting the urbanization and rural labor force transfer. The result is shown in Table 12.8, with the coordination degree being the dependent variable, and the number of samples being 12. From the test results we can deduct that the influence of the factors of the model selection on the coordination degree is in consistence with our theoretical analysis of the hypothesis. The test value of model regression R2 and F are prominent, which indicates the model is effective. From the respective variable coefficient symbol, the influence of each factor on the coordination degree is also in consistence with the theoretical hypothesis. Economic growth has a significantly positive impact on the coordination of urbanization and rural labor transfer, the coefficient was significantly different at 1% level. The proportion of the secondary and tertiary industries has a significantly negative impact on urbanization and the rural labor transfer coordination, the coefficient was significantly different at the 5% level. There is a significantly positive impact on the degree of coordination between

1.28

1.12

2013

2014

−0.13

2008

1.34

1.31

2007

2012

1.3

2006

1.37

1.17

2005

1.4

1.34

2004

2011

1.14

2003

2010

1.36

2002

1.38

1.29

2001

2009

1.31

0.35

1.60

1.22

4.47

3.34

3.37

−2.66

0.86

5.40

10.99

3.91

12.00

3.40

4.52

4.05

−2.35

53.79

52.56

51.26

49.68

48.05

45.99

45.11

44.03

43.01

42.11

39.63

38.81

38.09

35.09

35.88

31.35

1.26

4.04

7.79

22.13

25.04

21.43

0.59

23.49

15.32

18.46

25.08

22.82

14.56

9.96

10.71

0.48

−0.35

−0.1

−0.06

0.32

0.53

0.75

2.62

1.17

0.53

1.08

1.64

1.1

−0.22

0.46

−0.34

2.64

0.11

−0.03

0.37

0.03

−0.89

−1.94

0.92

2

−5.24

8.54

1.06

1.54

4.16

5.29

1.19

0.35

0.33

0.59

2.73

3.14

3.21

3.23

3.3

3.3

3.2

3.15

3.15

3.08

3.05

3.05

2.9

2.76

2.48

2.45

2.2

−0.29

2000

9.15

1999

31.03

1.28

1998

4.29

Coordination Rural labor Urbanization Regional Growth rate of the Farmland Per capita degree transfer rate (%) GDP growth 2nd & 3rd industries non-agri-use income ratio of rate (%) rate (%) proportion (%) ratio (%) urban and rural areas

Year

192.43

193.82

193.72

194.91

186.62

169.56

178.85

182.22

183.29

182.5

181.96

174.28

1

1

1

1

1

1

1

1

1

0

0

0

0

0

0

0

0

Industry Policy Agglomeration reform Score dummy variable

Table 12.7  Data on the factors affecting the coordination of urbanization and rural labor transfer. (Source Shanxi statistical yearbook)

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Table 12.8  Analyzing results of factors affecting the coordination of urbanization and rural labor transfer Independent variable

Coefficient estimation

Test value of T

Significance R2 level

R2 after adjustment

Test value of F

Constant term C

3.112

3.566

0.007

0.669

6.244

RGDP

0.065

5.379

0.001

RNAG

−0.161

−2.579

0.033

2.095

0.069

−1.009

−2.794

0.023

4.352

0.041

0.172

0.878

0.406

RALS RINC RIA DVP

0.043 0.675

0.796

urbanization and rural labor transfer, the coefficient is significant at the 10% level. The income gap between urban and rural areas has a significantly negative impact on urbanization and rural labor transfer coordination, the coefficient was significantly different at the 5% level. The degree of industrial agglomeration has a significantly positive impact on the coordination of urbanization and the rural labor transfer, the coefficient is significantly different at 5%. Due to the low sample size, the positive impact of policy reform on the degree of coordination is not significant, thus the error is too large. From the respective coefficient of variables, the urban-rural income gap has a greater impact on the coordination degree, the expansion of urban and rural incomes will greatly inhibit the coordinated development of urbanization and the rural labor transfer. Positively, economic development and industrial agglomeration are conducive to the coordination of urbanization and the rural labor transfer. Therefore, the key to coordination, urbanization and rural labor transfer is to unswervingly develop the economy and to promote industrial agglomeration, while at the same time narrowing the urban-rural income gap.

12.4 Research Conclusions and Policy Suggestions 12.4.1 Conclusion 1. The development of urbanization based on industrial agglomeration is of great significance to the local transfer of the rural surplus labor force. At the same time, relying on industrial agglomeration to speed up the process of urbanization, is a targeted solution to the lag of urbanization of Shanxi province. It is feasible to promote the transfer of rural surplus labor in Shanxi province.

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2. Mutual interaction is the interaction formed by urbanization and the rural labor transfer with mutual promotion, but also an adaptation to each other, that is, a higher degree of coordination relationship. The effect of the interaction between urbanization and rural labor transfer is that the long-term development trend of the two is basically synchronized. The constraints of the two have fully exerted an influence on minimizing and promoting impacts. Both can absorb each other’s reasonable core, which is conducive to developing their own in the process to form a virtuous circle. 3. Urbanization and rural labor transfer are part of the economic and social development. The sustainable development of Shanxi province requires an effective harmonious relationship between the two. If the coordination degree between urbanization and the rural labor force is rather high, not only the rural labor force can be better transferred to reduce an inefficient deployment of human resources, but it can also reasonably control the speed of urbanization to avoid a waste of social resources from excessive urbanization. 4. From 1998 to 2014, there were twists and turns in the coordination between urbanization and the rural labor in Shanxi province, but the overall trend was good. Apart from the mismatched and uncoordinated phenomenon caused by large fluctuations of economic and policy factors in some individual years, the urbanization and rural labor transfer of Shanxi province has mostly shown a mutual beneficial trend. 5. The coordination degree between urbanization and the rural labor transfer in Shanxi province is proportional to the speed of the economic growth, the degree of industrial development and the industrial agglomeration. 6. There is a negative relationship between the coordination degree of urbanization and rural labor transfer of Shanxi province, the proportion of secondary and tertiary industries and the income gap between urban and rural residents. 7. The revocation of the household registration system and the reform of the employment system under the background of the new period are conducive to the harmonious development of urbanization and rural labor transfer in Shanxi province. Due to the time lag of the system policy and the limitation of the selected data in this chapter, the influence of the institutional factors in the empirical test on urbanization and the rural labor transfer is not significant. However, through qualitative analysis, we believe that an innovation of the household registration system and the employment system is conducive to the harmonious development between urbanization and rural labor transfer.

12.4.2 Policy Suggestion Based on the above theory and empirical analysis, this chapter puts forward the policy suggestion of Shanxi province to realize the urbanization through the industrial agglomeration to solve the problem of the transfer of rural surplus labor as soon as possible in the light of the actual situation in Shanxi province.

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To improve the resistance mechanism of harmonious development between rural labor transfer and population urbanization, it is important to thoroughly implement the household registration system reform policy. In order to speed up the process of population urbanization, the state has introduced a number of relevant policies and measures, among with the gradual release of urban household registration, which opened a door for residents who are willing to live in the city. But, on the whole, the different pace and efforts of the country have an effect on the implementation of the policy. Therefore, local governments should pay close attention to the implementation, to ultimately find a solution for the lack of institutional supply. In addition, it should also focus on solving the problems of children’s schooling and the improvement of the social security system. The second step is to establish a transfer mechanism of rural land elements as soon as possible. Land is not only an important factor in production, but also the life insurance for rural residents. For the migrant farmers, giving up the land means to give up their wealth. In rural areas, farmers’ land property rights are unclear and circulation is strictly restricted. The transfer of land rights of farmers cannot reflect the sticky effect on population urbanization. It also causes a large number of “amphibious” farmers to form an anti-rally of population urbanization. Therefore, it is imperative to establish a splitting circulation mechanism of rural land property rights and finally to establish and improve the employment service system of rural labor. Based on the regional practice, resource-based industries and heavy chemical industries in Shanxi and other central and western regions were developed first, resulting in “capital exclusion labor”. Additionally, some industries without agglomeration effects (such as resource-based industries), which are very limited in their ability to absorb ­non-agricultural labor force, restrict the development of urbanization. The eastern region has chosen a labor-intensive light industrial road. Industrial succession and international experience are basically the same: light industry, heavy industry, and heavy processing industry development. At the same time, the level of urbanization has increased rapidly. The main problem in its development is that the enterprise’s demand for the city exceeds the city’s supply capacity and the population demand for the city is relatively low. For these two different regions, industrial policy, land policy and population migration policy should be treated differently. We should continue to vigorously develop ­labor-intensive industries in the central and western regions, to play the advantage of rich human resources and lower labor costs, and through the rise of the non-agricultural rate to promote the transfer of population to the city and town areas—the southeast coast area is developing capital-intensive industries and technology-intensive industries. At the same time, we should vigorously develop the tertiary industry.

Additional Literature 熊按.论扩张就业容量与转移农村剩余劳动力[J].武汉科技大学学报. 2005(2), p. 6. 吴学花.中国产业集聚分析[D].山东大学博士学位论文, 2006.

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吴勤堂.产业集群与区域经济发展藕合机理分析[J].管理世界, 2004(2), p. 133. 吴敬琏.农村剩余劳动力转移与“三农”问题.[J].宏观经济研究, 2006 (6). 魏守华.王缉慈.论专业化区域经济发展中地方政府的作用—以浙江嵘州市为例[J]生产力研 究, 2001(6), pp. 88–90. 魏后凯.中国制造业集中状况及其国际比较闭[J].中国工业经济, 2002.2., pp. 41–49. 魏后凯.中国制造业集中与非效率探讨闭[J].工业经济研究, 2003.4., pp. 1–6. 王子龙等.产业集聚水平测度的实证研究[J].中国软科学, 2006 (3), pp. 109–116. 王萍.中国农村剩余劳动力乡城转移问题研究.[D].东北财经大学博士学位论文, 2006. 王德.叶晖.我国地域经济差异与人口迁移研究.城市规划[J], 2006(9), pp. 52–56. 托马斯.莫尔.乌托邦.[M].戴镏龄.北京:商务印书馆, 2009, pp. 76–98. 托达罗.经济发展与第二世界.中国经济出版社, [M] 1992, p. 232. 佟光雾.聚集与积累一中国农村城镇化发展[M].哈尔滨东北林业大学出版社, 2005. 田新翠等.山西农村剩余劳动力转移现状及其对策.经济研究导刊, 2010 (19). 田心翠.曾世有.白宪生.山西农村剩余劳动力转移现状及其对策[J]经济研究导刊, 2010, p. 93 (19). 苏雪串.城镇化进程中的要素集聚、企业集群和城镇群发展[J].中央财经大学学报, 2004 (1), pp. 49–52.

Part IV Digitalization, the Financial Sector, and International Trade Cooperation

How a New Thinking Determines the Future of (Small) Banks

13

Marcel Seidel

Contents 13.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 13.2 Differences Between Marketing 1.0, Marketing 2.0 and Marketing 3.0. . . . . . . . . . . . . . 180 13.3 New Customer Image. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 13.4 Application of New Technologies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 13.5 Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

Abstract

Marketing has proven itself to be a constantly evolving business. One of the most famous minds who has been analyzing the marketing development for many decades is the well-known economist Philip Kotler. Banks need to adapt to these developments if they aim to survive. This task becomes much more urgent considering the fact that young, small, flexible and technology-updated financial companies such as FinTechs have been increasingly interfering with the established banking industry. As a result, traditional banks must react fast. The competition for the redistribution of market shares has long been in progress. In the current market, the size of a bank alone is no longer a guarantee of success. Rather than “the big ones eating the small ones”, banking, similar to other businesses nowadays, is the “fast” eating the “slow” ones.

M. Seidel (*)  FOM University of Applied Sciences, Stuttgart, Germany e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_13

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13.1 Introduction The banking landscape has been in vigorous motion for many years. After the financial crisis in 2009, the recovery road for the banks in Europe has been long and hard. They did not only have to regain lost trust from customers, they also had to meet the challenges faced by all companies in the German economy, which include all the megatrends such as globalization and connectivity of the ever-fast-growing economy. To meet these challenges, the banks need a successful marketing strategy. The well-known economist Dr. Philip Kotler has been monitoring and examining the marketing development within the last 40 years. He recounted these changes and published a serial of books on marketing. His most recent publication is titled “Marketing 4.0” (Kotler et al. 2017). In his books, Dr. Kotler describes the shifts in marketing in the past decades from product-driven Marketing (1.0) to customer-centric Marketing (2.0), and ultimately to human-centric Marketing (3.0). In Marketing 3.0, he observed customers who were transformed into “whole human beings with minds, hearts, and spirits” (Kotler et al. 2017). Therefore, he argues, that the future of marketing lies in creating products, services, and company cultures that embrace and reflect human values. The ­technology-advanced digital marketing strategies (4.0) will aid to achieve these goals.

13.2 Differences Between Marketing 1.0, Marketing 2.0, and Marketing 3.0 As Fig. 13.1 illustrates Marketing 1.0 started off with selling the factory’s output of products to all who would buy them. At this time, marketing was not called marketing. Instead, it was the simple sale of products. These products were fairly basic and were designed to serve a mass general market. The goal was to standardize and scale up to achieve the lowest possible costs of production so that these goods could be priced lower and made more affordable to more buyers. Henry Ford’s Model T automobile epitomized this strategy. Mr. Ford stated in 1909: “Any customer can have a car painted any color that he wants so long as it is black.” This was Marketing 1.0 or the product-centric era (Kotler, P. 2010). Later, in the 1980s, Marketing 2.0 came out, with its core being information technology. In many industries, Marketing 2.0 is still the working concept and lasts until today. During this period of time, consumers were well informed due to the development of various communication methods, and they could easily compare several similar product offerings. The value of products is defined by the consumers, who differ greatly in their preferences. A successful marketer must segment the market and develop a superior product to target a specific group of consumers. The golden rule “the customer is king” works well for most companies. Consumers are better off because their needs and wants

13  How a New Thinking Determines the Future of (Small) Banks Marketing 1.0

vs.

Marketing 2.0

181 vs.

Marketing 3.0

product-centric marketing

customer-oriented marketing

value-driven marketing

objective

sell products

satisfy and retain the consumers

make the world a better place

enabling forces

industrial revolution

information technology

How companies see the market

mass buyers with physical needs

smarter consumer with mind and heart

whole human with mind, heart and spirit

key marketing concept

product development

differentiation

values

company marketing guidelines

product specification

corporate and product positioning

corporate, vision, values

value proportions

functional

functional and emotional

functional, emotional and spiritual

interaction with consumers

one-to-many transaction

one-to-one relationship

many-to-many collaboration

new wave technology

Fig. 13.1  Comparison of Marketing 1.0, 2.0, and Marketing 3.0. (Source Based on Kotler et al. 2010)

are well addressed. They can choose from a wide range of products with functional characteristics and alternatives. Unfortunately, the consumer-centric approach implicitly assumed the view that consumers were passive targets of marketing campaigns, and the companies were trying to influence consumers’ mind and heart. With a variety of products to choose from, today’s consumers have developed a much different mindset when selecting goods. Of course, not all consumers have acquired the same selecting ability. However, this power is increasingly stronger in those who belong to the main banking group of the banks: the educated and wealthy customers. This leads into a direction that Kotler has described in Marketing 3.0—the value-driven marketing. In addition, due to the financial crisis in 2009, many consumers have realized that it is important to take sustainable business seriously and that they should even actively support it. Companies that practice Marketing 3.0 provide answers and help people who, for example, are concerned with the questions of how to make the world better. In return, they connect with their consumers at a higher level. In Marketing 3.0, companies differentiate themselves by their values. In a turbulent market, this differentiation is arguably a strong one. This is one of the reasons that the banking industry did not utilize Marketing 3.0 in general practice. Still, there are single institutes that emphasize the importance of employing a sustainable and appreciative approach with people (customers) and nature. In addition to the value-driven conversion of marketing, the advance of technological networking another very fundamental development that has a significant influence on marketing is led by.

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This evolvement in marketing is particularly evident when relating to the numerical development of social networks. Worldwide, social networks such as WeChat, WhatsApp or Facebook are experiencing high levels of access. Admittedly, this is something that, at first glance, does not necessarily affect the banks. On closer examination, however, dealing with customers, or creating a stable group of consumers, and enhancing the relationship to customers, are central tasks of a bank. Moreover, a steady decline of the frequency of customers’ contacts is another reason for banks to look for alternative ways to reach their customers. The shift to the usage of social networks by customers allows the consideration of at least two challenges that the banks need to face. First, they must deal with the changed behaviors of their customers adequately. Customers usually do not contact the company and the company usually does not contact individual customers. Today it is different: Customers are encouraged to contact the company via social networks, and the company builds individual relationships to customers, through social networks. Moreover, banks have to make use of, adapt to and apply the current technical possibilities while dealing with customers. This technological component of the development of customer relationships has led Kotler to talk about ‘Marketing 4.0’ in his latest book. In particular, a change to a thoroughly interconnected world is described (Kotler et al. 2017). From a perspective view, the change in marketing should, of course, be incorporated into the already existing marketing instruments (4P marketing instruments) that have been tested for many years. Their relationships amongst each other are shown in Fig. 13.2.

13.3 New Customer Image From this rather theoretical view, I would like to argue through the usage of some practical examples that support my thoughts. My research concentrates on smaller banks, mainly from the cooperative sector. Due to limited resources, smaller banks in particular

Fig. 13.2   The marketing of the financial services industry has to master two things

product

new customer image

place

promotion

use new technologies

price

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are finding it harder to establish connections or create adequate contact opportunities to their customers. In order for a company to be successful on the long run, the strategy must be continually adapted to the existing and, above all, future requirements. In this context, it is important to verify the mission and purpose of a company. The question to be asked is it exists at all. The answer to this question is crucial to formulate the vision of a company. The vision defines what the company wants to achieve in the long run. Subsequently, the values that are relevant to the company should be clearly identified. These values stand for the handlings of the company with respect to internal and external relations. Once a company has made the effort to formulate its values, it is equally important to communicate these values and, above all, to synchronize them with the values of the employees in an active manner. If this does not happen, the values often appear worthless or disappear in the desk drawer forever. On the Homepage of the the Steyler Bank we learn, that it is the oldest ethical bank in Germany (Steyler Bank 2017). Since its foundation in 1964, the Steyler Bank has been a serious counterpart to the primarily profit-oriented banking world (Steyler Bank 2017). In 1964, the Steyler Bank established its first solidarity and ethical investment. One reason is because our bank profits do not flow into the pockets of shareholders, we direct them directly to the aid projects of the Steyler Ordensleute (Steyler Bank 2017). As an ethical bank, the bank’s philosophy is to keep up with the religious principles of the Stele missionaries—according to the motto: ‘We advocate peace, justice and the preservation of creation’ (Steyler Bank 2017). This vision is both a chance for the society and a challenge. In the Steyler Ethikbank’s mission statement, therefore, those tasks, values, and goals are defined, which determine the daily ethical behavior in practice (Steyler Bank 2017). The GLS Bank is the first social and ecological bank in Germany. GLS stands for “Gemeinschaftsbank für Leihen und Schenken”, which translates as “community bank for loans and gifts”. The bank was founded in 1974. It currently finances around 23.000 projects and businesses (GLS Bank 2017). The GLS Bank focuses on cultural, social and ecological projects, which try to tackle challenges in our society by developing creative solutions. Loans are offered to projects like independent schools and kindergartens, organic farms, institutions using therapeutic pedagogy, nursing homes, projects for the unemployed, health-food stores and communal living projects, as well as sustainable businesses (GLS Bank 2017). Transparency is one of the main objectives of the GLS (GLS Bank 2017). Details of all the initiatives and the companies that have received loans are published in its magazine titled “Bankspiegel” along with the information on the development of the bank itself. What distinguishes the GLS Bank is not only the fact that the it invests its savers’ money responsibly, but also that savers with the GLS can choose the area in which their money will be invested (GLS Bank 2017).

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Moreover, when customers choose reduced interest payments for their savings, the GLS Bank is able to grant loans to charitable projects with an interest rate that only covers the basic loan administration costs of the bank. The work of the bank is supported by more than 40.000 cooperative members (GLS Bank 2017).

13.4 Application of New Technologies Technological development has been at great speed in recent years. The number of inventions that are useful to the banks is almost countless. Here, I concentrate on two important currents: the development of FinTechs as an increasing competition for banking and the use of apps (an application software) in banking. If a CEO of a bank was asked today if he knew which company is the world’s biggest fins, he would probably shake his head. Although the threat of FinTechs has now been known to the bank circles, oftentimes it is not dismissed as a long-term non-survivable trend. I consider this a mistake. If we look at the current developments in the FinTech market, the trend continues. Some examples are: • Lufax This largest Fintech company is valued at 10 billion dollars, which topples the values of the other companies. Lufax has so far provided 200.000 loans with a volume of 2.5 billion dollars. With plenty of fresh capital, Lufax CEO Gregory D. Gibb plans to develop Lufax to be a dominant platform in the Chinese market. • Lending Club The fierce growth of Lending Club is fueled by increasingly restrictive lending by the banks. Since its inception in 2007, the US-company has already arranged loans worth more than six billion dollars. In 2014, Lending Club went public. Currently, the company is valued at 6.5 billion dollars and is thus in second place. • Square Since 2013, Square has been offering an iPad-based checkout system with the Square Stand. Now the mobile payment provider is working on an alternative on Android basis. Twitter co-founder Jack Dorsey is the boss of Square, which has a corporate value of six billion dollars, the largest Fintech-company of this kind. To respond to these market changes, banks should actively monitor the threat and learn from the competition. If neither of these options was to be considered, it might result in a situation in which banks could no longer catch up. In terms of the development of application software for banking purposes, a lot has happened in the last few months. This is also good, as studies show that the younger and middle generation of bank customers simply assume that their bank offers this (Fig. 13.3).

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view all your finances in one place

74,5 %

pay a merchant in-store or online

62,8 %

remote deposite

62,6 %

view all your loyalty card/ points pay another person (P2P)

54,8 % 52,1 %

Fig. 13.3  Features ranked as “highly valuable” in mobile app. (Source own illustration based on Celent Research 2012)

13.5 Solution In summary we can conclude that at least two aspects are rather urgent matters in today’s banking industry. First, the needs of the customer shall be addressed. In particular, the changes in the needed structure should be respected. Respecting is then followed by active involvement of the company’s strategies and their adaptation. In addition, new technologies, which, admittedly, are increasingly being developed, must also be actively examined and involved in internal and external processes. This is not always a simple step because of the rapid development, especially for the small banks, which do not have large development departments (or even none) and resources. However, here again the much-quoted saying of the former BMW CEO Eberhard von Kühnheim “It’s not the big ones that eat up the little ones, but the fast ones that eat up the slow ones” (Zitate 2019).

References Celent Research. (2012). Celent Research on U.S. Mobile App Preferences. https://www.slideshare.net/MXenabled/7-tips-to-lead-the-digital-banking-revolution-white-paper. Accessed 17. April 2019. GLS Bank. (2017). https://www.gls.de/privatkunden/english-portrait. Accessed 17. April 2019. Kotler, P., Kartajaya, H., & Setiawan, I. (2010). Marketing 3.0—From products to customers to human spirits. Hoboken: Wiley. Kotler, P., Kartajaya, H., & Setiawan, I. (2017). Marketing 4.0—Moving from traditional to digital. Hoboken: Wiley.

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Steyler Bank. (2017). https://www.steyler-bank.de/Bank-Profil/Ethisch-handeln/Ethische-Bank/ c831.html. Accessed 13. May 2019. Zitate. (2019). https://www.zitate.de/autor/Kuenheim%2C+Eberhard+von. Accessed 13. May 2019.

Development Strategy of Coal Science and Technology Financing in Shanxi

14

Zhang Wenlong

Contents 14.1 The Origin and Importance of Science and Technology Financing. . . . . . . . . . . . . . . . . . 188 14.2 Analysis of the Applicability of Science and Technology Financing to the Coal Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 14.2.1 Features of Coal Industry Technology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 14.2.2 Point of Integration of Science and Technology Financing and the Science and Technology of the Coal Industry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 14.3 Development Foundation of Science and Technology Financing of Shanxi’s Coal Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 14.4 Strategies of Shanxi’s Science and Technology Financing Development. . . . . . . . . . . . . 193 14.5 Difficulties in Coal Science and Technology Financing and Countermeasures . . . . . . . . 195 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195

Abstract

The “revolution of coal” of Shanxi province needs the support of coal science and technology. Science and technology financing is an important tool to promote the development of coal science and technology. Based on the analysis of the connotation of science and technology financing, the integration of science and technology financing and the coal industry, and the foundation of the development of Shanxi province’s science and technology financing, this chapter puts forward that Shanxi province should take the innovation of the whole coal industry chain as the objective and take environment construction, system construction and platform construction as the W. Zhang (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_14

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starting point. The government’s policy guidance function and financial leverage is actively given play, to mobilize a variety of scientific research platforms, i.e. large coal enterprises, to carry out the coal science and technology research initiative and financial institutions to support the initiative of coal science and technology innovation, and vigorously promote the quality of coal science and technology. With these means, the forces of transformation can be productive. This chapter also makes suggestions for a solution to the difficult problems in the implementation of coal science and technology financing. The successful implementation of Germany’s Industry 4.0 and Made in China 2025 strategies requires a strong technological support. For Shanxi, as a big province of coal industry, the key to enhancing industrial core competitiveness lies in giving full play to the function of coal science and technology. Coal science and technology financing is the foundation of, and the guarantee for, innovation in coal science and technology. The development of coal science and technology financing needs the government and the market to work together.

14.1 The Origin and Importance of Science and Technology Financing Science and technology are primary productive forces, and technological innovation requires a strong financial support. Science and technology financing was initialized by the China Science and Technology Finance Association established in Guangzhou in 1992. Under the guidance of the country’s innovation-driven strategy, China’s research and development departments have conducted fruitful explorations and developments in science and technology financing in recent years. Theorists have conducted in-depth studies on the connotation, components, operation mechanism, practice mode and efficiency measures of science and technology financing. The central and local government departments have promulgated a large number of policy documents on promoting the development of science and technology financing. The development department fully combines the actual conditions of various regions and formed a unique financial support for technological innovation. Wang Hongqi et al. (2012) provide a scientific method and decision-making reference for the coordinated development of national science and technology innovation and science and technology financing, by constructing the model of degree-of-coordination and coordination degree of a composite system of science and technology innovation, science and technology and the financial system. Zhao Changwen et al. (2007) argue that science and technology financing is a series of systematic and innovative arrangements for a series of financial instruments, financial systems, financial policies and financial services that promote the development of scientific and technological achievements, the transformation of achievements and the development of high-tech industries. They are provided for scientific and technological

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innovation activities such as financial resources of the government, enterprises, markets, social intermediaries and other various forms of the main body of the system. From this definition, we can see that science and technology financing is a systematic solution to support science and technology innovation activities. Its purpose is to speed up the pace of scientific and technological innovation and industrialization of scientific and technological achievements by maximizing the financial support and risk management functions of finance. It is beneficial to use and enhance the scientific and technological contribution and modernization of industries, to improve the quality and efficiency of the economic development, and to promote the progress of society and the full freedom of mankind. A science and technology innovation needs to undergo the transformation from basic research, application development, pilot testing, commercialization, scale to real productivity, and risks innovation failure in all aspects of technological innovation. Zhang Laibu (2011) explored the functional orientation of the government in technological innovation by analyzing three forces that promote scientific and technological innovation: the market, the government, and the third force (informal relations). The more innovation faces the overall uncertainty, the more obvious gets the difference between private benefits and social benefits brought by innovation activities. The more reluctant a company is to invest capital, the more obvious the market failure effect will be. At this time, we should give full play to the government’s resource allocation function and prevent the lack of government from causing the entire society to invest insufficiently in science and technology. The more uncertainty the overall innovation is facing in the latter part of technological innovation, the more personal income will be contributed to the innovation of the industry to make up for the investment cost. The stronger the company’s willingness to invest capital, the higher is the financial market allocation capital and efficiency. We should try our best to avoid excessive government intervention in the enterprises to prevent the government offside phenomenon leading to inefficient investment in science and technology.

14.2 Analysis of the Applicability of Science and Technology Financing to the Coal Industry 14.2.1 Features of Coal Industry Technology First, technological innovation permeates all aspects of the coal industry chain. From a vertical perspective, the possibility of finding coal resources and accompanying resources and the accuracy of coal resource reserves depends on the advanced nature of coal exploration equipment and technologies. The feasibility and economic benefits of coal resource exploitation depend on the degree of modernization of mining equipment and technologies. The length of the extension of the coal industry chain depends on the degree of maturity of coal liquefaction, gasification technology and coal chemical

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technology. From a horizontal perspective, the joint exploitation and utilization technologies of coal and its accompanying resources, the energy-saving and environmental protection technologies in the process of coal resource development and the circular economy and technology that promote the common development of the coal industry and other industries, are important to enhance the economic benefits and ecological and environmental effects of the coal industry. Second, the industrial application of the coal industry technology threshold is higher. Coal resources are important energy resources for the national economy. The exploration and exploitation technologies, the extension of the industrial chain and the utilization of recycling economy and technology all require a high barrier to entry. The production scale of a single mine and the scale of raw coal owned by a business enterprise are the preconditions for the promotion and utilization of science and technology in the coal industry. For example, the annual mining scale of a single mine in the coal mining sector determines the economic feasibility of popularizing and applying mechanized mining equipment. In the extension of the coal industry chain, the amount of high-end chemical products produced by a ton of coal is extremely small but the unit value is very high. With a higher scale of raw coal to carry out the production of high-end chemical products economies of scale can be achieved. In the circular economy of coal, coal and coalbed methane mining, low thermal coal gangue power generation, fly ash production of building materials and other recycling economy chain in the upstream and downstream and related industries between the accompanying material have a strict proportional relationship. Companies only have reserves of resources and the scale of coal in order to carry out the circular economy of coal and thus achieve a range of economic effects.

14.2.2 Point of Integration of Science and Technology Financing and the Science and Technology of the Coal Industry First, “revitalizing coal” requires scientific and technological support. Shanxi province is a large province of coal resources. However, the long-term superiority of coal resources not only failed to turn into a sustained economic competitive advantage and social development superiority in Shanxi province, but has caused Shanxi province to suffer from such problems as high economic volatility, a deteriorating political environment, and the destruction of resources and the environment “resource curse” pain. In 2014, the Shanxi Provincial Party Committee and the provincial government put forward the strategy of “revitalizing coal” to promote the transformation of the “six types” of coal industry. The core of this strategy is relying on the power of science and technology to transform the traditional coal industry, depending on the quantity expansion into a full cycle and deep processing, high-end connotative development model, through the use of a new technology path of coal and related industries intensive access to deep processing of coal and high-end conversion of the market value to enhance the added value of the entire coal industry.

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Second, coal science and technology needs the joint efforts of the government and the market. Similar to other scientific and technological innovations, the scientific and technological innovation in the coal industry includes the key technical innovations of industry commonality and the unique technological innovations of enterprises. For the industry’s common key technologies, because of its strong fundamentals and large externalities, enterprises will be reluctant to invest more than their own profits. At this time, government financial support is of great significance. For the enterprise-specific technology, although the cost invested by the enterprise may be less than the expected return it can obtain (due to its social positive externalities), the government can encourage the investment of the enterprise to participate through the establishment of the industrial investment fund. Third, the industrial application of the coal technology industry has led to the special nature of science and technology of coal financing. At present, science and technology financing is generally based on the life cycle theory of enterprises, and explores the financial support issues of start-up, growth, maturity and recession of science and technology enterprises. However, the high threshold of the application of science and technology in the coal industry led to the main body of the innovation in the coal industry as a large-scale coal enterprise instead of a small and micro-enterprise in the initial stage. The focal point of coal science and technology financing is how to develop and utilize coal-based science and technology projects for large-scale coal enterprises. Unlike the start-up small and micro science and technology enterprises, the large coal enterprises have more abundant financial resources, which can alleviate problems such as the lack of collateral, which is often faced by science and technology finance. However, because science and technology innovation in the coal industry takes a long time and a large amount of capital investment, the input will directly affect the current business performance. In the case of managers’ shortsightedness, large-scale coal enterprises need to focus on solving the problem of lack of motivation for scientific and technological innovation.

14.3 Development Foundation of Science and Technology Financing of Shanxi’s Coal Industry Shanxi province has always attached great importance to coal science and technology research. After a long period of exploration and practice, Shanxi province was approved as a pilot zone for the comprehensive reform of the national resource-based economy in 2010 and “coal-based and diversified development” for the “12th Five-Year-Plan for National Economic and Social Development” of Shanxi province. A number of ­coal-based industry paths were proposed, a coal-based synthetic oil demonstration project was formed by the Lu’an Group in Shanxi Province, as well as the coal-to-methanol olefins project by the Shanxi Coking Group, the Tashan Recycling Economic Park of Shanxi Tongmei Group, the Shanxi Jin Coal Group of gas drainage and CBM

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development and utilization of technology, and other typical series of coal science and technology applications were formed. Since the new leadership took power in 2014, the pace of promoting scientific and technological innovation in coal has been stepped up. In November 2014, Shanxi province proposed to shift the coal industry to a ‘market-oriented, clean and low-carbon type, intensive and efficient type, extended circulation type, eco-friendly type and safeguarded type’. In July 2015, Shanxi province held a conference on science and technology innovation and released “Several Opinions of Shanxi Provincial People’s Government of Shanxi Province on Implementing Scientific and Technological Innovation” (Jin Fa 2015, No. 12) in August. The province’s research and experimental development funding (R&D) accounted for more than 2.5% of the GDP. The core area of the Science and Technology Innovation City was basically completed. Major strategic breakthroughs were made in coal-based science and technology, leading the strategic goals and tasks and corresponding strategic measures in supporting “six types of transformation” of the coal industry and making outstanding contributions to the clean and efficient use of coal. The Science and Technology Department of Shanxi Province set up a major project of low-carbon innovation in Shanxi province. In 2015, it will mainly support the innovation chain of the coalbed methane industry, the innovation chain of coal-fired power industry, the innovation chain of coal-coking industry, the innovation chain of coal chemical industry, the innovation chain of coal industry, the material industry innovation chain and carbon-rich agricultural industry innovation chain and other key common technical issues. In April 2015, the National Natural Science Foundation of China (NSFC) and the Shanxi Provincial People’s Government jointly funded the establishment of the coal-based low-carbon joint fund agreement, an agreement for the years from 2015 to 2019. The two sides jointly invested 50 million yuan each year into the joint funds. The fund concentrated on the economic and social development in Shanxi and similar resource-based regions, with a focus on coal mining, coalbed methane, coal chemical industry, coal mining equipment, new materials, coal power and new energy, environmental protection, ecological restoration and other major coal-based low-carbon areas related to major scientific issues and basic common key technology and engineering problems. They aimed to attract and gather scientists across the country to carry out basic and applied basic research. The Shanxi Provincial Science and Technology Department and the Shanxi Jincheng Anthracite Mining Group Co., Ltd. jointly established the “Coalbed Methane Research Fund” and the Lu’an Mining Group jointly established a “coal-based synthesis of Shanxi Province Fine Chemicals Research Fund” and other ­government-enterprise cooperation funds. At the same time, Shanxi province has also set up a national key laboratory (coal conversion, coal and CBM mining, mining equipment, intelligent manufacturing and other key national laboratories), an engineering technology center (Shanxi Province Green Mine Engineering Research Center, Shanxi Province Coal Mining Equipment Engineering Technology Research Center, Shanxi Coal Conversion Engineering Research Center, etc.), research institutes (Coal Research Institute of Taiyuan Branch, Chinese Academy of Sciences, Shanxi Institute of Coal

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Chemistry, etc.), as well as colleges and universities, as the core of a scientific research institutions system. In coal science and technology, Shanxi’s Provincial Science and Technology Fund Development Corporation was established in June 1993, which is a state-owned investment company that specializes in promoting the transformation of scientific and technological achievements in Shanxi province. In 2011, a government-led fund was set up as an innovation pilot for science and technology finance by the Ministry of Science and Technology.

14.4 Strategies of Shanxi’s Science and Technology Financing Development Shanxi province should take the strategy of “revitalizing coal” as the guideline, take the innovation of the coal industry chain as an objective, and thereby take environment construction, system construction and platform construction as the starting point. Through actively exerting the government’s policy guiding function and capital leverage, we will mobilize all kinds of scientific research platforms in an all-round manner. The enthusiasm of large-scale coal enterprises to tackle coal science and technology and the initiative of financial institutions to support scientific and technological innovation in coal resources will greatly enhance the promotion of science and technology in coal resources and their transformation into realistic productive forces. First, a clear coal-based industry innovation chain and classified support are suggested. Based on the coal industry chain, the innovation chain in all links of the industry chain will be sorted out. According to the stage characteristics of technological innovation, the stages of innovation chains (basic research, application development, pilot testing, commercialization, and scale) are clearly defined. Based on the government’s principle of ‘doing one thing and not doing the other’, the financial funds fully support the basic research projects of coal-based industries and lead various research platforms and coal-based enterprises to carry out applied research and development by means of joint funds and other means, finding other ways to guide the financial capital into the pilot-based enterprises, commercialization and large-scale production. Second, it is important to strengthen the mechanism of financial research into science and to establish a budget constraint system to ensure a steady increase in financial investment in science and technology innovation in coal-based industries. Further, the cooperation mechanism with the NSFC needs to be deepened, major tendering issues and general project support areas according to the major basic theoretical requirements of the coal industry innovation chain formulated, and focus laid on solving major scientific issues and key issues that are common to coal-based low-carbon areas in Shanxi province’s technical problem areas. The management system of scientific research funds will be reformed, the enthusiasm of scientific research personnel promoted, given full play to the function of research process evaluation and result evaluation, and the quality of

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basic scientific research projects is enhanced. The reform of the coal-based disciplines in key national coal-based laboratories, research institutes and institutions of higher learning will be intensified, and the reform of personnel, finance and assessment systems to create a coal-based academic special zone will be promoted and given full play to ­coal-based disciplines, the leading role of leading personnel and the cooperation of scientific research team, to create the output of important landmark coal-based industrial research results. Third, various types of coal-based industry science and technology innovation service platforms should be built. The establishment of an open and unified platform for science and technology management in Shanxi province should be accelerated and should do a good job in docking with the national science and technology management platform. The use of Big Data and other technical means should strengthen scientific research projects, the process and the results of management, and scientific research projects to ensure scientific research and that the research process is reasonable and delivers ­high-quality research results. The establishment of a scientific and technological achievements reserve and trading platform will be sped up and will strive to promote the specialized registration and convenient transactions of public scientific and technological achievements as well as other relevant coal-based scientific and technological achievements formed through financial support. It will furthermore promote the effective flow and rational conversion of coal-based scientific research achievements. The construction of a coal-based science and technology project reserve platform will be accelerated, in accordance with the coal-based industrial innovation chain and the coal-based science and technology innovation project stage characteristics. A science and technology project information platform will be build to display the project advantages of the team, enterprises or potential advantages of enterprises for the government and financial institutions support projects and provide them with timely and effective information. Fourth, the enthusiasm and initiative of the coal mine enterprise development and financial institutions need to be mobilized to support coal-based science and technology. Full play needs to be given to the dominant position of large-scale coal enterprises to encourage large-scale coal-based enterprises to establish R&D centers or key laboratories through their own policies by guiding and supporting financial resources and remuneration incentive mechanisms for state-owned enterprises, and ensuring a gradual annual growth for R&D expenses. A government-led fund needs to be set up in the form of a coal-based science and technology mother fund, relying on the coal-based science and technology sub-fund, related to the innovation of the coal industry chain to invest and operate by means of marketization. Financial support policies need to be formulated, such as financial incentives, risk compensation, loan interest subsidies and tariff subsidies to enhance the enthusiasm of financial institutions such as venture capital agencies, commercial banks, insurance companies and guarantee companies to invest in coal-based science and technology innovation. Coal enterprises need to be encouraged to set up subsidiaries on the basis of coal-based science and technology projects, to introduce project funds for instance through angel investment, venture capital and intellectual property

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mortgage financing, and promote the development and scale of coal-based science and technology projects through a sharing risks and sharing profits application.

14.5 Difficulties in Coal Science and Technology Financing and Countermeasures First, the implementation of coal science and technology financing requires the participation of governments, research institutes, enterprises and financial institutions. The government needs to effectively integrate the current fragmented resources through the top-level design to form a systematic financial solution for coal science and technology. Government resource integration and program design is one of the most difficult problems the implementation of coal science and technology financing are facing. Shanxi province can draw on the spirit of the state’s “Proposal on Deepening the Management Reform of the Central Government’s Science and Technology Plan (Special Projects, Funds, etc.)” and establish a joint conference system led by the Shanxi Provincial Department of Science and Technology, the Shanxi Provincial Department of Finance, the Shanxi Provincial Development and Reform Commission and other relevant departments. It is necessary to formulate the rules of procedure, be responsible for reviewing strategic plans for the development of science and technology of coal, to establish a layout and setting of coal science and technology plans as well as key tasks and guidelines for coal. Furthermore, the establishment of science and technology funds for coal, and incentive systems for scientific and technological innovation of coal enterprises, is central. Second, the classification of coal science and technology innovation directly involves the division of functions between the government and the market. In order to prevent the government from vacancy and offside situations, the classification of coal science and technology innovation is the second difficulty in the implementation of coal science and technology financing. Shanxi province can set up a strategic consultation group and a comprehensive jury composed of high-level coal-based industry experts from science, technology, industry and economics to provide a strategy for the development of coal science and technology—with the goal of ensuring the conciseness and classification of major science and technology projects in the coal industry, major financial support, project review and other aspects of the consultation work as far as possible.

References Wang et al. 2012: 王宏起,徐玉莲.科技创新与科技金融协同度模型及其应用研究[J]. 中国软科 学, 2012 (6), pp. 129–138. Zhang 2011: 张来武.科技创新驱动经济发展方式转变[J]. 中国软科学, 2011 (12), pp. 1–5. Zhao 2007: 赵昌文等. 科技金融[M].北京: 科学出版社, 2007. Jin 2015: 中共山西省委山西省人民政府:《中共山西省委山西省人民政府关于实施科技创新 的若干意见》(晋发[2015]12号).

Research on the Refinancing Problem of Shanxi’s Listed Resource Companies

15

Yuan Gaixia and Zhang Caixia

Contents 15.1 Research Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 15.2 Refinancing and the Definition of Its Main Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 15.3 Refinancing and Its Main Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 15.3.1 Financing Structure of Shanxi’s Listed Companies. . . . . . . . . . . . . . . . . . . . . . . 199 15.3.2 The Refinancing of Shanxi’s Listed Companies. . . . . . . . . . . . . . . . . . . . . . . . . 200 15.3.3 Refinancing of Listed Resource Companies in Shanxi. . . . . . . . . . . . . . . . . . . . 201 15.4 Analysis and Characteristics of Shanxi’s Listed Resource Companies’ Refinancing Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 15.4.1 Characteristics of Shanxi’s Refinancing of Listed Resources Companies. . . . . . 204 15.4.2 An Analysis of the Factors Influencing the Choice of Refinancing of Shanxi’s Listed Resource Companies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 15.5 Policy Suggestions for Promoting Refinancing of Shanxi’s Listed Resource Companies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 15.5.1 Building a Policy Environment Conducive to Refinancing. . . . . . . . . . . . . . . . . 210 15.5.2 Promote Regulatory Reform that is Conducive to Refinancing. . . . . . . . . . . . . . 211 15.5.3 Strengthen the Construction of Enterprises’ Conducive to Refinancing. . . . . . . 212 15.5.4 Promote Reform of State-Owned Enterprises in Favor of Refinancing. . . . . . . . 213 Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213

G. Yuan (*)    Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] C. Zhang e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_15

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Abstract

The listed companies are outstanding representatives of enterprise groups in China that have a significant influence on the national economic development and the industrial transformation. Their choices of financing behavior are not only transparent but also have a model effect. This chapter examines the refinancing behavior of Shanxi’s listed resource companies from two aspects, general and group characteristics. The study finds that the current refinancing selection of Shanxi’s listed resource companies is a combination of results of Shanxi’s resource-based economic structure, the development cycle of the coal industry, the influence of the state-owned assets management system, the policy and social governance environment, the level of the enterprises’ own development and other factors. The chapter also puts forward some policy suggestions on various factors influencing the refinancing of Shanxi’s listed resource companies.

15.1 Research Background The key factor that affects the business operation is capital. Whether the enterprise can expand the scale of production and achieve sustainable development, depends fundamentally on whether there is sufficient and stable financial support. Raising funds is the basic function of the capital market. Listed companies get their first financing from their initial public offering (IPO). In the process of business development, when the project construction, industrial chain expansion, and mergers and acquisitions (M&A) need to be consolidated, refinancing is often an unavoidable problem. In the current overall economic restructuring, the growth rate is slowing down and long-term, stable and low-cost refinancing funds are increasingly favored by listed companies. Shanxi is in the process of restructuring and upgrading the resource-based economy. The proportion of the traditional energy industry in the economy is too large and the development of high-tech industries appears sluggish. The distribution of listed companies is also in line with this pattern. By the end of 2016, there were 38 companies listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange in Shanxi province. According to the industry distribution, most of them are concentrated in traditional resource-based industries such as coal mining, coking, power generation and the chemical industry. The listed resource companies accounted for about 70.3% of the total number of listed companies in Shanxi. Overall, the listed companies in Shanxi (especially the listed resource-based companies) have problems due to limited refinancing, not large enough size, imbalance in the diversification of the structure of the stock and debt, and little motivation. There are still some common problems and constraints in the refinancing options and the ability to refinance by using the capital market platform still lags behind other regions. The listed companies in the developed western countries place their financing behavior basically in accordance with the theory of financing priority. When a company requires capital, it first considers using internal resources to raise funds and then considers seeking external

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financial support. In the case of external financing, debt financing is better than equity financing. We analyzed the refinancing behavior of listed resource companies in Shanxi and found that these groups are less motivated to engage in endogenous financing and prefer to raise funds externally. In particular, debt financing has the highest proportion, which is different from the western pecking order theory of financing. From the current domestic research on the financing structure and choice of listed companies, the focus of academic research lies mainly on the priority of the companies’ financing decisions. There is a trend to focus more attention on how to optimize the financing structure of individual listed companies. However, there is little research on the refinancing behavior of listed companies with regional economic characteristics. In this chapter, we used Shanxi’s listed resource companies as research object and studied how they used their refinancing options as well as the group characteristics.

15.2 Refinancing and the Definition of Its Main Methods The financial activities of modern enterprises mainly include three aspects: financing, investment and profit distribution. Financing is the forerunner of production and operation, and is the prerequisite for the survival and development of any enterprise. It plays a central role in the financial activities of enterprises. There are two main types of corporate foreign financing: equity and debt financing. The financing behavior of listed companies can be specifically divided into initial financing and refinancing. Initial financing generally refers to the financing behavior of listed companies through the IPO; and refinancing, relative to the initial financing, refers to the behavior of listing, and then raising funds through the rights issue, issuance and issuance of various types of bonds and bank loans and other means. Refinancing can be divided into two broad categories: equity refinancing and debt refinancing. Equity refinancing refers to the listed companies re-issuing shares to the public or specific investors in order to obtain financing funds in the case of lack of funds. There are mainly placement, issuance and issue of convertible bonds. Debt refinancing refers to the act of raising funds by applying for bank loans and issuing various types of bonds after listing. Currently, there are mainly loans, corporate bonds, medium-term notes, short-term financing bills and non-public targeted debt financing instruments.

15.3 Refinancing and Its Main Methods 15.3.1 Financing Structure of Shanxi’s Listed Companies At the end of December 2016, there were 38 A-share listed companies in Shanxi province, including 31 main boards, 4 small and medium-sized boards and 3 GEM companies. Most of them are concentrated in the traditional resource-based industries such as

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coal mining, coking, power generation and chemical industry. The listed companies have a market capitalization of 4558.5 billion yuan, a total market capitalization of 5229.7 billion yuan (including restricted sales), 61.46 billion outstanding shares, and a total share capital of 74.322 billion.1 In terms of financing structure, listed companies in Shanxi are mainly debt financing, and the proportion of debt financing and total equity financing is unbalanced. Among the equity financing, the initial financing is lower and the proportion of refinancing is higher. In refinancing, the private placement is the most important approach. In debt refinancing, the inter-bank market financing instruments have the absolute majority. In addition, the choice of financing is affected by the change of policies. The initial financing is suspended for several times due to the change of the IPO policies. With the liberalization of the issuance policy, no company has opted for share allotment financing. With the improvement of the corporate bond audit efficiency, the increase of corporate debt financing has shown a clear trend.

15.3.2 The Refinancing of Shanxi’s Listed Companies Since Shanxi’s first listed company went public in 1993, there was no refinancing of listed companies in Shanxi before 1996. From 1996 to the end of 2016, listed companies in Shanxi province realized a total refinancing of 1.74206 trillion yuan, of which 1.797 billion yuan were raised from rights issue, 87.109 billion yuan were raised through private placement, 23.25 billion yuan were raised publicly, and 600.5 billion yuan were raised from corporate bonds (Table 15.1). It can be found that with the adjustment of policies and the changes of market conditions, the choice of refinancing methods of Shanxi’s listed companies has certain stage characteristics. Basically, there was only the placement of shares before 2000; after 2006, the additional issuance of listed companies’ equity refinancing was the mainstream choice in the additional issuance of the private placement-oriented investments; corporate bonds had a larger increase after 2012, but convertible bond financing has had zero breakthrough.

1The

statistical standard here is that the financing of the A-share market of listed companies in Shanxi does not include the financing activities of listed companies before they move to Shanxi. The scope of the statistics is the refinancing data subject to China Securities Regulatory Commission’s (CSRC) examination and approval, excluding the data for refinancing through corporate bonds, inter-bank markets and other bonds. This caliper is also used in the following.

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Table 15.1  Refinancing of listed companies in Shanxi since 1996 (Unit: 100 million yuan). (Source Shanxi Provincial Bureau of Statistics (diff. volumes); Shanxi Statistical Yearbook 2015, Taiyuan) Year 1996

Allotment 0.69

Private placement 0

Public issuance 0

Corporate debt Total 0

0.69

1997

0

0

0

0

0

1998

2.61

0

0

0

2.61

1999

8.82

0

0

0

8.82

2000

16.06

0

0

29.04

2001

8.05

0

12.98 0

0

8.05

2002

0

0

5.27

0

5.27

2003

1.74

0

0

0

1.74

2004

0

0

0

0

0

2005

0

2006

0

61.77

0

0

0

0

0

61.77

2007

0

24.93

10.16 39.09

0

0

35.09

2008

0

9.45

0

48.54

2009

0

45.52

0

44

89.52

2010

0

23.26

165

10

198.26

2011

0

88.4

0

45

133.4

2012

0

52.61

0

146

198.61

2013

0

129.77

0

57

186.77

2014

0

2015

0

2016 Total

0 37.97

22.805 225.58

0

45.1

0

203.4

67.905 428.98

186.99

0

50

236.99

871.085

232.5

600.5

1742.055

15.3.3 Refinancing of Listed Resource Companies in Shanxi This article selects 27 listed companies in the coal, coking, power, steel, chemical and other resource industries in Shanxi province as samples of listed resource companies. From 1996 to the end of 2016, a total of 56 resource companies in Shanxi realized refinancing through listing, with a total financing amount of 108.1485 billion yuan (Table 15.2).

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Table 15.2  Refinancing of Shanxi’ listed resource companies since 1996 (Unit: 100 million yuan). (Source Shanxi Provincial Bureau of Statistics, diff. volumes) No. 1

2

Company code 600740

600780

Company name ST山焦

通宝能源

Refinancing Time

Type

Amount

1998

Allotment

1.02

2000

Allotment

1.81

2007

Private placement

10.16

2013

Private placement

15.6

1999

Allotment

2002

Public issuance

2011

Private placement Allotment

1.6 5.27 15.4

3

000737

南风化工

1998 2000

Allotment

3.94

4

000767

漳泽电力

1999

Allotment

7.22

2007

Private placement

9.99 32.14

5

6

7

8

9

000755

000825

600169

600123

000968

山西三维

太钢不锈

1.58

2013

Private placement

2000

Allotment

1.93

2003

Allotment

1.74

2007

Private placement

6

2001

Allotment

8.05

2006

Private placement

57.36

2008

Public issuance

35.46

2012

Corporate debt

50

2000

Allotment

1.49

2008

Private placement

9.45

2010

Private placement

16.86

2016

Private placement

5.71

2000

Allotment

2.65

2006

Private placement

2012

Corporate debt

30

煤气化

2010

Corporate debt

10

2009

Corporate debt

30

太原重工

兰花科创

4.41

10

000983

西山煤电

11

600281

太化股份

0

12

601699

潞安环能

0 (continued)

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Table 15.2   (continued) No. 13

Company code 600617

国新能源

600539

狮头水泥

600546

山煤国际

Refinancing Time

Type

Amount

2013

Private placement

35.19

2014

Backed by supporting funds

4.8

2015

Private placement

10.05

2016

Corporate debt

10

2009

Private placement

26.73

2011

Private placement

55

2014

Corporate debt

15

2009

Corporate debt

14

0

600348

阳泉煤业

601001

大同煤业

600392

盛和资源

2013

Private placement

22

000831

五矿稀土

2000

Allotment

1.94

2013

Private placement

28.81

2000

Allotment

2.3

2014

Private placement

5.66

2015

Private placement

9.3

2016

Private placement

12.26

000795

21

Company name

000403

英洛华

0

ST生化

0

22

000723

美锦能源

2016

Private placement

101.16

23

600157

永泰能源

2010

Private placement

6.4

2011

Private placement

18

2011

Corporate debt

5

2012

Private placement

49

2012

Corporate debt

16

2013

Corporate debt

47

2015

Private placement

100

2016

Private placement

49

2016

Corporate debt

40

Public issuance

8.94

24

000408

安泰集团

2007 2009

Private placement

10.34

25

002360

同德化工

2014

Private placement

1.125

26

002753

永东股份

0

27

600691

阳煤化工

0

Total

1081.845

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It is evident that listed resource-based companies’ refinancing options and changes in this period were consistent with the basic listed companies in Shanxi. But in addition, there are some unique group characteristics: 1. The total amount of refinancing is relatively small, 27 resource-based listed companies account for 71.05% of the total number of listed companies in Shanxi, but the total amount of refinancing accounts for about half of the total amount of financing of all listed companies. The refinancing willingness of listed resource companies is lower than that of other industries. 2. The frequency of refinancing and the preference for capital operation of companies’ refinancing was significantly higher in comparison to conservative companies. Yongtai Energy, for instance, conducted refinancing 9 times since 2010 whereas some companies have never conducted any refinancing. 3. In recent years, the issuance of corporate bonds has increased the frequency of financing, and the amount of financing is generally larger. Compared with the issuance and rights issue, listed resource companies prefer bond financing.

15.4 Analysis and Characteristics of Shanxi’s Listed Resource Companies’ Refinancing Options We conducted surveys on the status quo of the refinancing of listed companies in Shanxi area, which include • • • • • • •

the ownership and ownership structure of the companies, the categories of resources, the refinancing and mergers and acquisitions, the preference of financing, the choice of financing methods, the impact of refinancing and mergers and acquisitions restructuring success factors, the refinancing satisfaction, and other criteria.

This chapter provides the support and basis for analyzing the characteristics of refinancing of listed resource companies.

15.4.1 Characteristics of Shanxi’s Refinancing of Listed Resources Companies Combined with the questionnaire survey, this chapter examines the refinancing of listed companies in Shanxi province since 1996 and then analyzes the forms, proportions and scale of refinancing by using listed resource companies as a group. The study

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found that Shanxi’s listed resource companies’ refinancing options have the following characteristics: First, there are limitations to the way of refinancing, with less equity and securitization financing. Shanxi’s listed companies use more bank credit and debt financing, unbalanced debt financing and equity financing, leverage of direct financing and optimization of resource allocation. In recent years, the financing through the inter-bank bond market has enjoyed a rapid growth, forming a crowding-out effect on corporate bonds and corporate debt financing. Second, the frequency of equity refinancing is not high, and the form is relatively simple. There is a lack of sustainability in the utilization of capital markets by Shanxi’s listed resource companies. Many companies failed to make good use of the market refinancing mechanism on the basis of improving the economic efficiency of enterprises after their initial public offering. Among the existing equity refinancing activities, the additional issuance is the main form and the enthusiasm for other innovative forms of refinancing attempts is low. Third, the total M&A restructuring is small. M&A is an important form of equity refinancing and plays an essential role in the transformation and development of enterprises. According to preliminary statistics, Shanxi’s listed companies have never been involved in mergers and acquisitions, most of them are resource-listed companies. In the history of M&A, reorganization or refinancing has started after the suspension or failure of more than 10 investments, and also ended up with bankruptcies of resource-listed companies. Fourth, the state-owned resource listed companies refinancing frequency is not high. The scale and the market capitalization of Shanxi province are mostly state-owned enterprises in the top ten and are mainly concentrated in the traditional industries. They are cyclical, with great pressure for transformation and large capital needs. However, their utilization of capital markets is less than that of private-owned and emerging industries. The state-owned listed resource companies are not enthusiastic about financing innovation. Fifth, some listed resource companies are “passive” in refinancing. The performance of resource-based listed companies has been sluggish for a long time, and the number of ST companies in Shanxi province reached 7 at most. Some companies have become “zombie” enterprises in the capital market by means of non-operating income and assets transfer. The time window affects some companies’ motivation for mergers and acquisitions due to the long preparation and planning which is necessary in advance. Sixth, resource-based listed companies face some special difficulties in refinancing, such as license handling problems, and the independence of group shareholders and so on.

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15.4.2 An Analysis of the Factors Influencing the Choice of Refinancing of Shanxi’s Listed Resource Companies 15.4.2.1 The Resource-Based Economic Structure Is the Fundamental Factor Affecting the Choice of Refinancing 1. The companies failed to seize the opportunity of the industrial transformation of the “Coal Gold Years”. Coal-dominated and state-owned enterprises with the lagging nature of state-owned enterprises’ own decision-making led the resource-based economic restructuring, resulting in a combined lack of reform momentum of the listed companies in Shanxi province, the traditional resource industries and of the composition of the industry. The coal mines failed to utilize the capital market to improve their structure in advance and make strategic layouts with abundant funds and good returns in the previous “Coal Golden Years”. As a result, several major coal mills missed the excellent opportunity to place their assets in listed companies. Then the traditional industries’ gradual surplus with the stock market down led to listed resource-based companies being overwhelmed with maintaining their operating performance and, as a result, making less and less moves in the capital market. 2. The current economic downturn has put tremendous pressure on listed resource companies. Affected by the economic downturn, the coal industry has been in a weak position for a long time. The performance of most companies has remained sluggish. The operation has been in a dilemma and the loss has been aggravated. There is no sign of a short-term effective resolution and there are even potential risks of delisting. Affected by the operating performance of several major coal mines in Shanxi province, its listed resource companies have made it more and more difficult to readjust their capital market through restructuring their capital markets. Since 2013, some listed companies have failed coal-related asset restructuring. 3. “One coal alone” led to the slow development of new industries and private-owned enterprises. Shanxi was defined as the energy base by the state in the era of the planned economy, and the energy industry-based industrial structure was formed. After entering the market economy, there were amazing profits of the coal industry in the first decade, and large-scale social capital influx into coal-related industries, which came along with the birth of many private companies related to the coal industry. This indirectly extruded the development of the non-coal industry and new industries. After the coal industry entered a downward cycle, especially after the comprehensive transformation of Shanxi’s transition started, the industrial economy began to seek a transformation mentality. However, due to the fact that there is no advantage of coastal industries to relocate to central China and no mature non-coal industry is cultivated by itself, the development of new industries and private-owned enterprises is slow and there are fewer enterprises and public companies forming and maturing.

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15.4.2.2 To Simplify the Financing Preferences is the Main Factor Affecting the Choice of Refinancing 1. Enterprises are willing to choose the convenient and efficient traditional financing methods. Capital operation requires enterprises to clear ownership and to obtain complete licenses, perfect governance, and sometimes clear financial or performance requirements. These are high requirements for the enterprises’ qualifications themselves. Enterprises also need to go through the ownership, land, project approval, taxation, Energy Information Administration (EIA) and a series of examinations before the approval procedure by the commission. These procedures include time-scale of financing, high difficulty, and a high failure rate. Although the funds obtained through equity refinancing are free and long-term, there are many demands on financing projects, capital investment and income, etc., and the funds used have a low degree of freedom of use and require high disclosure of information. The requirements for bank loans are relatively simple and the formalities are convenient. The focus of the investigation is on the solvency of enterprises. The issuance process in the inter-bank market is simple and the funds can be flexibly used. This is the reason why many enterprises refinance their equity while choosing banks and inter-bank markets. 2. Several companies have some natural defects, which are difficult to improve for a long time, and they become an obstacle to refinancing and restructuring. On the one hand, the traditional industries such as coal-fired power listed by Shanxi listed companies are undergoing cyclical adjustments in recent years, and overall the industry is not profitable. The decline in operating performance has a significant impact on the companies’ direct financing and capital operation. On the other hand, the state-owned listed companies are not completely stripped when they are listed on the market; the same-industry competition with the holding group and the related-party transactions has not been solved completely. The refinancing of the capital market and mergers and acquisitions require large expenses for listed companies and controlling shareholders. Thirdly, the state-owned area under the jurisdiction of the controlling advantage is not strong. There may be a risk of decentralized control of equity refinancing. The state-owned enterprises would rather bear the higher costs of debt refinancing. 3. A good relationship between banks and state-owned listed companies favors credit financing. Shanxi’s listed resource companies are mostly state-owned and large-scale companies listed for a long time, with a good reputation and a banking system to establish more extensive cooperative relations. The cost of bank financing is not too high. If the companies only need a large amount of funds in the strategic transformation demand situation, or the direct financing of financial costs is significantly lower than the premise of bank financing, they will consider equity refinancing. 15.4.2.3 The Enterprises’ Own Quality is the Intrinsic Factor Affecting the Choice of Refinancing 1. The development of resource-based listed companies lacks a strategic plan for capital operation. Shanxi’s listed resource companies are more inclined to choose bank loans

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and do not attach importance to the capital market to find opportunities for capital. ‘New things’ on the capital market are not sensitive to the IPO after the financing of a small number of single tools for a variety of innovative financial instruments. One encounters unfamiliarity combined with the lack of awareness of capital operation. Companies pay more attention to quick benefits and performance. The use of capital markets to seek business transformation, as well as bigger and stronger long-term strategic planning, is not enough. Some large enterprise groups pay insufficient attention to improving governance, which may affect the transformation time window of mergers and acquisitions or makes them miss the opportunity. 2. There is an abundance of private capital in the area, but the capital market is not strong enough. Shanxi’s coal resources are important for the formation of l­arge-scale private capital. The dynamic development of the capital area of the jurisdiction as an important force should be promoted. But private capital is accustomed to s­ elf-development. Many entrepreneurs’ marketization and modern financial concepts are backward leading to a relatively confused industrial restructuring. They are not aware of the importance of financial investment and capital operation, and they lack the enthusiasm to have their private capital participate in the capital market. Shanxi area’s refinancing, mergers and acquisitions, and reorganization are not actively pursued. 3. The financial support industry is underdeveloped, and the capital market service institutions need to be improved. The support for the development and utilization of the capital market in Shanxi needs to be improved. The number of institutions such as brokerage firms and accounting firms is not sufficient and the quality needs to be improved. Local financial professionals with a limited serious knowledge of the capital market and practical experience have emerged. The area of business listing, financing and capital operation demand is more inclined to choose to hire professional service agencies from the field. The grassroots financial institutions with more direct contacts to enterprises have insufficient service capabilities and personnel, resulting in unsatisfactory service quality.

15.4.2.4 The Efficiency of the Administrative Environment is the External Factor Affecting the Choice of Refinancing 1. The government departments pay insufficient attention to the capital market. Some local governments do not pay enough attention to the capital market. The encouragement and guidance of the construction of a multi-level capital market is lacking and neither diverse nor targeted. 2. The scientific nature of encouraging policies and measures needs to be improved. When some of the incentive policies and measures were implemented, the regional differences in cities were not obvious. The specific promotion and implementation of the incentive measures were limited. The proportion of compensation funds to direct

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financing was relatively low. The policy incentives were still mainly reflected in the traditional indirect financing. In terms of financial incentives, government subsidies and green passage, some of the measures have actually been implemented in enterprises for a long time and the period for benefiting enterprises has been delayed. Some non-state-owned enterprises have not been uniformly treated in respect of policies, incentives and opportunities. 3. Administrative efficiency in handling complicated affairs needs to be further improved. Sometimes difficulties arise and time windows are missed concerning listed companies’ refinancing and acquisitions. Due to the different powers and responsibilities of different departments and the lack of coordination, some of the things that can be implemented in the eastern coastal areas have taken a long time in Shanxi province.

15.4.2.5 The Characteristics of the National Capital System are the Important Factors Affecting the Choice of Refinancing 1. Listed resource companies are mostly state-owned. The managers of the state-owned listed companies are greatly influenced by the controlling shareholders and the actual controllers. Especially the state-owned shareholders have more say in state-owned listed companies. Among Shanxi’s listed resource companies, some state-controlled listed companies and major shareholders have the same industry competitions and related transactions, affecting the standard operation of the company and limiting the potential of listed companies to use the capital market for refinancing. 2. The procedure of capital operation involving state-owned enterprises is complex. State-owned listed companies are subject to the long-term supervision of multiple departments, which not only abide the open market rules of capital markets but also comply with the regulatory requirements of state-owned assets. Refinancing and mergers and acquisitions often require more examination and approval formalities and a longer decision-making time. Sometimes the abortion of a project occurs when it is not possible to reach a consensus in time, or when the best market opportunity has been missed as soon as the procedure is completed. 3. There are also other problems resulting from the special attributes of state-owned enterprises. Due to historical reasons, state-owned listed companies have problems such as asset flaws and heavier social burdens. Besides, social responsibilities such as resource integration, relocation, elimination of backward production capacity, poverty alleviation and disaster relief will continue to occur. The performance of state-owned listed companies is also of importance: their decision-making, refinancing, mergers and acquisitions and other forms of influence.

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15.5 Policy Suggestions for Promoting Refinancing of Shanxi’s Listed Resource Companies 15.5.1 Building a Policy Environment Conducive to Refinancing 15.5.1.1 Strengthening the Awareness of the Government to Serve the Refinancing of Enterprises Relevant government departments should further change their concepts from the strategic height of promoting the transformation and upgrading of the resource-based economic structure to emphasizing the capital operation of resource-listed companies and strengthening the awareness of service-listed companies as well as supporting their refinancing and mergers and acquisitions reorganization. The transformation of listed companies should drive the optimization of the resource-based economic structure. It will promote the refinancing of listed resources-based companies in key tasks and lead relevant civil servants to be familiar with business and the economics of the financial and capital markets and continue to promote the refinancing and merger and reorganization of qualified resource listed companies. 15.5.1.2 Formulate a Package of Incentives to Promote Refinancing Relevant government departments should put forward scientific and effective supportive policies for listed resource companies to carry out refinancing, mergers and acquisitions, strategic adjustment and industrial integration, to balance the advantages and disadvantages by providing policy support. The market-oriented role of fiscal policy should be given priority in order to support listed companies of resource industries in the adjustment of main businesses, strategic integration and mergers and acquisitions with limited financial resources, material resources and resources of the government and give them provisions in supply of production factors such as electricity, land, labor and bank credits. There should also be charges, fines, taxes, financial subsidies, license management and other administrative acts. All guided resources should be concentrated to listed companies, taking advantage of the ideal integration of the resource development path to explore feasible ways of a transformation and an upgrading of a resource-based economic structure in Shanxi. 15.5.1.3 Improve the Efficiency of Refinancing Related to Government Administration Relevant governmental departments should open up the “green channel” and “process service” for the capital operation of enterprises and explore land, housing, taxation, industry and commerce, property rights, environmental protection and other environmental protection issues, that resource-listed companies face in the process of non-public issuance, asset restructuring, bond issuance and project approval, such as the approval of the filing procedures for one-stop service to speed up the work and to solve the problems

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encountered. The local government should profit from the experience and practices of governmental departments of the developed coastal cities and take the initiative to provide advice and suggestions for refinancing enterprises and to solve problems.

15.5.2 Promote Regulatory Reform that is Conducive to Refinancing 15.5.2.1 Increase the Decentralization and Implement the Supervision According to the Law Securities regulatory authorities should continue to increase the power of decentralization, introduce policies to encourage the efficient use of capital markets and make bold innovations in practice. They should enhance the enthusiasm of listed companies in participating in capital markets, and enhance the efficiency of issuance and approval of corporate bonds and convertible bonds as well. They should learn from the merits of the flexibility and convenience of the issuance of market financing instruments and promote the reform of the issuance mechanism and the enhancement of the attractiveness of debt refinancing instruments in the securities market. The level of sub-sector regulation should be enhanced, regulatory resources rationally allocated, government departments timely notified of the situation, policy proposals put forward and listed companies should be supported in resource-based refinancing and mergers and acquisitions. 15.5.2.2 Optimize the Key Work and Build an Effective Market The construction of a multi-level capital market should be promoted, the refinancing and mergers and acquisitions should be supported by listed resource companies in Shanxi, the main businesses should be diversified or changed, upstream and downstream industry chains built, and strategic transformation gradually carried out. A platform for communication and exchange needs to be set up, the market experience promoted, issues explored, innovations exchanged, and resource-based listed companies in Shanxi encouraged to embark on an innovative and diversified development—give play to the role of coordination and communication, and actively offer advice and suggestions to relevant departments of local governments so as to create conditions for solving the problems encountered by resource listed companies in capital markets. Encourage listed companies and capital markets intermediaries to establish long-term cooperative partnership. 15.5.2.3 Regulatory Service is to Support the Development of Refinancing Companies Regulatory services to support the development of refinancing companies include measures to enhance supervision, to strengthen the guidance and service of listed resource companies in policies and business, to promote enterprises to improve the corporate governance structure, to strengthen the confidence of transformation and development, and to enhance the ability of capital operation. It also means to actively enter the listed resource companies, to understand the specific needs and concerns, to carry out

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­ ulti-level training, to organize regular policy interpretation, to timely deliver the latest m capital market policy changes and developments so that resource-listed companies can seize the opportunity in a timely manner, and better participate in and capitalize on the market.

15.5.3 Strengthen the Construction of Enterprises’ Conducive to Refinancing 15.5.3.1 Optimize the Overall Financing Strategy of the Enterprises Under the downward pressure of the current economy, listed resource companies should respond to the call of the state on the adjustment of the industrial structure. They should actively carry out the capital operations such as issuance and financing, mergers and acquisitions, issuance of corporate bonds and other resources and put the advantageous resources such as capital and personnel into the state-supported industries. Resources listed companies should make good use of relevant preferential policies at the national, provincial and municipal levels, broaden diversified financing channels, form reasonable, complementary and diversified financing structures, reduce financial risks and make effective use of capital market refinancing. 15.5.3.2 Strengthen Business Management Innovation Resource-based listed companies should not only pay attention to financial performance indicators, but also strictly abide by the market rules, establish a scientific and standardized organizational structure and internal control system, and establish a solid foundation for the continuous use of capital market platforms for refinancing and M&A. Qualified companies should try their best to diversify ownership and explore the possibility of listing large state-owned enterprises as a whole. They also should try to carry out market capitalization management, equity incentive, and pilot the issue of preferred shares capital operation innovation mode. 15.5.3.3 Enhance the Standard Operation of Enterprises Listed resource companies withstand the pressure of industry restructuring, but they also need to enhance the standard operation, improve the corporate governance structure, transform the internal management processes and improve the docking of the capital market refinancing qualifications. They should establish a modern market economy awareness, get rid of over-reliance on the status of the funds and bank credit, and actively use the capital market for refinancing and mergers and acquisitions, to achieve transformation and development. They should learn from the advanced eastern regions and overseas markets, pay attention to the introduction and training of professionals, and hire high-quality intermediary service agencies to improve human resources and the intellectual environment.

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15.5.4 Promote Reform of State-Owned Enterprises in Favor of Refinancing The large-scale Shanxi capital market is of great significance. On the one hand, the reform of state assets management is conducive to optimizing the capital market structure. The quality of state-owned listed companies affects the quality of Shanxi’s capital market and the ability of sustainable development. With the deepening of the reform of state-owned assets management, resource listed companies will gain more space for development. On the other hand, the healthy and rapid development of listed companies is conducive to exploring feasible paths for the reform of state-owned enterprises, providing experience for the restructuring and transformation of a resource-based economy in Shanxi Province. The strict market rules in the securities market also help state-owned listed companies improve their governance level and optimize business management. At present, under the background of “cut excessive industrial capacity”, the real economic situation in Shanxi appears rather grim. The transformation of the economic structure based on coal is imperative. Listed companies with resources in the regional economy are under pressure to overcome overcapacity and to enhance their sustainable development capability as well as to monitor their corporate refinancing more closely. The use of a capital market refinancing platform for mergers and acquisitions as well as restructuring and development needs are more important and urgent. Therefore, in the next period of time, the Shanxi resources-based listed companies should use refinancing to overcome the economic difficulties and provide practical support for Shanxi’s economic restructuring.

Additional Literature 李锋瑞.我国上市公司再融资方式的对比分析[J].经济管理, 2010 (19), pp. 150–151. 李小军,葛桓志,陈红.中国上市公司再融资方式选择——基于大股东侵占的理论模型与实证 检验[J].山西财经大学学报, 2010 (9). 唐玮.中国上市公司再融资的方式与政策研究[J].中国集体经济, 2011 (16), p. 108. 吴晓军.上市公司股权再融资方式的选择及行为完善建议[J].经营者, 2011 (6), p. 110. 祝继高,陆正飞.产权性质、股权再融资与资源配置效率[J].金融研, 2011 (11). 应展宇.中国股票市场再融资监管规则变迁的制度经济分析[J].经济理论与经济管理, 2013 (5), pp. 91–101. 李源.山西省煤炭上市公司并购融资问题及发展策略[J].时代金融, 2014 (1), p. 112. 王立印.山西国有煤炭上市公司实施资本运营的障碍与对策研究[J].经济师, 2014 (12), pp. 150–152. 杨爽.山西煤炭上市公司资本结构优化——基于山西煤炭资源整合的背景[J].城市经济, 2014 (29), pp. 39–40. 李文华.定向增发:上市公司再融资及资本运作盛宴[J].南方金融, 2014 (10), pp. 72–75. 刘娥平等.控制权收益、公司质量与融资工具选择—基于再融资管制下的三方博弈分析[J].中 山大学学报(社会科学版), 2014 (5), pp. 185–197.

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Chen, K. C. W., & Wang, J. (2007). Accounting-based regulation in emerging markets: the case of China’s seasoned-equity of offerings [J]. The International Journal of Accounting, 2007(42), 221–236. Shanxi Provincial Bureau of Statistics (diff. volumes): Shanxi Statistical Yearbook 2015. Taiyuan. Solomon, E. (1963). Leverage and the cost of capital [J]. The Journal of Finance, 1963(2), 273–279.

Research on the Marxist Theory of International Economic Cooperation from the Perspective of Economic Globalization—a Case Study on Regional Energy Cooperation

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Kang Xuhua

Contents 16.1 Marx’ Doctrine and Economic Globalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 16.1.1 Marx’ Doctrine and the Emergence of Economic Globalization. . . . . . . . . . . . . 217 16.1.2 Marx’ Doctrine and the Development of Economic Globalization. . . . . . . . . . . 217 16.2 Marx’ Theory of International Economic Cooperation—Theory, Viewpoint and Venation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 16.2.1 The Origin of Marx’ Theory of International Economic Cooperation—Marx’ Thoughts on International Economic Cooperation . . . . . . . . . . . . . . . . . . . . . . . 219 16.2.2 The Inheritance of Marx’ Theory of International Economic Cooperation— Lenin’s Thoughts on International Economic Cooperation. . . . . . . . . . . . . . . . . 220 16.2.3 The Development of Marx’ Theory of International Economic Cooperation—Marx’ Thoughts on International Economic Cooperation. . . . . . 221 16.3 The Characteristics and Research Paradigm of Marx’s Theory of International Economic Cooperation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 16.3.1 Characteristics of Marx’ Theory of International Economic Cooperation . . . . . 224 16.3.2 The Research Paradigm of Marx’s Theory of International Economic Cooperation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 16.4 The Research on Regional Energy Cooperation Under the Guidance of Marx’s Doctrine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 16.4.1 The Important Enlightenment of Marx’s Doctrine for the Regional Energy Cooperation in China. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 16.4.2 The Nature of Regional Energy Cooperation in China. . . . . . . . . . . . . . . . . . . . 230 16.4.3 The Conditions for Regional Energy Cooperation in China. . . . . . . . . . . . . . . . 231 16.4.4 Restricting Factors of Regional Energy Cooperation in China. . . . . . . . . . . . . . 234

X. Kang (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_16

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16.4.5 The Realistic Choice of Regional Energy Cooperation in China . . . . . . . . . . . . 235 16.4.6 Institutional Choice of Regional Energy Cooperation as a Second Step. . . . . . . 237 16.5 Conclusions and Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 References and Additional Literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238

Abstract

The Marxist cooperation theory is not much reflected upon, but the international economic cooperation is increasing against the background of economic globalization. The question arises of how a socialist country, like China, seeks to develop in a capitalist economic system through international economic cooperation? This chapter is guided by the Marxist theory of international cooperation. Economic globalization is analyzed on the basis of Marxist views against the backdrop of international economic cooperation. Regarding Marxism as a guideline, we assessed the conditions, constraints and realistic choices of China’s regional energy cooperation by drawing conclusions from the analysis paradigm. Finally, we deducted that China should build a system to promote the realization of a new type of regional energy cooperation mechanism. With the world market increasingly deepening in global economic integration, the development of social productive forces has reached an unprecedented height. However, the existing relations of production are unable to realize the integrity and coordination of global economic integration. Extensive cooperation in various areas of economic development is an inevitable choice for all countries, especially in the energy sector, and related to the future development. The choices of cooperation modes and positions differ strongly from country to country. Socialist countries need strategies that can support and guide their practice. Marxism represents an important basis for China to build the Party and the nation, and to develop its economy. Therefore, facing the new trend, it seems more vital than ever for China to gain new ideological support and to develop motive force from it.

16.1 Marx’ Doctrine and Economic Globalization As a developing country, China has obtained very good development opportunities in economic globalization, but it also faces many challenges. As the largest developing country, how to correctly treat Marx’ doctrine, economic globalization and the implementation of appropriate theories as a strategy, is related to the future development of our country.

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16.1.1 Marx’ Doctrine and the Emergence of Economic Globalization After the emergence of the capitalist mode of production, especially within the machine building industry, both the supply as well as the demand have rapidly increased. Unfortunately, the demand was unable to catch up with the growth rate of supply. The increasing demand for raw materials, on the one hand, has led to an increase in the output of local raw materials. On the other hand, it has led to a growing range of sources of raw materials—including the factors that have led to economic globalization. However, the root cause of economic globalization lies in the restrictions caused by the supply and demand of the sales market. Marx believes that the demand for the product is determined by social consumption, and social consumption is not depending on the absolute productivity or spending power but on the distribution of an adversarial ­relationship-based consumption. The minimum distribution of consumption, “caused by most people in the society, is reduced to only change within rather narrow boundaries” (Marx 1982a, pp. 272–273). This is determined by the relationship between the distribution of the antagonism of social consumption. The actual demand is less than the absolute consumption ability, the latter being determined by the productivity (i.e. adapted to the productivity demand), so the consumer causes restrictions of the realization of the exchange of the market supply. In order to realize the multiplication of its own value, capital must break through this restriction and enlarge the sale of the product. It is this need to expand the product market that drives the bourgeoisie to engage all over the world. They settle everywhere, develop everywhere, and established connections everywhere (Marx and Engels 1995, p. 275). The process of economic globalization has come into being.

16.1.2 Marx’ Doctrine and the Development of Economic Globalization The emergence and development of economic globalization is essentially the result of the development of human social productive forces. In this process, the application of science and technology cannot be ignored. In particular, the rapid development of transportation and communication tools, driven by the development of science and technology, meet the need of globalization of capital. The capital turnover time consists of the production time and circulation time. Based on this and the notion that the capital circulation does not create value and surplus value, Marx believes that the nature of capital is required to shorten the circulation time in order to improve the speed of capital turnover. Marx elaborates in “Das Kapital” brilliantly as follows:

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“[...] On land, gravel roads are ranked behind the railway in secondary position, on the sea, slow irregular sailing has become more rapid, but has been pushed into the secondary position behind regular shipping routes, and the whole earth is full of telegraph lines [...] The circulation of goods to East Asia in 1847 took at least twelve months, and it has now been reduced to about twelve weeks […] The United States and India, due to this change in transport, have moved closer to the European industrial countries. […] The turnaround time of business in the world has been shortened to the same extent, and the capacity of capital, to participate in world business, has increased two times or more than three times.” (Marx 1982b, p. 85).

Marx describes the social and economic developments brought about by the technological change in his time. In addition, due to the other conditions unchanged, the absolute value of transported goods is inversely proportional to the volume and the transportation industry productivity (Marx 1982b, p. 169). Therefore, if the productivity level of the transportation industry is improved, the value added to the commodity can be reduced to lower the price of the commodity. Thus, under the same conditions, the capital with advanced means of transportation will be more competitive. The development of production requires a corresponding development of traffic and communication tools, leading to an inevitable expansion of economic globalization. Because “if on the one hand, with the progress of the development of capitalist production, transportation will reduce the amount of commodity circulation time, so in turn, this progress, as well as the possibility of transportation provided, causes a more open market and within a short time, the necessity to develop” the world market (Marx 1982b, p. 179). This discussion also expresses Marx’s concept and demonstration of the world market. Marx and Engels also have similar statements in the Manifesto of the Communist Party. “The bourgeoisie, as a result of opening up the world market, makes the production and consumption of all countries become cosmopolitan. The demand for old and domestic products is replaced by the demand for the new; the products of the far distant countries and regions. The local and national self-sufficiency lie in the past. Countries are increasing international transactions and are moving toward national mutual exchange and the interdependence from localities.” (Marx and Engels 1995) The formation of the world economic system brings the economic ties among countries closer and closer. More and more, through economic division of labor, it is difficult for any country in the world to have all the resources, funds, advanced technology and consumption that the market needs, in order to develop its own economy. In this case, countries must continue to participate in international economic cooperation in order to continue to develop their economies.

16.2 Marx’ Theory of International Economic Cooperation— Theory, Viewpoint and Venation International economic cooperation refers to the process of mutual adjustment of policies and actions between states, to meet the actual or expected economic capabilities of all parties. At present, international economic cooperation has become an important issue in the international community. Over the past thirty years of reform and opening up, China

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has also stepped out of a peaceful way of development that stands in the world in a cooperative way. This road does not deny the injustice and irrationality of the capitalist world order but emphasizes cooperation to solve the contradiction (Li 2005). In recent years, China displayed a gradual development of integration into the international system of western countries through economic cooperation. It needed international resources to obtain modernization and its power to effectively promote world peace and development. A large number of practical achievements confirm Marx’ earlier discussions on international economic cooperation, and also confirm that the principle of Marx is the most suitable for China’s development practice and can guide us to further develop the theory.

16.2.1 The Origin of Marx’ Theory of International Economic Cooperation—Marx’ Thoughts on International Economic Cooperation Marx’ international economic cooperation theory originated from Marx’ and Engels’ “To the Nation”. Here, national refers to modern times, created through the bourgeois revolution or the national independence movement, with one or several ethnic groups as the subject of a cooperative relationship, forming the national state. In the first half of the nineteenth century, the nation-state was formed and became the main body of modern international relations in Europe. At this point, competition and conflict among nations were obvious in countries, but cooperation and coordination also occurred frequently. How do Marx and Engels understand the cooperation and coordination between nations? For Marx and Engels, a nation is in conformity with the capitalist mode of production. Its basic attribute of political organization is characterized by several points, one of them being the “establishment of the national coordination of international cooperation as an essential prerequisite” (Marx and Engels 1995, p. 463). A second point is that the global capitalist system is constructed by the bourgeoisie. The proletariat of the world unite in order to fight the international alliance of the bourgeoisie. A third point is that “the nation’s political independence is the foundation of all international economic cooperation” (Marx and Engels 1995, p. 261). A fourth point is that through the proletarian revolution, the establishment of a new society, based on public ownership, will be established and “the principle of the new international society will be peaceful” (Marx 1995b, p. 308). The understanding of Marx and Engels has established the national character, class nature, equality and peace of international economic cooperation, and constructed the basic frame of Marx’ thought of international economic cooperation. The above discussion shows that, in the eyes of Marx and Engels, the formation of the world economic system is the basis of driving international economic cooperation and is marked by the formation of the world market. The eventual formation of the world market was driven by the industrial revolution. The heavy industry established the world market that was prepared by the discovery of the Americas.

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As Marx and Engels have revealed, as early as the middle of the nineteenth century, the world economic system had been formed, and the isolation between countries had been uplifted. With the further development of economic globalization, the production, consumption and circulation between countries have been closely linked, forming an indivisible whole. In accordance with the increasingly high degree of interdependence, countries are increasingly linked and the division of labor is progressing. Developing countries should not only rely on their own strength, but also participate in international economic cooperation. Regarding the economic aspects, this does not necessarily pose a pressure. On the contrary, countries sometimes work together to promote a national choice of foreign cooperation.

16.2.2 The Inheritance of Marx’ Theory of International Economic Cooperation—Lenin’s Thoughts on International Economic Cooperation Marx’ theory of international economic cooperation is a source for Lenin’s understanding of the dilemma of building socialism in one country. At the end of the 19th century and the beginning of the 20th Century, the stage of free capitalism developed towards imperialism. The fierce struggle between imperialist countries led the socialist revolution to break out and to win the support of the Russian population. After that, the Soviet Union, which took the lead on the socialist road, was confronted with the dilemma of building socialism in one country. In the plight of the development, “Lenin makes a new interpretation with time conditions for international economic cooperation: the real peace policy is the vanguard of the proletarian revolution in Russia, which will promote the international proletarian world federation, a world federation of all ethnic groups associated with socialism, which is the implementation of a joint and shared free state form” (Lenin 2009, p. 4). Among them, national injustice is the biggest obstacle to thwart the international unity of the proletariat. We can understand the essence of the “obstacle” as an unequal form of exploitation. Under the influence of the World’s common economic relations, Soviet Russia had to cooperate with capitalist countries. Lenin’s theory of international cooperation provides important theoretical guidance for the peaceful coexistence of different system countries and the transfer of the socialist system from one country to many countries. In summary, in the eyes of Marx, Engels, Lenin and others, there are two main reasons for the international economic cooperation. One reason is the objective need of the world’s economic division of labor and the other reason is the need to consolidate and build socialism.

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16.2.3 The Development of Marx’ Theory of International Economic Cooperation—Marx’ Thoughts on International Economic Cooperation After Marx, Engels and Lenin, a large number of people further developed Marx’ theory of economic cooperation. Especially around the 1970s, a large number of Marx doctrines emerged, focusing on the study of international political economy. Based on the thoughts of Marx, Engels and Lenin and the characteristics of modern international economic cooperation, the theories of dependency, the World System Theory, the Gramsci School and the Structuralist School were founded. Although these theories are different, they basically agree in their essence in the area of international economic cooperation.

16.2.3.1 The Main Aspects of the Marx Doctrine The Dependency Theory The Dependency Theory explores the position of developing countries. The theory analyses and explores the gap between developing and developed countries in international relations as well as the causes of inequality. The Orthodox Dependency Theory argues that developing countries should change the loose state of existing and instead walk the road of self-improvement, namely through a South-South cooperation. It is advocated by Marx’ thought of “proletarians of the world unite”, promoting the idea that changing the internal structure of developing countries is the only way to break the dependency. It is through a reconstruction that an internal breakthrough mode can be achieved. In fact, since the 1955 Bandung Conference, held by the non-aligned movement, and also with the group of 77, the South Asian Association for regional cooperation, the world has started launching and spreading a South-South cooperation. The outcome is dependent on the point of view of the Orthodox Dependency Theory. It is too narrow, extreme and one-sided regarding developing and developed countries, as the cooperation between both is excluded. It is difficult to turn developing countries into developed countries with “economic surplus” alone. The development speed would still be lagging behind. The Modified Attachment Theory argues that developing countries should not only improve their national strength but also gradually reinforce cooperation with developed countries and the world capitalist system that is attached to economic development. They should also reform the irrational international political and economic order and establish the national development in the relatively favorable international economic new order (Cardoso 1973, pp. 142–178). Compared with the Orthodox Dependency Theory, the Modified Dependency Theory has a relatively open field of vision, but has at the same time not given a more detailed explanation regarding the specific way of cooperation or design of the mechanism.

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The View of World System Theory The World System Theory is based on the criticism of the Theory of Modernization and is drawing on the Theory of Dependency. Wallerstein, the representative of this theory (Wallerstein 1974), states that international economic cooperation mainly serves class struggle, including the cooperation within the working-class in the developed and ­semi-peripheral countries. Wallerstein puts forward the “center – edge – edge” in the world system, between the semi-periphery and between the center and in the periphery. In these countries the nationalist movement’s cooperation is controlled by central states as well as partly controlled by marginal countries, such as some of the economically powerful countries in Latin America, the entire periphery of Europe, and some of the Asian countries. Wallerstein describes capitalism as the core of the modern world system. The capitalist world system is characterized by oppression, exploitation and inequality. As a result, there is periodic turbulence and the expansion of the capitalist world system on the geographical scale is becoming more and more limited, which will inevitably require the recombination of political and economic decision-making. This will constitute the third possible form of the world system, namely, a socialist world government. This is the modern world system, which has been put forward in succession to Marx. Wallerstein’s “world history” perspective, based on Marx, lies in the analysis of the development trend of the world system. It states that when the capitalist production cannot be developed any further, when the contradictions and constraints have become the world’s contradiction and the limits of the capitalist mode of production, then there will be a socialist or communist mode of production as replacement. The leading capitalist economy and economic globalization will also be marked by socialism or communism replaced by economic globalization. The View of the Gramsci School This genre of the Marx doctrine promotes the idea that international economic cooperation and international cooperation should follow the same ideology and system combination. More important however, is the thought of cooperation—namely that through education and a change of people’s subjective consciousness to form a collective in the world—which will promote international social change. Marx’s view on “communication” is interpreted as “thought, idea, the production of an initiation, directly related to people’s physical activities, an intertwining of communication with people’s materialand real life, and language. People’s imagination, thinking and spiritual communication are the direct products of people’s material actions.” (Marx and Engels 1995, p. 72). This also expresses Marx’s and Engels’s assumption that spiritual exchange and material exchange are both equal. But we should also keep in mind that it is difficult to achieve material economic and trade cooperation regardless of the size of the region. The formation of the system, even the ideological cooperation, is even more difficult. First of all, the level of development between countries is not the same. Not only with regard to developed countries, but also with regard to developing countries, the difference is obvious. In developed countries

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or developing countries, this difference exists objectively. Secondly, the differences on the material side lie on the surface. The ‘deeper factors’ are the differences in ideology, religion and other aspects rooted in history, which may play an impending and fundamental role in international cooperation. Thirdly, the differences among the political systems will form a strong exogenous influence in the process of cooperation. Although the Gramsci School view of Marx has some idealistic tendency, it provides us with a new angle to recognize the issue of regional economic cooperation on a higher level. The Structuralist School of Thought This school represents the core idea of the ‘English School’, including the Theory of Structural Rights and the Theory of Structural Conflict. The Structural Power Theory sees international economic cooperation as a comprehensive cooperation including production and security cooperation, financial cooperation, knowledge cooperation, transportation cooperation, trade cooperation, energy cooperation and welfare cooperation. Cooperation is considered as being in mutual dependence on the origin of globalization and market oriented factors. The structure of the Conflict Theory can be described as follows: both sides will trade investment, currency, civil aviation, security and other aspects of an extensive cooperation (Krasner, translated by: Li 2001, p. 268). But there is a slight difference between the vision of a “South-South cooperation”, a “North Korea cooperation” and the peaceful coexistence and cooperation of countries supported by different systems, promoted by Lenin.

16.2.3.2 Common Views of ‘Marx Masters’ Marx’s greatest originality is based on an overarching view of the world’s political economy rather than its specific core areas. From the perspective of the consequences of global expansion of capitalism, he explores the interactive evolution of international political economy. The Marx doctrine agrees that developed countries and developing countries’ relationships are essentially of an exploitative nature. Getting rid of the dependence on the developed countries, and thereby finally achieving the decolonization and modernization of the developing countries, has become a core proposition of the Marx school. Comparing the above analysis ideas and main points of Marx’s theory, we can sum up their common views on the issues related to international economic cooperation as follows. International Economic Cooperation is the Key Link Marx thought that the international economic cooperation mainly refers to the cooperation activities, with the movement and reconfiguration of production factors as the main content in the field of production. (Cui et al. 2009, pp. 1–2). The nature and mode of economic cooperation determine the nature and mode of cooperation in other fields, including political cooperation, cultural cooperation and security cooperation. This is in line with the basic relationship between the economic foundation and the superstructure theory in Marx’s political economy.

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The Principle of Impartiality and Continuity Marx’s cognition of international economic cooperation is based on the protection of the weak and a harmonious development of the world order. He does not attempt to protect specific rights and interests but emphasizes that only absolute or relative fairness and justice can maintain the long-term development of the world. He advocates that the weak cooperate for the sake of due interests. Although there are divergent views on the mode and form of cooperation and different schools of thought, it is scientific and reasonable to establish a view of economic cooperation based on the principle of mutual benefit and to maintain the basis of long-term cooperation. Dialectical Unity of Confrontation and Cooperation Marx believes that cooperation and confrontation exist in international affairs. The economic and political links between sovereign states and different groups within the world must be cooperation and confrontation. As the congenital and historical conditions lead to an uneven distribution of interests, there is an antagonism and the main way to resolve the conflict is cooperation. Cooperation and confrontation are two aspects of the contradiction. International economic cooperation itself is an institutional arrangement in which countries seek a balance of interests in competition and confrontation. Therefore, confrontation and cooperation are bound to be the two aspects of dialectical unity in the process of cooperation. With the two aspects shifting, the region and the international community are constantly gaining opportunities for development and improvement.

16.3 The Characteristics and Research Paradigm of Marx’s Theory of International Economic Cooperation 16.3.1 Characteristics of Marx’ Theory of International Economic Cooperation Marx’s theory of international economic cooperation follows the consistent ideological characteristics of Marx and Engels and has been further developed in the process of advancing history.

16.3.1.1 Materialism Marx always regarded the contradiction of the movement between productive forces and productive relations as the fundamental motivating force. He views the essence and the law of the occurrence and development of the international economic cooperation phenomenon of the relationship between the economic base and the superstructure. International economic cooperation derives from the stage of free competition capitalism. When the machine industry productivity increases rapidly, it leads to “surplus products”—a process, which has contradictory effects on the market. Regarding the sale of the products, the bourgeoisie run the world and establish a world market for

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production and consumption. This promotes international economic division. However, at the same time this has established a cross national and cross regional mutual dependence of “savings since the integration of the world power” (Wang 1994, p. 632). This power is economic globalization. International economic cooperation is the inevitable product of economic globalization. The European integration is one of the typical capitalist forms of a community of states generated in this way (Guo 1989, p. 142). The road of cooperation has led to great achievements. After the end of the cold war, the global economy has gained a rare peaceful environment, which is adapted to the global development of productive forces. The countries constantly adjust their foreign policies. International economic cooperation has become the best choice for all countries. China has also actively participated in the process of economic globalization through the ­all-around cooperation with the world. As an important part of the process of economic globalization, China has formed a strong interaction with economic globalization.

16.3.1.2 Duality In building a bourgeoisie expansion of the global capitalist system, Marx thought that capitalist countries show a duality within the international community through ethnic relations and class relations. The Two Elements of International Economic Cooperation The two elements of international economic cooperation in national relations mainly refer to the cooperation between capitalist countries and developing countries. Due to the formation of colonial rule and on the basis of the history of the unfair international economic division, the developing countries are marginalized in the face of the old colonialists who “do not want us to have the development” (Deng 1998, p. 220). This is an unfair treatment. Most of the backward countries are still in the dilemma of development, and the gap between the North and the South continues to expand. The Two Characters of Class Relations in the International Economic Relations The two characters of class relations in the international economic relations refer to the cooperation between the socialist countries and the capitalist countries. On the one hand, the socialization of production—and the inherent power against the bourgeois exploitation and the oppression of the proletarian revolution—needs to promote the international union of socialist countries, after the establishment of the international federation of the proletariat to build a socialist and a capitalist group, like an anti-road group. On the other hand, in cases in which there are economic or public relations, countries are required to cooperate and share ideology. The western capitalist countries’ search for cooperation in an attempt to achieve a peaceful evolution of the socialist countries, has not fundamentally changed. The socialist countries have faced the long-term pressure of a peaceful evolution through western capitalist countries. However, it is a phased objective choice to seek cooperation with the socialist countries, which are not fully capable of replacing the capitalist countries.

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16.3.1.3 Change In view of the various unfair factors caused by the two elements of international economic cooperation, Marx’s doctrine highlights the important features of changing the global capitalist system. Based on the credo of the emancipation of the proletariat and all mankind and the historical mission of the proletarians to unite, Marx and Engels promote building a new society based on public ownership and national integration, until the demise of the state. Lenin proposed the establishment of a socialist federal state union, the international federation of the east and west of the proletariat, with the social public product of labor as a link and the Russian proletariat as the vanguard. This process sought a variety of ways of cooperation with a step by step approach. China, in its opening to the outside world and as a big socialist country is still in the process of development (Deng, X. 1993, p. 281). After years of unremitting efforts, China has stepped into the front line from being a participant in the international economic cooperation system to assuming the responsibility of being an advocate in building a harmonious world with lasting peace and common prosperity by building a democratic, diverse and win-win cooperative relationship and promoting fair change in the international economic cooperation system. 16.3.1.4 Peace Marx and Engels predicted that a new society based on public ownership, planned production and cooperation would make peace through the international principle of a new society. In the course of developing scientific socialism, Lenin put forward the idea of the “concession”. The concession system is an important part of the Lenin initiative. In March 1921, the implementation of the new economic policy, a form of state capitalism, began. Under the supervision of the Soviet regime, some industrial and mining enterprises entered into a contract with the state and rented, under certain conditions and time limits, forests, oil, land, and capitalist business. The tenants had to pay a portion of their production to the Soviet state and profit was extracted according to the contract. After the expiration of the contract, the state would turn over the enterprise. Similar to Stalin’s Soviet Union and the United States, the British capitalist country’s anti-fascist alliance and the United Nations, Mao Zedong sought to establish ‘the Third World as the main body, covering a vast area of the middle zone of the national united front against imperialism and hegemonism’ to achieve a peaceful coexistence with the capitalist countries. China’s reform pursues the same goal by opening up and, through the efforts of dialogue, building political mutual trust, strengthening mutually beneficial economic development and international cooperation, and finding ways to resolve the contradictions and differences of all countries in the world. These cooperative actions are efforts made to create a peaceful environment for the peaceful development of the socialist countries.

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16.3.2 The Research Paradigm of Marx’s Theory of International Economic Cooperation 16.3.2.1 The Foothold of Dialectical Materialism and Historical Materialism Marx and Engels believe that the international economic cooperation phenomenon only derives from the basic way of peoples’ material life. To find the law of development of human society derives from the contradiction between productive forces and production relations in the international economic cooperation and to reveal the origin, and development in this process, plays a decisive role in the economic interests. In the international economic cooperation theory of “economic materialism”, Marx and Engels explained the phenomenon of international economic cooperation from the materialistic perspective and gave clear economic reasons for the emergence and the development of international cooperation (Wu 2008, p. 14). 16.3.2.2 The Perspective of Common Interest Marx and Engels transcend the needs of individual national interests and understand the cooperative relationship among countries from the perspective of the overall interests of the world. The contradiction between capitalist productive forces and production relations are a fundamental driving force of human society (“the peoples of the world”) in world history and the regional history of “all countries to get rid of the natural economy and the formation of the overall state of closing the country to international exchange, mutual exchanges and mutual dependence of the development of history.” (Liu 2007). The existence and development of the common interests of the world is the premise of the development of international cooperation, including economic interests and political interests. Political interests include the whole world peace and the cooperation among countries with different systems. On this basis, countries need to seek economic benefits with the help of the common economic relations formed by the productive forces across borders. Complementary Effects in the Economic Structure Complementary effects in the economic structure are, for example, the advanced technology and capital of western capitalist countries and the complementary economy of China’s huge markets. Spillover Effects of Economic Cooperation China’s market and western capitalist countries’ advanced technology and capital combination create “numerous opportunities for development and the development of a strong vitality” (Renmin Ribao 1997). Mutual Prevention of Non-traditional security Threats With the development of economic globalization, the non-traditional security problems, which are directly related to political, military and other traditional security problems,

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can directly lead to human survival threats or national security threats. It is difficult to cope with the power of a country alone, and cooperation is the right choice.

16.3.2.3 Class View The international economic cooperation is a special social relationship beyond the scope of the nation-state and is occurring in a global capitalist system. The use of class views has become an important feature of Marx’s and Engels’s analysis of international economic cooperation. In the global capitalist system, any destruction caused by free competition in any individual country will be reproduced on a larger scale in the world market (Marx and Engels 1995, p. 228.) Among them, “class” has become a new and more decisive behavior unit in the international community (Wang, H. 1994, pp. 637– 638). According to Marx and Engels, the face of the international community is divided into two opposing class forces in reality. The requirements of world unity have become the dominant force in the reform of the international society. The unbalanced development of the world has intensified and the history of the international struggle between the proletariat and the bourgeoisie has also been a struggle for the elimination of the unbalanced development of the world. 16.3.2.4 Forms and Attributes of Cooperation It is difficult to develop cooperation founded on different ideologies, social systems, development levels and cultural differences. However, the existence of these common interests makes international cooperation possible. Through the establishment of political mutual trust and the strengthening of the economic reciprocity and development cooperation mechanism, Marx’s doctrine is continuously innovating the ways of international cooperation. The proletariat and the socialist countries have tried a variety of forms of cooperation, such as the early Communist-, the First International-, Second International-, Third International-, and the Communist International League and, at present, the “Partnership” and other multilateral organizations. In various forms of international cooperation, Marx sought to build a democratic, diverse and win-win international economic cooperation.

16.4 The Research on Regional Energy Cooperation Under the Guidance of Marx’s Doctrine 16.4.1 The Important Enlightenment of Marx’s Doctrine for the Regional Energy Cooperation in China 16.4.1.1 Adhering to the Principle of Multiple Cooperation China should adhere to the principle of international cooperation based on regional economic cooperation, supplemented by regional political and cultural cooperation. Regional energy cooperation itself is regarded as a long-term task in terms of economic,

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political, cultural, security and other aspects. China should mainly seek its stability, in order to avoid the impact of the regional situation on the energy cooperation. We should not only focus on the diversification of the field of cooperation, but also insist on the diversification of cooperation objects and the diversification of cooperation methods, in order to prevent the fluctuation of regional cooperative relations. In the practice of energy cooperation, China has initially secured Russian, Pakistani, Kazakh and other bilateral cooperation projects and founded the China Association of Southeast Asian Nations (ASEAN), the Shanghai Cooperation Organization, the “One Belt, One Road” strategy and other multilateral cooperation projects. Based on this foundation, China should focus on actively promoting the establishment of a regional cooperation framework and a long-term mechanism, and effectively exert the influence in the region, in order to achieve an effect on a greater scale.

16.4.1.2 Based on the Interests of the People Whether it is regional energy cooperation or a wider cooperation, it is important to resolutely safeguard the interests, especially of the Chinese people. In international cooperation, the rights and interests of developing countries are particularly vulnerable to infringement. China should resolutely safeguard its national interests, pay attention to the advantages and avoid disadvantages in the regional energy cooperation, resolutely abandoning the adverse cooperation that endangers the sustainable development of people’s lives, population, resources and the environment. China’s dependence on energy has reached unprecedented levels. As of 2014, the dependence on oil has reached nearly 60%, while China’s energy supply gap has also been increasing. In the search for energy cooperation, we cannot be blind because of the urgent demand and should not make choices that could be detrimental to the people of our country. Otherwise, the efficiency of the cooperation would be difficult to guarantee and the positive effects would be reduced. 16.4.1.3 Seeking Long-Term and Stable Cooperation In terms of the current process of globalization, sovereign states will continue to exist, and the real global integration is still a long way ahead. A sovereign state will inevitably meet confrontation and there will be struggle among nations. Regional cooperation and confrontation are concomitant, and the dialectical relationship between the two determines that no one can destroy them, and they can only promote each other to form a benign development. For our country, we need to look at the regional energy cooperation in the view of development. We need to seek long-term stable cooperative relations and cooperation in competition and realize seeking common ground and common development. The central task and the ultimate goal is to build a harmonious surrounding environment. This will be a gradual process, and the pressure of competition between sovereign states and regions will exert a strong impediment to this process. The regional conditions, energy cooperation characteristics and environmental factors will change constantly. China can be divided into stages and levels to promote energy cooperation and

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to continuously adjust the ideas and strategies to adapt to the impact of these changes. In this process, the supply of public goods such as consensus, system and convention in the cooperative organization will become an important guarantee for the smooth progress of cooperations.

16.4.2 The Nature of Regional Energy Cooperation in China At present, the volume of global economic development is very large, and the power source of economic development—energy issues—have become a constraint on the economic development of various countries. The problem cannot be solved by any country or alone. Energy cooperation is the only way of economic development at present and in the future.

16.4.2.1 Economy Energy functions as a bulk commodity. All kinds of energy are the commodities that the countries around the world seek to produce and consume on a large scale for their economic development and for social progress. They are also the important sources of international trade increment among countries. Its pricing mechanism, trade and settlement methods, transportation costs and other factors have a profound impact on the economic and social development costs of countries. According to the theory of division of labor and comparative advantage, the countries in the region reconfigure their respective advantages, divide and cooperate to carry out regional production, and to obtain surplus of cooperation to improve economic efficiency. 16.4.2.2 Spillover The international cooperation in the energy field covers commodity trade, transportation and energy infrastructure, cross-border oil and gas pipeline construction and operation, energy pricing rules and other fields, and many industry spillovers to economic sectors and duties, as well as financial and legal aspects of cooperation. This also determines the importance of the energy cooperation and the universality of the connotation and needs to provide a more comprehensive mechanism system through regional cooperation and to ensure the long-term and stable development of the region. 16.4.2.3 Strategy For major energy producing countries, energy exports are often important sources of finance. For the consumer countries, energy import is directly related to the sustainable development of the economy and society. For the energy transfer countries, the control of the energy transportation channel guarantees the national income and the international influence of the country. The cooperation between the three parties in the field of energy is related to national security and political stability. Therefore, energy cooperation has often become a strategic game between countries, in order to achieve important policy objectives (Fig. 16.1).

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energy resources countries cooperaon

energy consuming countries

energy transferring countries

Fig. 16.1  Energy cooperation bodies schematic diagram

16.4.3 The Conditions for Regional Energy Cooperation in China 16.4.3.1 Willingness to Cooperate and Regional Stability Since it is a cooperation, we must first have a strong willingness to cooperate and find a basic consensus for agreeing on the trend and mutual benefit of the regional energy development. Xi pointed out, in a speech held in October 2013 at a Forum on Diplomacy, that “China’s periphery is full of vigor and vitality, has obvious advantages and a great potential for development. The surrounding environment of our country is stable. Good neighborly friendship and mutually beneficial cooperation is the mainstream of neighboring countries” relations with China (Xi 2013). China’s “One Belt, One Road” project will be integrated in the same development platform and will bring a historic opportunity for regional peace and cooperation, at the same time stimulating the enthusiasm of the surrounding area to participate in energy cooperation. Today, China’s neighboring countries and regions have reached the mainstream views of regional development cooperation. In fact, in recent years, China and the neighboring countries have become increasingly focussed on the economy, trade, energy, culture, society, environmental protection, and non-traditional security field of functional cooperation. This is also due to the stability of the regional security situation. Compared to other developing regions, the implementation of the energy cooperation has laid a good foundation, although there have been some disputes in the Asian region, of which China is one country. In general, the region has maintained a relatively stable situation. 16.4.3.2 Economic Leading and Factor Complementation In regional cooperation, a relatively strong economy is required to undertake the leading role. In the Asian region, this task might be taken on by China. At present, China has sent many positive signals to neighboring countries regarding the overall development trend and the driving role of the regional economy. China is already the largest country of the region with more than 120 trade partners and an annual import value of 2 trillion U.S. dollar worth of goods. As a global trade partner, it creates manifold jobs and

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investment opportunities (Yao 2014). This laid the foundation for China’s leading position in regional cooperation. In terms of energy, China is absolutely on the demand side, while in the surrounding areas there are a number of important energy-producing countries. These countries need to diversify energy sales, the introduction of technology and the investment of energy in China, and then use the results of China’s economic development to accelerate the development of energy infrastructure in the country. Specifically, China and the neighboring countries are complementary in their performance with respect to the following aspects: capital, technology, the market, resources and other aspects. Energy Cooperation Between China and Russia Russia is facing the problem of economic development and national transformation. There is an urgent need to expand exports and to introduce investment. In 2013, the Sino-Russian energy cooperation reached a new height, ‘building a strong relationship between both countries with a Sino-Russian energy cooperation strategy’. In 2013, the two sides reached (a) a long-term oil supply agreement, (b) an agreement on the Tianjin refinery, (c) a crude oil supply increasing cooperation agreement, (d) the East and West Russia to China natural gas pipeline agreement to supply oil and liquefied natural gas, and (e) an agreement on nuclear fuel. The crisis in the Ukraine at the beginning of 2014 prompted the US and European countries to sanction Russia’s energy sector and reduce energy imports from Russia, which prompted Russia to pay more attention to the Far East market and deepen its cooperation with China. The energy cooperation between China and Russia is not limited to the development and utilization of oil and natural gas, but will also extend to coal, nuclear power and other fields. Russia is one of the most important energy partners of China. Energy Cooperation Between China, the Middle East and Central Asian Countries The Middle Eastern and Central Asian oil producing countries intend to open up the upstream oil and gas industry in China, and the desire to promote economic and trade cooperation with China through energy cooperation, and thus to promote its own economic restructuring, is strong. China’s moderately open energy downstream industries and markets attract greater attention from the neighboring countries. Among them, Kazakhstan is carrying out the strategy of industrial innovation and development and has begun to shift the focus of foreign direct investment (FDI) and cooperation to ­non-resource areas. Mongolia and other Central Asian countries are the preferred focus of transportation development, mineral products and agricultural products processing, light industry and service industry in the economic development, the “Giuseppe Railway” and the construction of a highway network, to look forward to. China, Kazakhstan, Russia and Mongolia have a bright future in the regional cooperation mechanism.

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Table 16.1  Regions and main areas of energy cooperation. (Source Based on Shi 2015) Cooperation subjects

Main areas of cooperation

China—Russia

The development and import of oil and gas

China—Middle East

Oil and gas exploration, trade

China—Central Asia

Transport, mineral products and agricultural products processing, light industry and service industry

China—Southern Asia

Infrastructure, science and technology

Energy Sources in China and South Asian Countries The South Asian countries and China have a huge potential for cooperation in the field of science and technology infrastructure (Table 16.1). The economic integration of the countries in the region to build the Pakistan Economic Corridor and the Bangladesh, China, India and Myanmar (BCIM) Economic Corridor will revitalize the entire region and promote the construction of an interconnection (Fig. 16.2).

16.4.3.3 Political Mutual Trust and Mechanism Guarantee China pursues partnerships with its neighbors and an amicable, secure and prosperous neighborhood surrounding foreign policy. It adheres to the correct outlook, honesty and benefits. Xi Jinping stated: “China’s peripheral diplomacy embodies affinity, honesty, benefits and capacity” (Xi 2013). This deserves a good foundation for political mutual trust in China. One of the most important results of the Shanghai Cooperation Organization summit in Bishkek in August 2007 was that the member states signed a cooperation agreement on energy—a solid step for regional energy cooperation in China. Based on this, China has also actively participated in multilateral cooperation mechanisms, such as the Asia Pacific Economic Cooperation Organization (APEC), the Group of 20 (G20), the BRIC countries (Brazil, Russia, India and China) and so on. By promoting regional energy

exploration and development

infrastructure

upper reach

smelting processing

trade and transportation

transportation safety

middle reach

marketing management

lower reach

Fig. 16.2  Energy cooperation industrial chain between China and surrounding countries and regions

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cooperation and deepening development, the connotation of the existing international mechanism is more abundant, and the foundation is firmer.

16.4.4 Restricting Factors of Regional Energy Cooperation in China Regional energy cooperation should not only provide the flow of commodities or resources within the region, but also be a model for the international affairs in the region. It is the particularity, complexity and strategic nature of energy that determines that energy cooperation will be more constrained than general economic cooperation.

16.4.4.1 Internal Constraints The Difference Between the Social System and Ideology Deep-seated factors restricts the regional energy cooperation mechanism. There are two different political systems, by which the countries surrounding China are ruled, the socialist system and the capitalist system. Regarding the level of development, there are developed countries (Japan, Russia), newly industrialized countries (South Korea) developing countries and countries in transition. Although the differences between the social system and the ideology cannot impede economic cooperation (including energy cooperation), they are at least a negative factor. Even the “Cold War mentality” is still playing a role, and some countries lack the concept of mutual benefit and so on, which may become a potential obstacle. Obvious Dispute of Reality China’s peaceful development of the surrounding area is a broad trend, but there are still some unstable factors, such as the North Korean nuclear issue, the Taiwan issue, and the Diaoyu Islands issue which is not only a territorial issue but is in itself is a problem related to energy. These are direct and real factors that restrict the development of a multilateral energy cooperation mechanism among the countries in the region. The Lack of a Multilateral System At present, most of the regional energy cooperation in China is still bilateral cooperation. The institutional supply of multilateral cooperation is not perfect, and even cannot reach the requirements of mutual benefit or a win-win situation. The multilateral cooperation of the remaining energy is mainly formed through alliance or organization, and the institutional framework is limited to the Common Goal Model and the Shared Information Model (Zen 2005, p. 113). The Common Goal Model points out the necessity of reaching an agreement on the goal that is to be achieved, without specifying the way and method of realization. The common goal is also directional and suggestive to the actor. The Shared Information Model requires that the actors provide timely and high-quality information to avoid misunderstanding and confusion, which will help to formulate the

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correct policy and facilitate the supervision of all parties involved. The reason lies in the difference of their respective interests, caused by differences between the member states. Within the multilateral system of resource and economy, the cooperation profit distribution is not a reasonable standard and mode.

16.4.4.2 The Influence of External and Environmental Factors The Influence of Foreign Countries In recent years, the United States’ “Return to Asia Pacific” strategy had a great impact on China and its surrounding areas. With the shift of the strategic focus of the United States and the accelerated plundering of energy in the region of Asia, the pressure on China for energy cooperation in China’s peripheral areas increased. In fact, the United States are using North Korea’s nuclear issue to block the economic cooperation between China and its surrounding areas in order to strengthen the strategic influence and deterrence of the United States in the region and to contain China’s development. The key reason for this effect lies in the excessive reliance on the global energy strategy control system in the United States, such as Japan and the Philippines. The Status Restriction of China in the Regional Cooperation Organization Although the existing multilateral cooperation organizations are still imperfect, they are still a relatively effective platform to obtain the right to energy cooperation. We found that not only the International Energy Agency is specializing in energy issues and the establishment of the international organization in this way, but even the global economic cooperation has become an important way to deal with the problem of energy, building an energy cooperation relationship. China’s identity differences in the existing international organizations and the influence of some still non-members, will be an especially important obstacle for China to play its due role in the regional energy cooperation to seek benefit. In view of this, it is necessary for China to lead the development of new energy cooperation organizations that are in line with their own interests and the interests of the surrounding areas, in order to maintain regional stability to the greatest extent and to ensure regional development space. At present, China’s participating energy cooperation organizations can be divided into general cooperative organizations, dialogue type cooperative organizations, substantive cooperative organizations and leading cooperative organizations, according to the degree of China’s participation in the cooperations (Table 16.2).

16.4.5 The Realistic Choice of Regional Energy Cooperation in China In the face of the above constraints, China should focus on promoting a regional multilateral energy cooperation, taking energy cooperation as a core issue, and carrying out substantive energy cooperation in a broader perspective. It should actively lead the

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Table 16.2  Energy cooperation organizations China participated in and participation modes Degree of participa- Cooperation organization tion in cooperation

Participation status

Cooperation method

General cooperation IEA, OPEC and G8

Non-member countries

Participate, observe, etc.

Dialogue cooperation

Independent Oil Exporting Member countries Countries, International Energy Conference, World Energy Council, World Energy Conference, Energy Charter, Organization for Economic Co-operation and Development (OECD), etc.

Substantive cooperation

UNCTAD, EU, APEC, GCC, ASEAN, SCO, etc.

Leading cooperation Asian Infrastructure Investment Bank (AIIB), “the Belt and Road”

Actively participate in related forums, conduct regular dialogues, and discuss relevant cooperation matters

Member/non- Deeply participate in all member aspects of environmental countries and energy issues, formulate specific energy cooperation plans, and sign relevant agreements Originating country

Lead preparations, organizational structure, rulemaking, and validation by member countries

establishment and improvement of a long-term and stable mechanism of energy cooperation in the surrounding areas to achieve a scale effect of energy cooperation.

16.4.5.1 Mode Choice of Regional Energy Cooperation as a First Step Judging from the type of cooperation, China should transcend the limitations of bilateral cooperation, build a multilateral energy cooperation mechanism, combine the two organically, and select the most suitable energy cooperation mode according to the object and environment. Specific to the multilateral energy cooperation mechanism, it can follow and learn from the World Energy Charter organization (“Energy Charter Treaty”), which took effect in April 1998 and covers oil, natural gas, coal and renewable resources, energy resources, exploration and development, from design to transport and distribution. Its main content involves four aspects of international investment, trade, transit transportation and dispute settlement in the field of energy. The first legally binding multilateral investment protection agreement provides a legal framework and mechanism for trans-regional energy investment, trade, transportation, energy efficiency and environmental protection, as well as the settlement of disputes. The experience from the areas of cooperation and the multilateral energy cooperation mechanism need to go beyond the simple business relations development from the

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general trade cooperation and mutual investment, gradually to the production direction, strive for exploration, exploitation and transportation, storage, processing and environmental protection of oil and gas resources and cover all source links and fields.

16.4.6 Institutional Choice of Regional Energy Cooperation as a Second Step 1. The international energy market monitoring and emergency system need to be improved, the development of oil and gas resources promoted, in order to increase supply based on the energy demand and supply basic equilibrium, as well as to ensure stable and sustainable international energy supply and reasonable prices of energy to meet the global energy demand. 2. The establishment of a joint oil reserve system will be an important aspect of strengthening regional cooperation and building a multilateral energy cooperation mechanism. 3. It will be important to establish the information and data sharing system to ensure the effectiveness of the regional symmetry and transmission mechanism of information. 4. The formation of advanced an energy technology research and promotion system could actively promote cooperation in the efficient use of fossil fuels such as clean coal technology. Renewable energy should be promoted as well as nuclear energy, hydrogen energy and other major energy technology research and development cooperation. The establishment of a clean, safe, economical and reliable world future energy supply system should be explored.

16.5 Conclusions and Implications The idea of regional cooperation is becoming the leading thought of the world in dealing with national affairs and foreign exchanges. It can be stated that the 21st Century is the century of regional cooperation. Especially for energy issues that affect global development. Each individual economy is powerless in the face of this issue. This is the practice of our country’s inheritance and development and the cooperative thought of Marx’ doctrine in reality. We need to adhere to the Marx doctrine of materialist dialectics and historical materialism, draw lessons from the experience of history and combine these with the reality of China’s economic development, using the socialist country strategy as a guide, seeking the classical theory and the development of regional economy integration in line with China’s interests, and formulate a reasonable cooperation mechanism and long-term perspective to go on.

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References and Additional Literature Marx, K. (1982a). Das Kapital (3 [M] ed., pp. 272–273). Beijing: People’s Publishing House. Marx, K. (1982b). Das Kapital (2 [M] ed.). Beijing: People’s Press. Marx, K., & Engels, F. (1995). Selected works of Marx and Engels (Vol. 1). Beijing: People’s Publishing House. 崔日明、李兵、刘文革:《国际经济合作》[M],机械工业出版社,2009. 《邓小平文选》第3卷[M],人民出版社,1993. 《邓小平思想年谱(1975–1997)》[M],人民出版社,1998. 郭锐、桑林:《变革中的国际政治经济学:主要流派及其核心原理》[J],《辽宁大学学报(哲学 社会科学版)》,2009 (1). 郭吴新:《世界经济》,第2册,高等教育出版社,1989. 《江泽民在美国哈佛大学的演讲》,《人民日报》,2.11.1997. Li, B. (2005). What is Marx’s theory of international relations? World economy and politics, 5(2005), 37–44. 《列宁专题文集(论社会主义)》[M],人民出版社,2009. 《列宁选集》(第3版)第4卷[M],人民出版社,2012. 刘航:《国际政治经济学的国际经济合作思想及对中国的启示——马克思主义流派与非 马克思主义流派的比较》,《外国经济学说与中国研究报告》,2012. 柳瑟青:《马克思主义国际关系学的奠基之作——〈德意志意识形态〉理论贡献的新视角》 [J],《现代国际关系》,2007 (5). 马克思:《资本论》第2卷[M],人民出版社,1982. 马克思:《资本论》第3卷[M],人民出版社,1982. 《马克思恩格斯选集》(第2版)第1卷[M],人民出版社,1995. 《马克思恩格斯全集》第21卷[M],人民出版社,2003. 《马克思恩格斯全集》第35卷[M],人民出版社,2013. 石泽:《能源资源合作:共建“一带一路”的着力点》[J],《新疆师范大学学报》(学社会科学 版)2015 (1). 谭培文等主编:《马克思主义经典著作选编与导读》(第l版)[M],人民出版社,2005. 唐严林:《国际政治背景下东北亚多边能源合作机制的构建》[J],《西伯利亚研究》,2006 (8). 习 近 平 :《 我 国 周 边 外 交 体 现 亲 、 诚 、 惠 、 容 ——在 周 边 外 交 工 作 座 谈 会 上 的 讲 话》,24.10.2013. 习近平:《让命运共同体意识在周边国家落地生根———在周边外交工作座谈会上的讲 话》,25.10.2013. 王菲,《中国与中亚国家能源合作开发的政治经济学分析》[J],《云南行政学院学报》,2009 (3). 王沪宁:《政治的逻辑——马克思主义政治学原理》[M],上海出版社,1994. 吴恩裕:《马克思的政治思想》[M],商务印书馆,2008. 叶蓁蓁:《国际能源合作模式与中国的战略选择》[D],外交学院,2005. 中华人民共和国商务部:《姚坚就“中国成为世界第一货物贸易大国”发表谈话》,1.3.2014. [美]查尔斯·P.金德尔伯格:《1929~1939年世界经济萧条》[M],宋承先、洪文达译,上海:上海 译文出版社,1986. [美]罗伯特·基欧汉:《霸权之后:世界政治经济中的合作与纷争 》[M],苏长河等译,上海世纪 出版集团, 2001. [美]曼库尔·奥尔森:《集体行动的逻辑》[M],陈郁等译,上海:上海人民出版社, 1995. [美]斯蒂芬·克莱斯纳:《结构冲突》[M],李小华译,浙江人民出版社, 2001.

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Cardoso, F. H. (1973). Associated-dependent development: Theoretical and practical implications. In A. Stepan (Ed.), Authoritarian Brazil: Origins, policies and futures (pp. 142–178). New Haven: Yale University Press. Shi, Z. (2015). Focus of cooperation for energy resource of silk-road economic belt. Journal of Xinjiang Normal University (Philosophy and Social Sciences), 2015(1). Wallerstein, I. (1974). The rise and future demise of the world capitalist system: Concepts for comparative analysis. Comparative Studies in Society and History, 16(4) (Sep. 1974), 387–415.

Designing Trustworthy Smart Contracts in International Trade Blockchains

17

Roger W. H. Bons

Contents 17.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 17.2 Trustworthy Trade Procedures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 17.3 Reasoning About Smart Contracts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244 17.4 Conclusion and Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248

Abstract

This paper investigates the role of blockchain in the coordination of ­inter-organizational activities. Rather than focusing on the role of cryptocurrencies, we explore the potential of smart contracts—formalized agreements between parties that run on blockchains and that can verify the fulfilment of certain conditions and trigger the next steps automatically to save handling costs. When parties would come to rely on such automated contracts, they have to be sure that these contracts manage and distribute the risks equally among the participants. We have adopted a formal modelling approach we developed in the 1990s to reason about the correctness and the compliance to risk management principles. This is applied to the case of inter-organizational trade, as this is a domain that requires a high level of cooperation between many parties, but also entails a high risk of opportunistic behaviour. With our research, we help the design of inter-organizational controls to be implemented

R. W. H. Bons (*)  FOM University of Applied Sciences, Essen, Germany e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_17

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in smart contracts, including trusted third parties who witness the execution of certain steps and reliably report this to the blockchain to enable the next step to be taken.

17.1 Introduction The launch of the first Bitcoin in 2009 (Diedrich 2016; Nakamoto 2008) has triggered, according to many, the next big revolution in the overarching age of digitization. A digital currency was born, independent of central authorities and with the ability to digitally transmit funds between pseudonymous parties without the intervention of third party intermediaries, such as banks. To this day, the Bitcoin system itself has not been compromised (Ross 2016), offering proof that the underlying mechanics work. A fact, this cannot be transferred to some of the real-world interfaces, which enable people to exchange regular currencies into Bitcoins and vice versa. In some instances, people lost their digital currency, for instance with the Mt. Gox heist and an estimated loss of 850.000 Bitcoins (Kindergan 2017). With the increasing value and relative anonymity of the users, digital currency exchanges are becoming important targets for hackers (Wieczner 2017). But one could argue, that such exchanges are in fact new instances of trusted third parties, the kind that the “Cypherpunks” (Diedrich 2016), who developed the technology, tried to eliminate in the first place, and as such would only reaffirm their strive towards a truly independent currency. The underlying technology behind Bitcoin has become known as “blockchain” or “Distributed Ledgers” and has indeed led to many new initiatives, such as Ethereum, Hyperledger, Aeternity and others (Aeternity 2017; Ethereum 2017; Linux Foundation 2017). These initiatives extend the single-purpose logic of Bitcoin into a generalized form of transaction execution, called “smart contracts”, where the set of agreements between multiple parties are modelled as a computer program executed on the blockchain. This ensures that transactions only occur when the pre-conditions are met, but also ensures that the transactions will occur in such cases, without the possibility of any single party stopping or manipulating them. Unfortunately, most blockchain initiatives have inherited the aim to eliminate any and all third-party intermediaries, with the claim that such parties only increase costs and/ or that they are only in the game to get a position of power based on the knowledge they can gather from observing the transactions they facilitate. Regardless if this might or might not be accurate, it does position the blockchain technology as a fundamental eliminator of entire industries, based on the assumption, that people and businesses rather rely on the execution of an uncontrolled and unowned piece of software than on a supervised entity with a real-world presence, that can be sued in case of misbehaviors. And although there might be areas where this is precisely what participants want, we propose that in most common situations, there is, in fact a need for accountability, combined with a genuine desire to pay as little as possible for the trust services rendered.

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It is in this spirit that this paper investigates the possibilities offered by blockchains. Many of the traditional trusted third parties, in particular, banks, insurance companies, health care providers, but also energy companies, are looking into the technology to see how it can help them reduce their costs. They recognize that the current ways of working are indeed costly, but this is not only due to the human involvement in the operation or commercial considerations, but also due to the fact that intermediary parties are taking part in the risk, which has to be financially compensated as well. Not ruling out that there may be some current practices that are overpriced due to a limited supply base. Initiatives such as R3, where financial service providers work together on blockchain initiatives, and Hyperledger, an initiative from the Linux Foundation, are an illustration that there is an awareness of the blockchain potential to innovate the trust service industry (Linux Foundation 2017; R3 2017). We focus our research on the ability of blockchains to facilitate inter-organizational processes through “smart contracts”. We will concentrate on the international trade domain, which is a well-documented domain with many centuries of experience in governing multi-party transactions. In this paper, we want to contribute to this endeavor by offering a framework for the analysis of said smart contracts, in particular in settings that involve activities of multiple parties and that go beyond bi-lateral agreements between service providers and their clients. We will start by specifying the concept of “trustworthy trade procedures” as an objective way to discuss risks and the presence of opportunism, especially in cases where parties interact remotely and/or online (Bons 1997). Subsequently, we discuss the concept of “smart contracts” and will relate the definition which is currently known in the blockchain community to a body of scientific literature that emerged in the 1980s and 1990s. In the final section, we offer a first outlook of a design framework for smart contracts. We conclude with research outlooks and a call of projects to verify these prototypical concepts.

17.2 Trustworthy Trade Procedures The concept of trust, or the lack of it, is by no means new, in particular in the setting of international trade. In fact, the origin of trade finance and some of the best known financial instruments, such as stocks, but also letters of credit, originated hundreds of years ago, when ships sailed across the world in search of riches, but doing so while facing enormous risks of not returning. It led to constructs for the distribution of that risk among several parties (the original idea of stocks) as well as the introduction of trusted third parties or agents who could observe whether or not a party had performed according to the agreed plan. Since parties were not always able to observe the actions of their counterparts in person and as they happened, they started to rely on testimonies of trusted third parties, as communicated in documentation by those trusted parties. Receiving documentary evidence of a trusted witness would have the same

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risk-mitigating value as witnessing the transaction in person, and would as such lead to initiating the next step in the agreed procedure, e.g., releasing the payment after receiving evidence that the goods have been put on transport. Since such additional steps and document exchanges need to be agreed upon upfront, the negotiation between buyer and seller became more than just an agreement on price, quality, and quantity. It now includes a detailed procedure on how the agreement was to be executed and which documents where to be provided, with sufficient safeguards for both parties to protect against opportunistic behavior from either side during this settlement stage (Bons 1997). Shifting the focus on what this means in the day and age of IT supported business operations, the internal view on processes and data management is well known and is the subject of fields such as business process modelling. Modern enterprise systems offer the ability to model the processes as separate entities, providing flexibility when processes are changed and ensuring clear separations between data and processes. Who (or which system) is responsible or accountable for which activities, and who is to be consulted/informed are the focus of traditional RACI matrices that govern process execution (Feltus et al. 2009). However, our scope is the modelling of processes and the associated responsibilities and accountabilities across organizations, as that is where the aforementioned coordination and trust mechanisms have to occur. If further levels of automation in inter-organizational processes are to be achieved to further reduce the costs of execution, parties must agree on the procedure of how to interact. In Bons (1997) we defined a “trade procedure” as “a sequence of external activities, defined between roles, which constitute a transaction between a number of parties”. The “role” concept refers to “a model of a meaningful cluster of external activities, recognized by the business world”, for instance “bank”, “transporter” etc. In actual transactions, roles become instantiated by organizations, such as “ING Bank Netherlands B.V.” or “Maersk Shipping Lines Inc.”. As is clear from the reference, this idea is not new, and a standardization body was already active in this domain in the 1990s under the term “Open Electronic Data Interchange (EDI)”. Open referred to the development of industry standard “scenarios” that would specify how specific types of contracts were to be executed, both from a business operational and an information technological perspective (ISO/IEC 2015). It is our belief, that this body of knowledge can offer some important insights for the discussion of smart contracts in the blockchain era. In the next section, we discuss how the concept of a trade procedure connects to the concept of smart contracts.

17.3 Reasoning About Smart Contracts In the blockchain community, the concept of “smart contracts” is attributed to Nick Szabo’s publication (Szabo 1996), in which he defines the term as “a set of promises, specified in digital form, including protocols within which the parties perform on the other promises”. The extension of Bitcoin with the “Solidity” language to express such

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contracts was most notably observed in the “Ethereum Blockchain” (Diedrich 2016) and must be considered as a great breakthrough. Now, not only transactions are recorded in an irreversible way (when validated by the community running the blockchain), but entire processes can be executed in a predictable, irreversible and decentralized way. The real world communicates with the blockchain through so-called “Oracles” (Diedrich 2016), which can be implemented as Application Programming Interfaces (or APIs), sensors or more advanced Internet of Things devices. They inform the blockchain that a real-world status has changed, upon which each node of the blockchain inspects the criteria modelled in the contract. When satisfied, the nodes automatically execute the next step according to the smart contract formal instructions. The Byzantine consensus mechanism of the blockchain will determine, which of the executions are in fact correct and will adopt the new state together with all other validated changes in this block. As such, no single entity can control the flow of the contract beyond the parameters modelled into the contract (similar to termination clauses in legal contracts) and the execution thereof is removed from several internal systems to a single centrally shared system. Which it is not, of course, since the blockchain runs on each node and there is not a single party who “owns” or “runs” the system, while each of the internal systems of the participants must somehow interact with the node to make the “real world” connections through Oracles. But it does help to logically position it in this way to be able to reason about it. Figure 17.1 illustrates this, based on the trade procedure concept introduced in Bons (1997). The big challenge now is to develop smart contracts that work and treat all parties fairly. It is in this area that we believe this paper represents a discursive contribution, based on our earlier work on “trustworthy trade procedures”, which are “trade procedures that govern transactions in which the risk of opportunistic behavior by one or more parties is present, but which provides sufficient inter-organizational controls to limit this risk” (Bons, 1997). Scientifically, Szabo’s introduction of smart contracts is not the first time that the modelling of legal contracts to enable automated execution has been discussed. In fact, Ronald Lee already discussed several formal modelling aspects of electronic contracts back in the 1980s (Lee 1988a, b) with the aim of “integrating these aspects in a logic programming formulation that demonstrates their relevance and usefulness for electronic contracting in the form of an operating prototype”. The research by Lee and several doctoral students resulted in various formalisms that did not only allow for the modelling of transactions (Documentary Petri Nets (Bons et al.1995; Lee and Bons 1996)), or the modelling of obligations (based on deontic logic (Van der Torre 1997)), but also to allow for automated generation of procedures based on a specification of constraints (Lee 1999). In this paper, we focus on the three-level framework (Bons 1997) that was developed to facilitate the formal reasoning about the procedural aspects (Szabo’s “protocols” (Szabo 1996)). It distinguishes between the “business level”, the “communication level” and the “infrastructure level” (see Fig. 17.2). At the business level, we reason about which activities are to take place to satisfy the primary objectives of the business transaction. In a simple commercial transaction,

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Fig. 17.1  The blockchain as a trade procedure. (Source Based on Bons 1997)

business transaction

infrastructure level

communication level

business level

communication requirements

information exchanges

controlled by

impose

communication technology

implement

Fig. 17.2  A framework for analyzing trade procedures

this could be the provisioning and shipping of goods on the one hand, and the transfer of funds on the other, as well as the actual transportation. We also need to identify the secondary activities that are needed to control the proper execution or settlement of the contract in the presence of opportunistic behavior. One example might be the execution of an inspection of the goods, a confirmation of the status of the goods when they arrive at the port and so on. The coordination of all these activities happens through the exchange of information. Some “documents” or “messages” are exchanged to assist the

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coordination and operational alignment of the parties, while other documents are more formal in nature and their exchange constitutes legal state changes. At the business level of the analysis, we identify which control actions and resulting information are needed and which are the functions of these “information exchanges”, the so-called “illocutionary force” of the information (Austin 1962). At the communication level, we address the consequences of these functions based on the way information is exchanged and based on the communication medium used for it. When organizations decide to rely on information about a transaction rather than witnessing the transaction itself, that information becomes the next source of risk. To steal a container, it would be sufficient to forge or manipulate the Bill of Lading document that is used (in its paper form) to collect the container at the destination. Whoever holds the document will receive the goods. In Bons (1997), this requirement was referred to as “uniqueness”, meanwhile it has become known as the “double spent problem”. But also more basic requirements, such as integrity, authentication and non-repudiation are part of the equation when documents become valuable. The final level of consideration is the infrastructure level. While in the pre-computer days documents were protected by watermarks, seals, special ink and many other features—we currently only know because they are used in bank notes—we need different solutions if we want to move the execution of transactions to the digital domain. In Bons (1997) we already discussed cryptographic solutions such as public key infrastructures, hash-functions and their application in encryption and digital signatures. However, at that time, no solutions were available that would practically solve the “double spent” problem also known as the “uniqueness requirement”. Blockchain does solve this problem convincingly, given the (almost) decade that Bitcoin now runs without coins being copied at will.

17.4 Conclusion and Outlook We believe that the development of smart contracts can be a significant contribution to the simplification of inter-organizational processes and may result in major cost savings for all stakeholders. However, such contracts need to be designed with sufficient safeguards for all stakeholders regarding the risks of opportunistic behavior. Especially in a situation where no central entity can be approached to repair damages if something goes wrong, businesses and citizens will require such guarantees. Our prior research on the design of trustworthy trade procedures not only offers the framework discussed in this paper, but also includes domain-specific knowledge on international trade and a design environment where prototypes can be tested and audited based on a set of design principles derived from international law and trade practices (Bons 1997). We hope that our approach and framework will not only help in the design process, but also in the formal verification process.

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Work is ongoing to include the main features offered by blockchain technology into the framework, in particular, the ability to witness transactions and the guaranteed execution of smart contracts. We are actively looking to set up experiments with parties in the logistics and trade finance chain, especially in an international setting. For instance, during a travelling conference with several Chinese universities in February 2017 (Oberheitmann 2017), we have identified a joint interest in working on such pilot projects and we are looking forward to extending our research in this direction with our partners abroad.

References Aeternity. (2017). Aeternity. aeternity.com. Accessed 29 Sept 2017. Austin, J. (1962). Speech acts—How to do things with words. Cambridge: Harvard University Press. Bons, R. (1997). Designing trustworthy trade procedures for open electronic commerce—The automated auditing of inter-organisational controls. Dissertation Rotterdam School of Management, Erasmus University, Self-published, Rotterdam. Bons, R., Lee, R. M., Wagenaar, R. W., & Wrigley, C. D. (1995). Modelling i­nter-organizational trade using documentary petri nets. Electronic Markets, 5(1), 189–198. https://doi. org/10.1080/10196789500000012. Diedrich, H. (2016). ethereum—Blockchains, digital assets, smart contracts, decentralized autonomous organizations (0.9.7.1). Sydney: Wildfire Publishing. Ethereum. (2017). ethereum. ethereum.org. Accessed 29 Sept 2017. Feltus, C., Petit, M., & Dubois, E. (2009). Strengthening employee’s responsibility to enhance governance of IT: COBIT RACI chart case study. In Proceedings of the first ACM Workshop on Information Security Governance, 23–32. ISO/IEC. (2015). Open-edi reference model (No. 14662:2010). https://www.iso.org/standard/55290.html. Accessed 23 Apr 2019. Kindergan, A. (2017). Is bitcoin safe? https://www.credit-suisse.com/corporate/en/articles/newsand-expertise/is-bitcoin-safe-201701.html. Accessed 29 Sept 2017. Lee, R. M. (1988a). A logic model for electronic contracting. Decision Support Systems, 4(1), 27–44. Lee, R. M. (1988b). International contracting—A formal language approach. In R. Sprague (Ed.), Proceedings of Hawaii International Conference on Systems Sciences (I/69–78). Lee, R. M. (1999). Automated generation of electronic procedures: Procedure constraint grammars. In Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. Lee, R. M., & Bons, R. W. H. (1996). Soft-coded trade procedures for Open-EDI. International Journal of Electronic Commerce 1(1), 27–49. http://www.jstor.org/stable/27750799. Accessed 23 Apr 2019. Linux Foundation. (2017). Hyperledger. https://www.hyperledger.org/. Accessed 29 Sept 2017. Nakamoto, S. (2008). Bitcoin: A Peer-to-peer electronic cash system. Www.Bitcoin.Org, https:// doi.org/10.1007/s10838-008-9062-0. Oberheitmann, A. (2017). DigiTrans CD—Chinese-German Contributions to digital transformation (in German). http://digitrans.fom.de/die-delegation.html. Accessed 23 Apr 2019. R3. (2017). R3. https://www.r3.com/. Accessed 29 Sept 2017.

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Ross, A. (2016). The industries of the future. New York: Simon & Schuster. Szabo, N. (1996). Smart contracts: building blocks for digital markets. EXTROPY: The Journal of Transhumanist Thought, (16), 18, p–2. Van der Torre, L. (1997). Reasoning about obligations: defeasibility in preference-based deontic logic. PhD Thesis, Erasmus University Rotterdam, published in Tinbergen Research Series nr. 140, Thesis Publishers Amsterdam. Wieczner, J. (2017). Bitcoin: Hacking coinbase, cryptocurrency’s “Goldman Sachs.” Retri. http:// fortune.com/2017/08/22/bitcoin-coinbase-hack/. Accessed 20 Juli 2017.

Part V Digitalization and Innovation

The Changing Role of SMEs in Innovation Activities in Germany–The Example of the Automobile Value-Added Chain

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Michael Rothgang and Wolfgang Dürig

Contents 18.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254 18.2 SMEs as Suppliers in the Automotive Industry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 18.2.1 Function, Structure and Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 18.2.2 Role of SMEs in Innovation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256 18.3 Challenges for SMEs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258 18.3.1 Market Power and Challenges in the Value Chain. . . . . . . . . . . . . . . . . . . . . . . . 258 18.3.2 Electro-Mobility and SMEs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260 18.4 A Possible Solution: A More Active Role of SMEs in Lightweight Forging . . . . . . . . . . 261 18.4.1 The Challenges of SMEs in the Forging Industry. . . . . . . . . . . . . . . . . . . . . . . . 261 18.4.2 Factors Preventing Technology Transfer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262 18.4.3 Possible Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263 18.5 Discussion and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266

Abstract

In the past, small and medium-sized Enterprises (SMEs) mostly have had a rather passive role in innovation processes of the automobile value chain. Although SMEs are involved in different sections of the value chain (mostly in positions that are further away from the Original Equipment Manufacturers), they mostly contribute to

M. Rothgang (*) · W. Dürig (*)  RWI–Leibniz Institut für Wirtschaftsforschung, Essen, Germany e-mail: [email protected] W. Dürig e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_18

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incremental improvements of the final product. We scrutinize the effects of the present challenges that the automobile industry in Germany faces (like increasing international competition or technological change) with a focus on the role of SMEs. In our analysis we find that the changes SMEs face in their environment can pose threats to their position in the value chain. One example is the growing importance of electric vehicles that jeopardizes the business strategies of SMEs that produce parts for the power train. However, we also find that these challenges induce firms to pursue a more active role in innovation processes that may benefit the long-term competitiveness of the industry. We display this development by looking at the massive forging industry that is an important SME dominated part of the automobile value chain.

18.1 Introduction For the German economy, the automotive industry plays an important role in terms of value added and employment. In addition to large manufacturers (OEMs and systems suppliers), a substantial number of small and medium-sized enterprises (SMEs) are part of the value chain, for example as suppliers of parts, engineering firms, or accessory specialists. With respect to market power and industry development, the big manufacturers dominate. The majority of SMEs is located at the lower end of the value chain. Often, their role has been denominated as workbench of the large firms in the industry. In recent years, the automotive industry (and especially SMEs in the value chain) are confronted with far-reaching challenges. The business strategies of SMEs are jeopardized by the internationalization of supply chains and new competitors from Asia. The combustion engines are under discussion due to their contribution to environmental pollution. Policy is pushing for a shift towards electro-mobility. In this contribution, we are going to focus on how these changes in the market and technology environment influence the position and behavior of SMEs. We ask how their contribution to innovation in the automotive sector can be characterized, and whether or not their role has changed over time. We furthermore scrutinize whether the perception of the passive role of SMEs is still correct or whether the present challenges induce them to capture a much more active role. Our analysis is based on several studies that were conducted in recent years. Core results have been obtained as part of an industrial collective research project; a research network on lightweight forming.1

1The

research has been financed by the Federal Ministry for Economic Affairs and Energy via the German Federation of Industrial Research Associations. Research associations involved are the Research Association for Steel Application (FOSTA), the Heat Treatment and Material Engineering Association (AWT), the Research Association for Drive Technology (FVA), and the Research Association of Steel Forming (FSV).

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Fig. 18.1  The automobile value chain. (Source own illustration based on Jürgens and Meißner 2005, p. 55. SME are mainly found in the darker colored areas)

The paper approaches as follows: in Sect. 18.2, the status of the automobile value chain and core trends in the industry are discussed. Section 18.3 scrutinizes the role of SMEs in the value chain. In Sect. 18.4, the consequences of the existing trends and the challenges for SMEs are scrutinized. In Sect. 18.5 we discuss our findings and conclude.

18.2 SMEs as Suppliers in the Automotive Industry 18.2.1 Function, Structure and Size As early as 2002, an average 65% of a vehicle was no longer manufactured by OEMs, but by suppliers of parts and systems (Weymann Consulting 2012). Several studies show that in a wave of outsourcing at the end of the eighties and in the early nineties, the share of value added produced by the suppliers substantially increased (Bratzel and Moritz 2010). The input-output tables for Germany show that the value-added share of production inputs from suppliers in different sectors reached 76.7% in 2013. While this share had increased from the middle of the 1990s (from 64% to 80%), it has decreased again since 2008, still being substantially larger than in the middle of the 1980s (Dehio et al. 2018, forthcoming). Important reasons for this longer-term trend towards outsourcing by OEMs are an increasing specialization in the value chain and the concomitant use of new components and materials. The OEMs take advantage of the flexibility of suppliers, their specialist knowledge and at the same time distribute the risks of production. The decrease since 2008 was partly driven by the goal of OEMs to bring back some competencies they had lost before. A shift in value added to the suppliers does not mean that SMEs have

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primarily increased in importance (Holz et al. 2016). Above all, mainly system suppliers have benefited from this development. At the same time, the car manufacturers have passed on the competitive pressure, to the downstream value chain, which has substantially affected SMEs. Figure 18.1 shows the value added chain, in which these developments took place. SMEs can be found in all parts of the supply chain, but predominantly in the dark colored fields. They are often to be found in research and development and in the production of tools, but also as suppliers of components, and in sales/repair. At least 50% of the supplying companies are SMEs according to the EU definition (Verband der Automobilindustrie 2017).2 The interaction of the individual players is crucial to the functioning of such a differentiated value chain. This is not only about the smooth and timely provision of services and components, but also about cooperation in the area of innovation. The car is, from a technical point of view, a rather complex product, which is produced in serial production in large quantities. Cooperation in the value-added chain guarantees high quality and constant improvements that meet consumer needs. Germany is the third largest car producer in the world after China and the USA. Its strong position is often traced back to the differentiated cooperation of the units in the value chain (Dietz 2015). At the same time, the German supply system has a special characteristic with respect to the role of SMEs: In addition to OEMs and large international suppliers, there are still nationally positioned suppliers (especially also SMEs) that primarily supply customers in Germany. They often follow a passive risk-mitigation strategy and trust their long-term business relationships. Among them, numerous suppliers work according to blueprints and specifications from their customers. These firms are faced with substantial changes in technology and market competition.

18.2.2 Role of SMEs in Innovation In the automotive industry, technological innovations are an important part of the competition. This can be seen in the large number of innovations that have found their way into the vehicles (Fig. 18.2, below the time axis). The most important innovations in the automotive sector address aspects like, function, driving safety, but also environmental requirements that lead to the development of a steady flow of innovations like particle

2These

firms have no more than 249 employees and sales of less than 50 million euros. In Germany, a different definition of SMEs is often used that comprises companies with up to 499 employees and up to 50 million euros in turnover. https://www.ifm-bonn.org/definitionen/kmu-definition-des-ifm-bonn/, 30.10.2017.

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Fig. 18.2  Innovation in the automobile value chain

filters for diesel engines, hybrid technology, or innovations that reduce fuel consumption (see Aigle and Marz 2010). At the same time, also process innovations have been implemented. During the last 15 to 20 years, production efficiency has been increased, leading to substantial rise in labor and total factor productivity. Continuing improvements and the use of robots has led to considerable changes in the production process. Between 2006 and 2015, real labor productivity has increased by 37%, by 52% in SMEs and 27% in large firms (Dehio et al. 2018). Therefore, the question arises, which role SMEs have played for innovations in this innovation system. Most of the innovations mentioned are systems innovations for which systems suppliers play an important role. SMEs only had a prominent role in the development of the market for GPS navigation. Systems suppliers need specialized knowledge provided by the medium-sized, supplying companies. Each component is not only subject to stringent quality criteria, but suppliers are also encouraged to participate in the optimization of the product. This is not least because OEMs precisely specify their requirements, but leave it to the supplying company to implement these requirements. Car manufacturers, therefore, pass the innovation and the cost pressure on to the suppliers along the value added chain. Most of the SMEs contribute to innovation by continuously improving their parts and at the same time increasing production efficiency. The smaller companies are the smaller is (at least on average) their capacity to carry out their own technical developments. We can also find possible obstacles to innovation for SMEs: they lack financial resources, they do not have the necessary staff, and they simply do not want to take the risk of going new ways.

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18.3 Challenges for SMEs 18.3.1 Market Power and Challenges in the Value Chain In the following, we highlight the challenges faced by SMEs in the automotive industry (see e.g. Berking et al. 2012 for an elaborated account). Major challenges are shown in Fig. 18.3 and discussed below. SMEs in the automotive value-added chain generally have little market power. This becomes obvious in the drafting of contracts. Thus, OEMs and systems suppliers are often able to dictate the terms of cooperation. One example is a worldwide availability of supply-products, which is demanded by the medium-term delivery obligation. For SMEs, this often poses a problem. In addition, the majority of medium-sized suppliers are confronted with increasing quality and cost requirements of OEMs, as foreseen productivity increases are already built into medium-term contracts. SMEs in the supply chain therefore often have problems to stay innovative as immediate cost pressure makes it attractive to reduce R&D activities. Of particular importance to SMEs in the value chain is also the competitive pressure to introduce new materials and product designs to production. In these cases, ­medium-sized companies have to make considerable efforts to implement new machinery and equipment.

cost and quality demands from customers

global availability of components

effect of new regulations (CO2,...)

challenges for the automobile industry

new materials and production processes

shift / changes in the value added chain

new competitors

two examples: 1. disruptive innovation: electromobility 2. initiative of SME firms: lightweight massive forging

Fig. 18.3  Challenges for SMEs in the automobile industry

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At the same time, new competitors are changing the established structure in some areas of the automotive value chain. This becomes obvious, for example, analyzing the production increase in assistance systems of motor vehicles, which are mainly supplied by firms of the electrical industry or computer science industry. Completely different competitors will be added in the course of the change of drive systems, i.e. by electro-mobility. This leads to the question as to what extent SMEs in the automotive value-added chain can succeed in securing their status by increasing their own R&D efforts. The oftentimes skeptical view that numerous medium-sized suppliers will not survive the current and future structural change is to counteract the fact that simply times of rapid change in the market and technology environment open up new market segments, in which SMEs can be successful. Because of the foreseeable challenges for SMEs, significant changes will probably take place in the value-added chain. However, it would be wrong to look at the challenges only from the perspective of a threat (see Fig. 18.4). Times of structural change are also always times for innovations. In many cases, e.g. for small and medium-sized enterprises, new market chances might arise. This is also true for firms from sectors that have not yet been close to the automotive industry. Strong forces (as those currently emerging) that promote change in the value added system, are calling into question existing sector delimitations. This is already visible in the automotive industry as IT companies and power suppliers are now discovering the market for themselves. By looking at the example of electro-mobility, we can observe how the market situation for SMEs is likely to change.

adjustments in the value added chain decreased demand for massive steel solutions, a segment with many SMEs

risks

pressure to innovate and adapt new requirements, competitors

development of new market segments innovative solutions in the energy supply infrastructure

consequences for SMEs

chances

contribution to value added and innovation new materials, component design

chances and risks for established SMEs, new ventures and firms from other markets like aviation and IT

Fig. 18.4  Consequences for SMEs in the automobile industry

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18.3.2 Electro-Mobility and SMEs Electro-mobility will lead to a restructuring of the automotive value chain (see Funk 2015). An electric drive vehicle eliminates many previously required components in the engine compartment (e.g. drive train, gearbox, exhaust system, cooling systems, etc.). The combustion engine consists of around 2500 parts, an electric motor of only about 250 (F. Geiger 2017). As a result, fewer suppliers are needed (see Lange 2014). At the same time, many components of a car with an internal combustion engine are also required to produce an electric vehicle (e.g. bodywork, seats, interior equipment, for an account of the major changes see Bauer et al. 2012, 2015). Figure 18.5 illustrates the potential effects of switching from electric mobility to SMEs in the automotive sector. Again, the areas with a strong SME stock are highlighted in the figure. This change creates considerable risks for such SMEs, whose components and supplies are no longer required for electrically powered vehicles. It is foreseeable that steel-processing companies in the automotive value-added chain will find it particularly difficult to maintain their market position. Some of the companies will be able to adapt to other products or components by moving the production profile. Others will try to open up new markets through innovation. At the same time, electro-mobility also creates opportunities for new ventures. In phases of innovative change, the area of R&D is of particular importance. Several smalland medium-sized engineering companies will participate to develop, investigate and test

changes in the value added chain

Research and Development, production of tools and production plants SMEs: tool producers, smaller development firms

raw material suppliers

producers of parts and components

system suppliers

SMEs: massive forging firms

SMEs: locking systems

OEMs (Original Equipment Manufacturers)

sales, trade/repair shops, recycling

value added chain of energy production and supply

facility mgmt., recycling SMEs: plastics recycling

effects along the value added chain • components are also necessary in the e-car (body), are not necessary any more (exhaust system) or completely different (powertrain) • new components (e-car)

Fig. 18.5  Consequences for SMEs in the automobile industry

SMEs are especially affected • as suppliers • when new market segments develop

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new technical solutions. Graduates from technical colleges are encouraged to start their own business. With the shift to electric mobility, logistics in the value chain are also changing. New procurement and distribution channels must be organized (see Funk 2017; Kampker et al. 2010). Here, too, new opportunities open up for SMEs. New or different parts for electric vehicles are needed. This also opens up opportunities for medium-sized companies. Large parts of the knowledge of SMEs in the supply chain are by no means completely devalued, but are adapted to new fields of application. Sales and Services in the automotive sector are strongly influenced by medium-sized companies. Workshops must adapt to new technologies. This is connected to equipment and tools that are geared to electric drives. In addition, the staff must be made familiar with the new technology. Even if there are significant challenges to the companies, there is a good chance that this area will continue to be characterized by medium-sized businesses. Electro mobility needs a corresponding infrastructure with electricity stations. This opens up new market opportunities for medium-sized companies. The change will certainly lead to existential problems of some suppliers, but at the same time new market opportunities will open up, in which small- and medium-sized enterprises can play their comparative advantages.

18.4 A Possible Solution: A More Active Role of SMEs in Lightweight Forging 18.4.1 The Challenges of SMEs in the Forging Industry This section scrutinizes one SME dominated industry in the value added chain of the automobile industry that is faced with special challenges with respect to market and technology development: The massive forging industry. We look at the strategies that firms in that industry choose in order to tackle these challenges. Metal forming is an important part of the automobile value added chain. Besides massive forming, there is also sheet metal forming that is dominated mostly by large firms and not regarded in our analysis. The massive metal/steel forging sector uses steel materials from steel mills and forms them for the use in different sectors, especially the automotive sector. This area of industry is mainly dominated by SMEs, although few large firms are present in the sector as well. Only a small part of the firms perform R&D by themselves. Others form product parts based on the specifications of their customers and do not maintain own R&D departments in order to improve product characteristics and quality. In the past, one characteristic feature of the sector has been the following: massive forging firms often have been in a rather inactive role in the value chain. It was rather difficult for them to push innovative materials or product designs, as their customers

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often wanted them to produce their products according to customers’ specifications. Over time, different challenges arose: • New competitors from abroad offered cheaper forging parts. • Other materials like aluminum competed with steel solutions. • There was a general trend to reduce the weight of automobiles in order to reduce fuel consumption and to improve the handling of the car. However, up to now the focus of lightweight design is on the body and other materials (using plastic and Aluminium). • Electric mobility challenges the business strategies for many of these firms, as much less massive steel parts are needed for electric vehicles. In answer to these challenges, the firms in that industry started an initiative for lightweight forging. The initiative identified the components that are relevant for massive lightweight forging (Busse et al. 2019): • It addresses components in powertrain, chassis; • these parts have a substantial share of the overall weight of an automobile (400 kg); • it is possible to substantially reduce the weight of these parts. Core idea of the initiative has been to become more active and innovative in order to improve technology transfer and—finally—to increase the competitiveness of that industry. However, there are also challenges for implementing lightweight solutions in the value added chain. These challenges, amongst others, are tackled by a research project that is funded by the Federal Ministry for Economic Affairs and Energy. This project increases knowledge transfer along the value added chain, contributes to the cooperation, and increases visibility of lightweight solutions.

18.4.2 Factors Preventing Technology Transfer Several problems have to be tackled when the firms in the forging industry try to increase their competitiveness by launching new lightweight solutions in the value added chain (see also Rothgang et al. 2017). The analysis of these problems in this section is based on (a) a written survey of firms from the total value added chain (from steel plants up to OEMs) on lightweight forging and technology transfer mechanisms3 and (b) interviews with firm representatives on the same topic. Figure 18.6 shows the assessment of the probability that different kinds of factors prevent the implementation of lightweight solutions in the value-added chain.

3The

results are taken from a survey of firms that participate in the research network that addressed 64 firms. 39 questionnaires were completed and could be used (return rate of 60%).

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numerous possible obstacles in development / materials, production and costs / customer too high production costs for products of massive lightweight construction lack of knowledge about the design with alternative materials development costs cannot be passed on to the price lack of knowledge about (long-term) material properties capacities or knowledge in the development are not sufficient lack of experience with process properties technical testing is too complex

45%

50%

55%

60%

65%

Fig. 18.6  Barriers in the value chain: The view of firms in the automotive value chain. (Source standardized survey of companies from the accompanying committees of the massive forging Project, Q 7: n = 38)

The assessment is done by not only forging firms but also by representatives from firms in other parts of the value added chain that are involved in the development of lightweight solutions. The firms named much more factors from the market side as well as research and production than the ones mentioned in Fig. 18.6. Only factors are displayed that were assessed to be (very) probable by more than 50% of the answering firms. As it was to be expected in the context of the survey, many firms (actually more than 60%) see production cost as a very important obstacle when implementing lightweight solutions. However, other factors have to do with characteristics of the value added chain or the knowledge base of the firms. Examples are a lack of knowledge about the design using alternative materials or about specific process properties, and/or too complex and costly methods of technical testing. Overall, we see that there are multiple possible obstacles for innovation within the organizations involved in the innovation and production process. The situation still becomes somewhat more difficult as the value added chain for many massive forging parts is quite long, which means that there are many points in the value added chain where problems in knowledge transfer can possibly arise.

18.4.3 Possible Solutions In order to identify possible solutions to the challenges, the firm representatives were asked to name the factors, which determine the implementation of lightweight solutions

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25 20 15 10 5 0 costs / economics

communication with customers in the process chain

technical problems

costs and availability of the materials

costs of competition production / with other organisation materials / problems competition in the industry

legal regulations

overcoming of accustomed processes

Fig. 18.7  Determinants of implementation of solid lightweight construction in motor vehicles. (Source standardized survey of companies from the accompanying committees of the massive forging project, Q 9: n = 35. Respondents mentioned up to 3 factors, which decide on the future use of massive lightweight solutions)

(Fig. 18.7). To be precise, the representatives were asked to name up to three factors that possibly decide on the future use of solutions in the field of massive lightweight construction in the automotive industry. As was to be expected, cost and economic factors were named by the largest share of the firms (23%). However, communication problems were named at second rank (21% of the respondents) even before technical problems. This shows that there are problems that could possibly be overcome by a better coordination and common precompetitive efforts to overcome factors that prevent innovation. In addition, several other factors were mentioned that partly have to do with ­industry-external factors (legal regulations), partly with firm-internal processes (overcoming accustomed processes), or technical determinants (technical problems, competition with other materials). Overall, this account shows that there are important factors that can be overcome by a common effort and by taking on a more active role in innovation activities.

18.5 Discussion and Conclusions Finally, we relate the results of our discussion on the changing role of SMEs in the automobile value chain to the theoretical and empirical knowledge in innovation research on the different possible roles of SMEs and draw general conclusions on the changing role of SMEs and the possibilities that they possess.

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In innovation research, a distinction is drawn between different innovation regimes (e.g. Audretsch 1997; Malerba and Orsenigo 1995). An entrepreneurial regime is characterized by open structures and the parallel existence of different technological solutions. SMEs have the possibility to be successful by bringing forward new solutions and by acquiring a segment of the new market share and—in case they are successful—by establishing themselves in a settling market at a later stage. In a routinized regime, on the other hand, one technological solution has prevailed and competition is about being successful in increasing productivity and realizing economies of scale. SMEs are integrated into value chains (often in a much more backward position), their competition being characterized by a strict orientation towards cost. In many discussions, these different regimes are connected with various phases of market development, the initial phase being characterized by an entrepreneurial regime and the latter phase by a routinized regime. This is the core idea of industry life cycles. However, as it turns out, this type of dynamic innovation pattern can mainly be observed in some consumer product markets (Münter 1999). In the automobile industry, innovation characteristics have partly “changed back” from a routinized towards an entrepreneurial regime. This development is due to changing demands of customers and society, new regulations, and at the same time new technological possibilities (e.g. ecological and automated driving). These changes in the innovation regime have led to challenges and risks for different kinds of SMEs: • Incumbents, i.e. firms that are already in the value chain face the risk that their role in the value chain is in danger (e.g. the parts they produce will eventually not be needed anymore). At the same time, they have the chance to become more active in innovation processes and develop new products (either in the automobile value added chain or within other markets like mechanical engineering). • New ventures have the possibility to address new demands in the value chain. One example might be electro scooters that have been developed by involving some SMEs in the area of Aachen together with the city’s university (RWTH Aachen) and the “Deutsche Post”.4 The chances and risks faced by established SMEs become transparent if we look at the forging firms and the development of the market and the industry initiative of lightweight forging. Our example also shows how important precompetitive public R&D project funding by the programme for industrial collective research can be for SMEs in developing a new role in the value added chain. As these examples show, the value added chain of the automobile industry has developed from a routinized regime towards an entrepreneurial regime. It can be described

4https://www.streetscooter.eu/,

October 26, 2017.

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as a “living organism”, which combines continual improvement, new applications, and change. SMEs are able to gain a more active role in innovation, if they are successful in filling new market segments. However, there is also a danger that their value added can possibly also become obsolete. This concerns established firms that have the opportunity to gain competitiveness by increasing their innovation activities. However, it also concerns start-ups, or firms from other markets, that have the possibility to establish themselves as suppliers in the automobile value added chain. What does this mean for the role of SMEs in other sectors of the economy? Surely, the automotive industry is a special case in that SMEs have been integrated into a rather rigid value added chain in the past. However, also in other sectors like machinery, developing markets and new technological trends (like the ever-increasing importance of information and communication technologies) pose challenges to SMEs and tend to spur traditional production networks.

References Aigle, T., & Marz, L. (2010). Automobilität und Innovation – Ein interdisziplinärer Überblick über das Innovationsverhalten in der Automobilindustrie. Sachverständigentag am 1. und 2. März 2010 in Berlin. https://www.vdtuev.de/svt-archiv/svt2010/downloads/5_Dr_Aigle.pdf. Accessed 20 Nov 2017. Audretsch, D. B. (1997). Technological regimes, industrial demography and the evolution of industrial structures. Industrial and Corporate Change, 6(1), 49–82. Bauer, W., Borrmann, D., Brand, M., Dispan, J., Frieske, B., Herrmann, F., et al. (2012). Elektromobilität und Beschäftigung. M. Wirkungen der Elektrifizierung des Antriebsstranges auf Beschäftigung und Standortumgebung (ELAB). Stuttgart: Fraunhofer. Bauer, W., Borrmann, D., Brand, M., Cacilo, A., Dungs, J., Herrmann, F., et al. (2015). Strukturstudie BWe mobil 2015. Elektromobilität in Baden-Württemberg. Stuttgart: e-mobil BW GmbH & Fraunhofer – IAO, Ministerium für Finanzen und Wirtschaft Baden-Württemberg. Berking, J., Borreck, M., Bosser, T., Duckwitz, M., Gong, L., Juckenack, S., et al. (2012). FAST 2025 – Future automotive industry structure. Berlin: VDA e. V. Bratzel, S., & Moritz, A. (2010). Erfolgsfaktoren der Automobilzulieferer im Zeichen der Krise. In A. G. Concentro Management (Ed.), Concentro turnaround investment guide (pp. 131–144). Köln: Finanzierung in der Unternehmenskrise. Busse, A., Dehio, J., Dürig, W., Neipp, C., Zoch, H. W., & Tinscher, R. (2019). Gemeinsamer Abschlussbericht der Leittechnologievorhaben 24 LN und 25 LN des Forschungsverbundes „Massiver Leichtbau – Innovationsnetzwerk für Technologiefortschritt in Bauteil-, Prozess- und Werkstoff-Design für massivumgeformte Bauteile der Automobiltechnik“. Aachen: Institut für Werkstofftechnik & RWI-Leibniz-Institut für Wirtschaftsforschung. Dehio, J., Rothgang, M., & Stiebale, J. (2018). Langfristentwicklung von Innovation und Produktivität. Fachlos 1: Sektor-Fallstudien. Studie im Auftrag der Expertenkommission Forschung und Innovation (EFI), forthcoming. Dietz, W. (2015). Mittelständische Automobilzulieferer – Chancenpotenziale und strategische Optionen. Zuliefertag Baden-Württemberg am 12. November 2015. Stuttgart.

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Funk, W. (2015). Herausforderungen der E-Mobility für das Schnittstellenmanagement der Automobilhersteller (OEM). In H. Proff (Ed.), Entscheidungen beim Übergang in die Elektromobilität (pp. 71–82). Wiesbaden: Springer. Funk, W. (2017). Blickpunkt Automobilzulieferer: Wirkungen der E-Mobility auf die Unternehmensführung und das Controlling der Automobilzulieferer. In Proff, H., & Fojcik, T. M. (Eds.) Innovative Produkte und Dienstleistungen in der Mobilität. Wiesbaden: Springer. https://doi.org/10.1007/978-3-658-18613-5_11. Geiger, F. (2017). Automobilzulieferer vor Megawandel durch E-Mobilität! Wer gewinnt, wer verliert? Godmode-Trader.de, https://www.godmode-trader.de/analyse/automobilzulieferer-vormegawandel-durch-e-mobilitaet-wer-gewinnt-wer-verliert,5393382. Accessed 25 Sept 2019. Holz, M., Nielen, S., Paschke M., Schröder, C., & Wolter, H.-J. (2016). Globale Vernetzung, Kooperation und Wertschöpfung im Mittelstand. IfM-Materialien 252. Bonn: Institut für Mittelstandsforschung (IfM). Jürgens, U., & Meißner, H.-R. (2005). Arbeiten am Auto der Zukunft – Produktinnovationen und Perspektiven der Beschäftigten. Berlin: Sigma-Verlag. Kampker, A., Burggräf, P., & Deutskens C. (2010). Produktionsstrukturen für Komponenten künftiger Elektrofahrzeuge. ATZ.prod, Heft 3, 48 f. https://doi.org/10.1007/bf03224133. Lange, E. (2014). Elektromobilität – Zulieferer im Wandel. Industrieanzeiger, 2014(28), 13. Malerba, F., & Orsenigo, L. (1995). Schumpeterian pattern of innovation. Cambridge Journal of Economics, 19, 47–65. Münter, M. T. (1999). Wettbewerb und die Evolution von Industrien: Schriften zur Nationalökonomie, Bd.  25. Bayreuth: Verl. für Nationalökonomie, Management und Politikberatung (NMP). Rothgang, M., Dehio, J., & Dürig, W. (2017). Innovation transfer of lightweight forging solutions in the automobile value added chain. Paper presented at the conference Steel in Cars and Trucks, Amsterdam, June 18–22. Verband der Automobilindustrie. (2017). Zahlen und Daten. https://www.vda.de/de/services/ zahlen-und-daten/zahlen-und-daten-uebersicht.html. Accessed 22 Nov 2017. Weymann Consulting. (2012). Future automotive industry structure 2025 (Bd. 45). Materialien zur Automobilwirtschaft Frankfurt a. M.: VDA.

A Research on Total Rewards, Labor Productivity and Labor Absorption of Non-State-Owned Manufacturing Enterprises in China

19

Chen Hong and Yang Junqing

Contents 19.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 19.2 Literature Review and Research Hypothesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 19.2.1 Total Rewards. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 19.2.2 Total Rewards and Labor Absorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272 19.2.3 Total Rewards and Labor Productivity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 19.2.4 The Mediating Effect of Labor Productivity on Total Rewards and Labor Absorption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 19.3 Research Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 19.3.1 Samples and Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 19.3.2 Variables Measurement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 19.4 Data Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 19.4.1 Discriminant Validity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 19.4.2 Common Method Bias and Descriptive Statistics. . . . . . . . . . . . . . . . . . . . . . . . 277 19.4.3 Hypothesis Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 Acknowledgements: We appreciate the support of the National Natural Science Foundation of China for the project (71373149) of Research on the Remuneration, Profit and Labor Absorption of Non-State-Owned Enterprises in China—Transformation of Management Method in Non-State-Owned Enterprises and the Development of Basic Theory about Labor and Employment. H. Chen (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] J. Yang (*)  Shanxi University of Finance & Economics, Taiyuan, China e-mail: [email protected] © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 A. Oberheitmann et al. (eds.), German and Chinese Contributions to Digitalization, FOM-Edition, https://doi.org/10.1007/978-3-658-29340-6_19

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19.5 Conclusion and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 19.5.1 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 19.5.2 Research Significance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 19.5.3 Limitations and Prospect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

Abstract

With the gradual disappearance of the old demographic dividend, the ­non-state-owned manufacturing enterprises in China have experienced more serious labor shortage and the low labor cost advantage has become unsustainable. Coupled with the transformation and upgrading of the manufacturing industry, the demand for h­ igh-quality labor has increased and the salary increase has become inevitable. However, the management practice of non-state-owned manufacturing enterprises fails to inspire employees with salaries which leads to the decline of employees’ work enthusiasm and frequent labor conflicts, making it more and more difficult to attract, motivate and retain employees. Therefore, it has become an urgent problem for the ­non-state-owned manufacturing enterprises to motivate employees and absorb labor force effectively. The concept of Total Rewards extends compensation to all elements of value to employees, including economic and non-economic areas. In accordance with the theory of Efficiency Wages and the concept of Total Rewards, the mediation effect of labor productivity on the five factors of total rewards and labor absorption has been verified by analyzing 494 questionnaires from 71 non-state-owned manufacturing enterprises. As a result, the analysis shows that the implementation of Total Reward management can motivate employees’ enthusiasm and creativity, and improve the labor productivity of enterprises, which results in better labor absorption of the enterprises. Consequently, it is recommended that non-state-owned manufacturing enterprises should transform the management philosophy, conduct humanistic management and carry out personalized total rewards management.

19.1 Introduction By the end of 2016, the manufacturing sector had the largest number of employees in all urban units in China, accounting for 27.36%.1 But for a long time, the non-state-owned manufacturing enterprises in China have gained an international comparative advantage of sufficient labor force and low labor costs (Qu 2010). As the old demographic divide gradually disappears and manufacturing enterprises gradually transform and

1National

Bureau of Statistics of China, http://www.stats.gov.cn/tjsj/ndsj/2017/indexch.htm.

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upgrade under the new normal, there is a shortage in demand for unskilled workers and an increased demand for skilled workers, which results in a serious labor shortage (Ling 2015). The Investigation Report on Turnover and Salary Adjustment of 2016 (investigation of 51 professions) indicates that the turnover rate of manufacturing employees is as high as 20.9%,2 ranking top place of all industries. Thus, the imbalance between labor supply and demand, lack of working enthusiasm and a high turnover rate have become the salient issues facing non-state-owned manufacturing enterprises in China. We can find an explanation taking over the managerial perspective: the management mode of “lower wages—increasing profits—enlarging capital accumulation—absorbing labor force” (Yang 2010)—implemented by non-state-owned manufacturing enterprises in China in the long run, which takes pay merely as a cost and consequently fails to inspire labors by salaries—subsequently leads to the loss of working enthusiasm and frequent labor conflicts. Even if the enterprises are aware of the incentive role of wages, they do not pay much attention to the diverse needs of employees in practice and thereby, despite raising the wages, do not achieve a high employee satisfaction or enthusiasm. With the economy entering the new normal, talents and human capital are playing an increasingly important role in the development of enterprises, and human resources advantages have become an important source of core competitiveness. Employees, especially the generation of the post 1980s, are more individualized and diverse in demand (Wen and Zhou 2015; Liu 2005). With the rise of sense of entitlement, the employees’ reservation wages are constantly increasing and there is a higher demand and preference for self-actualization (He 2003). Hence it grows into an important issue to have a concept of how to attract, motivate and retain employees and establish harmonious labor relations, so that a win-win situation for the employees, the enterprises and society can be achieved. Based on the idea of Efficiency Wages and the Total Rewards theory by WorldatWork, this chapter explores to build a new model of Total Rewards, labor productivity and labor absorption, so that we can realize harmonious labor relations and provide a new path for macro employment from the perspective of micro management (Rogers and Marcotte 2010).

19.2 Literature Review and Research Hypothesis 19.2.1 Total Rewards In 2006, the WorldatWork proposed a second-edition Total Reward model after revising its first edition in 2000. In the new model, total rewards refer to monetary or ­non-monetary return that is issued to employees in exchange for their time, talent, effort,

2Chinese

shtml.

Social Science Net, http://www.cssn.cn/dybg/gqdy_sh/201512/t20151223_2796105.

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and outcome. It includes five factors: compensation, benefits, work-life balance, performance and recognition, as well as development and career opportunities (Rogers and Marcotte 2010). As the latest wage theory in business management, the Total Rewards model has received great attention since it was put forward in the 1970s. It shifts emphasis from the employers to the employees and pays more attention to the incentive function of noneconomic rewards such as employees’ psychological income, and consequently coordinated the interests of enterprises and employees in a better way. It makes the compensation management of a company more flexible, which is a great advantage of Total Rewards. Compared to common salary systems, it also includes more dimensions of the human environment, and thus takes the comprehensive needs of employees into account. Only by changing the compensation management structure, employee satisfaction and business performance are concurrently improved without increasing the salary budget.

19.2.2 Total Rewards and Labor Absorption The adverse selection model of Efficiency Wages (Malcomson 1981; Stiglitz 1975; Weiss 1980) suggests that, as a signal or screening mechanism, efficiency wages will automatically screen employees who work hard and efficiently, while employees with low efficiency or low enthusiasm will not choose such an enterprise. Yao’s research suggests that enterprises that provide efficiency wages can motivate employees and reduce turnover. Furthermore they can cultivate employees’ sense of loyalty and redouble their efforts (Yao and Li 2004). At the same time, when compensation and benefits are guaranteed, a reasonably designed pay grade and salary-raising policies based on performance and capabilities can improve employees’ pay satisfaction, and thus reduce their turnover intention (Chen 2010). The enterprise that implements total rewards management is itself an enterprise that embraces the concept of “humanistic management”. It respects the initiative and creativity of its employees and shows concern about their career development and capability upgrading. Moreover, the company takes the needs of employees’ work and life fully into account and shares the achievement with the employees. In this way, the enterprise has a strong retention ability for internal employees and a higher attraction ability for external employees. We thus formulated hypothesis one: the Total Rewards perception of employees of non-state-owned manufacturing enterprises will have positive effects on the labor absorption of the enterprises. That is, in more specific terms, the employees’ perception of h1a) compensation, h1b) benefits, h1c) work-life balance, h1d) performance and recognition, and h1e) the development and career opportunities of the enterprises will positively affect the labor absorption of the enterprises.

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19.2.3 Total Rewards and Labor Productivity According to the Efficiency Wage theory, the labor productivity is an important guarantee for an enterprise to promote internal management efficiency. Only the efficiency improvement of internal production and management can achieve the goal of maximizing profits. As the labor productivity mainly depends on the allocation and utilization of the labor resources, it will help boost the labor productivity when providing employees with competitive and motivating compensation packages (Fan 2009). Yang’s empirical research in the coal resources area shows a positive correlation between the wage level, pension insurance, and the labor productivity (Yang et al. 2014). As a major factor affecting the well-being of employees (Li et al. 2015), a solid ­work-life balance must be named, which enables employees to work more happily and thus much more effectively. Development and career opportunities set clear goals for employees and provide them with a path to achieve these goals. As a result, development and career opportunities could play a good incentive role for employees, and help them to improve their labor productivity on their own initiative. According to the equity theory, a clear payroll system and a fair and reasonable performance appraisal system will enhance the perceived fairness of employees, increase their work enthusiasm, and consequently bring about a higher labor productivity. At the same time, recognition based on performance or contributions of employees will enhance their self-efficacy and creativity concurrently (Zhang and Long 2013), which will bring about the boosting of labor productivity. Hence, all the Total Rewards factors, i.e. compensation, benefits, work-life balance, performance and recognition as well as development and career opportunities, can satisfy the various needs of the employees and motivate them to improve their labor productivity. On these grounds, hypothesis two was formulated stating that the Total Rewards perception of employees of non-state-owned manufacturing enterprises will have positive effects on the labor productivity of the enterprises. That is, namely, the employees’ perception of h2a) compensation, h2b) benefits, h2c) work-life balance, h2d) performance and recognition, and h2e) the development and career opportunities of the enterprises will positively affect the labor productivity of the enterprises.

19.2.4 The Mediating Effect of Labor Productivity on Total Rewards and Labor Absorption As mentioned earlier, the total rewards perception of employees positively influences the enthusiasm and creativity of employees, and improves their job security and work ­well-being. In return, it also raises the human capital and promotes the labor productivity of enterprises, as well as it simultaneously builds harmonious labor relations and reduces the turnover rate of employees, which is beneficial for the enterprises to absorb labor better. Furthermore, enterprises with higher labor productivity are more likely to expand

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compensation benefits work-life balance performance & recognition development & career opportunities

labor productivity

labor absorption

Total Rewards

Fig. 19.1  A model of the relationship between total rewards perception, labor productivity and labor absorption

and hire more employees. And when a specific enterprise with higher labor productivity has acquired excess profit, it’s more probable for it to expand to absorb more labor force. Accordingly, hypothesis three states that labor productivity has mediated the total rewards perception of employees and the labor absorption of the enterprises. That is, specifically, the labor productivity has mediated the perception of h3a) compensation, h3b) benefits, h3c) work-life balance, h3d) performance and recognition, and h3e) the development of career opportunities and of the labor absorption of the enterprises. In brief, the hypothesis concerning the relations of total rewards perception, labor productivity and labor absorption of non-state-owned enterprises can be summarized as illustrated by the model in Fig. 19.1.

19.3 Research Design 19.3.1 Samples and Procedures In the research project supported by the National Natural Science Foundation of China, which is the basis of this article. The group members collected questionnaires from 30 provinces across China. The samples are non-state-owned enterprises, namely all kinds of enterprises except state-owned and controlling share hold enterprises. The respondents are the in-service employers of these enterprises. The investigators conducted on-site guidance when filling in the questionnaires and then collected anonymous questionnaires on the spot. Eventually, 1617 copies of valid questionnaires were collected, accounting for 65.46% of all the samples, including 494 employee samples from 71 manufacturing enterprises. Among the 71 companies, limited liability companies, incorporated companies, sole proprietorship enterprises, and partnership enterprises respectively account for 39.4%, 43.7%, 4.2%, and 8.5%. The average age of the investigated companies is 15 years.

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Among the respondents, the male account for 64.3%, and urban residents account for 63.7%, and employees born after 1980 take a proportion of 63%. As to the educational background, employees who attended the junior middle school or below, senior middle school, junior college or higher vocational education, and acquired an undergraduate degree and above respectively account for 14.1%, 26.9%, 24.2%, and 34.8%. The production workers account for 26.4%, and the marketers for 22.5%. The median of the monthly employee income is 3900 yuan.

19.3.2 Variables Measurement Total Rewards. According to the Total Rewards theory of WorldatWork and the Total Rewards perception scale of Yang (Yang and Yang 2015), the five dimensions of Total Rewards are considered to be compensation, benefits, work-life balance, performance and recognitions, as well as development and career opportunities. The sample items are as follows: • • • • •

the salary increases year by year, my company fully covers social insurance for employees, employees’ holidays rest time can be guaranteed, the assessment criteria are easy to achieve, and my company supports further training.

The Cronbach’s Alpha of each dimension is respectively 0.798, 0.785, 0.866, 0.861, 0.923, which denotes the high internal consistency of the scale. Labor productivity: With reference to the performance evaluation scale of Tsui (Tsui et al. 1997) and Li (Li and Yan 2007), four items are used to measure labor productivity, such as the productivity of the employees of a company. Also, the Cronbach’s Alpha of 0.815 indicates a high internal consistency. Labor absorption: Three items are used to measure the labor absorption in reference to Batt (Batt and Colvin 2011) and Ni (Ni et al. 2013). An example of such an item is the increase of the company’s personnel. The Cronbach’s Alpha of 0.772 signifies a high internal consistency. The variables above are all evaluated by the employees, and the average of each variable is summed up to the construct of enterprise-level. The between-group variance of each variable is significant (as shown in Table 19.1) when aggregating. It is thus assumed that there are enough differences between groups of each variables. Therefore, it appears appropriate to aggregate the employees’ perception of Total Rewards, labor productivity, and labor absorption to the enterprise level.

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Table 19.1  Significance analysis of the between-group variance of each variable at enterprises level Sum of squares DC

Mean square

F

Significance

216.735

70

3.096

18.643

0

70.252

423

0.166

Total

286.988

493

Between group

129.162

70

1.845

9.645

0

80.922

423

0.191

Total

210.084

493

Between group

174.012

70

2.486

12.288

0

85.573

423

0.202

Total

259.586

493

Between group

115.289

70

1.647

8.979

0

0.183 11.168

0

7.521

0

7.286

0

Between group Within group

PA

Within group WL

Within group P

Within group B

PL

77.592

423

Total

192.881

493

Between group

253.232

70

3.618

Within group

137.025

423

0.324

Total

390.257

493

Between group

104.193

70

1.488 0.198

Within group L

df

83.715

423

Total

187.908

493

Between group

116.061

70

1.658

96.254

423

0.228

212.315

493

Within group Total

The abbreviations DC, PR, WL, P, B, PL, and L in this table represent, respectively, development and career opportunities, performance and recognition, work-life balance, compensation, benefits, labor productivity, and labor absorption

19.4 Data Analysis 19.4.1 Discriminant Validity The discriminant validity analysis in Table 19.2 shows that all indicators of the ­seven-factor model are significantly better than other models, and all the indexes are in accordance with the statistical requirements. In addition, compared to the competition model, the smallest AIC of the seven-factor model also reveals the best fitting effect, and it is still reliable for seven exogenous factors.

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Table 19.2  The discriminant validity of each variable χ2

df

χ2/df

RMR

RMSEA

GFI

NFI

CFI

AIC

897.575

384

2.337

0.01

0.073

0.927

0.942

0.966

1054.368

Six-factor 904.368 model

390

2.319

0.009

0.098

0.923

0.937

0.966

1059.575

Fourfactor model

996.423

399

2.497

0.012

0.134

0.884

0.908

0.937

1128.423

Threefactor model

1001.463

402

2.491

0.036

0.145

0.576

0.596

0.715

1127.463

Twofactor model

1001.726

404

2.48

0.042

0.146

0.541

0.555

0.669

1123.726

Onefactor model

1034.739

405

2.555

0.042

0.149

0.531

0.538

0.651

1154.739

Sevenfactor model

“+” indicates that two factors are combined into one, and the seven-factor model stands for DC, PR, WL, P, B, PL, and L; the six-factor model stands for DC, PR, WL, P, B, and PL+L; the four-factor model stands for DC+PR+WL, P+B, PL, and L; the three-factor model stands for DC+PR+WL, P+B, and PL+L; the two-factor model stands for DC+PR+WL+P+B and PL+L; while the one-factor model stands for DC+PR+WL+P+B+PL+L. The sample size is 71, and the abbreviations used are the same as in Table 19.1

19.4.2 Common Method Bias and Descriptive Statistics Since both, the independent and the dependent variables of the questionnaire, originate from the self-reporting of the respondents, it is probable that this causes common method bias, which reduces the research validity. Exploratory factor analysis is conducted on compensation, benefits, work-life balance, development and career opportunities, performance and recognition, labor productivity and labor absorption. The first factor without rotation is saved as a new variable, and then a partial correlation analysis is carried out after controlling this variable. As the partial correlation shows in Table 19.3, there was a statistically significant correlation between the five factors of Total Rewards and labor productivity, labor productivity and labor absorption. Therefore, we can infer that there is no serious common method bias, and we can proceed to perform the correlation and regression analysis. At the same time, Table 19.3 also shows the mean, standard deviation and correlation coefficient of each variable. We can see that compensation (ß = 0.599, p