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Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt
Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt
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Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt
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Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt
Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt

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Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt
Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt
Journal Article

Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt

2023
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Overview
Effectively utilizing water resources, which is a fundamental natural resource and a vital economic resource, directly impacts how a country’s economy develops. In this study, the Super-SBM model is used to calculate the city water resource green efficiency (CWRGE) of the Yangtze River Economic Belt (YREB), 108 cities that are prefecture level or higher, from 2006 to 2021. And its temporal and spatial evolution as well as its affecting variables are examined. The results indicate that, as a whole, the YREB’s CWRGE has not yet achieved an effective level. The CWRGE in the YREB generally exhibits a trend of “first decreasing and then increasing, then decreasing and then increasing” and shows a “W”-shaped evolution law, and the overall trend is upward. There are just seven cities with effective data envelopment analysis (DEA), namely Changzhou, Hangzhou, Shanghai, Xuzhou, Changde, Changsha, and Yuxi. During the reporting period, the CWRGE of cities of various scales showed significant gaps: mega cities > big cities > small and medium-sized cities. From a regional perspective, the highest rate of CWRGE was found downstream of the YREB cities, then upstream, and the middle was the lowest. Spatial correlation findings demonstrated that both the agglomeration range and the outlier range were distributed, and there were mainly two positive aggregations of space forms (“high-high (H-H) type” and “low-low (L-L) type”), and the spatial distribution changed. The results of the spatiotemporal evolution demonstrate that there are more and more cities with high efficiency, as well as cities with low efficiency. From the results of the Tobit regression model, the CWRGE in the YREB are significantly improved by the economical development level, industrial scale, and water usage structure. While foreign direct investment and environmental regulation have considerable detrimental impacts, the impact of scientific and technological investment is not significant.