Spatial correlation network of Chinese-style ecological modernization and its influencing factors - Huiping Wang; Yuezhan Huang (Ecological Indicators)
This paper constructs an evaluation index system of Chinese-style ecological modernization (CSEM) based on the idea of “six-in-one”, and measures the CSEM of 30 provinces in China from 2011 to 2021 by using entropy value method. The improved gravity model, social network analysis and QAP regression model are used to study the characteristics of the spatial correlation network of CSEM and its influencing factors. The study finds that: First, the CSEM demonstrates a consistent upward trajectory, yet there exists a notable spatial disparity, with the eastern region exhibiting higher CSEM compared to other regions. Second, the inter-provincial connection of CSEM has exhibited a network structure, albeit it has not attained the optimal state of spatial correlation yet. The network density remains low, and the spatial spillover effect demonstrates a west-to-east trend, where the western region has emerged as the “spillover highland”. Meanwhile, Beijing, Shanghai, Jiangsu, and Zhejiang occupy a central and dominant position within the network. Third, the network can be divided into several factions based on subordination, with obvious geographical proximity pointing between provinces, in which subgroup III was initially composed of six provinces, including Guangdong, and shrunk to Guangdong, Guangxi and Hainan after 2017, while Sichuan, Chongqing and Guizhou formed the new subgroup IV, demonstrating the dynamic characteristics of the subordination network over time. Fourth, the spatial network of CSEM is segmented into four blocks: net benefit, net spillover, two-way spillover and broker. The role division and linkage effect between the four blocks is obvious. Fifth, differences in the urbanization, geographical proximity, economic development, technological innovation and industrial advancement all contribute positively to the development of the network, while differences in resource consumption inhibit the formation of network.