Online reviews and ratings help consumers learn more about a product. However, mixed findings have been found regarding the effects of ratings on consumer decision-making. Such lack of effect may be due to the limitation of single-dimensional ratings. This paper aims to explore whether multi-dimensional ratings help reconcile the mixed findings and empirically examines the value of multi-dimensional online rating system (versus single-dimensional online rating system) from an information transfer perspective. Our key identification strategy hinges on a natural experiment that took place on www.TripAdvisor.com (TripAdvsior) that allows us to identify the causal effect with a difference-in-difference approach. Our key findings, first show that ratings tend to be more dispersed and are trending down in single-dimensional rating system and provide support that consumers form more accurate expectation from multi-dimensional ratings and are therefore less likely to be disappointed (resulting in lower ratings) or “surprised” (leading to higher dispersion of ratings). Second, we show that lower priced restaurants benefit more from the rating system change. The average rating of low priced restaurants will increase in larger magnitude than that of high priced restaurants. Third, consumers rate a restaurant based on their experience in the least satisfied dimension in the single-dimensional rating system. However, in the multi-dimensional rating system, the rating reflect consumers’ overall experience. The results demonstrate the information value of multi-dimensional ratings. Our study provides important implications for a better design of online WOM systems to help consumers match their preferences with product/service attributes.
Poster number: 19