Spatial correlation network structure of green innovation efficiency and its driving factors in the Bohai Rim region

Kaixuan Di (), Zuankuo Liu (), Shanglei Chai (), Kanyong Li () and Yu Li ()
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Kaixuan Di: Shandong Normal University
Zuankuo Liu: Shandong Normal University
Shanglei Chai: Shandong Normal University
Kanyong Li: Shandong Jiaotong University
Yu Li: Shandong Normal University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 11, No 6, 27227-27247

Abstract: Abstract As the integration point of green development and innovation-driven, green innovation has become the key to promote high-quality and sustainable development in the Bohai Rim region. This study calculates the green innovation efficiency (GIE) of 43 cities in the Bohai Rim region based on the super slacks-based measure (super-SBM) model, further using the social network analysis and quadratic assignment procedure analysis methods to explore the GIE spatial correlation network structure and its driving factors. The findings show that (1) the GIE between cities in the Bohai Rim region exhibits complex and stable network characteristics; (2) Beijing and Tianjin exert an important influence on the green innovation development of other cities; (3) each city is divided into four functional blocks, with strong spatial spillover effects between the blocks; and (4) the closer the geographical distance is, the more similar the environmental regulations are, and the easier it is for spatial associations to occur. The differences in the level of urban economic development, openness, human capital, and infrastructure are conducive to promoting the establishment of spatial associations. Finally, based on the conclusions, the study provides a theoretical basis and policy recommendations for improving the quality and efficiency of green innovation and collaborative development in the Bohai Rim region.

Keywords: Bohai Rim region; Green innovation efficiency; Social network analysis; Super-SBM model; QAP analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03757-1

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