Spatial Analysis and Prediction of Ecological Welfare Performance: Evidence from 284 Prefecture-level Cities in China


  • Linxinyu Wang



Ecological Welfare Performance; Two-stage DEA Model; Social Network Analysis; Space Markov Chain.


The general debate of the 78th session of the United Nations reaffirmed the importance of the Sustainable Urban and Community Development Goal (SDG 11), however, the pervasive accounting gaps still lead to significant challenges in the monitoring and evaluation of SDG 11 indicators. This paper focuses on ecological welfare performance accounting, aiming to assess the weaknesses and internal gaps of regional SDG 11 at the aggregate level, so as to promote eco-city planning and management, improve the well-being potential of urban residents, and reduce the adverse impact on the ecological environment. Taking China as a developing country as a case, the two-stage DEA model is used to measure the ecological welfare performance of 284 cities in China from 2007 to 2022, and the spatiotemporal pattern of efficiency at each stage of the ecological welfare transformation process is described, a modified gravitational model is constructed to transform the "attribute data" of ecological welfare performance into "relationship data", and the characteristics of network structure are described with the help of social network analysis, and the formation mechanism of the spatial correlation network of ecological welfare performance is revealed and its dynamic evolution characteristics are revealed through the spatial Markov chain.


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Jin Shuqin, Zhang Jiuhong, Gu Baojing. China from the Perspective of the World: Effectiveness, Gaps and Prospects for the Implementation of the United Nations Sustainable Development Goals [J]. Chinese Population Resources and Environment, 2023, 33(12): 1-10.

Ke Bing, Sun Xinzhang. China's Exploration of the Implementation of the United Nations 2030 Agenda for Sustainable Development at the City Level: An Innovation Demonstration Zone for the National Sustainable Development Agenda[J]. Chinese Population Resources and Environment, 2023, 33(07): 1-8.

Li-Qun L, Chun-Xia L, Yun-Guang G. Green and sustainable City will become the development objective of China’s Low Carbon City in future[J]. Journal of Environmental Health Science and Engineering, 2014, 12(1): 34.

Lei S, Pozo D, Wang M, et al. Power economic dispatch against extreme weather conditions: The price of resilience[J]. Renewable and Sustainable Energy Reviews, 2022, 157: 111994.

Sun Y, Li Y, Yu T, et al. Resource extraction, environmental pollution and economic development: Evidence from prefecture-level cities in China[J]. Resources Policy, 2021, 74: 102330.

Hong P, Schmid B, De Laender F, et al. Biodiversity promotes ecosystem functioning despite environmental change[J]. Ecology Letters, 2022, 25(2): 555-569.

Liu Qian, Qu Guangbo, Lu Dawei. Some New Needs for Basic Research on Environmental Pollution and Health in China[J]. Bulletin of Chinese Academy of Sciences, 2021, 36(05): 614-621.

He C, Huang Q, Bai X, et al. A Global Analysis of the Relationship Between Urbanization and Fatalities in Earthquake-Prone Areas[J]. International Journal of Disaster Risk Science, 2021, 12(6): 805-820.

Li C, Yu L, Oloo F, et al. Slum and urban deprivation in compacted and peri-urban neighborhoods in sub-Saharan Africa[J]. Sustainable Cities and Society, 2023, 99: 104863.

González-García S, Rama M, Cortés A, et al. Embedding environmental, economic and social indicators in the evaluation of the sustainability of the municipalities of Galicia (northwest of Spain)[J]. Journal of Cleaner Production, 2019, 234: 27-42.

Zeng Weiping, Li Lin, Yin Zihui. The impact of economic agglomeration on urban public health in China[J]. Chinese Population Resources and Environment, 2023, 33(09): 204-214.

Xia Qingjie, Song Lina, Appleton Simon. Trends and patterns of urban poverty in China: 1988-2002[J]. Economic Research Journal, 2007, (09): 96-111.

Lao Xin, Xue Lan. Spatial Distribution of Higher Education Resources in China and Its Impact on Regional Economic Growth[J]. Higher Education Research, 2016, 37(06): 26-33.

Zhu Dajian. Ecological Economics: Economics and Management of Sustainable Development[J]. Bulletin of the Chinese Academy of Sciences, 2008, (06): 520-530.

Wang L, Zhang P, Tan S, et al. Assessment of urban air quality in China using air pollution indices (APIs)[J]. Journal of the Air & Waste Management Association, 2013, 63: 170-178.

Zhang Yue, Wang Jingjing, Cheng Yu. Spatio-temporal characteristics of China's industrial carbon emission performance and its influencing mechanism of technological innovation[J]. Resources Science, 2022, 44(07): 1435-1448.

Bai J Y. Bird biodiversity increased with the area of urban green spaces expanding after 40 years of tree planting in Beijing [J]. Ecosystem Health and Sustainability, 2023.

Song T, Cai J, Chahine T, et al. Towards Smart Cities by Internet of Things (IoT)—a Silent Revolution in China[J]. Journal of the Knowledge Economy, 2021, 12(2): 1-17.

Long Liangjun, Wang Xia, Guo Bing. Research on Urban Ecological Welfare Performance Evaluation Based on Improved DEA Model: A Case Study of 35 Large and Medium-sized Cities in China[J]. JOURNAL OF NATURAL RESOURCES, 2017, 32(04): 595-605.

Deng Yuanjian, Yang Xu, Ma Qiangwen, et al. Regional Differences and Convergence of Ecological Welfare Performance Level in China[J]. Chinese Population Resources and Environment, 2021, 31(04): 132-143.

Long Liangjun. Research on Urban Ecological Welfare Performance Evaluation Based on Two-stage Super-NSBM Model [J]. Chinese Population Resources and Environment, 2019, 29(07): 1-10.

Liou J, Chiu C. Analyzing the Relationship between CO2 Emission and Economic Efficiency by a Relaxed Two-Stage DEA Model[J]. Aerosol and Air Quality Research, 2015, 15.

Dong S, Ren G, Xue Y, et al. Urban green innovation's spatial association networks in China and their mechanisms[J]. Sustainable Cities and Society, 2023, 93: 104536.

Zhang R, Cao Y, Wu K, et al. Research on the effect of green credit on ecological welfare performance: Evidence from China[J]. Frontiers in Environmental Science, 2022, 10.

Wang Shaojian, Gao Shuang, Huang Yongyuan, et al. Spatiotemporal evolution pattern and prediction of urban carbon emission performance in China based on super-efficient SBM model[J]. Acta Geographica Sinica, 2020, 75(06): 1316-1330.







How to Cite

Spatial Analysis and Prediction of Ecological Welfare Performance: Evidence from 284 Prefecture-level Cities in China. (2024). Academic Journal of Science and Technology, 11(2), 196-202.

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