The impact of artificial intelligence usage on supply chain resilience in manufacturing firms: a moderated mediation model

Purpose Manufacturing firms must strengthen their supply chain resilience to survive in turbulent business environments. This study explores how artificial intelligence (AI) can be leveraged to enhance supply chain resilience. Design/methodology/approach Drawing on organizational information processing theory, the research investigates the impact of AI usage on proactive and reactive supply chain resilience by fostering referent power in the context of demand dynamism. The study analyzes survey data from 285 Chinese manufacturing firms using structural equation modeling and regression analysis. Findings The results indicate that AI usage can enhance both proactive and reactive supply chain resilience. Referent power only mediates the relationship between AI usage and reactive supply chain resilience. Furthermore, this mediating effect is stronger under high-level demand dynamism. Originality/value This study highlights the value of AI usage in strengthening supply chain resilience and uncovers its underlying mechanisms. Theoretical and practical implications are discussed.

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Institutions

Publication Details

Journal
Journal of Manufacturing Technology Management
Published
2025-02-07
DOI
https://doi.org/10.1108/jmtm-07-2024-0379
Citations
13
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
28.94
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article

The impact of artificial intelligence usage on supply chain resilience in manufacturing firms: a moderated mediation model

Xiaochen Yue, Mary Kang, Yanming Zhang
13 citations
Journal of Manufacturing Technology Management
Supply Chain Resilience and Risk Management
28.94
article

The impact of artificial intelligence usage on supply chain resilience in manufacturing firms: a moderated mediation model

Xiaochen Yue, Mary Kang, Yanming Zhang
article en
13 citations

Abstract

Purpose Manufacturing firms must strengthen their supply chain resilience to survive in turbulent business environments. This study explores how artificial intelligence (AI) can be leveraged to enhance supply chain resilience. Design/methodology/approach Drawing on organizational information processing theory, the research investigates the impact of AI usage on proactive and reactive supply chain resilience by fostering referent power in the context of demand dynamism. The study analyzes survey data from 285 Chinese manufacturing firms using structural equation modeling and regression analysis. Findings The results indicate that AI usage can enhance both proactive and reactive supply chain resilience. Referent power only mediates the relationship between AI usage and reactive supply chain resilience. Furthermore, this mediating effect is stronger under high-level demand dynamism. Originality/value This study highlights the value of AI usage in strengthening supply chain resilience and uncovers its underlying mechanisms. Theoretical and practical implications are discussed.

Journal of Manufacturing Technology ManagementVol. 36(4)
Chongqing University (CN), Shanghai Jiao Tong University (CN), Dalian University of Technology (CN)
Openalex Percentile: Top 1%
Supply Chain Resilience and Risk Management
28.94
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The impact of artificial intelligence usage on supply chain resilience in manufacturing firms: a moderated mediation model — Xiaochen Yue, Mary Kang, et al. · Journal of Manufacturing Technology Management (2025) | TGRS Research Map | TGRS