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Usefulness, funniness, and coolness votes of viewers: An analysis of social shoppers’ online reviews

In Lee (Department of Computer Sciences, Western Illinois University, Macomb, Illinois, USA)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 14 May 2018

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Abstract

Purpose

The purpose of this paper is to investigate the relationships between five characteristics of social shoppers’ online reviews (the number of all reviews made by a reviewer, the number of friends of a reviewer, the review score, the number of review words, and images/photos) and the usefulness, funniness, and coolness to viewers for the restaurant businesses and the health and wellness businesses.

Design/methodology/approach

A sample of 1,114 online reviews of social shoppers was collected from Yelp.com. A zero-inflated Poisson regression was used due to a high number of zero votes in the dependent variables for usefulness, funniness, and coolness. The regression identified the review characteristics that are strongly associated with the number of usefulness, funniness, and coolness votes made by viewers.

Findings

The analysis shows that for the health and wellness businesses, all three dependent variables (usefulness, funniness, and coolness) have the number of reviews, the number of friends, and the number of words as significant independent variables. The results indicate that a reviewer who has more friends and is more experienced in giving reviews is likely to be more influential in generating a perceived value of the online review. The analysis also shows that all three dependent variables of the restaurant businesses have the number of words as a significant independent variable. It is found that there is a negative relationship between the review score and the usefulness votes for both restaurant businesses and health and wellness businesses. The effect of the review score on the coolness votes was not consistent.

Research limitations/implications

This study is the first research attempt in understanding social shoppers’ online reviews and their usefulness, funniness, and coolness to viewers, and therefore makes significant contributions to research and practice. The comparison was made between restaurant businesses and health and wellness businesses. The result indicates that for the health and wellness businesses, managers need to pay attention to social shoppers with a high number of friends and high number of words in a review. It is also noted that it is necessary to analyze review characteristics separately for each business type. However, as is typical in many empirical studies, this study is not without limitations. While the author limited the analysis of social shoppers’ online reviews to the five characteristics, additional variables may influence the number of votes, too. This study is limited to social shoppers’ reviews and the findings may not be generalized to regular customers’ online reviews. Future research should also examine whether similar results can be obtained at other review sites such as TripAdvisor and Zagat.

Originality/value

Despite the potential significance of social shoppers’ online reviews, the critical mass of empirical studies still lacks in this area. For a more comprehensive interpretation of review characteristics, this study develops hypotheses based on the literature review on electronic word of mouth and source credibility models and investigates the effect of the five review characteristics on the viewers’ perceived usefulness, funniness, and coolness. Unlike previous studies focused on a single business type, this study compares the results obtained for restaurant businesses and health and wellness businesses and demonstrates that viewers in each business type respond differently to social shoppers’ online reviews.

Keywords

Acknowledgements

The author offers special thanks to anonymous reviewers for their valuable comments and suggestions.

Citation

Lee, I. (2018), "Usefulness, funniness, and coolness votes of viewers: An analysis of social shoppers’ online reviews", Industrial Management & Data Systems, Vol. 118 No. 4, pp. 700-713. https://doi.org/10.1108/IMDS-04-2017-0151

Publisher

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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