AI-Enabled Predictive Analytics and Supply Chain Disruption Response Performance in Logistics Firms: Moderating Role of Data Governance Maturity

This study examines the links among AI enabled predictive analytics capability, real time logistics data integration, and supply chain disruption response performance in emerging market logistics firms while evaluating the moderating influence of data governance maturity. Drawing on organizational information processing theory and dynamic capabilities theory, it frames disruption response performance as the result of organizational capabilities that convert predictive intelligence and current integrated logistics information into timely, coordinated, and effective actions. Data governance maturity serves as a boundary condition that shapes whether integrated logistics data can be turned into stronger disruption responses. A quantitative cross sectional design gathered responses through a five point Likert scale questionnaire from 385 Vietnamese professionals knowledgeable about logistics operations, supply chain management, AI analytics, information technology, risk management, or data governance. IBM SPSS version 26 supported reliability assessment, exploratory factor analysis, and multiple linear regression, while Hayes’ Process Macro Model 1 examined the moderating effect. The findings show that AI enabled predictive analytics capability (β = 0.588) and real time logistics data integration (β = 0.415) significantly improve supply chain disruption response performance. Predictive analytics capability yields the stronger direct effect, underscoring the importance of anticipating disruption signals and operational consequences. Data governance maturity further reinforces the positive association between real time logistics data integration and disruption response performance through a significant interaction coefficient of 0.311. The results reveal that digital connectivity alone cannot guarantee effective disruption responses. Emerging market logistics firms must pair predictive analytics and current integrated data with clear ownership, standardized quality controls, secure access, continuous monitoring, and operational authority to act.