Examination of the spatial-temporal evolution and level measurement of industrial green manufacturing development: A case study of the Yangtze River Economic Belt
Zihao Zheng,
Xinquan Ge and
Zongshui Wang
PLOS ONE, 2025, vol. 20, issue 10, 1-21
Abstract:
With the increasingly serious problems of global climate change and resource tension, green manufacturing has become an important direction of industrial development. This paper constructs an evaluation index system for the development level of industrial green manufacturing based on the panel data of 11 provinces in the Yangtze River Economic Belt from 2018 to 2022, and utilizes the Entropy-GRA-TOPSIS method, the natural breakpoint classification method, Theil index, and Moran’s I to explore the development level, spatiotemporal characteristics, regional differences, and spatial correlation of industrial green manufacturing in the Yangtze River Economic Belt, and puts forward the corresponding suggestions. The results show that: the development level of industrial green manufacturing in the Yangtze River Economic Belt shows an upward trend, with an average annual growth rate of 5%, but there are large regional differences, showing a development pattern of “strong in the east and weak in the west”; the regional spatial differences continue to expand, but shrink in 2022, and the overall differences among the three major regions mainly originate from the inter-regional differences, with the central region having the largest differences and contribution rate, and the central region having the largest differences and contribution rate, and the central region having the largest differences and contribution rate. The overall differences among the three regions mainly come from inter-regional differences, with the central region having the largest differences and contribution rate, and the intra-regional differences and contribution rate also showing a fluctuating growth trend; the green development of industry in the Yangtze River Economic Belt shows a significant positive spatial correlation in general, with the HH-type mostly in the eastern provinces and cities, and the LL-type mostly in the central and western provinces and cities.
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0324804
DOI: 10.1371/journal.pone.0324804
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