Efficiency Evaluation and Influencing Factors of Green Innovation in Chinese Resource-Based Cities: Based on SBM-Undesirable and Spatial Durbin Model

Yaguai Yu, Zanzan Xu, Panyi Shen (), Lening Zhang and Taohan Ni
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Yaguai Yu: Business School, Ningbo University, Ningbo 315211, China
Zanzan Xu: Business School, Ningbo University, Ningbo 315211, China
Panyi Shen: Business School, Ningbo University, Ningbo 315211, China
Lening Zhang: Business School, Ningbo University, Ningbo 315211, China
Taohan Ni: Business School, University of Nottingham, Ningbo 315199, China

IJERPH, 2022, vol. 19, issue 21, 1-17

Abstract: Based on data from 64 resource-based cities in China from 2010 to 2019, the efficiency of green innovation is evaluated by using the super-efficiency SBM Model with undesired outputs, while influencing factors of green innovation efficiency are analyzed by the spatial Durbin model. The results are as follows. First, as for the efficiency evaluation, the average green innovation efficiency in 62 resource-based cities from 2010 to 2019 is only 0.5689, while the green innovation efficiency of declining cities is the highest, and the growth type is the lowest in the comprehensive planning cities. Second, based on spatial self-correlation in resource-based cities, the government support, and the influencing factors including the industrial structure and economic development, have positive impacts, while the environmental regulations and opening to the outside world will inhibit the urban green innovation. Therefore, to enhance the green innovation efficiency in resource-based cities, some suggestions include formulating differentiated development strategies, forming regional cooperation mechanisms, increasing government scientific and technological support, determining the reasonable intensity of environmental regulations, setting entry barriers for polluting enterprises, and optimizing industrial structure.

Keywords: green innovation in resource-based cities; efficiency evaluation; influencing factors; super-efficiency SBM model with undesired outputs; spatial Durbin model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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