The DOI matches its Crossref record; 178 of the 178 references it cites were found in a registry or an index.
Understanding the use of Virtual Reality in Marketing: A text mining-based review
Open accessAbstract
Abstract The current study intends to highlight the most relevant studies in simulated realities with special attention to VR and marketing, showing how studies have evolved over time and discussing the findings. A text-mining approach using a Bayesian statistical topic model called latent Dirichlet allocation is employed to conduct a comprehensive analysis of 150 articles from 115 journals, all indexed in Web of Science. The findings reveal seven relevant topics, as well as the number of articles published over time, the authors most cited in VR papers and the leading journals in each topic. The article also provides theoretical and practical implications and suggestions for further research.
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Cites
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The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
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User Acceptance of Information Technology: Toward A Unified View1
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Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Structural equation modeling in practice: A review and recommended two-step approach
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Cited by
Marketing in the Metaverse: Conceptual understanding, framework, and research agenda
Giang Barrera, K., & Shah, D. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2022.113420 · Cited by 674
Virtual and augmented reality: Advancing research in consumer marketing
Wedel, M., Bigné, E., & Zhang, J. (2020) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2020.04.004 · Cited by 565
Artificial intelligence in business: State of the art and future research agenda
Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2020.11.001 · Cited by 554
Self-citationDincelli, E., & Yayla, A. (2022) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2022.101717 · Cited by 490
Jang, B., Kim, M., Harerimana, G., Kang, S.-U., & Kim, J. W. (2020) · Applied Sciences · doi:10.3390/app10175841 · Cited by 442
“Recently, text classification has been applied in specialized fields such as sentiment analysis and clinical [33–35], law [36,37], healthcare [38–40], and business marketing [41,42].”
Method
Metadata
- Authors
- Loureiro, S. M. C., Guerreiro, J., Eloy, S., Langaro, D., & Panchapakesan, P.
- Venue
- Journal of Business Research
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 100
- Pages
- 514-530
- ISSN
- 0148-2963 (ISSN-L)
- OpenAlex
- W2900303671
- Cited by
- 320
- References
- 178
- FWCI
- 52.40
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Understanding the use of Virtual Reality in Marketing: A text mining-based review. https://app.cochat.ai/papers/10.1016/j.jbusres.2018.10.055
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- Loureiro, S. M. C., Guerreiro, J., Eloy, S., Langaro, D., & Panchapakesan, P. (2019). Understanding the use of Virtual Reality in Marketing: A text mining-based review. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2018.10.055
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
