The authors propose a fast and efficient algorithm for constructing D-optimal conjoint choice designs for mixed logit models in the presence of respondent heterogeneity. With this new algorithm, the construction of semi-Bayesian D-optimal mixed logit designs with large numbers of attributes and...

Within the context of choice experimental designs, most authors have proposed designs for the multinomial logit model under the assumption that only the main effects matter. Very little attention has been paid to designs for the attribute interaction models. In this paper, we present Bayesian...

In this paper, we propose an efficient individually adapted sequential Bayesian approach for constructing conjoint choice experiments. It uses Bayesian updating, a Bayesian analysis and a Bayesian design criterion for generating choice-set-designs for each individual respondent based on previous...

Conjoint choice experiments have become a powerful tool to explore individual preferences. The consistency of respondents' choices depends on the choice complexity. For example, it is easier to make a choice between two alternatives with few attributes than between five alternatives with several...