The Value of Multidimensional Rating Systems: Evidence from a Natural Experiment and Randomized Experiments

Online product ratings offer information on product quality. Scholars have recently proposed the potential of designing multidimensional rating systems to better convey information on multiple dimensions of products. This study investigates whether and how multidimensional rating systems affect consumer satisfaction (measured by product ratings), based on both observational data and two randomized experiments. Our identification strategy of the observational study hinges on a natural experiment on TripAdvisor when the website started to allow consumers to rate multiple dimensions of the restaurants, as opposed to only providing an overall rating, in January 2009. We further obtain rating data on the same set of restaurants from Yelp, which controls for the unobserved restaurant quality over time and allows us to identify the causal effect using a difference-in-differences approach. Results from the econometric analyses show that ratings in a single-dimensional rating system have a downward trend and a higher dispersion, whereas ratings in a multidimensional rating system are significantly higher and convergent. Findings from two randomized experiments suggest that the multidimensional rating system helps consumers find products that better fit their preferences and increases the confidence of their choices. We also show that the observed results cannot be explained by the priming effect due to rating system interface or a list of other alternative explanations. The combined evidence from the natural experiment and randomized experiments support the view that the multidimensional rating system enhances rating informativeness and provide implications for designing online rating systems that help consumers match their preferences with product attributes. Data and the online appendix are available at https://doi.org/10.1287/mnsc.2017.2852 . This paper was accepted by Anandhi Bharadwaj, information systems.