Abstract
In a classical conjoint choice experiment, respondents choose one profile from each choice set that has to be evaluated. However, in real life the respondent does not always make a choice: often he/she does not prefer any of the alternatives offered. Therefore, including a no-choice option in a choice set makes a conjoint choice experiment more realistic. In the literature three different models are used to analyze the results of a conjoint choice experiment with a no-choice option: the no-choice multinomial logit model, the extended no-choice multinomial logit model and the nested no-choice multinomial logit model. We develop optimal designs for each of these models using the D-optimality criterion and the modified Fedorov algorithm. We compare the optimal designs with a reference design that was constructed ignoring the no-choice option and we discuss the impact of the different designs and models on the precision of estimation and the predictive accuracy based on a simulation study.
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