Journal of Management Information Systems

Volume 36 Number 4 2019 pp. 1347-1377

Information Processing on Online Review Platforms

Siering, Michael and Janze, Christian

ABSTRACT:

Online reviews represent an important decision aid for consumers. Therefore, the question of whether online reviews reflect the currently available information is of high importance. Nevertheless, previous research neglects information processing on online review platforms. We address this research gap and analyze whether restaurant health inspection results have an impact on the review generation process of online restaurant reviews. We find that while severe health inspection results lead to changes of online review star ratings, information processing depends on the current environment. We find indications for corrective actions after critical health inspections: on the one hand, the restaurant health score improves, which shows an increase in restaurant quality. On the other hand, we observe indications for an increased amount of fake reviews in case of poorly-graded restaurants. We contribute to theory by providing an understanding of the nature of information processing on online review platforms. For practitioners, our findings allow for an understanding of the dynamics of online review generation. Furthermore, we outline the importance of considering the risk of deceptive behavior.

Key words and phrases: online reviews, online review platforms, restaurant inspections, efficient market hypothesis, adaptive market hypothesis, event study, online deception, user-generated content