The literature indicating that person-, context-, and task-specific factors cause consumers to utilize different decision strategies has generally failed to affect the specification of choice models used by practitioners and academics alike, who still tend to assume an utility maximizing,...

This paper introduces a new member of the generalized extreme value (GEV) family of discrete choice models that directly incorporates choice set generation modeling into the specification via the GEV generating function. Though still a two-stage model of choice set generation and choice, the...

This paper proposes a behavioral interpretation of the choice set generation process that is useful for structuring and specifying discrete models that incorporate this stage of choice. The key concept is the notion of random constraints, which is operationalized in the form of probabilistic...

This research proposes an extension to the traditional compensatory utility maximization framework which has guided most theoretical and statistical work in choice modeling applications, including those in transportation demand estimation work. Attribute cutoffs are incorporated into the...

The use of stated preference analyses to evaluate choice of health care products has been growing in recent years. This paper shows how revealed preference data can be enriched with stated preference data and highlights the relative advantages of revealed and stated preference data. The...

A new class of finite mixture discrete choice models, denoted FinMix (fin miks), is introduced. These arise from the combination of a finite number of core Generalized Extreme Value (GEV) models to achieve more flexible functional forms, particularly in terms of error covariance structures....