Unlocking supply chain performance through AI-enabled integrating capabilities and environmental dynamism – a study using SEM-fsQCA approach

Abstract

This study aims to examine the role of artificial intelligence (AI)-enabled integrating capabilities (AIEIC) and environmental dynamism (ED) in enhancing supply chain agility (SCa) and customer integration (CI) for superior supply chain performance (SCp). The study further addresses the mediating roles of SCa and CI, adopting a human-centric perspective in which these mechanisms represent adaptive and relational responsiveness to improve SCp. The primary data were collected from 373 valid respondents and analysed the linear relationship primarily through “structural equation modelling (SEM)”; and “fuzzy set qualitative comparative analysis (fsQCA)” was used for non-linear configurational insights into high performance outcomes. This study draws on the dynamic capability view and contingency theory to provide theoretical support for the analyses and evidence from India. The study reveals that AIEIC and ED have a positive impact on SCp. SCa and CI were treated as human-centric responses, where SCa captures human-centric capabilities, and CI captures human-centric coordination to improve SCp. Additionally, the necessary conditions for fsQCA and the combined effect of all variables on solution consistency were examined, indicating that a high-performance outcome might be achieved in a dynamic environment even in the absence of AIEIC, highlighting the strong influence of human-centric responses. Given the current results, managers should prioritise human-centric mechanisms, such as job security for employees and customer responsiveness. Note that, in resource-constrained organisations where managers cannot afford AI investments, they should focus on human-centric solutions. The contribution of this study shifted from a technology-oriented solution to a human-centric approach, indicating that AIEIC performs better when integrated with SCa and CI in dynamic environments to improve SCp. By using both SEM and fsQCA, this study assesses the robustness of the interconnections among the study variables through multiple pathways.