The Value of Multi-Dimensional Rating System: An Information Transfer View

32 Pages Posted: 11 Nov 2014

See all articles by Ying Liu

Ying Liu

Arizona State University (ASU) - Department of Information Systems

Pei-Yu Chen

Arizona State University (ASU) - Department of Information Systems

Yili Hong

Arizona State University (ASU) - W.P. Carey School of Business

Date Written: November 10, 2014

Abstract

Online reviews and ratings help consumers learn more about products. 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 examine 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 (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 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 ratings 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.

Keywords: multi-dimensional rating system, WOM performance, natural experiment, difference-in-difference

Suggested Citation

Liu, Ying and Chen, Pei-Yu and Hong, Yili, The Value of Multi-Dimensional Rating System: An Information Transfer View (November 10, 2014). Available at SSRN: https://ssrn.com/abstract=2521996 or http://dx.doi.org/10.2139/ssrn.2521996

Ying Liu (Contact Author)

Arizona State University (ASU) - Department of Information Systems ( email )

Tempe, AZ
United States

Pei-Yu Chen

Arizona State University (ASU) - Department of Information Systems ( email )

Tempe, AZ
United States

Yili Hong

Arizona State University (ASU) - W.P. Carey School of Business ( email )

Tempe, AZ 85287-3706
United States

HOME PAGE: http://yilihong.github.io/

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