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Measurement and spatial statistical analysis of green science and technology innovation efficiency among Chinese Provinces

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Abstract

This paper measured the efficiency of green science and technology (S&T) innovation in 30 Chinese provinces from 2008 to 2017 by constructing a three-stage super-efficiency DEA model that contains undesired output and then analyzed the spatial performance for these provinces. The purpose is to calculate exactly the extent to which S&T innovation in different regions of China has contributed to economic development, excluding negative impacts on the ecological environment and any spatial differences that have emerged in the past decade. The results show that the overall performance of green S&T innovation efficiency in Chinese regions was poor in the past decade, and there is still much room for improvement. In addition, China's investment in S&T innovation and environmental management is inefficient and wasteful. From the temporal perspective, efficiency in green innovation shows a slowly increasing trend. From the spatial perspective, the efficiency shows a strict correlation with economic development, that is, an obvious three-level spatial distribution pattern of "east, middle, and west".

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 41401634)and Social Science Research Foundation of Nanjing University of Posts and Telecommunications (Grant No. NYY220006).

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Authors and Affiliations

  1. School of Management, Nanjing University of Posts and Telecommunications, No. 66 Xin Mofan Rd, Nanjing, 210003, Jiangsu, China

    Wu Mingran

  2. Information Industry Convergence Innovation and Emergency Management Research Center, Nanjing, 210003, China

    Wu Mingran

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  1. Wu Mingran
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Correspondence to Wu Mingran.

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Handling Editor: Luiz Duczmal.

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Mingran, W. Measurement and spatial statistical analysis of green science and technology innovation efficiency among Chinese Provinces. Environ Ecol Stat 28, 423–444 (2021). https://doi.org/10.1007/s10651-021-00491-7

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  • DOI: https://doi.org/10.1007/s10651-021-00491-7

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