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Circular economy (CE) is an interdisciplinary domain which establishes suitable relationships between economic growth and its surroundings for the sustainable application of natural assets. CE is one of the trending research topics that has received considerable attention in recent years. The objective of this study is to systematically review the publications in the intersection of Artificial Intelligence (AI) and CE through both bibliometric and network analyses. This includes exploring the existing research trends, identifying emerging themes, analyzing how AI is transforming CE domains, and discovering the future direction for AI integration in CE. A total of 821 data points employed in this study are extracted from the Scopus database for the period between 2011 to 2023. Bibliometric tools such as VOSviewer, Biblioshiny, and Gephi are used to generate bibliographic maps and networks, unveiling the publication trends, most influential authors, leading articles, top contributing institutions, total annual publications, and most prolific country. Along with citation patterns and co-citation analyses, PageRank analysis is applied to indicate the most scientifically and academically influential paper on CE. Further, bibliometric coupling of documents reveals six thematic clusters —waste management, sustainability, reverse logistics, recycling, reuse, and remanufacturing on the nexus of AI and CE. The study also highlights the upcoming trends of AI in CE and proposes a PRISM framework to outline the implementation of AI tools to build technical abilities, aiming at improved CE performance. Finally, the outcomes of this study can be used by future researchers, policymakers, and industry practitioners to guide future research on AI-enabled CE.
Raut et al. (Sun,) studied this question.
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