How Does the Variance of Product Ratings Matter?

Monic Sun ()
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Monic Sun: Graduate School of Business, Stanford University, Stanford, California 94305; and Marshall School of Business, University of Southern California, Los Angeles, California 90089

Management Science, 2012, vol. 58, issue 4, 696-707

Abstract: 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.

Keywords: information transmission; product ratings; social media; user-generated content (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (188)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:58:y:2012:i:4:p:696-707

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