We propose a unifying framework for benefit and demographic segmentation based on the analysis of rank-order choice data collected in conjoint studies. The model identifies a number of unobserved segments, estimates the conjoint model within each segment, and at the same time estimates the...

We attempt to provide insights into how heterogeneity has been and can be addressed in choice modeling. In doing so, we deal with three topics: Models of heterogeneity. Methods of estimation and Substantive issues. In describing models we focus on discrete versus continuous representations of...

Response latencies provide information about consumers' choice behavior in a conjoint choice experiment. The authors use filtered response latencies to scale the covariance matrix of a multinomial probit model and show that this leads to better model fit and holdout predictions, even if the...

Conjoint choice designs are frequently applied in practice, and often a base alternative is added to the design. When such a 'no-choice' base alternative is present in conjoint choice experiments a constant term should be added to the design ('X'-) matrix with attribute dummies when effects type...

Paul Green, writing with Carmone and Wachpress (1976), was among the first scholars to introduce latent variable models to marketing by utilizing the CANDECOMP procedure (Carroll 1980) on contingency tables. A year later, Green, Carmone, and Wachpress (1977) introduced logit and log-linear...