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...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Computers in Human Behavior Reports |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2451958824001167 |
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| author | Mohammad Wasiq Abu Bashar Irfanullah Khan Brighton Nyagadza |
| author_facet | Mohammad Wasiq Abu Bashar Irfanullah Khan Brighton Nyagadza |
| author_sort | Mohammad Wasiq |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-acb5dd73597d45a69ff4e461e221a7b3 |
| institution | OA Journals |
| issn | 2451-9588 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computers in Human Behavior Reports |
| spelling | doaj-art-acb5dd73597d45a69ff4e461e221a7b32025-08-20T01:57:56ZengElsevierComputers in Human Behavior Reports2451-95882024-12-011610048310.1016/j.chbr.2024.100483Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigationMohammad Wasiq0Abu Bashar1Irfanullah Khan2Brighton Nyagadza3College of Administration and Financial Sciences, Saudi Electronic University, Riyadh, 11673, Saudi ArabiaDepartment of Management and Marketing, College of Business, University of Bahrain, Sakhir, Manama, BahrainDepartment of Management Studies, Echelon Institute of Technology, Faridabad, 121101, IndiaYork St John University, London Campus, London, England, United Kingdom; Korea University Business School, Korea University, Seoul, South Korea; Corresponding author. York St John University, London Campus, London, England, United Kingdom.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.http://www.sciencedirect.com/science/article/pii/S2451958824001167Customer engagementMetaverseBibliometricTopic modellingLDA analysisVOSviewer |
| spellingShingle | Mohammad Wasiq Abu Bashar Irfanullah Khan Brighton Nyagadza Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigation Computers in Human Behavior Reports Customer engagement Metaverse Bibliometric Topic modelling LDA analysis VOSviewer |
| title | Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigation |
| title_full | Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigation |
| title_fullStr | Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigation |
| title_full_unstemmed | Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigation |
| title_short | Unveiling customer engagement dynamics in the metaverse: A retrospective bibliometric and topic modelling investigation |
| title_sort | unveiling customer engagement dynamics in the metaverse a retrospective bibliometric and topic modelling investigation |
| topic | Customer engagement Metaverse Bibliometric Topic modelling LDA analysis VOSviewer |
| url | http://www.sciencedirect.com/science/article/pii/S2451958824001167 |
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