Research on spatial-temporal heterogeneity of driving factors of green innovation efficiency in Yangtze River Delta urban agglomeration—empirical test based on the Geographically Weighted Regression model

Abstract

Firstly, based on the data of 40 cities in the Yangtze River Delta from 2010 to 2019, the paper uses the Unexpected Super-SBM model to estimate the green innovation efficiency of each city. On this basis, the paper establishes a Geographically Weighted Regression model to explore the spatial-temporal heterogeneity of the effects of influencing factors on green innovation efficiency. The findings indicate that: The direction and strength of each influencing element on the green innovation efficiency of the Yangtze River Delta cities are varied at the urban spatial scale. The degree of opening up significantly boosts the green innovation efficiency, but the impact intensity shows spatial differences. The green innovation efficiency is promoted by government technology support, but its intensity tends to weaken. In addition, financial support has a negative impact on most cities. Over time, the impact of economic development level on urban green innovation efficiency has changed from inhibition to promotion, and the impact intensity tends to weaken. Industrial structure and environmental regulation tend to show two effects of promotion and obstruction in different cities from weak inhibition. Industrial structure and environmental regulation tend to show two effects of promotion and obstruction in different cities from weak inhibition. The research conclusion of this paper has important theoretical significance and practical value for accelerating the construction of a green, low-carbon and circular economic system in the Yangtze River Delta region, and achieving the “dual carbon” goal.