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Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces

The spatial correlation pattern of economic resilience is an important proposition for China’s sustainable economic development. This paper measures the economic resilience of 31 provinces in China from 2012 to 2020, and explores the spatial correlation of economic resilience from the overall, group...

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Autores principales: Wang, Huiping, Ge, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Palgrave Macmillan UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243094/
https://www.ncbi.nlm.nih.gov/pubmed/37305355
http://dx.doi.org/10.1057/s41599-023-01783-y
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author Wang, Huiping
Ge, Qi
author_facet Wang, Huiping
Ge, Qi
author_sort Wang, Huiping
collection PubMed
description The spatial correlation pattern of economic resilience is an important proposition for China’s sustainable economic development. This paper measures the economic resilience of 31 provinces in China from 2012 to 2020, and explores the spatial correlation of economic resilience from the overall, group and individual perspectives and its influencing factors. The results show that first, a tightly ordered hierarchy of economic resilience formed in each province of China after 2016. Among them, Jiangsu, Shandong, Guangdong, Hubei, and Shaanxi are the most important clustering points and radiation centers in the spatial correlation framework of economic resilience. Second, being adjacent to marginal and core provinces will maintain the province’s centrality index category to the greatest extent, while being adjacent to sub-core and general provinces leads the province to gain more opportunities for upward transfer. Third, the essence of the interprovincial economic resilience subordination linkage in China is manifested in the aggregation of city clusters or economic circles. The northern economic resilience linkage system with the Bohai Rim as the core contains more provinces but is less stable. Provinces located in the Yangtze River Delta region are the opposite. Fourth, the proximity of geographical location and the difference in human capital level drive the formation of spatial association networks, while the difference in external openness and the difference in physical capital inhibit the formation of networks.
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spelling pubmed-102430942023-06-06 Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces Wang, Huiping Ge, Qi Humanit Soc Sci Commun Article The spatial correlation pattern of economic resilience is an important proposition for China’s sustainable economic development. This paper measures the economic resilience of 31 provinces in China from 2012 to 2020, and explores the spatial correlation of economic resilience from the overall, group and individual perspectives and its influencing factors. The results show that first, a tightly ordered hierarchy of economic resilience formed in each province of China after 2016. Among them, Jiangsu, Shandong, Guangdong, Hubei, and Shaanxi are the most important clustering points and radiation centers in the spatial correlation framework of economic resilience. Second, being adjacent to marginal and core provinces will maintain the province’s centrality index category to the greatest extent, while being adjacent to sub-core and general provinces leads the province to gain more opportunities for upward transfer. Third, the essence of the interprovincial economic resilience subordination linkage in China is manifested in the aggregation of city clusters or economic circles. The northern economic resilience linkage system with the Bohai Rim as the core contains more provinces but is less stable. Provinces located in the Yangtze River Delta region are the opposite. Fourth, the proximity of geographical location and the difference in human capital level drive the formation of spatial association networks, while the difference in external openness and the difference in physical capital inhibit the formation of networks. Palgrave Macmillan UK 2023-06-05 2023 /pmc/articles/PMC10243094/ /pubmed/37305355 http://dx.doi.org/10.1057/s41599-023-01783-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wang, Huiping
Ge, Qi
Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces
title Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces
title_full Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces
title_fullStr Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces
title_full_unstemmed Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces
title_short Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces
title_sort spatial association network of economic resilience and its influencing factors: evidence from 31 chinese provinces
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243094/
https://www.ncbi.nlm.nih.gov/pubmed/37305355
http://dx.doi.org/10.1057/s41599-023-01783-y
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