Whose AI matters? Examining the bilateral effects of AI capability orientation on supply chain resilience

Purpose This study employs the actor-partner interdependence model (APIM) to examine how supplier and buyer artificial intelligence capability orientations (AICO) differentially influence supply chain resilience (SCR), while considering the moderating effect of dependence asymmetry. Design/methodology/approach Analyzing 818 supplier-buyer dyadic pairings from the China Stock Market & Accounting Research (CSMAR) Database and annual report data, we constructed a supplier–buyer interdependence model. Findings Results reveal that when suppliers have a dependence advantage, their AI capability orientation positively impacts both parties’ resilience, while buyers’ AI capability orientation shows no significant effect. Conversely, when buyers hold the advantage, their AI capability orientation positively affects both parties’ resilience, while suppliers’ AI capability orientation has no significant impact. Originality/value This research illuminates the complex interplay among AI capability orientation, SCR and resource dependence, offering novel insights into the dynamic shifts in AI roles during disruptions. The findings provide a framework for developing effective SCR strategies and highlight AI’s critical role in navigating global supply chain complexities.

Authors

Publication Details

Journal
International Journal of Operations & Production Management
Published
2025-04-16
DOI
https://doi.org/10.1108/ijopm-09-2024-0790
Citations
14
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
31.17
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article

Whose AI matters? Examining the bilateral effects of AI capability orientation on supply chain resilience

Xianhao Xu, Chung‐Yean Chiang, Xingwei Lu, Fan Wu
14 citations
International Journal of Operations & Production Management
Supply Chain Resilience and Risk Management
31.17
article

Whose AI matters? Examining the bilateral effects of AI capability orientation on supply chain resilience

Xianhao Xu, Chung‐Yean Chiang, Xingwei Lu, Fan Wu
article en
14 citations

Abstract

Purpose This study employs the actor-partner interdependence model (APIM) to examine how supplier and buyer artificial intelligence capability orientations (AICO) differentially influence supply chain resilience (SCR), while considering the moderating effect of dependence asymmetry. Design/methodology/approach Analyzing 818 supplier-buyer dyadic pairings from the China Stock Market & Accounting Research (CSMAR) Database and annual report data, we constructed a supplier–buyer interdependence model. Findings Results reveal that when suppliers have a dependence advantage, their AI capability orientation positively impacts both parties’ resilience, while buyers’ AI capability orientation shows no significant effect. Conversely, when buyers hold the advantage, their AI capability orientation positively affects both parties’ resilience, while suppliers’ AI capability orientation has no significant impact. Originality/value This research illuminates the complex interplay among AI capability orientation, SCR and resource dependence, offering novel insights into the dynamic shifts in AI roles during disruptions. The findings provide a framework for developing effective SCR strategies and highlight AI’s critical role in navigating global supply chain complexities.

International Journal of Operations & Production ManagementVol. 45(8)
Openalex Percentile: Top 0%
Supply Chain Resilience and Risk Management
31.17
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Whose AI matters? Examining the bilateral effects of AI capability orientation on supply chain resilience — Xianhao Xu, Chung‐Yean Chiang, et al. · International Journal of Operations & Production Management (2025) | TGRS Research Map | TGRS