5 research outputs found
Travel Choice Inertia: The Joint Role of Risk Aversion and Learning
This paper shows how travellers that are faced with a series of risky choices become behaviourally inert due to a combination of risk aversion and learning. Our theoretical analyses complement other studies that conceive inertia as resulting from the wish to save cognitive resources. We first present a model of risky travel mode choice. We show that if travellers dislike risk, and part of the quality of travel alternatives is only revealed upon usage, inertia emerges due to a learning-based lock-in effect. We extend our analyses to capture forward-looking behaviour and the provision of travel information
The long road to automated trucking: Insights from driver focus groups
With the rapid progress of automated driving technology, self-driving vehicles are
on the horizon. In this study, we look at what is likely to be the first implementation
of a form of automated driving on public roads, i.e., truck platooning, where virtually
connected trucks drive at short headways to save fuel and associated emissions. With
progressing technology, we may see platoons with drivers resting while being in the truck
or even platoons in which not all trucks require drivers. Hence, platooning technology
has a significant impact on the jobs of truck drivers. Driver acceptance of this emerg-
ing technology is therefore an important factor in the implementation of platooning and,
consequently, automated driving in general. In this study, we explore the range of per-
spectives that exist among drivers by conducting focus groups in the Netherlands. These
discussions indicate that drivers foresee that platooning will eventually become a reality
but believe it will have a negative impact on the quality of their work and their job satisfaction
Individuals' Decisions in the Presence of Multiple Goals
This paper develops new directions on how individuals’ use of multiple goals can be incorporated in econometric model
Incorporating Mental Representations in Discrete Choice Models of Travel Behaviour
We introduce an extension of the discrete choice model to take into account individuals’ mental representation of a choice problem. We argue that, especially in daily activity and travel choices, the activated needs of an individual have an influence on the benefits he or she pursues in the choice of an alternative. The benefits in turn determine which attributes are considered in evaluating choice alternatives taking into account mental costs. The extended model considers the formation of a mental representation of a choice problem as an integral part of the choice process. We show how formation of a mental representation and making a choice can be modelled jointly in an integrated RUM framework. We further show how the integrated model can be estimated based on combined observations of mental representations and choice outcomes using maximum likelihood estimation. A comparative analysis shows that observations of the mental representations may significantly improve predictions and enhance our insights in situation-dependent motivations underlying preferences. We illustrate the approach using a dataset that involves measurements of mental representations and choice behaviour in the area of transport mode choice
Effect of an ionic liquid on the flexural and fracture mechanical properties of EP/MWCNT nanocomposites
This paper develops new directions on how individuals’ use of multiple goals can be incorporated in econometric models of individual decision-m