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

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.

Authors

Publication Details

Journal
Computers in Human Behavior Reports
Published
2024-09-05
DOI
https://doi.org/10.1016/j.chbr.2024.100483
Citations
23
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
26.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Brighton Nyagadza, Mohammad Wasiq, Abu Bashar, Irfanullah Khan
23 citations
Computers in Human Behavior Reports
Digital Marketing and Social Media
26.04
article

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

Brighton Nyagadza, Mohammad Wasiq, Abu Bashar, Irfanullah Khan
article en
23 citations

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.

Computers in Human Behavior ReportsVol. 16
Openalex Percentile: Top 0%
Digital Marketing and Social Media
26.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.