Managing score heterogeneity between online consumer review websites

Abstract

This paper describes an alternative approach to measuring score heterogeneity between online consumer review websites. This topic is important in tourism management and in the hospitality sector, where it is helpful to be aware of the ratings obtained by services, from information readily available on the website. We approach this issue by considering tests of multiple population means, assuming this question can be viewed as a clustering problem and that all feasible data configurations can be tested using a Bayesian procedure from which the posterior probabilities of each cluster model are computed. The proposed Bayesian model is a useful alternative to frequentist multiple testing methods, which neglect uncertainty regarding other potential configurations. We draw conclusions about the overall score parameter and propose a Bayesian model averaging model for estimation purposes. Finally, the proposed Bayesian framework is illustrated in detail using a real dataset.