Research on the impact of artificial intelligence on the the manufacturing industry chain resilience

Strengthening the robustness and the stability of industrial chains is not only a necessary pathway to achieving the strategic goals of China's new development paradigm but also a fundamental pillar in building a modern economic system with Chinese characteristics. Drawing on panel data from 30 Chinese provinces spanning 2011 to 2022, this study constructs index systems for artificial intelligence (AI) and manufacturing industry chain resilience (Mir) using the entropy weight method. It systematically examines the effects of AI on Mir and its underlying mechanisms. The key findings are as follows: AI significantly enhances Mir, a result confirmed through multiple robustness tests; Mechanism analysis reveals that AI improves Mir primarily through technological innovation effects and digital empowerment effects; Threshold effects indicate that AI's impact on Mir exhibits nonlinear characteristics under varying levels of AI development and digital infrastructure; Heterogeneity analysis shows a pronounced structural divergence in AI's resilience-enhancing effects, with stronger technological empowerment observed in high-resilience cluster, dimensions of adaptive recovery and innovative reconfiguration, and export-oriented industry chains. This study offers a novel theoretical perspective and methodological framework for assessing Mir within the new development paradigm.

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Publication Details

Journal
Scientific Reports
Published
2025-09-29
DOI
https://doi.org/10.1038/s41598-025-18956-1
Citations
2
Primary Topic
Regional resilience and development
Type
article
Field-Weighted Citation Impact
6.26

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article

Research on the impact of artificial intelligence on the the manufacturing industry chain resilience

Qiangqiang He, Piyapatr Busababodhin, Guoqing Chen, Wenjing Li et al.
2 citations
Scientific Reports
Regional resilience and development
6.26
article

Research on the impact of artificial intelligence on the the manufacturing industry chain resilience

Qiangqiang He, Piyapatr Busababodhin, Guoqing Chen, Wenjing Li, Xiangling He
article en
2 citations

Abstract

Strengthening the robustness and the stability of industrial chains is not only a necessary pathway to achieving the strategic goals of China's new development paradigm but also a fundamental pillar in building a modern economic system with Chinese characteristics. Drawing on panel data from 30 Chinese provinces spanning 2011 to 2022, this study constructs index systems for artificial intelligence (AI) and manufacturing industry chain resilience (Mir) using the entropy weight method. It systematically examines the effects of AI on Mir and its underlying mechanisms. The key findings are as follows: AI significantly enhances Mir, a result confirmed through multiple robustness tests; Mechanism analysis reveals that AI improves Mir primarily through technological innovation effects and digital empowerment effects; Threshold effects indicate that AI's impact on Mir exhibits nonlinear characteristics under varying levels of AI development and digital infrastructure; Heterogeneity analysis shows a pronounced structural divergence in AI's resilience-enhancing effects, with stronger technological empowerment observed in high-resilience cluster, dimensions of adaptive recovery and innovative reconfiguration, and export-oriented industry chains. This study offers a novel theoretical perspective and methodological framework for assessing Mir within the new development paradigm.

Scientific ReportsVol. 15(1)
Xihua University (CN), Mahasarakham University (TH), Chongqing University (CN), Chengdu Medical College (CN), Chengdu Jincheng College
Ministry of Education of the People's Republic of China
Openalex Percentile: Top 4%
Regional resilience and development
6.26
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