Unpacking the power of user-generated videos in hospitality and tourism: a systematic literature review and future direction
Özet
We review user-generated video (UGV)-research in hospitality and tourism (H&T), provide an overview of its current-state, and suggest ways forward. We adopted a systematic literature review methodology and reviewed 66 articles with TCM (theory/context/methodology) framework. UGV-research focuses on (i) destination image perception, (ii) short-form videos and travel live-streaming, (iii) behavioral intentions, and (iv) crisis management. Theoretical development is diverse, given the descriptive nature of research questions, but it is still in its infancy. The context varies by H&T setting, type of social media platform, population, and country. Research methods and techniques range from traditional analysis to advanced machine learning or artificial intelligence-based quantitative approaches, predominantly qualitative methods.
Anahtar Kelimeler
Tam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Polat, Eray | |
| dc.contributor.author | Çelik, Fatih | |
| dc.contributor.author | Ibrahim, Blend | |
| dc.contributor.author | Köseoglu, Mehmet Ali | |
| dc.date.accessioned | 2026-10-22T10:22:38.171388121Z | |
| dc.date.available | 2026-10-22T10:22:38.171388121Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | We review user-generated video (UGV)-research in hospitality and tourism (H&T), provide an overview of its current-state, and suggest ways forward. We adopted a systematic literature review methodology and reviewed 66 articles with TCM (theory/context/methodology) framework. UGV-research focuses on (i) destination image perception, (ii) short-form videos and travel live-streaming, (iii) behavioral intentions, and (iv) crisis management. Theoretical development is diverse, given the descriptive nature of research questions, but it is still in its infancy. The context varies by H&T setting, type of social media platform, population, and country. Research methods and techniques range from traditional analysis to advanced machine learning or artificial intelligence-based quantitative approaches, predominantly qualitative methods. | |
| dc.identifier.doi | 10.1080/10548408.2023.2296655 | |
| dc.identifier.eissn | 1540-7306 | |
| dc.identifier.endpage | 914 | |
| dc.identifier.issn | 1054-8408 | |
| dc.identifier.issue | 9 | |
| dc.identifier.scopus | 2-s2.0-85181959808 | |
| dc.identifier.startpage | 894 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/gumushane/14380 | |
| dc.identifier.volume | 40 | |
| dc.identifier.wos | WOS:001138337600001 | |
| dc.language.iso | en | |
| dc.publisher | Routledge | |
| dc.relation.ispartof | Journal of Travel and Tourism Marketing | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | behavioral intention | |
| dc.subject | co-word analysis | |
| dc.subject | destination image | |
| dc.subject | short-form videos | |
| dc.subject | social media platforms | |
| dc.subject | systematic literature review | |
| dc.subject | TCM framework | |
| dc.subject | travel live-streaming | |
| dc.subject | User-generated content | |
| dc.subject | user-generated video | |
| dc.subject.classification | Hospitality, Leisure, Sport & Tourism | |
| dc.subject.classification | Social Sciences - Other Topics | |
| dc.subject.other | SOCIAL MEDIA | |
| dc.subject.other | INFORMATION | |
| dc.subject.other | STRATEGIES | |
| dc.subject.other | TIKTOK | |
| dc.subject.other | TRUST | |
| dc.title | Unpacking the power of user-generated videos in hospitality and tourism: a systematic literature review and future direction | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| rdl.citation.openalex | 55 | |
| rdl.citation.scopus | 61 | |
| rdl.citation.wos | 43 | |
| rdl.oa.status | closed | |
| rdl.source.index | SCOPUS | |
| rdl.source.index | WOS | |
| rdl.wos.index | Social Science Citation Index (SSCI) |
