How Does the Variance of Product Ratings Matter?

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.

Exploring a Mental Scaling Effect on Online Consumer Ratings: Identifications of Shopping Behaviors and Information Processing Rules

“…Researchers have verified basic reasoning, such as high ratings generally resulting in sales increase 7 , whereas others extended the scope of their study to other conditional factors, such as the spread of ratings 8 and product types 9 , which moderate the perception of ratings. The asymmetric effects between positive and negative reviews have also been observed 10 .…”

“…For example, when a consumer refers to a rating of 4.3 to value a product, the magnitude of the rating is perceived as 4.3, based on the dominant decimal system that our society has been using for centuries. This calculation mechanism is 8 …”

The influence of the source and valence of word-of-mouth information on post-failure and post-recovery evaluations

“…As discussed earlier, considerable research has shown that pre-purchase eWOM and WOM can influence customers' post-purchase evaluations (King et al 2014;Sun 2012;Kim and Gupta 2012;Mudambi and Schuff 2010;Gupta and Harris 2010;Zhang et al 2010). To account for these effects, several researchers have applied the availability-diagnosticity theory (Herr et al 1991;Bone 1995).…”

“…Much research on eWOM has examined the influence of valence on the value of the review (Kim and Gupta 2012), helpfulness of the review (Mudambi and Schuff 2010;Zhang et al 2010), persuasiveness (Zhang et al 2010;Park and Lee 2009), evaluation of the product (Kim and Gupta 2012), and customer demand (Sun 2012;Sonnier et al 2011;Li and Hitt 2008;Chevalier and Mayzlin 2006;see Floyd et al 2014 for review). In this study, we focus specifically on the customer evaluation process and propose that WOM valence will moderate the relationship between failure severity and post-failure satisfaction.…”

“…Customers frequently rely on pre-purchase word-of-mouth recommendations (WOM) to influence many types of purchase decisions (King et al 2014;Sun 2012;Kim and Gupta 2012;Kim and Ko 2012;Mudambi and Schuff 2010;Gupta and Harris 2010;Zhang et al 2010). Some experts estimate that pre-purchase WOM is the principal driver for 20-50 % of all purchases (Bughin et al 2010, p. 2).…”