Reverse logistics (RL) is a fundamental component of the circular economy (CE) that supports the recovery, reuse, and recycling of products and materials. The growth of metaverse-connected technologies, including digital twins, VR/AR, and blockchain, creates new opportunities for virtualizing RL processes, increasing traceability, and improving decision-making. However, no methodological or comprehensive review of the intersection of RL, CE, and immersive technologies exists. To address this gap, this study provides a literature review and bibliometric analysis of 198 publications in the Scopus database from 2003 to 2025, following the SPAR-4-SLR protocol. Using performance analysis, keyword co-occurrence, bibliographic coupling, and thematic evolution methods, this study outlines six keyword clusters and seven bibliographic coupling clusters. The major themes include blockchain-based circularity, battery recovery from electric vehicles, streamlining the remanufacturing process, and the adoption of immersive technologies. The results highlight a transition from traditional digitization to immersive changes in RL–CE scholarship. This study provides a conceptual framework that integrates metaverse technologies with the sequential phases of RL, thereby offering managerial insights into transparency, efficiency, and sustainability. Furthermore, the analysis highlights the policy importance of extended producer responsibility (EPR) and design for disassembly (DfD). Finally, the review provides a synthesized conceptual map and a research agenda to drive metaverse-facilitated RL toward the CE paradigm.
Building similarity graph...
Analyzing shared references across papers
Loading...
Tran et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69f04e9b727298f751e7287e — DOI: https://doi.org/10.1007/s43621-026-03277-8
Toan Cong Tran
Thanh Thi Tuyet Le
Discover Sustainability
Ho Chi Minh City University of Technology
University of Economics Ho Chi Minh City
Industrial University of Ho Chi Minh City
Building similarity graph...
Analyzing shared references across papers
Loading...