The Effect of Generative Artificial Intelligence–Driven Supply Chain on Circular Supply Chain Practices: Are Lean Supply Chain Management and Human Capital the Missing Links?

In dynamic environments and with increasing uncertainty in global supply chains, adopting contemporary practices and strategies such as the circular economy has become urgent and necessary. This study addresses a number of gaps in this regard by examining the impact of generative artificial intelligence–driven supply chain (GAISC) on both lean supply chain management (LSCM) and circular supply chain practices (CSCP) in Jordanian manufacturing companies, as well as the moderated mediation effects of LSCM and human capital (HC). Prior to data analysis and model testing, 180 responses were collected. Subsequently, the necessary tests were conducted to validate the measurement model and test the structural model using partial least squares‐structural equation modeling (PLS‐SEM). The study yielded several interesting results, with most hypotheses being accepted. GAISC had a strong and positive impact on both LSCM and CSCP, and LSCM had a positive impact on CSCP. On the other hand, the results revealed that LSCM mediated the positive relationship between GAISC and CSCP; however, the moderate effect of HC on the relationship between GAISC and LSCM was not supported, and therefore H5 and H6 were rejected. This research made a number of theoretical and practical contributions that helped address and bridge research gaps in the field of supply chain sustainability.