Abstract
With the maturity of the consumers' life, its importance is growingly recognized to examine the variability of the preference among consumers as well as the average preference. In this paper, we propose a Bayesian hierarchical model to estimate the distribution of preference from a paired comparison experiment of multiple objects. In the likelihood function of Thurstone's model, each individual has his/her own preference scores of the objects. The distribution of the preference is regarded as a prior for the parameters, and has hyper parameters. We formulate the prior distribution in terms of a self-consistency index, mean preference directions of objects, and preference variability indices of objects. The posterior distribution of the parameters and the hyper parameters are estimated by Markov chain Monte Carlo algorithm. With an experiment of twenty varieties of violet, we show that the most preferred varieties in the experiment can be different from those with high purchasing probabilities.
