Research and evaluation of spatiotemporal dynamic of network green innovation efficiency in China—based on meta-Frontier theory

Frontiers in Environmental Science

Environmental Science

Fengjing Han¹  Yueming Han²  Shiyou Qu² 

[1] Business School, Lingnan Normal University, Zhanjiang, Guangdong, China;School of Management, Harbin Institute of Technology, Harbin, Heilongjiang, China;

关键词: meta-Frontier;    two-stage network SBM model;    green innovation efficiency;    GML index;    spatial correlation;    Tobit regression;   

DOI  :  10.3389/fenvs.2023.1209883

 received in 2023-04-21, accepted in 2023-07-31,  发布年份 2023

来源: Frontiers

【 摘 要 】

Green innovation has emerged as a crucial driver for advancing green and high-quality development. Exploring the evolutionary patterns of green innovation efficiency is crucial for achieving the “dual carbon” goals and realizing the benefits of both economic growth and environmental sustainability under the framework of new development concepts. This study employs the network SBM-DEA model under meta-Frontier and group-Frontier. Additionally, it considers the GML index and Moran’s I to conduct a comprehensive analysis of the evolving efficiency of green innovation in Chinese provinces from 2008 to 2020, then uses the Tobit regression model to verify the influencing indicators for green innovation efficiency. The examination covers various aspects, including the stage of green innovation, the diversity of technology accumulation, the comparability of pre- and post-development, the spillover effects in geographical space, and the diversity of influencing factors. The research findings indicate the following: 1) The group division exhibit a high level of geographical correlation, and the efficiency of green innovation in the two-stage and network displays heterogeneity across distinct frontiers. The efficiency loss in the Green Achievement Transformation stage is bigger than that in the Green Technology Research and Development stage. 2) There is an overall increase in green innovation efficiency of each type during most years, and the spatial correlation and stability of the two-stage and network green innovation efficiency have improved year by year. Provinces with higher Green Innovation Environment Composite Index have the highest concentration of “high-high” efficiency agglomeration. 3) Environmental regulation intensity, factor endowment, property rights structure, foreign direct investment and energy consumption have varying degrees of constraints on green innovation, and the regional economic development level can significantly improve the efficiency of various green innovations. Finally, this paper provides some suggestions, including stimulating innovation vitality, formulating differentiated policies, strengthening regional innovation collaboration, and mobilizing resources from various stakeholders. These recommendations aim to provide guidance and reference for promoting green innovation and achieving sustainable development in different regions.

【 授权许可】

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Copyright © 2023 Han, Qu and Han.