Location
260-055, Owen G. Glenn Building
Start Date
12-15-2014
Description
This paper 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 TripAdvisor.com that allows us to identify the causal effect with a difference-in-difference approach. Our key findings, first show that consumers’ ratings for the same restaurants are significantly higher in TripAdvisor after its adoption of the multidimensional rating system. Second, we show that restaurants with lower price level benefit more from rating system change. Third, we show that the ratings in single-dimensional rating system are similar to the lowest dimension in the multi-dimensional system. 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.
Recommended Citation
liu, ying; Chen, Pei-yu; and Hong, Yili, "The Value of Multi-dimensional Rating Systems: An Information Transfer View" (2014). ICIS 2014 Proceedings. 11.
https://aisel.aisnet.org/icis2014/proceedings/EconomicsandValue/11
The Value of Multi-dimensional Rating Systems: An Information Transfer View
260-055, Owen G. Glenn Building
This paper 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 TripAdvisor.com that allows us to identify the causal effect with a difference-in-difference approach. Our key findings, first show that consumers’ ratings for the same restaurants are significantly higher in TripAdvisor after its adoption of the multidimensional rating system. Second, we show that restaurants with lower price level benefit more from rating system change. Third, we show that the ratings in single-dimensional rating system are similar to the lowest dimension in the multi-dimensional system. 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.