dc.contributor.author | Cai, Yanting | |
dc.contributor.author | Li, Gang | |
dc.contributor.author | Wen, Long | |
dc.contributor.author | Liu, Chang | |
dc.date.accessioned | 2024-05-07T03:12:55Z | |
dc.date.available | 2024-05-07T03:12:55Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | https://thuvienso.hoasen.edu.vn/handle/123456789/15208 | |
dc.description | International Journal of Hospitality Management 117 (2024) 103633 | vi |
dc.description.abstract | Big data contain a vast amount of information which is valuable for researchers and decision-makers both in
normal and crisis situations. This bibliometric study aims to present the progress, theoretical foundations, and
intellectual structure of big data analytics in the hospitality and tourism research domain. Literature records
were collected via the Web of Science and screened to maximize relevance. The overall literature dataset
included 1184 papers, comprising both review and empirical articles. From this dataset, 47 publications related
to the COVID-19 pandemic were identified and formed a sub-dataset to capture the specific research focuses
during the crisis. The research themes and their evolutionary paths were identified by keyword clustering and
keyword Time Zone analysis. Co-citation analysis was implemented to visualize the intellectual structure. Based
on the systematic review, this study proposes future research directions. | vi |
dc.language.iso | en | vi |
dc.publisher | Elservier | vi |
dc.subject | Big data analytics,Hospitality and Tourism,Scientometric analysis,Intellectual structure,Future directions | vi |
dc.title | Intellectual landscape and emerging trends of big data research in hospitality and tourism: A scientometric analysis | vi |
dc.type | Article | vi |