Author(s)

Soo Kyoung Lee, Min-Joo Rah^*

Affiliation(s)

School of Education, Pusan National University, Busan, South Korea.

Corresponding Author

Min-Joo Rah

ABSTRACT

The integration of deep learning technologies into retail supply chain management marks a revolutionary transformation in how global retail organizations operate, optimize, and innovate. This comprehensive review examines the profound impact of deep learning across all aspects of retail supply chain operations, from demand forecasting and inventory optimization to logistics planning and customer experience enhancement. Through analysis of implementations across major global retailers, we document remarkable improvements in operational efficiency, including forecast accuracy improvements of 20-45%, inventory cost reductions of 25-35%, and transportation cost savings of 15-30%. Our review synthesizes findings from over 200 implementation cases across North America, Europe, and Asia, providing insights into successful deployment strategies, implementation challenges, and emerging opportunities. This work serves as both a theoretical framework and practical guide for retailers navigating the artificial intelligence revolution in supply chain management.

KEYWORDS

Deep learning; Retail supply chain; Logistics management; Digital transformation; Supply chain analytics; Retail operations

CITE THIS PAPER

Soo Kyoung Lee, Min-Joo Rah. Deep learning in retail supply chain management: an evolution. World Journal of Economics and Business Research. 2024, 2(2): 43-37. DOI: https://doi.org/10.61784/wjebr3024.

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