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Urban green innovation efficiency and its influential factors: the Chinese evidence

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Abstract

To ameliorate the efficiency of urban green innovation is the key to realizing green economic transition. This paper constructs a Super-NSBM model with green patents as the intermediate output, uses this model to assess and decompose the green innovation efficiency of 284 Chinese cities, and finally analyzes the spatiotemporal characteristics and influential factors. The research result showed the gap of urban green innovation total efficiency among various regions in China is narrowing, while the spatial differentiation of decomposition efficiency is deepening. This means that a spatial collaborative innovation division pattern of “Eastern Region R&D + Southwest and Northeast Region Transformation” has gradually formed. In the meantime, this paper also found that the spillover effects of the urban green innovation total efficiency and phased efficiency all can form a significant demonstration effect on the surrounding areas. Finally, financial agglomeration, industrial structure, knowledge sharing, economic activity, higher education, opening, and environmental regulations may affect urban green innovation total efficiency and phased efficiency, and this effect has regional heterogeneity.

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Funding

This research is supported by the National Social Science Foundation of China (No. 20FJLB018).

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Authors and Affiliations

  1. School of Economics and Trade, Hunan University, Changsha, China

    Bin Liao & Lin Li

Authors
  1. Bin Liao
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  2. Lin Li
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Contributions

BL took part in conceptualization, methodology, investigation, writing—original draft, software, formal analysis, writing—review & editing, validation, visualization; LL involved in resources, funding, supervision.

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Correspondence to Bin Liao or Lin Li.

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The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.

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Liao, B., Li, L. Urban green innovation efficiency and its influential factors: the Chinese evidence. Environ Dev Sustain 25, 6551–6573 (2023). https://doi.org/10.1007/s10668-022-02316-4

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