Dual Representation Of Monotone Convex Functions On L-0

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In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

Since the 70s, there has been a growing interest in activity-based modelling. This approach models the need to travel as a result of performing daily activities (Bowman and Ben-Akiva, 2001). Nevertheless, the activities need to be scheduled which involves ...

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...

Travel time is a major component in understanding travel demand. However, the quantification of demand and forecasting hinges on understanding how travel time is perceived and reported. Travel time reporting is typically subject to errors and this paper fo ...

The focus of this thesis is to include the passengers and their behavior inside the train timetable design. This is done through three main objectives: timetable design based on passenger satisfaction, exploitation of hybrid cyclicity and choice based reve ...

This thesis develops models of activity and destination choices in pedestrian facilities from WiFi traces. We adapt the activity-based travel demand analysis of urban mobility to pedestrians and to digital footprints. We are interested in understanding the ...

Latent class models are a convenient and intuitive way to introduce taste heterogeneity in discrete choice models by relating attributes of the decision makers with unobserved behavioral classes, hence allowing for a more accurate market segmentation. Esti ...

Compromise alternatives have an intermediate performance on each or most attributes rather than having a poor performance on some attributes and a strong performance on others. The relative popularity of compromise alternatives among decision-makers has be ...

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 whi ...

Recent interest in the topic of random scale heterogeneity in discrete choice data has led to the development of specialised tools such as the G-MNL model, as well as repeated claims that studies which fail to separate scale heterogeneity from heterogeneit ...

In contrast with expected utility theory, empirical findings indicate that decision-makers are sensitive to departures from reference points rather than states. Several tests of the reference-dependent preference framework have been carried out in experime ...

Discrete choice models are defined conditional to the analyst's knowledge of the actual choice set. The common practice for many years has been to assume that individual-based choice sets can be deterministically generated on the basis of the choice contex ...

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single-choice contexts, there is a dearth of s ...

This chapter focuses on valuation in the context of choice under uncertainty. When valuation is a pursuit distinct from choice, values revealed through choice may be different from the valuations that emerge from the (choice-independent) computations. In m ...

Decision making under risk is central to human behavior. Economic decision theory suggests that value, risk, and risk aversion influence choice behavior. Although previous studies identified neural correlates of decision parameters, the contribution of the ...

Dual Representation Of Monotone Convex Functions On L-0

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Stochastic adaptive resampling for the estimation of discrete choice models

Representing location choice within activity-based models

Enhancing discrete choice models with representation learning

Mitigating the impact of errors in travel time reporting on mode choice modelling

Behaviorally Driven Train Timetable Design

Activity choice modeling for pedestrian facilities

Integrating psychometric indicators in latent class choice models

An empirical comparison of travel choice models that capture preferences for compromise alternatives

A mixed random utility Random regret model linking the choice of decision rule to latent character traits

Linking response quality to survey engagement: A combined random scale and latent variable approach

Revisiting reference point formation, gains-losses asymmetry and non-linear sensitivities with an emphasis on attribute specific treatment

An analysis of the implicit choice set generation using the Constrained Multinomial Logit model

A Behavioral and Neural Evaluation of Prospective Decision-Making under Risk

The Neurobiological Foundations of Valuation in Human Decision Making under Uncertainty

Neural Correlates of Value, Risk, and Risk Aversion Contributing to Decision Making under Risk