Consideration Sets in Conjoint Analysis

A study models product consideration as preceding choice in a segment-level conjoint model. A latent-class tobit model to estimate cardinal, segment-level preference functions based on consumers' preference ratings for product concepts considered worth adding to the consumers' self-explicated consideration sets is proposed. The probability with which the utility of a product profile exceeds an unobserved threshold corresponds to its consideration probability, which is assumed to be independent across product profiles and common to consumers in a segment. A market-share simulation compares the predications of the proposed model with those obtained from an individual-level tobit model and from tradition ratings-based conjoint analysis. Simulations that assess the robustness of the proposed estimation procedure, which uses an E-M algorithm to obtain maximum likelihood parameter estimates, are also presented.