Whose AI matters? Examining the bilateral effects of AI capability orientation on supply chain resilience
Xingwei Lu et al.
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.
14 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.62 × 0.4 = 0.25 |
| M · momentum | 0.85 × 0.15 = 0.13 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.