UNDERSTANDING HOW AI-DRIVEN ANALYTICS AND REAL TIME MONITORING SHAPE SUPPLY CHAIN RESILIENCE THROUGH TRANSPARENCY AND AGILITY

Abstract

Supply chain disruptions have intensified interest in understanding how digital technologies support organizational resilience under uncertainty. This study aims to examine how AI-powered analytics and real-time monitoring contribute to supply chain resilience through information transparency, while accounting for the moderating role of organizational agility. Using a quantitative, cross-sectional design, data were collected from managerial personnel in manufacturing firms and analyzed using partial least squares structural equation modeling. The findings reveal that AI-powered analytics and real-time monitoring significantly enhance supply chain resilience, both directly and indirectly through information transparency. Information transparency emerges as a critical mediating mechanism, while organizational agility strengthens its impact on resilience. The results extend Dynamic Capability Theory by demonstrating how digital sensing, transparent information flows, and adaptive reconfiguration jointly shape resilient outcomes