Third-Party Product Review and Firm Marketing Strategy
Marketing Science
Using Online Conversations to Study Word-of-Mouth Communication
Marketing Science
Promotional Chat on the Internet
Marketing Science
When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry
Journal of Management Information Systems
Do online reviews matter? - An empirical investigation of panel data
Decision Support Systems
Buyer-Initiated vs. Seller-Initiated Information Revelation
Management Science
Pricing, Frills, and Customer Ratings
Marketing Science
Optimal Search for Product Information
Management Science
Using social software for enhancing IS talents' e-learning motivation
Proceedings of the 2013 annual conference on Computers and people research
The influence of online word-of-mouth on long tail formation
Decision Support Systems
Hi-index | 0.01 |
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.