Research on green innovation efficiency measurement and influencing factors in the three major coastal urban agglomerations in China - Ying, Shuli; Fang, Qiquan; Ji, Yanting (Frontiers in Environmental Science, 2023)
In the context of the in-depth promotion of the urban green development process, this paper selects the panel data of 40 cities in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) urban agglomerations from 2010 to 2020 as the research object. The super-efficiency SBM (slack-based measure) model and Malmquist-Luenberger (ML) index are used to measure the green innovation efficiency (GIE) and its dynamic evolution rules, and the Tobit regression model is constructed to analyze the influencing factors of GIE. The results show that the PRD urban agglomeration has the highest GIE level, while the GIE level in BTH and YRD shifted around 2015. Technical efficiency and technological progress together lead to increased GIE, with technological progress having a higher impact than technical efficiency. The regression coefficients of urbanization level, industrial structure, and science and technology level are 0.0071, 0.0078, and 0.0616, respectively, significantly promoting GIE. The coefficients of economic development level, foreign direct investment, environmental regulations, and SO2 emissions are -0.2198, -0.1163, -0.005, and -0.011, respectively, significantly inhibiting GIE. The coefficient of vegetation cover of 0.0228 has no significant effect on GIE. This study enriches the theoretical results on the meso-level of GIE and provides theoretical guidance and practical directions for promoting green innovation in urban agglomerations, achieving peaking carbon and carbon neutrality, and promoting green and high-quality development.