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Cited by 640

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Hospitality and Tourism Online Reviews: Recent Trends and Future Directions

Schuckert, Markus, Liu, Xianwei, Law, Rob·2015·Journal of Travel & Tourism Marketing

Abstract

In view of the increasing popularity of online reviews and their significant impact on individual buying behavior as well as on the supply side, this study reviewed and analyzed articles related to online reviews in tourism and hospitality published in academic journals between 2004 and 2013. Based on a keyword-driven search and a content analysis, 50 articles were identified as relevant and classified into five topics. The findings revealed that (a) more than half of the analyzed articles focus on hotels and apply empirical methods based on secondary data, (b) more attention has been paid to the relationship between online reviews and online buying as well as satisfaction and online management, and (c) opinion mining of online reviews, motivation to post reviews, and the role of reviews are evenly distributed. This paper also discussed significant topical and methodological trends, contributes to an overall understanding of existing research and its limitation.

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Metadata

Authors
Schuckert, M., Liu, X., & Law, R.
Venue
Journal of Travel & Tourism Marketing
Published
2015-07-04
Volume
32
Issue
5
Pages
608-621
ISSN
  • 1054-8408 (ISSN-L)
  • 1540-7306
OpenAlex
W2114011738
Cited by
640
References
11
FWCI
131.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Hospitality and Tourism Online Reviews: Recent Trends and Future Directions. https://app.cochat.ai/papers/10.1080/10548408.2014.933154
The paper
Schuckert, M., Liu, X., & Law, R. (2015). Hospitality and Tourism Online Reviews: Recent Trends and Future Directions. Journal of Travel & Tourism Marketing. https://doi.org/10.1080/10548408.2014.933154

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.