Automated Return Reason Classification and Reverse Logistics Optimisation: AI-Driven Frameworks for Retail Returns Management Efficiency

Authors

  • Thomas Jensen Associate Professor of Computer Science, Aalborg University

Keywords:

automated return reason classification, reverse logistics optimisation, frameworks, retail returns management efficiency, machine learning

Abstract

Managing returns effectively is a pressing issue for both customers and retailers alike. The growing volume of returns, fluctuations in demand, and increasing customer habits of over-ordering make the flawless running of returns management an extremely complex task for retailers. Such retailers have to invest a lot of time and effort in returns management to ensure that more business comes their way; without this, they are bound to only focus on customer service.

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Published

31-12-2021

How to Cite

[1]
“Automated Return Reason Classification and Reverse Logistics Optimisation: AI-Driven Frameworks for Retail Returns Management Efficiency”, Human-Computer Interaction Persp., vol. 1, no. 2, pp. 50–60, Dec. 2021, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/hcip/article/view/784