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Measuring the Dynamic Efficiency of Regional Industrial Green Transformation in China

Jinpeng Fu (), Guirong Xiao (), Lingling Guo () and Chunyou Wu ()
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Jinpeng Fu: Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China
Guirong Xiao: Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China
Lingling Guo: Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China
Chunyou Wu: Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China

Sustainability, 2018, vol. 10, issue 3, 1-19

Abstract: The green concept has become one of the key demands of the current era of development in China. As an attempt to cope with climate change and constraints of resources and environment, the industrial green transformation is bound to have a dramatic impact on the whole society. This paper enriches the understanding of industrial green transformation by highlighting its social attributes. Combining a hybrid model with a window analysis, this paper measures the dynamic efficiency of regional industrial green transformation in China from 2006 to 2015. In general, Beijing, Tianjin, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong and Guangdong obtain the best performance; industrial water use has the lowest and most unstable efficiency among various resources. Tobit regression model, thereafter, is used to analyze the impact of hypothetical factors on the efficiency of industrial green transformation. The findings demonstrate that reduction and lean management of state-owned property, promoting the development of the productive service industry, minimizing the proportion of fossil energy use and establishing an excellent economic basis can have nationally positive impacts on the regional industrial green transformation; the progress of the productive service industry is the key to industrial green transformation in Eastern China, while the internal optimization of the industrial sector should be paid more attention in other regions, especially in Western China. Finally, detailed discussions and policy suggestions at a regional level as well as research prospects are given.

Keywords: industrial green transformation; efficiency; influencing factors; industrial policy; China; Data Envelopment Analysis (DEA) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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