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Louviere, Jordan
Street, Deborah
Burgess, Leonie
Wasi, Nada
Islam, Towhidul
Marley, Anthony A. J.
Year of Publication: 
[Journal:] Journal of Choice Modelling [ISSN:] 1755-5345 [Volume:] 1 [Year:] 2008 [Issue:] 1 [Pages:] 128-163
We show how to combine statistically efficient ways to design discrete choice experiments based on random utility theory with new ways of collecting additional information that can be used to expand the amount of available choice information for modeling the choices of individual decision makers. Here we limit ourselves to problems involving generic choice options and linear and additive indirect utility functions, but the approach potentially can be extended to include choice problems with non-additive utility functions and non-generic/labeled options/attributes. The paper provides several simulated examples, a small empirical example to demonstrate proof of concept, and a larger empirical example based on many experimental conditions and large samples that demonstrates that the individual models capture virtually all the variance in aggregate first choices traditionally modeled in discrete choice experiments.
choice Models
econometric models
discrete choice experiments
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