Model-robust choice experiments: discussion and case study
Article first published online: 22 JUN 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Quality and Reliability Engineering International
Volume 28, Issue 1, pages 115–122, February 2012
How to Cite
Lawson, J. S., Henderson, S. and Peterson, J. (2012), Model-robust choice experiments: discussion and case study. Qual. Reliab. Engng. Int., 28: 115–122. doi: 10.1002/qre.1225
- Issue published online: 18 JAN 2012
- Article first published online: 22 JUN 2011
- utility-neutral design;
- locally optimal design;
- Bayesian optimal design;
- projection properties
Choice experiments are an effective way of obtaining objective information regarding the voice of the customer. They can be used to obtain the relevant customer attributes and importance rankings used in the first step of quality function deployment. They are also used extensively in marketing research. Optimal designs for choice experiments have been discussed in the literature. However, optimal designs are only optimal for a particular model. In this article we borrow ideas from quality engineering and industrial experimentation to develop designs for choice experiments that are model-robust (in the sense that they are efficient for fitting a model involving main effects plus a few interactions that need not be specified in advance). A case study is presented to illustrate the use of a model-robust design for a choice experiment. Two unsuspected interactions were discovered in the case study, and this discovery led to added insight regarding customer preferences and importance rankings of product attributes. These insights would not have been possible if an optimal design for the main effects model had been used. Copyright © 2011 John Wiley & Sons, Ltd.