Choice-based conjoint analysis (CBC) is used widely in marketing for product design, segmentation, and marketing strategy. We propose and test a new "polyhedral" question-design method that adapts each respondent's choice sets based on previous answers by that respondent. Individual adaptation...

We propose and test new "polyhedral" question design and estimation methods that use recent developments in mathematical programming. The methods are designed to offer accurate estimates after relatively few questions in problems involving many parameters. With polyhedral question design, each...

Web-based customer panels and web-based multimedia capabilities offer the potential to get information from customers rapidly and iteratively based on virtual product profiles. However, web-based respondents are impatient and wear out more quickly. At the same time, in commercial applications,...

In most marketing experiments, managerial decisions are not based directly on the estimates of the parameters but rather on functions of these estimates. For example, many managerial decisions are driven by whether or not a feature is valued more than the price the consumer will be asked to pay....

Adaptive metric utility balance is at the heart of one of the most widely used and studied methods for conjoint analysis. We use formal models, simulations, and empirical data to suggest that adaptive metric utility balance leads to partworth estimates that are relatively biased—smaller...

We propose and test new adaptive question design and estimation algorithms for partial profile conjoint analysis. Polyhedral question design focuses questions to reduce a feasible set of parameters as rapidly as possible. Analytic center estimation uses a centrality criterion based on...