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Samadhiya, Ashutosh, Agrawal, Rohit, Kumar, Anil, Yadav, Sanjeev and Garza-Reyes, Jose Arturo (2025) Can prescriptive analytics empower Metaverse for sustainable operations and supply chains? A text mining and introspective analysis. International Journal of Logistics Management. ISSN 0957-4093 (In Press)
Purpose: The arrival of the Metaverse is expected to revolutionize organizational practices, which substantially impact sustainability in logistics and supply chain. In addition, prescriptive analytics-based methodological improvements might make Metaverse self-sustaining. This study assesses the current reflective discussion about the function of prescriptive analytics in Metaverse. It proposes alternative streams for additional research in this area so that we can understand the relationship between Metaverse, prescriptive analytics, sustainable operations, and supply chain.
Design/methodology/approach: We use structural topic modeling (STM), a text-mining approach, to critically assess the literature and analyze 161 articles.
Findings: Primary and secondary topics were developed using STM findings for comparison. Also, a research framework is created by sketching out the study following the findings of the review. Finally, we conclude with a list of unanswered research issues that might serve as a starting point for future investigations into the role of prescriptive analytics in empowering Metaverse for sustainable operations.
Originality: This study provides original insights into how prescriptive analytics can drive sustainable operations through Metaverse, offering a roadmap for future empirical research in this emerging area.
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