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The Determinants of Helpful Hotel Reviews: A Social Influence Perspective

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  • Yukyung Son

    (Department of Business Administration, Graduate School, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Republic of Korea)

  • Kyungmo Kang

    (Department of Big Data Analytics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Republic of Korea)

  • Ilyoung Choi

    (Department of Big Data Analytics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Republic of Korea)

  • Jaekyeong Kim

    (Department of Big Data Analytics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Republic of Korea
    School of Management, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Republic of Korea)

Abstract

Online hotel reviews regarding specific experiences and the sensibility of hotel reviewers are important sources of information for consumers who want to book hotels in the future. However, since thousands of reviews are written for one hotel, it is practically impossible for customers to read all the reviews. To alleviate this problem, OTAs (online travel agencies) provide a helpful vote of reviews, helping customers to quickly find helpful reviews without much effort. Therefore, in this study, a ZINB (zero-inflated negative binomial regression) was performed to investigate factors that influence the helpfulness of hotel reviews using the social influence theory. As a result of the analysis, it was found that location, service, and value of the hotel, alongside normative influencing factors and the length of the review (including informational influencing factors), affect the helpfulness of the review regardless of the city. The results of this study are expected to help hotel managers to take remedial action on negative reviews and strengthen the promotion of positive reviews, potentially helping to increase customer satisfaction.

Suggested Citation

  • Yukyung Son & Kyungmo Kang & Ilyoung Choi & Jaekyeong Kim, 2022. "The Determinants of Helpful Hotel Reviews: A Social Influence Perspective," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14881-:d:969267
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    References listed on IDEAS

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    1. Meek, Stephanie & Wilk, Violetta & Lambert, Claire, 2021. "A big data exploration of the informational and normative influences on the helpfulness of online restaurant reviews," Journal of Business Research, Elsevier, vol. 125(C), pages 354-367.
    2. 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.
    3. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Grenoble Ecole de Management (Post-Print) halshs-01923196, HAL.
    4. Burnkrant, Robert E & Cousineau, Alain, 1975. "Informational and Normative Social Influence in Buyer Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(3), pages 206-215, December.
    5. Filieri, Raffaele, 2015. "What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM," Journal of Business Research, Elsevier, vol. 68(6), pages 1261-1270.
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