Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigation

Abstract

This study is a comprehensive retrospective bibliometric and topic modelling analysis of customer engagement within the metaverse. We carefully investigated a sample of 409 articles extracted from the Scopus database and used in this analysis. The aim was to explore the evolution, current state, and emerging trends in this rapidly evolving field. Utilizing advanced bibliometric tools including Biblioshiny and ScientoPy, alongside network visualisation software VOSviewer, we systematically mapped the intellectual landscape, identifying key publications, authors, and institutions that have significantly contributed to the discourse. Furthermore, through machine learning-based Latent Dirichlet Allocation (LDA) analysis, we dissected the thematic structure of the literature, revealing the predominant topics and their interrelations. Our findings highlighted the dynamic nature of customer engagement strategies in the metaverse, emphasizing Design of Immersive Platforms, Personalisation & Customization, and the Interaction & Participation implications of virtual interactions. This study not only synthesizes existing knowledge but also uncovers gaps in the literature, suggesting directions for future research. By providing a holistic view of the domain, this research serves as a valuable resource for academics, practitioners, and policymakers interested in the intersection of customer engagement and virtual environments.

Keywords

• Customer engagement
• Metaverse
• Bibliometric
• Topic modelling
• LDA analysis
• VOSviewer