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This paper examines the informational role of product ratings. We build a theoretical model in which ratings can help consumers figure out how much they would enjoy the product. In our model, a high average rating indicates a high product quality, whereas a high variance of ratings is associated with a niche product, one that some consumers love and others hate. Based on its informational role, a higher variance would correspond to a higher subsequent demand if and only if the average rating is low. We find empirical evidence that is consistent with the theoretical predictions with book data from Amazon.com and BN.com. A higher standard deviation of ratings on Amazon improves a book's relative sales rank when the average rating is lower than 4.1 stars, which is true for 35% of all the books in our sample. This paper was accepted by Pradeep Chintagunta, marketing.
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Monic Sun
Management Science
Stanford University
University of Southern California
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Monic Sun (Sat,) studied this question.
www.synapsesocial.com/papers/69de9d3d7ed287395e55a11a — DOI: https://doi.org/10.1287/mnsc.1110.1458