This paper deals with urban sustainable development in China. We propose a network data envelopment analysis (DEA) model with a slack-based measure (SBM) to analyze the eco-efficiency of 284 Chinese cities, enabling us to find a way to open the “black box” in conventional DEA models and introduce social well-being factors into the model, and depict the role of local government in providing public service and improving social well-beings. We set up a framework of urban development by dividing the process of into two steps. The first stage is a production system translating inputs and natural resources into GDP and waste production, which will be inputs to the second stage for distribution and consumption to realize social welfare and environmental protection. The results show eco-efficiency of Chinese cities experienced a significant decrease from 2005 to 2016, which should be mainly attributed to the distribution and consumption processes. Structural differences are described by regions, administrative level and clusters. These results are compared with an existing urban sustainability index system developed by McKinsey and an ANOVA approach is conducted to reveal differences between cities across regions and clusters. This article sheds new light on the understanding of urban sustainable construction and development in China regarding the service performance of local government. View Full-Text
Sun, B.; Wang, H.; Ortiz, J.; Huang, J.; Zhao, C.; Wang, Z. A Decomposed Data Analysis Approach to Assessing City Sustainable Development Performance: A Network DEA Model with a Slack-Based Measure. Sustainability 2022, 14, 11037. https://doi.org/10.3390/su141711037
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