Artificial Intelligence In Reverse Logistics: A Systematic Literature Review
Abstract
The growing interest in recent years in the transition to a circular economy has also increased the importance of reverse logistics systems. At the same time, developments in artificial intelligence are impacting supply chain operations by streamlining decision-making. This study aims to conduct a systematic literature review to examine the impact of artificial intelligence on reverse logistics in the context of the circular economy and to provide a comprehensive synthesis of existing literature on its application. Using the Scopus database, relevant articles were selected with the keywords "Artificial Intelligence," "reverse logistics," and "circular economy."
Descriptive and thematic analyses were conducted on the final sample of articles after applying the inclusion and exclusion criteria. The results show that important reverse logistics tasks, such as return prediction, waste sorting and classification, routing optimization, and product recovery decision-making, are increasingly using artificial intelligence techniques. The findings also demonstrate how quickly research in this field has expanded in recent years, which is indicative of the growing significance of digital technology for sustainable supply chain management.
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