UNDERSTANDING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON SUPPLY CHAIN MANAGEMENT

Abstract

The retail industry is experiencing a significant transformation driven by increasing complexity, competitive pressures, and evolving consumer preferences. Traditional statistical frameworks for performance evaluation and operational enhancement are giving way to innovative methodologies that push the sector beyond conventional boundaries. Manufacturers are bypassing intermediaries to engage directly with consumers, reshaping product markets and presenting both challenges and opportunities for retailers. In this dynamic landscape, the efficiency of supply chain orchestration emerges as a critical determinant of competitive advantage. Retail supply chains, historically viewed as cost centers, are now under pressure to prioritize speed, responsiveness, and cost-effectiveness. However, achieving these objectives often involves trade-offs and complexities. Operations research offers a systematic approach to addressing the multifaceted challenges inherent in retail supply chain management. By harnessing analytical tools and methodologies, retailers can optimize decision-making processes, improve operational efficiency, and advance strategic goals in a rapidly evolving marketplace. This paper investigates the evolving role of operations research in navigating the intricate dynamics of retail supply chain management. Drawing upon insights from recent studies and incorporating a case study on disposition decisions in reverse logistics, we aim to provide valuable insights to supply chain managers and researchers. Our findings facilitate informed decision-making, contributing to the advancement of sustainable supply chain practices within the retail sector.