Understanding online product ratings: A customer satisfaction model. (November 2015) - Engler, Tobias H.; Winter, Patrick; Schulz, Michael
Abstract: Online product ratings have become a major information source for customers, retailers, and manufacturers. Both practitioners and researchers predominantly interpret them as a reflection of product quality. We argue that they in fact represent the customer's satisfaction with the product. Accordingly, we present a customer satisfaction model of online product ratings which incorporates the customer's pre-purchase expectations and actual product performance as determinants of ratings. We validate our model by applying it to two datasets collected at the German website ofAmazon.com . The results indicate that both factors have a significant influence on online product ratings, supporting the proposed interpretation of ratings. Highlights: We refine the current understanding of online ratings. The baseline of online ratings is built by expectations and product performance. We validate our model by applying it to datasets collected on the website of Amazon. We propose an expectation based rating system for online shops.