Understanding the use of Virtual Reality in Marketing: a text mining-based review

Detalhes bibliográficos
Autor(a) principal: Loureiro, S. M. C.
Data de Publicação: 2018
Outros Autores: Guerreiro, J., Eloy, S., Langaro, D., Panchapakesan, P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/16949
Resumo: 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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spelling Understanding the use of Virtual Reality in Marketing: a text mining-based reviewVirtual realitySimulated realitiesMarketingText miningThe 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.Elsevier2018-12-13T12:03:15Z2019-11-09T00:00:00Z2019-01-01T00:00:00Z20192019-05-25T12:48:18Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/16949eng0148-296310.1016/j.jbusres.2018.10.055Loureiro, S. M. C.Guerreiro, J.Eloy, S.Langaro, D.Panchapakesan, P.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:41:44Zoai:repositorio.iscte-iul.pt:10071/16949Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:19:27.622096Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Understanding the use of Virtual Reality in Marketing: a text mining-based review
title Understanding the use of Virtual Reality in Marketing: a text mining-based review
spellingShingle Understanding the use of Virtual Reality in Marketing: a text mining-based review
Loureiro, S. M. C.
Virtual reality
Simulated realities
Marketing
Text mining
title_short Understanding the use of Virtual Reality in Marketing: a text mining-based review
title_full Understanding the use of Virtual Reality in Marketing: a text mining-based review
title_fullStr Understanding the use of Virtual Reality in Marketing: a text mining-based review
title_full_unstemmed Understanding the use of Virtual Reality in Marketing: a text mining-based review
title_sort Understanding the use of Virtual Reality in Marketing: a text mining-based review
author Loureiro, S. M. C.
author_facet Loureiro, S. M. C.
Guerreiro, J.
Eloy, S.
Langaro, D.
Panchapakesan, P.
author_role author
author2 Guerreiro, J.
Eloy, S.
Langaro, D.
Panchapakesan, P.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Loureiro, S. M. C.
Guerreiro, J.
Eloy, S.
Langaro, D.
Panchapakesan, P.
dc.subject.por.fl_str_mv Virtual reality
Simulated realities
Marketing
Text mining
topic Virtual reality
Simulated realities
Marketing
Text mining
description 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.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-13T12:03:15Z
2019-11-09T00:00:00Z
2019-01-01T00:00:00Z
2019
2019-05-25T12:48:18Z
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url http://hdl.handle.net/10071/16949
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0148-2963
10.1016/j.jbusres.2018.10.055
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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