An analytical study on integrating Artificial Intelligence and Industry 4.0 technologies for supply chain resilience and sustainability

This study examines how the adoption of AI-driven predictive analytics (AIDPA) and Industry 4.0 (I4.0) technologies enhances supply chain resilience (SCR) and sustainable supply chain performance (SSCP) in the food manufacturing industry, with SCR serving as a mediating factor. Grounded in the Dynamic Capabilities View (DCV), the research employs a quantitative approach using data collected from 194 professionals working in the food manufacturing sector. Structural Equation Modeling (SEM) was employed to test the hypothesized relationships and assess both direct and mediating effects. The results reveal that AIDPA and I4.0 integration have a strong positive influence on both SCR and SSCP. Moreover, SCR plays a critical mediating role in linking technology adoption to sustainable supply chain performance, underscoring its strategic importance in driving sustainability transitions. The study contributes to the growing body of knowledge on the intersection of digital technologies, resilience, and sustainability, offering practical insights for organizations in developing economies seeking to leverage technological capabilities to achieve adaptability, competitiveness, and sustainable growth through the lens of dynamic capabilities.