Bayesian D-Optimal Choice Designs for Mixtures

Tinbergen Institute Discussion paper 14-057/III

43 Pages Posted: 10 May 2014

See all articles by Aiste Ruseckaite

Aiste Ruseckaite

Erasmus University Rotterdam (EUR) - Department of Econometrics

Peter Goos

University of Antwerp; KU Leuven

D. Fok

Econometric Institute - Erasmus University Rotterdam; Erasmus Research Institute of Management (ERIM); Tinbergen Institute Rotterdam

Date Written: May 7, 2014

Abstract

Consumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of waiting time (e.g., in-vehicle and out-of-vehicle travel time) in a transportation setting. Choice experiments may help to determine how the respondents' choice of a product or service is affected by the combination of ingredients. In such studies, individuals are confronted with sets of hypothetical products or services and they are asked to choose the most preferred product or service from each set.

However, there are no studies on the optimal design of choice experiments involving mixtures. We propose a method for generating an optimal design for such choice experiments. To this end, we first introduce mixture models in the choice context and next present an algorithm to construct optimal experimental designs, assuming the multinomial logit model is used to analyze the choice data. To overcome the problem that the optimal designs depend on the unknown parameter values, we adopt a Bayesian D-optimal design approach. We also consider locally D-optimal designs and compare the performance of the resulting designs to those produced by a utility-neutral (UN) approach in which designs are based on the assumption that individuals are indifferent between all choice alternatives. We demonstrate that our designs are quite different and in general perform better than the UN designs.

Keywords: Bayesian design, Choice experiments, D-optimality, Experimental design, Mixture coordinate-exchange algorithm, Mixture experiment, Multinomial logit model, Optimal design

JEL Classification: C01, C10, C25, C61, C83, C90, C99

Suggested Citation

Ruseckaite, Aiste and Goos, Peter and Fok, Dennis, Bayesian D-Optimal Choice Designs for Mixtures (May 7, 2014). Tinbergen Institute Discussion paper 14-057/III. Available at SSRN: https://ssrn.com/abstract=2435058 or http://dx.doi.org/10.2139/ssrn.2435058

Aiste Ruseckaite (Contact Author)

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Peter Goos

University of Antwerp ( email )

Prinsstraat 13
Antwerp, Antwerp 2000
Belgium

KU Leuven ( email )

Oude Markt 13
Leuven, Vlaams-Brabant 3000
Belgium

Dennis Fok

Econometric Institute - Erasmus University Rotterdam ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands
+31 10 408 1333 (Phone)
+31 10 408 9162 (Fax)

Tinbergen Institute Rotterdam ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Register to save articles to
your library

Register

Paper statistics

Downloads
61
Abstract Views
834
rank
353,800
PlumX Metrics