A big data exploration of the informational and normative influences on the helpfulness of online restaurant reviews

With the proliferation of user generated online reviews, uncovering helpful restaurant reviews is increasingly challenging for potential consumers. Heuristics (such as “Likes”) not only facilitate this process but also enhance the social impact of a review on an Online Opinion Platform. Based on Dua...

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Bibliographic Details
Published in:Journal of business research 2021-03, Vol.125, p.354-367
Main Authors: Meek, Stephanie, Wilk, Violetta, Lambert, Claire
Format: Article
Language:English
Subjects:
Big data
Business schools
Dual process theory
Helpfulness
Online restaurant reviews
Restaurants
Social impact theory
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Summary:With the proliferation of user generated online reviews, uncovering helpful restaurant reviews is increasingly challenging for potential consumers. Heuristics (such as “Likes”) not only facilitate this process but also enhance the social impact of a review on an Online Opinion Platform. Based on Dual Process Theory and Social Impact Theory, this study explores which contextual and descriptive attributes of restaurant reviews influence the reviewee to accept a review as helpful and thus, “Like” the review. Utilising both qualitative and quantitative methodologies, a big data sample of 58,468 restaurant reviews on Zomato were analysed. Results revealed the informational factor of positive recommendation framing and the normative factors of strong argument quality and moderate recommendation ratings, influence the generation of a reviewee “Like”. This study highlights the important filtering function a heuristic can offer prospective customers which can also result in greater social impact for the Online Opinion Platform.
ISSN:0148-2963
1873-7978
DOI:10.1016/j.jbusres.2020.12.001