[Characteristics and Dynamic Evolution of the Spatial Correlation Network of Green Development in China].

Green development is a core and key link as well as a distinct characteristic identifier for achieving high-quality development. Accurately clarifying its development status is of great significance for promoting the comprehensive green transformation of China's economy and society. Taking 31 provinces in China from 2012 to 2023 as the research objects （excluding data from Hong Kong， Macao， and Taiwan）， this study comprehensively employs the non-desired Super-SBM model and the modified gravity model to construct the spatial correlation network of green development. From both macro and micro perspectives， the social network and motif analysis models are utilized to analyze the characteristics and structure of the spatial correlation network of green development， and the dynamic exponential random graph model （TERGM） is constructed to explore the dynamic evolution mechanism of the network. The research shows that： ① The spatial correlation of green development among various provinces in China was increasingly close， but the total amount of network relations had not yet reached its maximum potential. It also showed a feature of "dense in the east and sparse in the west" in spatial distribution. The Beijing-Tianjin-Hebei region and the Jiangsu-Zhejiang-Shanghai region were always at the center of the green development network. ② A few key provinces such as Shanghai， Beijing， and Jiangsu consistently held a dominant position in the spatial correlation network， showing a clear "club convergence" feature. Currently， the eastern region has formed an internal cohesive sub-group， while the central and western regions have established more inter-regional correlation relations with the eastern region. ③ The "bidirectional spillover" and "net spillover" sectors were mainly distributed in the central and western provinces， while the "net benefit" and "broker" sectors were mainly in the eastern coastal provinces. During the research period， all sectors had undergone varying degrees of reorganization. The network motifs in the research period mainly presented a chain structure， but in the 2023 network and the mean network， the full-channel motif structure had taken on the most important position. ④ Geographical spatial adjacency， endogenous network structure， economic scale， openness to the outside world， industrial structure， and financial development， among other relationship variables， all exerted significant influences on the formation and evolution of the spatial correlation network of green development， and these influences have shown obvious heterogeneity characteristics over time intervals.