Exploring the relationship between artificial intelligence and resilience in manufacturing industrial chains: mechanisms, effects and empirical evidence
Sirui Liu, Yang Fu, Hanqi Song, Ping Han

TL;DR
This study explores how artificial intelligence boosts resilience in manufacturing chains using data from 30 Chinese provinces.
Contribution
The study reveals AI's direct and indirect effects on industrial resilience and identifies regional and nonlinear patterns.
Findings
AI significantly and robustly enhances manufacturing industrial chain resilience directly.
AI indirectly improves resilience by promoting regional economic development.
AI's impact is strongest in eastern China and follows a nonlinear pattern based on data development levels.
Abstract
Using panel data from 30 Chinese provinces for the period 2012–2023, this study systematically examines the mechanisms, nonlinear characteristics, and spatial heterogeneity of artificial intelligence’s impact on the resilience of manufacturing industrial chains. The results indicate that AI exerts a significant and robust direct positive effect on industrial chain resilience. Furthermore, AI indirectly enhances resilience by promoting regional economic development. The urbanization rate positively moderates this relationship, with a higher urbanization level amplifying AI’s enabling effect. A threshold analysis reveals that the influence of AI exhibits nonlinear characteristics based on the development level of data elements; beyond a certain threshold, its positive effect displays a pattern of “marginal increase.” Heterogeneity analysis shows that AI’s enabling effect varies…
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Taxonomy
TopicsRegional resilience and development · Supply Chain Resilience and Risk Management · Infrastructure Resilience and Vulnerability Analysis
