We propose and test a choice model based on the notion that the category an alternative is perceived to fall into determines the attribute importance weights used to evaluate that alternative. For example, space is more important than fuel economy for an SUV, but the opposite is true for a...

An increasing number of studies are concerned with the use of alternatives to random utility maximisation as a decision rule in choice models, with a particular emphasis on regret minimisation over the last few years. The initial focus was on revealing which paradigm fits best for a given...

Income is a key variable in many choice models. It is also one of the most salient examples of a variable affected by data problems. Issues with income arise as measurement errors in categorically captured income, correlation between stated income and unobserved variables, systematic over- or...

Discrete choice (DC) models are often used to describe consumer behaviour at a disaggregate level. At this level, a choice decision is defined in terms of a set of alternatives representing different ‘varieties’ of a particular product differentiated mainly by their quality attributes rather...

We consider the manner in which the well-established path independence conditions apply to Small and Rosen's (1981) problem of discrete-continuous demand, focussing especially upon the restricted case of discrete choice (probabilistic) demand. We note that the consumer surplus measure promoted...

In a discrete choice experiment, each respondent chooses the best product or service sequentially from many groups or choice sets of alternative goods. The alternatives are described by levels of a set of predefined attributes and are also referred to as profiles. Respondents often find it...

We propose and describe a comprehensive theoretical framework that integrates choice models and structural equation models. Referred to as "structural choice modelling" the framework easily combines data from separate but related choice experiments. We describe the mathematical properties of the...

A generation of new models has been proposed to handle some complex human behaviors. These models account for the data ambiguity, and therefore extend the application field of the discrete choice modeling. The facial expression recognition (FER) is highly relevant in this context. We develop a...

Model misspecification is a serious issue since misspecification generally renders statistical inference invalid. However, specification testing of discrete choice models is rarely applied. This paper describes a nonparametric test procedure which uses a combination of smoothed residual plots...