Spatiotemporal evolution characteristics and influencing factors of China’s interprovincial industrial green efficiency based on the super-efficiency SBM model

With the rapid development of the economy and excessive resource consumption, improving industrial green efficiency is a crucial pathway to achieving sustainable industrial development. Based on the super-efficiency SBM model and using provincial panel data from 2005 to 2022, this study measures China’s industrial green efficiency index. It constructs an indicator system with 36 specific indicators selected from seven dimensions: industrial governance, economic foundation, factor input, technological efficiency, environmental governance, natural factors, and pollutant emissions. The study employs the geographical detector method to conduct an in-depth analysis of the driving effects of industrial green efficiency. The key findings are as follows: (1) Since 2005, China’s industrial green efficiency index has exhibited an initial increase followed by a slight decline, dropping from 0.668 to 0.623. (2) The pace of China’s green transition has been gradually accelerating, yet significant disparities in green efficiency indices remain among provinces, with particularly pronounced gaps between the developed eastern regions and the underdeveloped western regions. (3) The Moran’s Index indicates that 77.4% of China’s provinces show a positive spatial correlation between their industrial green efficiency and that of neighboring provinces, with this proportion on the rise. Strong spatial clustering is observed in Shanghai, Zhejiang, and Fujian, while spatial dispersion is noted in Hebei and Guangdong. (4) Industrial governance has the most significant driving effect on industrial green efficiency, followed by economic foundation (1.153), factor input (0.772), technological efficiency (0.637), environmental governance (0.567), natural factors (0.338), and pollutant emissions (0.239). (5) At present, economic development, industrial upgrading, capital investment, and green finance are the key driving forces behind industrial green efficiency. The negative impact of pollutant emissions has been gradually decreasing, while the role of technological innovation, though important, has shown a marginal diminishing trend in the later stages. Additionally, the digital economy’s contribution to industrial green efficiency has been steadily increasing.

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Journal
Frontiers in Environmental Science
Published
2025-10-21
DOI
https://doi.org/10.3389/fenvs.2025.1625233
Primary Topic
Energy, Environment, Economic Growth
Type
article
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article

Spatiotemporal evolution characteristics and influencing factors of China’s interprovincial industrial green efficiency based on the super-efficiency SBM model

Shanshan Ye, Ruibin Xu, Jinyu Wang
Frontiers in Environmental Science
Energy, Environment, Economic Growth
article

Spatiotemporal evolution characteristics and influencing factors of China’s interprovincial industrial green efficiency based on the super-efficiency SBM model

Shanshan Ye, Ruibin Xu, Jinyu Wang
article en

Abstract

With the rapid development of the economy and excessive resource consumption, improving industrial green efficiency is a crucial pathway to achieving sustainable industrial development. Based on the super-efficiency SBM model and using provincial panel data from 2005 to 2022, this study measures China’s industrial green efficiency index. It constructs an indicator system with 36 specific indicators selected from seven dimensions: industrial governance, economic foundation, factor input, technological efficiency, environmental governance, natural factors, and pollutant emissions. The study employs the geographical detector method to conduct an in-depth analysis of the driving effects of industrial green efficiency. The key findings are as follows: (1) Since 2005, China’s industrial green efficiency index has exhibited an initial increase followed by a slight decline, dropping from 0.668 to 0.623. (2) The pace of China’s green transition has been gradually accelerating, yet significant disparities in green efficiency indices remain among provinces, with particularly pronounced gaps between the developed eastern regions and the underdeveloped western regions. (3) The Moran’s Index indicates that 77.4% of China’s provinces show a positive spatial correlation between their industrial green efficiency and that of neighboring provinces, with this proportion on the rise. Strong spatial clustering is observed in Shanghai, Zhejiang, and Fujian, while spatial dispersion is noted in Hebei and Guangdong. (4) Industrial governance has the most significant driving effect on industrial green efficiency, followed by economic foundation (1.153), factor input (0.772), technological efficiency (0.637), environmental governance (0.567), natural factors (0.338), and pollutant emissions (0.239). (5) At present, economic development, industrial upgrading, capital investment, and green finance are the key driving forces behind industrial green efficiency. The negative impact of pollutant emissions has been gradually decreasing, while the role of technological innovation, though important, has shown a marginal diminishing trend in the later stages. Additionally, the digital economy’s contribution to industrial green efficiency has been steadily increasing.

Frontiers in Environmental ScienceVol. 13
Beijing Technology and Business University (CN), Ministry of Natural Resources (CN), Shaoguan University (CN), Ministry of Water Resources of the People's Republic of China (CN)
Openalex Percentile: Top 61%
Energy, Environment, Economic Growth
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