Mixed-logit models are currently the state of the art in discrete-choice modelling, and their
estimation in various forms (in particular, mixing revealed-preference and stated-preference …

This paper combines the use of random coefficient discrete choice models that allow for
correlated errors in the form of unobserved preference heterogeneity with an investigation of …

The need for cost effective research techniques in transport has led to increasing use of
Stated Preference data, as well as the development of mixed models, based on multiple …

A number of papers have recently contrasted classical inference estimation methods for logit
models with Bayesian methods. It has been argued that two particularly appealing features …

In this paper, the mixed logit (ML) using Bayesian methods was employed to examine
willingness-to-pay (WTP) to consume bread produced with reduced levels of pesticides so …

We show a substantive problem exists with the widely-used ratio of coefficients approach to
calculating willingness to pay (WTP) from discrete choice models. The correctly calculated …

The mixed logit model is considered to be the most promising state of the art discrete choice
model currently available. Increasingly researchers and practitioners are estimating mixed …

The mixed logit model is considered to be the most promising state of the art discrete choice
model currently available. Increasingly researchers and practitioners are estimating mixed …

In Alberini et al.(this volume), an overview of the workhorse model (the Multinomial Logit, or
MNL) for discrete choice analysis was presented from its conception to its practical use in …

Hybrid choice models have been developed as an extension of discrete choice models,
particularly multinomial logit models, in an attempt to include attitudinal variables. The …