Mitigating Effect of Regional Textile Industry Chain Resilience on Economic Fluctuations
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Abstract
Despite increasingly frequent disruptions in global supply chains, systematic quantitative research and regional comparisons on how textile industry chain resilience mitigates external economic shocks remain limited. This study constructs a three-dimensional resilience evaluation framework incorporating supply stability, synergy strength, and recovery speed based on input–output tables and enterprise linkage data, and quantifies the overall resilience level using the entropy method. Complex network analysis is employed to identify key nodes and shock transmission paths within the industrial chain, revealing structural vulnerabilities and propagation characteristics. Furthermore, a spatial Durbin model is developed to establish a regional spatial response framework that captures both direct and indirect marginal effects of resilience enhancement on economic fluctuations from local and neighboring perspectives, forming an integrated “measurement–identification–response” methodology. Such network-oriented modeling also provides useful references for distributed information transmission and resilient infrastructure optimization in intelligent electromagnetic and communication systems. Experimental results show that industry chain resilience is negatively correlated with GDP volatility (correlation coefficient of -0.112), while resilience enhancement reduces economic volatility across eight provinces. The total effects in Jiangsu and Guangdong reach 5.0%, with more than 50% of the mitigation benefit attributed to industrial restructuring, demonstrating that strengthened regional resilience effectively suppresses economic shocks and generates significant spatial spillover effects.
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