IDEAS home Printed from https://ideas.repec.org/a/eee/ininma/v36y2016i6p929-944.html
   My bibliography  Save this article

Predicting hotel review helpfulness: The impact of review visibility, and interaction between hotel stars and review ratings

Author

Listed:
  • Hu, Ya-Han
  • Chen, Kuanchin

Abstract

The tourism industry has been strongly influenced by electronic word-of-mouth (eWOM) in recent years. Currently, there are only limited studies available that look into hotel review helpfulness. This present study addresses three hidden assumptions prevalent in online review studies: (1) all reviews are visible equally to online users, (2) review rating (RR) and hotel star class (HSC) affect review helpfulness individually with no interaction, and (3) characteristics of reviews and reviewer status stay constant.

Suggested Citation

  • Hu, Ya-Han & Chen, Kuanchin, 2016. "Predicting hotel review helpfulness: The impact of review visibility, and interaction between hotel stars and review ratings," International Journal of Information Management, Elsevier, vol. 36(6), pages 929-944.
    • Handle: RePEc:eee:ininma:v:36:y:2016:i:6:p:929-944
    DOI: 10.1016/j.ijinfomgt.2016.06.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0268401215301845
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijinfomgt.2016.06.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Zhiwei & Park, Sangwon, 2015. "What makes a useful online review? Implication for travel product websites," Tourism Management, Elsevier, vol. 47(C), pages 140-151.
    2. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    3. Pan, Yue & Zhang, Jason Q., 2011. "Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews," Journal of Retailing, Elsevier, vol. 87(4), pages 598-612.
    4. Chaves, Marcirio Silveira & Gomes, Rodrigo & Pedron, Cristiane, 2012. "Analysing reviews in the Web 2.0: Small and medium hotels in Portugal," Tourism Management, Elsevier, vol. 33(5), pages 1286-1287.
    5. Park, Sangwon & Nicolau, Juan L., 2015. "Asymmetric effects of online consumer reviews," Annals of Tourism Research, Elsevier, vol. 50(C), pages 67-83.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    2. Saito, Taiga & Takahashi, Akihiko & Koide, Noriaki & Ichifuji, Yu, 2019. "Application of online booking data to hotel revenue management," International Journal of Information Management, Elsevier, vol. 46(C), pages 37-53.
    3. Moro, Sérgio & Ramos, Pedro & Esmerado, Joaquim & Jalali, Seyed Mohammad Jafar, 2019. "Can we trace back hotel online reviews’ characteristics using gamification features?," International Journal of Information Management, Elsevier, vol. 44(C), pages 88-95.
    4. Srikanth Parameswaran & Pubali Mukherjee & Rohit Valecha, 2023. "I Like My Anonymity: An Empirical Investigation of the Effect of Multidimensional Review Text and Role Anonymity on Helpfulness of Employer Reviews," Information Systems Frontiers, Springer, vol. 25(2), pages 853-870, April.
    5. Ragini, J. Rexiline & Anand, P.M. Rubesh & Bhaskar, Vidhyacharan, 2018. "Big data analytics for disaster response and recovery through sentiment analysis," International Journal of Information Management, Elsevier, vol. 42(C), pages 13-24.
    6. Rongqin Liu & Yun Zhang & Chuan Luo & Shangyu Tan & Yunqu Gong, 2024. "Review content type and hotel review helpfulness: direct and moderating effects," Information Technology and Management, Springer, vol. 25(4), pages 383-406, December.
    7. Fink, Lior & Rosenfeld, Liron & Ravid, Gilad, 2018. "Longer online reviews are not necessarily better," International Journal of Information Management, Elsevier, vol. 39(C), pages 30-37.
    8. Jimenez-Marquez, Jose Luis & Gonzalez-Carrasco, Israel & Lopez-Cuadrado, Jose Luis & Ruiz-Mezcua, Belen, 2019. "Towards a big data framework for analyzing social media content," International Journal of Information Management, Elsevier, vol. 44(C), pages 1-12.
    9. Jiahua Du & Jia Rong & Sandra Michalska & Hua Wang & Yanchun Zhang, 2019. "Feature selection for helpfulness prediction of online product reviews: An empirical study," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-26, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yani Wang & Jun Wang & Tang Yao, 2019. "What makes a helpful online review? A meta-analysis of review characteristics," Electronic Commerce Research, Springer, vol. 19(2), pages 257-284, June.
    2. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Post-Print halshs-01923243, HAL.
    3. Zheng, Lili, 2021. "The classification of online consumer reviews: A systematic literature review and integrative framework," Journal of Business Research, Elsevier, vol. 135(C), pages 226-251.
    4. Srikanth Parameswaran & Pubali Mukherjee & Rohit Valecha, 2023. "I Like My Anonymity: An Empirical Investigation of the Effect of Multidimensional Review Text and Role Anonymity on Helpfulness of Employer Reviews," Information Systems Frontiers, Springer, vol. 25(2), pages 853-870, April.
    5. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Grenoble Ecole de Management (Post-Print) halshs-01923243, HAL.
    6. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    7. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    8. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Post-Print halshs-01923196, HAL.
    9. Xiaomo Liu & G. Alan Wang & Weiguo Fan & Zhongju Zhang, 2020. "Finding Useful Solutions in Online Knowledge Communities: A Theory-Driven Design and Multilevel Analysis," Information Systems Research, INFORMS, vol. 31(3), pages 731-752, September.
    10. Yi Feng & Yunqiang Yin & Dujuan Wang & Lalitha Dhamotharan & Joshua Ignatius & Ajay Kumar, 2023. "Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach," Annals of Operations Research, Springer, vol. 328(1), pages 387-418, September.
    11. Srivastava, Vartika & Kalro, Arti D., 2019. "Enhancing the Helpfulness of Online Consumer Reviews: The Role of Latent (Content) Factors," Journal of Interactive Marketing, Elsevier, vol. 48(C), pages 33-50.
    12. Arenas-Márquez, F.J. & Martínez-Torres, M.R. & Toral, S.L., 2021. "How can trustworthy influencers be identified in electronic word-of-mouth communities?," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    13. Zhu, Yongmin & Liu, Miaomiao & Zeng, Xiaohua & Huang, Pei, 2020. "The effects of prior reviews on perceived review helpfulness: A configuration perspective," Journal of Business Research, Elsevier, vol. 110(C), pages 484-494.
    14. Lien Thi Kim Nguyen & Hao-Hsuan Chung & Kristine Velasquez Tuliao & Tom M. Y. Lin, 2020. "Using XGBoost and Skip-Gram Model to Predict Online Review Popularity," SAGE Open, , vol. 10(4), pages 21582440209, December.
    15. Harrison-Walker, L. Jean & Jiang, Ying, 2023. "Suspicion of online product reviews as fake: Cues and consequences," Journal of Business Research, Elsevier, vol. 160(C).
    16. Miyea Kim & Jeongsoo Han & Mina Jun, 2020. "Do same-level review ratings have the same level of review helpfulness? The role of information diagnosticity in online reviews," Information Technology & Tourism, Springer, vol. 22(4), pages 563-591, December.
    17. Kübler, Raoul V. & Lobschat, Lara & Welke, Lina & van der Meij, Hugo, 2024. "The effect of review images on review helpfulness: A contingency approach," Journal of Retailing, Elsevier, vol. 100(1), pages 5-23.
    18. Zhang, Chenxi & Xu, Zeshui, 2024. "Gaining insights for service improvement through unstructured text from online reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    19. Dongpu Fu & Yili Hong & Kanliang Wang & Weiguo Fan, 2018. "Effects of membership tier on user content generation behaviors: evidence from online reviews," Electronic Commerce Research, Springer, vol. 18(3), pages 457-483, September.
    20. Babajide Abubakr Muritala & Maria-Victoria Sánchez-Rebull & Ana-Beatriz Hernández-Lara, 2020. "A Bibliometric Analysis of Online Reviews Research in Tourism and Hospitality," Sustainability, MDPI, vol. 12(23), pages 1-18, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ininma:v:36:y:2016:i:6:p:929-944. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-information-management .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.