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• W4220918724 abstract "As the second largest economy in the world, China faces serious environmental issues. Currently, how to promote sustainability has become an important priority for policymakers and has attracted great attention from researchers. To evaluate sustainability, this study proposes a new methodological framework. This framework consists of a new data envelopment analysis (DEA) model, concepts of natural and managerial disposability, strong complementary slackness conditions, efficiency Theil index and K-Means clustering method. With the use of this framework, this study obtains unified efficiency measures, technology-based measures, and efficiency inequality measures. These measures assist decision makers in promoting efficiency, mitigating environmental degradation and promoting sustainability. Empirically, this study considers the case of 198 Chinese cities from 2010 to 2016. Five main conclusions are presented. First, Chinese cities improved their unified efficiency scores under both natural and managerial disposability. Second, there is a significant number of occurrences of undesirable congestion, which means that most Chinese cities can save considerable resources during the production process. Third, there is a limited number of occurrences of desirable congestion, implying that only a small portion of Chinese cities have achieved a high level of sustainability. Fourth, efficiency inequality across Chinese cities has gradually decreased over time, where technology diffusion plays an important role. Finally, China faces considerable regional/provincial inequality. Looking ahead, cities that lag behind should put significantly more effort into enhancing both economic prosperity and environmental protection." @default.
• W4220918724 created "2022-04-03" @default.
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• W4220918724 date "2022-04-01" @default.
• W4220918724 modified "2023-10-18" @default.
• W4220918724 title "Evaluating the sustainability of Chinese cities: Indicators based on a new data envelopment analysis model" @default.
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• W4220918724 doi "https://doi.org/10.1016/j.ecolind.2022.108779" @default.
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