Spatial correlation network of Chinese-style ecological modernization and its influencing factors

• An evaluation index system of CSEM is constructed. • The CSEM grew steadily by 36.1% from 2011 to 2021. • The provincial CSEM exhibits a complex multi-threaded network structure. • The CSEM network can be divided into different factions via subgroups. • The influencing factors of the formation of CSEM network are tested. 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.

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Publication Details

Journal
Ecological Indicators
Published
2025-03-01
DOI
https://doi.org/10.1016/j.ecolind.2025.113297
Citations
4
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
4.42
Controls
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article

Spatial correlation network of Chinese-style ecological modernization and its influencing factors

Yonghui Huang, Huiping Wang
4 citations
Ecological Indicators
Land Use and Ecosystem Services
4.42
article

Spatial correlation network of Chinese-style ecological modernization and its influencing factors

Yonghui Huang, Huiping Wang
article en
4 citations

Abstract

• An evaluation index system of CSEM is constructed. • The CSEM grew steadily by 36.1% from 2011 to 2021. • The provincial CSEM exhibits a complex multi-threaded network structure. • The CSEM network can be divided into different factions via subgroups. • The influencing factors of the formation of CSEM network are tested. 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.

Ecological IndicatorsVol. 172
Xi'an University of Finance and Economics (CN)
Openalex Percentile: Top 7%
Land Use and Ecosystem Services
4.42
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