A comparison of criteria to design efficient choice experiments

Roselinde Kessels*, Peter Goos, Martina Vandebroek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


To date, no attempt has been made to design efficient choice experiments by means of the G- and V-optimality criteria. These criteria are known to make precise response predictions, which is exactly what choice experiments aim to do. In this article, the authors elaborate on the G- and V-optimality criteria for the multinomial logit model and compare their prediction performances with those of the D- and A-optimality criteria. They make use of Bayesian design methods that integrate the optimality criteria over a prior distribution of likely parameter values. They employ a modified Fedorov algorithm to generate the optimal choice designs. They also discuss other aspects of the designs, such as level overlap, utility balance, estimation performance, and computational effectiveness.
Original languageEnglish
Pages (from-to)409-419
Number of pages11
JournalJournal of Marketing Research
Issue number3
Publication statusPublished - Aug 2006
Externally publishedYes

Cite this