Abstract

This paper provides a comprehensive synthesis of three decades of scholarly research on reverse supply chains by examining how the field has evolved and identifying promising directions for future research. Specifically, this study addresses two overarching research questions: (1) How has the reverse supply chain field evolved in terms of theoretical perspectives, technological adoption, and research focus over time? (2) What future research trajectories emerge from the literature regarding the role of digital technologies and artificial intelligence in reverse supply chains? To address these questions, a systematic literature review (SLR) is conducted to identify and select high-quality and relevant journal articles, followed by a rigorous content analysis to uncover dominant themes, conceptual shifts, and methodological trends. The analysis reveals six distinct evolutionary stages of reverse logistics research: the infancy stage, the golden age, the strategic stage, the multidisciplinary stage, industrial revolution stage, and artificial intelligence stage. Each stage is characterized by unique research foci, theoretical foundations, and operational challenges. In particular, the most recent stage highlights the growing integration of digital technologies, artificial intelligence, and sustainability considerations, reflecting a shift toward intelligent and system-oriented reverse logistics. Based on this evolutionary analysis, the paper develops a structured research agenda that outlines key theoretical, methodological, and technological opportunities for future investigations. This study contributes to the literature by offering a longitudinal and systematic perspective on the evolution of reverse logistics research and by providing an integrative framework that supports the advancement of future studies in an increasingly digital and sustainable context.

Keywords

  • Reverse supply chains artificial intelligence digitalization sustainability circular economy

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