Randomized trial investigates how AI capability enhances supply chain performance with integration strategies.
Purpose Drawing on the resource-based view and resource orchestration theory, this study investigates how AI capability, defined as a firm’s ability to deploy AI-based resources to enhance data processing and decision-making, interacts with downstream customer and upstream supplier integration to improve supply chain responsiveness and efficiency. This study further clarifies the distinct and differentiated pathways through which upstream and downstream integration shape the effectiveness of AI. Design/methodology/approach To test our conceptual model, we utilized survey data from 426 AI-adopting Chinese manufacturing firms. The hypothesized relationships were examined using hierarchical regression analysis to isolate the moderating effects of supply chain integration. Findings AI capability significantly enhances both supply chain responsiveness and supply chain efficiency. Customer integration strengthens the effect of AI capability on responsiveness, whereas supplier integration strengthens the effect on efficiency, indicating two distinct integration pathways through which AI creates supply chain value. Originality/value By the resource-based view and resource orchestration theory, this study clarifies how AI capability interacts with upstream and downstream integration to shape performance outcomes. The results offer actionable insights for managers seeking to align AI investments with appropriate integration strategies to build agile, efficient, and resilient supply chains.
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Zhong et al. (2026) studied this question.
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