Estimating the Effect of Online Consumer Reviews: An Application of Count Data Models

Abstract

This study estimates the effect of online consumers' star ratings on perceived evaluations of consumer reviews such as usefulness and enjoyment. The data includes 5090 online reviews of about 45 restaurants located in London and New York respectively. The results reveal curvilinear (U-shaped) relationships between star ratings and usefulness and enjoyment. That is, online consumers perceive extreme ratings (positive or negative) as more useful and enjoyable than moderate ratings. Additionally, the findings of this research indicate the usefulness of the negative binomial model, which allows researchers to manage the features of count data as well as address the heteroscedasticity in linear regression and the overdispersion problem in the Poisson regression model.