Exploring Heuristic cues for Consumer Perceptions of Online Reviews Helpfulness: the Case of Yelp.Com

Guopeng Yin, Li Wei, Wei Xu, Minder Chen
2014 Pacific Asia Conference on Information Systems  
With the prevalence of online reviews, consumers are more inclined to be exposed to an unwieldy glut of information. In contrast to the research on the outcomes of online reviews, recent studies have shifted attention to the antecedents of online reviews, particularly investigating what characteristics lead to a review that is perceived more helpful by online consumers. Our research model of online review helpfulness is built upon a rich stream of literatures demonstrating how people are
more » ... ed and influenced by information, especially the dual process theories. In this study, we specifically focus on the effect of heuristic factors: rating deviation with existing reviews' average rating, and peer recognitions of the reviewer including network centrality and "elite" status. The model is empirically tested based on 16343 reviews of hotels from Yelp.com using zero-inflated negative binomial regression. Empirical results indicated that, in addition to a review's content attributes, rating deviation and peer recognitions of the reviewer also have significant impacts on consumer perceptions of review helpfulness. These findings add new theoretical insights into the research of online review helpfulness, and offer practical implications for online review providers to have a better prediction of valuable reviews.
dblp:conf/pacis/YinWXC14 fatcat:r2nb4cativeftm3bcefkkrdpoe