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Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China
The coordinated development of industrial agglomeration and economic resilience can drive regional economic advantages; this type of development has become a catalyst for sustainable growth and high-quality development of the economy in China. This study applied models, including the coupling coordi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9362362/ https://www.ncbi.nlm.nih.gov/pubmed/35966337 http://dx.doi.org/10.1007/s10668-022-02588-w |
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author | Zheng, Ziyan Zhu, Yingming Pei, Yu Wang, Litao |
author_facet | Zheng, Ziyan Zhu, Yingming Pei, Yu Wang, Litao |
author_sort | Zheng, Ziyan |
collection | PubMed |
description | The coordinated development of industrial agglomeration and economic resilience can drive regional economic advantages; this type of development has become a catalyst for sustainable growth and high-quality development of the economy in China. This study applied models, including the coupling coordination degree, spatial autocorrelation, and Tobit, to explore the heterogeneous characteristics of the coupling of China’s industrial agglomeration and regional economic resilience from 2005 to 2019. Additionally, by applying the perspectives of economic and geographic location, indicators were selected to analyze the associated influencing factors, including industrial externalities, new economic geographies, economic policy factors, and other aspects. We found that the overall coupling between industrial agglomeration and economic resilience increased over the study period, but with only a moderate level of coordination. Provinces with high, moderate, and low levels of coordination eventually emerged along a strip-like alternating pattern in space. The dependence increased with an increase in space, but was not significant, and there was a lack of benign interaction between the regions. With respect to interactivity between locations, the interaction of the east and the coast was the most active. There were lower levels of interaction between the west and inland regions. This further confirmed the significant temporal and spatial heterogeneity of the coupling. Environmental pollution, market consumption, the quality of space, and technological support significantly promoted the coupling; opening to the outside world did not. Specifically, with respect to economic location, market consumption and spatial quality had a significant positive effect on the eastern coupling. The center and west regions were significantly affected by economic density and market consumption, and the northeast region was affected by spatial quality and capital intensity. Concerning geographical location, market and technological forces strongly promoted interactions in both the coast and inland regions. The study found that both the government and the market need better guidance to effectively engage with and shape industrial agglomeration and economic resilience in a scientific, reasonable, localized, and distinctive manner. |
format | Online Article Text |
id | pubmed-9362362 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-93623622022-08-10 Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China Zheng, Ziyan Zhu, Yingming Pei, Yu Wang, Litao Environ Dev Sustain Article The coordinated development of industrial agglomeration and economic resilience can drive regional economic advantages; this type of development has become a catalyst for sustainable growth and high-quality development of the economy in China. This study applied models, including the coupling coordination degree, spatial autocorrelation, and Tobit, to explore the heterogeneous characteristics of the coupling of China’s industrial agglomeration and regional economic resilience from 2005 to 2019. Additionally, by applying the perspectives of economic and geographic location, indicators were selected to analyze the associated influencing factors, including industrial externalities, new economic geographies, economic policy factors, and other aspects. We found that the overall coupling between industrial agglomeration and economic resilience increased over the study period, but with only a moderate level of coordination. Provinces with high, moderate, and low levels of coordination eventually emerged along a strip-like alternating pattern in space. The dependence increased with an increase in space, but was not significant, and there was a lack of benign interaction between the regions. With respect to interactivity between locations, the interaction of the east and the coast was the most active. There were lower levels of interaction between the west and inland regions. This further confirmed the significant temporal and spatial heterogeneity of the coupling. Environmental pollution, market consumption, the quality of space, and technological support significantly promoted the coupling; opening to the outside world did not. Specifically, with respect to economic location, market consumption and spatial quality had a significant positive effect on the eastern coupling. The center and west regions were significantly affected by economic density and market consumption, and the northeast region was affected by spatial quality and capital intensity. Concerning geographical location, market and technological forces strongly promoted interactions in both the coast and inland regions. The study found that both the government and the market need better guidance to effectively engage with and shape industrial agglomeration and economic resilience in a scientific, reasonable, localized, and distinctive manner. Springer Netherlands 2022-07-30 /pmc/articles/PMC9362362/ /pubmed/35966337 http://dx.doi.org/10.1007/s10668-022-02588-w Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Zheng, Ziyan Zhu, Yingming Pei, Yu Wang, Litao Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China |
title | Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China |
title_full | Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China |
title_fullStr | Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China |
title_full_unstemmed | Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China |
title_short | Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China |
title_sort | spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9362362/ https://www.ncbi.nlm.nih.gov/pubmed/35966337 http://dx.doi.org/10.1007/s10668-022-02588-w |
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