Stated preference modelling of intra-household decisions: Can you more easily approximate the preference space?

  • Matthew J. BeckEmail author
  • John M. Rose


While the study of choices focuses primarily on the individual decision maker, there is growing interest in the examination of the choices made by groups. Much of the research into the choices of multiple decision makers has revealed that they differ significantly to those of individuals. In this study of household vehicle choice we similarly compare individual choices to group choices and support this finding. Consequently any research into choices that involve groups should acquire data from those groups. In this paper we show how this may be done via an interactive agency choice experiment which makes the individual preferences endogenous to the choice of the group. This method and many like it, however, involve significant time, incentive and administrative costs that often make such studies prohibitive. In this paper we also compare another class of model, minimum information group inference, which is designed to provide an overview of the likely group choice and while not having the specificity of detail as other methods, has the advantage of being much easier and cheaper to implement and is perhaps the only methodology that can be employed when it is not feasible for respondents to interact. We find that this method is a good approximation of group choice, mapping the preference space over which group choice is likely to be located.


Household choice Vehicle purchasing Stated preference Group choice 



The authors would like to acknowledge the comments and suggestions from three anonymous referees whose work has helped shape this paper.

Author contribution

Matthew Beck, in conjunction with John Rose, developed the idea for this paper, designed the experiment, collected the data, modelled the data, did the literature review, and wrote the paper.


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Institute of Transport and Logistics StudiesThe University of SydneyDarlingtonAustralia
  2. 2.Business Intelligence and Data Analytics (BIDA)University of Technology, SydneyUltimoAustralia

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