A mixed model approach to conjoint analysis

Abstract

In this decision-driven era, it has become vital for modelers to efficiently model consumer choices and preferences (from a marketing perspective for instance). Conjoint analysis is a known method which has been used to perform such analyses. A mixed effects model is proposed to perform a conjoint analysis with normal responses, illustrated by an application of modeling respondent’s preferences to different industrial detergents. The proposed model allows for predicting how observed attributes (which describes a product in terms of its characteristics and features) of decision makers and choice options, influence decisions. Inference regarding the parameters of the proposed model with a normal distribution is discussed in the mixed effect conjoint setting. Extensions of this model, regarding Bayesian prior selection are also discussed.