All Reviews Are Not Created Equal: The Dissagregate Impact of Reviews and Reviewers at Amazon.com
2007-03-01T00:00:00Z (GMT) by
Online product review networks play an important role in Internet commerce by transmitting information that customers can use to evaluate physical products in a digitally mediated marketplace. These networks frequently include an explicit social component allowing consumers to view both how community members have rated individual product reviews and the social status of individual reviewers. Moreover, the prior literature has not analyzed the impact of these social cues on consumer behavior, focusing instead on the impact of aggregate review ratings. We extend this prior work by analyzing how these social factors impact consumer responses to disaggregate review information. To do this, we use a new dataset collected from Amazon.com’s customer reviews of books. This dataset allows us to control for the degree to which other community members found the review helpful, and the reputation of the reviewer in the community. We find that reviews that the community finds helpful have a stronger impact on consumer purchase decisions than other reviews do. Moreover, these reviews have a stronger impact on less popular books than more popular books, where consumers may be able to use other outside information sources to form an opinion of the product. We also find evidence consistent with the hypothesis that featured reviews have a stronger impact on consumer purchase decisions than other reviews do. Finally, contrary to our expectations, we do not find that more prominent members of the community have a stronger impact on consumer purchase decisions than other community members do. Overall, our results suggest that the micro-level dynamics of community interactions are valuable in signaling quality — over-and-above the aggregate-level summary quality scores. One important implication of this result is that the micro-level dynamics of reputation communities make it harder for self-interested parties to manipulate reviews versus an environment where an uninformative review from a new community member carries as much weight as an informative review from an established and respected community member.