Models and Optimal Designs for Conjoint Choice Experiments Including a No-Choice Option

By Bart Vermeulen, Peter Goos, Martina Vandebroek. 2008

111 citations recorded by the source corpus.

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 options 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 the two most appealing of these models using the D-optimality criterion and the modified Fedorov algorithm and compare these optimal designs with a reference design, which is constructed while ignoring the no-choice option, in terms of estimation and prediction accuracy. We conclude that taking into account the no-choice option when designing a no-choice experiment only has a marginal effect on the estimation and prediction accuracy as long as the model used for estimation matches the data-generating model.

Subfields: Economics and Econometrics, General Decision Sciences, Marketing

View Paper: https://www.semanticscholar.org/paper/1bf1a41fbd5776566043d4b77656657b05fd342f

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In Economics and Econometrics

1. Steven T. Yen
2. C. Russell
3. B. Lin
4. Emma C. Stephens
5. Christopher B. Barrett
6. L. Pieroni
7. David Aristei

In Marketing

1. C. Russell
2. Emma C. Stephens
3. David Aristei
4. Christopher B. Barrett
5. B. Lin
6. L. Pieroni

Citations in the corpus

• Factors Influencing Willingness-to-Pay for the Energy Star Label (2010, background): “ASC takes a value of 1 if the “none” option is chosen and 0 if one of the three alternatives is chosen (Vermeulen et al., 2008).”