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Spatial and Temporal Evolution and Driving Factors of Urban Ecological Well-Being Performance in China

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  • Jing Bian

    (School of Management, Xi’an University of Architecture and Technology, Xi’ an 710055, China
    Research Center of Green Development and Mechanism Innovation of Real Estate Industry in Shaanxi Province, Xi’an University of Architecture and Technology, Xi’an 710055, China)

  • Feng Lan

    (School of Management, Xi’an University of Architecture and Technology, Xi’ an 710055, China
    Research Center of Green Development and Mechanism Innovation of Real Estate Industry in Shaanxi Province, Xi’an University of Architecture and Technology, Xi’an 710055, China)

  • Yulin Zhou

    (School of Management, Xi’an University of Architecture and Technology, Xi’ an 710055, China
    Research Center of Green Development and Mechanism Innovation of Real Estate Industry in Shaanxi Province, Xi’an University of Architecture and Technology, Xi’an 710055, China)

  • Zhenzhen Peng

    (School of Management, Xi’an University of Architecture and Technology, Xi’ an 710055, China
    Research Center of Green Development and Mechanism Innovation of Real Estate Industry in Shaanxi Province, Xi’an University of Architecture and Technology, Xi’an 710055, China)

  • Mingfang Dong

    (School of Management, Xi’an University of Architecture and Technology, Xi’ an 710055, China)

Abstract

Extensive development leads to the decline of ecological well-being, and it is necessary to improve the urban ecological well-being performance (EWP). This paper adopted the Super-slack-based measure (Super-SBM) model to evaluate the EWP of 285 Chinese prefecture level cities from 2011 to 2017. The exploratory spatial data analysis method (ESDA) was used to explore the spatial and temporal evolution characteristics of the EWP, and then the spatial Durbin model (SDM) was adopted to analyze the driving factors of the EWP. The results show that the trend of the overall average EWP has experienced a stage evolution process of “upward → downward → upward”. The urban EWPs have significant spatial agglomeration and path dependence. The economic development level and technological progress had the positive impacts on the EWP, and the urbanization level, economic extroversion and industrial structure had the negative impacts on the EWP. The result reveals that there was a “U-shaped” relationship existing between urbanization level and the EWP. The negative spatial spillover effect of urbanization level on the EWP was significant. The corresponding policy implications were put forward. This study will provide strategic guidance for policy makers to optimize and enhance the urban EWP.

Suggested Citation

  • Jing Bian & Feng Lan & Yulin Zhou & Zhenzhen Peng & Mingfang Dong, 2022. "Spatial and Temporal Evolution and Driving Factors of Urban Ecological Well-Being Performance in China," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:9996-:d:887722
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    Cited by:

    1. Zhicheng Lai & Lei Li & Zhuomin Tao & Tao Li & Xiaoting Shi & Jialing Li & Xin Li, 2023. "Spatio-Temporal Evolution and Influencing Factors of Ecological Well-Being Performance from the Perspective of Strong Sustainability: A Case Study of the Three Gorges Reservoir Area, China," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    2. Yu Zhang & Xi Cai & Yanying Mao & Liudan Jiao & Liu Wu, 2023. "What Is the State of Development of Eco-Wellbeing Performance in China? An Analysis from a Three-Stage Network Perspective," Land, MDPI, vol. 12(8), pages 1-18, July.
    3. Can Zhang & Jixia Li & Tengfei Liu & Mengzhi Xu & Huachun Wang & Xu Li, 2022. "The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance," IJERPH, MDPI, vol. 19(19), pages 1-27, October.
    4. Ling Bai & Tianran Guo & Wei Xu & Kang Luo, 2022. "The Spatial Differentiation and Driving Forces of Ecological Welfare Performance in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    5. Haoyang Lu & Jing Tong & Yajiao Tang, 2022. "Analysis of Green Credit and the Ecological Welfare Performance Based on Empirical Models and ARIMA(2,3,2): Taking China as an Example," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    6. Yuanyuan Zhu & Rui Zhang & Jiaxing Cui, 2022. "Spatial Differentiation and Influencing Factors in the Ecological Well-Being Performance of Urban Agglomerations in the Middle Reaches of the Yangtze River: A Hierarchical Perspective," IJERPH, MDPI, vol. 19(19), pages 1-22, October.
    7. Wanxin He & Jianhua Fu & Youxi Luo, 2023. "A Study of Well-Being-Based Eco-efficiency Based on Super-SBM and Tobit Regression Model: The Case of China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 167(1), pages 289-317, June.
    8. Jing Bian & Feng Lan & Zhao Hui & Jiamin Bai & Yuanping Wang, 2022. "Ecological Well-Being Performance Evaluation of Chinese Major Node Cities along the Belt and Road," Land, MDPI, vol. 11(11), pages 1-19, October.

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