A hierarchical Bayes model for assortment choice

in this research, the authors merge an established methodology-hierarchical Bayesian modeling-and an existing utility model-Farquhar and Rao's (1976) balance model-to describe individual choices among assortments of multiattr ibuted items. This approach facilitates addressing three managerial questio ns of direct importance: (1) Which assortment of a given size has the most customers for whom it is the preferred assortment (and what fraction of cus tomers)? (2) Which products should be added to a given assortment to maximi ze the fraction of customers who can find their most preferred assortment? and (3) For a given assortment, what type of customer is likely to purchase it? The model is applied to assortment choices constructed from a set of e ight popular magazines with five measured attributes: business, current eve nts, human interest stories, sports, and technology. The analysis indicates that consumers are heterogeneous: Some customers are price sensitive and u nresponsive to the magazine attributes, and others are sensitive to the mag azine features but do not necessarily want more of them. In addition, the a uthors observe that many subjects do not prefer varied assortments; rather, consumers focus on purchasing magazines with high levels of the attribute they want.