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Provincial Inclusive Green Growth Efficiency in China: Spatial Correlation Network Investigation and Its Influence Factors

Author

Listed:
  • Baitong Li

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

  • Jian Li

    (School of Management, Tianjin University of Technology, Tianjin 300384, China
    College of Management and Economics, Tianjin University, Tianjin 300372, China)

  • Chen Liu

    (China Shanghai Architectural Design & Research Institute. Co., Ltd., Shanghai 200063, China)

  • Xinyan Yao

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

  • Jingxuan Dong

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

  • Meijun Xia

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

Abstract

Inclusive green growth efficiency (IGGE) analysis is an effective tool for improving coordinated economic, social, and environmental development. This study incorporated the game cross-efficiency DEA to measure the IGGE of 30 provinces in China. Then, the modified spatial gravity model and social network analysis model were applied to construct and analyze the spatial correlation network structure of the IGGE. The quadratic assignment procedure was used to mine the influencing factors that affect the formation and evolution of the spatial correlation network of the IGGE. The results are as follows. (1) During the study period, there were significant differences in the IGGE among the 31 provinces, among which the eastern provinces were higher than the central and western provinces. (2) The spatial correlation of the IGGE presented a complex and multi-threaded network structure, indicating that the IGGE has a noticeable cross-regional spillover effect. Beijing, Tianjin, Zhejiang, Shanghai, Jiangsu, and Guangdong played the role of the “net spillover” block. Qinghai, Guizhou, Guangxi, and the surrounding provinces played the role of the “primary beneficial”. The Yangtze delta and Pearl River Delta economic zone (primarily including Shanghai and Guangdong) acted as a “bridge” to the Yunnan–Guizhou region and the surrounding provinces. (3) The spatial adjacency, degree of openness, economic development, and environmental governance were the prominent factors influencing the formation and evolution of the IGGE spatial correlation network. This work provides an example of constructing an IGGE correlation network while considering various factors, such as the economy, population, and distance. It also could help policymakers clarify the IGGE spatial correlation pattern and the provinces’ roles and potential for IGGE synergic improvement.

Suggested Citation

  • Baitong Li & Jian Li & Chen Liu & Xinyan Yao & Jingxuan Dong & Meijun Xia, 2023. "Provincial Inclusive Green Growth Efficiency in China: Spatial Correlation Network Investigation and Its Influence Factors," Land, MDPI, vol. 12(3), pages 1-24, March.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:692-:d:1098712
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    References listed on IDEAS

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    Cited by:

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    2. Congxian He & Bingze Song & Ruiqing Shi & Rumeng Rao, 2025. "Spatiotemporal Disparities in Inclusive Green Growth in Less Developed Regions: A Study on Old Revolutionary Base Areas in China," SAGE Open, , vol. 15(4), pages 21582440251, October.
    3. Nie, Song & Zeng, Gang & Zhang, Xu & Guo, Qiaozhe, 2024. "Does local government debt pressure hamper green transition? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 1185-1201.
    4. Jinkuan Yu & Yao Sun & Feng Wei, 2024. "Green Development of Chinese Agriculture from the Perspective of Bidirectional Correlation," Agriculture, MDPI, vol. 14(9), pages 1-20, September.
    5. Tianjun Xu & Gangmin Weng & Wei Guo, 2024. "Coupling Coordination Analysis of China’s Tourism Inclusive Green Growth System and Its Dynamic Evolution," Sustainability, MDPI, vol. 16(23), pages 1-18, November.

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