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The Economic Network Resilience of the Guanzhong Plain City Cluster, China: A network analysis from the evolutionary perspective

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  • Shanshan Ye
  • Zhu Qian

Abstract

This article applies the network analysis to evaluate the resilience of economic network in Guanzhong Plain City Cluster (GPCC) and examine the impact of network structural properties on economic resilience, thus providing an innovative research perspective and a theoretical framework for evaluating the economic resilience of the city cluster. A modified gravity model is introduced to construct the economic network. Three structural properties of the network, hierarchy, assortativity, and cohesion, are used to evaluate the resilience of the GPCC from 2008 to 2018 and illustrate the characteristics of the resilience. The results show that the economic network of the GPCC is strongly hierarchical with a growing trend, a declining disassortativity, and a weak cohesion. Although the network has formed a core‐peripheral structure, its hierarchy and disassortativity would result in low resilience and high vulnerability, at the risk of external shocks to the GPCC. The impact of the network structure on economic resilience is analyzed by using a regression model, which verifies the validity of applying the network theory to resilience analysis. The results suggest that improving the interactions and economic connections between core and peripheral cities will strengthen the resilience of the GPCC.

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  • Shanshan Ye & Zhu Qian, 2021. "The Economic Network Resilience of the Guanzhong Plain City Cluster, China: A network analysis from the evolutionary perspective," Growth and Change, Wiley Blackwell, vol. 52(4), pages 2391-2411, December.
  • Handle: RePEc:bla:growch:v:52:y:2021:i:4:p:2391-2411
    DOI: 10.1111/grow.12530
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    2. Yiwen Wang & Jiangang Xu & Di Liu & Yuye Zhou, 2023. "Analysis and Comparison of the Industrial Economic Resilience in the Taihu Lake Basin under the 2008 Financial Crisis and the 2018 Sino-US Trade War," Land, MDPI, vol. 12(2), pages 1-22, February.

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