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

Author:

Li Baitong1,Li Jian12,Liu Chen3,Yao Xinyan1,Dong Jingxuan1,Xia Meijun1

Affiliation:

1. School of Management, Tianjin University of Technology, Tianjin 300384, China

2. College of Management and Economics, Tianjin University, Tianjin 300372, China

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

Funder

Tianjin Science and Technology Planning Project of China

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

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