A Study On The Spatial And Temporal Differentiation Of Green Innovation Efficiency In The Eastern Coastal Urban Agglomeration Of China

In light of contemporary growth paradigms,China’s commitment to attaining its "dual-carbon" objective of carbon peaking and neutrality,alongside the establishment and enhancement of a "green,low-carbon,circular economic system",serve as crucial strategic measures for resolving security issues concerning energy resource allocation and promoting high-quality ecological development.These initiatives also constitute a necessary trajectory for sustainable socio-economic growth.Of particular note is the vital role that green innovative technologies play in fostering an economic cycle.Such technologies significantly contribute to reducing energy consumption,minimizing environmental pollution,and encouraging high-quality economic progress.As the driver of China’s economic expansion and the hub for factor production,the eastern coastal area,marked by its strategic economic belt and urban agglomerations,is a matter of urgent consideration for both academia and the government.Accordingly,an examination of its green innovation efficiency carries both theoretical and practical implications for its trajectory towards green sustainable development.This paper primarily employs the Super-SBM model,factoring in unexpected outputs,and the GML index methodology to ascertain the industrial green innovation efficiency across five urban clusters in the eastern coastal region of China,encompassing 74 cities,from both static and dynamic viewpoints.Subsequently,using ArcGIS 10.2 and the natural discontinuity method,we scrutinize the spatial distribution variances of efficiency scores within these urban clusters,investigating their internal evolutionary characteristics.We further explore the spatial distribution direction and centroid trajectory through the computation of standard deviation ellipse and spatial distribution center of gravity.Lastly,we conduct a spatial autocorrelation analysis and dissect the direct and spatial spillover effects of factors impacting green innovation efficiency via the spatial Durbin model.Our findings indicate that:(1)the green innovation efficiency within China’s eastern coastal areas is generally low with sluggish growth.Ranking the efficiency of the five urban clusters from highest to lowest,we have the Pearl River Delta,Yangtze River Delta,Shandong Peninsula,Beijing-Tianjin-Hebei,Guangdong,Fujian,and Zhejiang urban clusters.The dynamic analysis results of the GML index method suggest that the total factor productivity of green innovation in these regions is generally on the rise,with any decreases remaining relatively minor.Furthermore,through the decomposition of the GML index,it is revealed that enhancements in green innovation efficiency in these cities largely depend on technological advancements.(2)In terms of spatial evolution characteristics,notable disparities exist in green innovation efficiency across the cities in the eastern coastal region.Cities with superior green innovation levels are markedly centralized within urban agglomeration areas.The variation range of the standard deviation ellipse angle lies between 0.09 °～4.15 °,displaying a "south-north" orientation.The centroid of green innovation efficiency generally moves in a "northwest to southeast" direction,predominantly within the Yangtze River Delta urban agglomeration.(3)Pertaining to the spatial spillover effect of green innovation efficiency,the degree of external openness and infrastructure development significantly boost local green innovation efficiency;however,they exhibit a markedly negative spillover effect on surrounding cities’ green innovation efficiency.The urbanization level significantly depresses green innovation efficiency both locally and in surrounding cities,whereas the level of information technology enhances green innovation efficiency locally and in surrounding regions.In conclusion,to augment the green innovation efficiency of industrial enterprises in eastern coastal regions,this study proffers policy recommendations in areas such as modern industrial system enhancement,efficient use of information technology infrastructure,and adaptive strategies tailored to local conditions.