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The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance
In the “full world” where natural capital is scarce, within the limits of the ecological environment, the improvement of welfare is a fundamental requirement for sustainable development. The ecological wellbeing performance (EWP) of 284 cities in China from 2007 to 2020 was measured by the supereffi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566643/ https://www.ncbi.nlm.nih.gov/pubmed/36232265 http://dx.doi.org/10.3390/ijerph191912955 |
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author | Zhang, Can Li, Jixia Liu, Tengfei Xu, Mengzhi Wang, Huachun Li, Xu |
author_facet | Zhang, Can Li, Jixia Liu, Tengfei Xu, Mengzhi Wang, Huachun Li, Xu |
author_sort | Zhang, Can |
collection | PubMed |
description | In the “full world” where natural capital is scarce, within the limits of the ecological environment, the improvement of welfare is a fundamental requirement for sustainable development. The ecological wellbeing performance (EWP) of 284 cities in China from 2007 to 2020 was measured by the superefficient SBM-DEA model, considering undesirable output, and analyzing the evolutionary trends of overall comprehensive technical efficiency, pure technical efficiency, and scale efficiency. The Theil index was used to explore the source and distribution of the Chinese cities’ EWP differences. Exploratory spatial data analysis (ESDA) and the spatial Durbin model (SDM) were applied to analyze the spatial distribution characteristics and driving factors of cities’ EWP. The results showed the following: (1) Regarding spatial and temporal distribution, the EWP of Chinese cities showed a fluctuating upward trend, in which pure technical efficiency > scale efficiency. (2) Considering regional differences, the differences in cities’ EWP were mainly intraregional rather than interregional. The contribution rates of distinct regions to the differences in EWP varied, i.e., western region > eastern region > central region > northeastern region. (3) In terms of spatial correlation, China’s EWP showed positive spatial correlation, i.e., high–high agglomeration and low–low agglomeration. (4) Concerning influencing factors, the level of financial development, the structure of secondary industries, the level of opening-up, and the degree of urbanization significantly improved EWP. Decentralization of fiscal revenue significantly inhibited improvement of EWP. Decentralization of fiscal expenditure and technological progress had no significant impact on the EWP. In the future, to improve cities’ EWP, China should focus on reducing differences in intraregional EWP, overcoming administrative regional limitations, encouraging regions with similar locations to formulate coordinated development plans, promoting economic growth, reducing levels of environmental pollution, and paying attention to the improvement of social welfare. |
format | Online Article Text |
id | pubmed-9566643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95666432022-10-15 The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance Zhang, Can Li, Jixia Liu, Tengfei Xu, Mengzhi Wang, Huachun Li, Xu Int J Environ Res Public Health Article In the “full world” where natural capital is scarce, within the limits of the ecological environment, the improvement of welfare is a fundamental requirement for sustainable development. The ecological wellbeing performance (EWP) of 284 cities in China from 2007 to 2020 was measured by the superefficient SBM-DEA model, considering undesirable output, and analyzing the evolutionary trends of overall comprehensive technical efficiency, pure technical efficiency, and scale efficiency. The Theil index was used to explore the source and distribution of the Chinese cities’ EWP differences. Exploratory spatial data analysis (ESDA) and the spatial Durbin model (SDM) were applied to analyze the spatial distribution characteristics and driving factors of cities’ EWP. The results showed the following: (1) Regarding spatial and temporal distribution, the EWP of Chinese cities showed a fluctuating upward trend, in which pure technical efficiency > scale efficiency. (2) Considering regional differences, the differences in cities’ EWP were mainly intraregional rather than interregional. The contribution rates of distinct regions to the differences in EWP varied, i.e., western region > eastern region > central region > northeastern region. (3) In terms of spatial correlation, China’s EWP showed positive spatial correlation, i.e., high–high agglomeration and low–low agglomeration. (4) Concerning influencing factors, the level of financial development, the structure of secondary industries, the level of opening-up, and the degree of urbanization significantly improved EWP. Decentralization of fiscal revenue significantly inhibited improvement of EWP. Decentralization of fiscal expenditure and technological progress had no significant impact on the EWP. In the future, to improve cities’ EWP, China should focus on reducing differences in intraregional EWP, overcoming administrative regional limitations, encouraging regions with similar locations to formulate coordinated development plans, promoting economic growth, reducing levels of environmental pollution, and paying attention to the improvement of social welfare. MDPI 2022-10-10 /pmc/articles/PMC9566643/ /pubmed/36232265 http://dx.doi.org/10.3390/ijerph191912955 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Can Li, Jixia Liu, Tengfei Xu, Mengzhi Wang, Huachun Li, Xu The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance |
title | The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance |
title_full | The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance |
title_fullStr | The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance |
title_full_unstemmed | The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance |
title_short | The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance |
title_sort | spatiotemporal evolution and influencing factors of the chinese cities’ ecological welfare performance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566643/ https://www.ncbi.nlm.nih.gov/pubmed/36232265 http://dx.doi.org/10.3390/ijerph191912955 |
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