Effects of Stated Choice Design Dimensions on Model Estimates^☆

Abstract

There have always been concerns about task complexity and respondent burden in the context of stated choice (SC) studies, with calls to limit the number of alternatives, attributes and choice sets. At the same time, some researchers have also made the case that too simplistic a design might be counterproductive given that such designs may result in issues of omitting important decision variables. This paper aims to take another look at the effects of design complexity on model results. Specifically, we make use of an approach devised by Hensher (2004)¹ in which different respondents in the study are presented with designs of different complexity, and look specifically at effects on model scale in a UK context, adding to previous Chilean evidence by Caussade et al. (2005). The results of our study indicate that the impact of design complexity may be somewhat lower than anticipated, and that more complex designs may not necessarily lead to poorer results. In fact, some of the more complex designs lead to higher scale in the models. Overall, our findings suggest that respondents can cope adequately with large number of attributes, alternatives and choice sets. The implications for practical research are potentially significant, given the widespread use, especially in Europe, of stated choice designs with a limited number of alternatives and attributes.

Citation

Chintakayala, P.K., Hess, S., Rose, J.M. and Wardman, M. (2010), "Effects of Stated Choice Design Dimensions on Model Estimates^☆", Hess, S. and Daly, A. (Ed.) Choice Modelling: The State-of-the-art and The State-of-practice, Emerald Group Publishing Limited, Leeds, pp. 195-215. https://doi.org/10.1108/9781849507738-008