Article ID: | iaor2007576 |
Country: | United States |
Volume: | 43 |
Issue: | 3 |
Start Page Number: | 409 |
End Page Number: | 419 |
Publication Date: | Aug 2006 |
Journal: | Journal of Marketing Research |
Authors: | Vandebroek Martina, Kessels Roselinde, Goos Peter |
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.