Commonly used discrete choice model analyses (eg, probit, logit and multinomial logit
models) draw on the estimation of importance weights that apply to different attribute levels …

There is growing interest in exploring the view that both revealed preference (RP) and stated
preference (SP) data have useful information and that their integration will enrich the overall …

Discrete choice methods model a decision-maker's choice among a set of mutually
exclusive and collectively exhaustive alternatives. They are used in a variety of disciplines …

One of the nagging issues in using discrete choice models is how softer attributes, such as
attitudes and perceptions, that are not explicitly manipulated within the context of the choice …

Until recently, computational constraints forced researchers in thediscrete choice area to
limit themselves to very simple statistical models, such as the multinomial logit (MNL), in …

This paper proposes a methodology for incorporating psychometric data such as stated
preferences and subjective ratings of service attributes in econometric consumer's discrete …

Multinomial logit choice models based on latent class (LC) or HB methods are utilized in
marketing research today along with simulators which predict choices and market shares …

This report shows you how to use the multinomial logit model (Manski and McFadden, 1981;
Louviere and Woodworth, 1983) to investigate consumer's stated choices. The multinomial …

Understanding and predicting the behavior of decision makers when choosing among
discrete goods has been one of the most fruitful areas of applied research over the past thirty …

Over the past two decades, validation of choice models has focused on predictive validity
rather than parameter bias. In real-world validation of choice models, true parameter values …