ECIS 2020 Research Papers

Abstract

Online reviews play a considerable role in reducing the information asymmetry between sellers and potential consumers. Despite the rich body of literature on online reviews and rating behaviors, little is known about the influence that the ease (or difficulty) involved in evaluating a product or service has on ratings. Similarly, certain product or service characteristics are easier to review and evaluate than others. In this paper we investigate the potential rating differences that arise from the ease of evaluation, both on a category and on an attribute level. In two distinct studies we analyze datasets from, respectively, Yelp (category level) and Google Maps (attribute level) and conduct linear regression with fixedeffects. Our results suggest that ratings of easy-to-evaluate product and service categories are more extreme than ratings of difficult-to-evaluate categories, whereas this does not hold for attributes. These contrasting results between category and attribute level reveal that the impact of ease of evaluation cannot be fully explained by expectation-disconfirmation theory and, therefore, we briefly discuss alternative theoretical explanations. Our results also have important practical implications for platforms offering goods and services that differ in ease of evaluation, in order to redress the biases created by these differences in rating behaviors.

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