Abstract
This paper studies the consumer self-selection bias in the e-word-of-mouth (eWOM) systems, e.g. consumer review websites. Under Bayesian framework, this study extends our understanding of this bias and discovers two new sources through developing a system of structural models of consumer review behaviors tested by a large data set. Our model and results provide evidences that the timing and content of a review introduce significant amount of bias into ratings in a simultaneous fashion. Specifically, we find that after controlling for various exogenous effects the two sources of bias persist: a subsequent rating is positively associated with the time interval between two consecutive reviews by the same consumer, and is negatively associated with the length of a review. Clearly, our findings confirm that modern eWOM systems have notable flaws despite of their mechanical advantages. We further discuss the possible mechanisms as well as the economic impact underlying these findings.
Recommended Citation
Ma, Xiao and Kim, Sung, "Revisiting Self-Selection Biases in E-Word-of-Mouth: An Integrated Model and Bayesian Estimation of Multivariate Review Behaviors" (2011). ICIS 2011 Proceedings. 1.
https://aisel.aisnet.org/icis2011/proceedings/onlinecommunity/1
Revisiting Self-Selection Biases in E-Word-of-Mouth: An Integrated Model and Bayesian Estimation of Multivariate Review Behaviors
This paper studies the consumer self-selection bias in the e-word-of-mouth (eWOM) systems, e.g. consumer review websites. Under Bayesian framework, this study extends our understanding of this bias and discovers two new sources through developing a system of structural models of consumer review behaviors tested by a large data set. Our model and results provide evidences that the timing and content of a review introduce significant amount of bias into ratings in a simultaneous fashion. Specifically, we find that after controlling for various exogenous effects the two sources of bias persist: a subsequent rating is positively associated with the time interval between two consecutive reviews by the same consumer, and is negatively associated with the length of a review. Clearly, our findings confirm that modern eWOM systems have notable flaws despite of their mechanical advantages. We further discuss the possible mechanisms as well as the economic impact underlying these findings.