Ambivalence as a Predictor of Online Review Helpfulness

Online platforms, such as Yelp and TripAdvisor, have facilitated ubiquitous and convenient access to a large number of online reviews about almost any product/service. However, they impose an information load on the consumers due to their large number of reviews. The review star rating is practiced to ameliorate consumers' information load. A review star rating shows the reviewer's overall evaluation of a product/service. Nonetheless, the extant research findings about the relationship between star rating and review helpfulness are mixed. Star rating, being a unidimensional bipolar measure, is unable to correctly capture the underlying evaluations of the review content. Our contention in this research is that the use of review ambivalence is a better predictor of review helpfulness than the traditional star rating. To that end, we provide the theoretical foundation and pertinent methodology to assess our research question.