Buyer Choice Simulators, Optimizers, and Dynamic Models

Abstract

Collecting and analyzing respondents' conjoint data is an essential part of the analytical process. As noted by John Hauser and Vithala Rao in their excellent discussion of conjoint analysis over the past 30 years (see Chapter 6), marketing researchers have expended intense efforts on data collection and partworth estimation. Partworths have been estimated by full profile, Adaptive Conjoint Analysis, hybrid conjoint, and categorical conjoint, with or without empirical or hierarchical Bayes enhancement. Partworth measurement and estimation processes are central to the accuracy and usefulness of all conjoint studies. Accordingly, much has been written about the pros and cons of various conjoint data collection and parameter estimation methods.