All Reviews are Not Created Equal: The Disaggregate Impact of Reviews and Reviewers at Amazon.Com

Abstract

Online product review networks help to transmit information that customers can use to evaluate product quality. The prior literature has found that, in the aggregate, better product reviews lead to higher sales. However, product review networks increasingly include an explicit social component that allows consumers to evaluate individual reviews based on the status of the reviewer and on the "helpfulness" of the review to the community.

In this research, we extend this literature by analyzing the impact of reviews at a disaggregate level. We find that reviews that the community finds helpful have a stronger influence on consumers' purchase decisions than other reviews do. Moreover, these reviews have a stronger impact on less popular books than on more popular books, where consumers may be able to use other outside information sources to form an opinion of the product.

Overall, our results suggest that the micro-level dynamics of community interactions are valuable in signaling quality over-and-above aggregate-level scores. One 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 consumers only have aggregate quality measures.

Keywords: electronic commerce, recommendation system, digital word-of-mouth, econometrics

JEL Classification: L86, M3, O30