Table of Contents

Handbook of Choice Modelling

Handbook of Choice Modelling

Elgar original reference

Edited by Stephane Hess and Andrew Daly

Choice modelling is an increasingly important technique for forecasting and valuation, with applications in fields such as transportation, health and environmental economics. For this reason it has attracted attention from leading academics and practitioners and methods have advanced substantially in recent years. This Handbook, composed of contributions from senior figures in the field, summarises the essential analytical techniques and discusses the key current research issues. It will be of interest to academics, students and practitioners in a wide range of areas.

Chapter 7: Stated choice experimental design theory: the who, the what and the why

John M. Rose and Michiel C.J. Bliemer

Subjects: economics and finance, environmental economics, transport, environment, environmental economics, transport, urban and regional studies, transport


Unlike most survey data where information on both the dependent and independent variables is captured directly from respondents, stated preference data where respondents make decisions based in hypothetical markets, of which stated choice (SC) data is a subset, is unique in that typically only the dependent variable is provided by the respondent. With the exception of covariate information which is often ignored in most analysis, the primary variables of interest, consisting of attributes and their associated levels, are designed in advance and presented to the respondent in the form of competing alternatives in SC studies. However, increasing evidence of both an empirical (for example, Bliemer and Rose, 2011; Louviere et al., 2008) and theoretical nature (for example, Burgess and Street, 2005; Sandor and Wedel, 2001, 2002, 2005) suggests that the allocation of the attribute levels over the experiment may impact upon the model outputs obtained, particularly when small samples are involved. As such, rather than simply randomly assigning the attribute levels shown to respondents over the course of an experiment, experimental design theory has traditionally been applied to allocate the attribute levels to the alternatives in some systematic manner. A review of the literature, however, suggests that little consensus exists as to what specific experimental design theory, or aspects thereof, are appropriate for SC studies.

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