People make all kinds of choices every day, such as driving to work rather than taking public transport. Many of these choices have a direct impact on demand for products, services or public infrastructures. Understanding people’s choice behaviour can not only infer people’s preferences for certain products or services but more importantly make future demand forecasts. Over the last fifty years, there has been a steadily growing interest in applying a quantitative statistical method, discrete choice modelling, to study individual and household choice behaviour. Discrete choice models provide a theoretically robust and tractable tool for modelling and analysing various choices across many fields such as transport, health, and marketing...@en

Vehicle-to-grid (V2G) technology could turn electric vehicles (EVs) into a potentially valuable solution to the problem of increased load demand caused by large-scale EV integration. Successful market penetration of V2G relies not only on developing the technology itself, but also on EV drivers' willingness to participate in this technology. This paper aims to explore Dutch EV drivers' preferences for participating in V2G contracts. In particular, we conduct a context-dependent stated choice experiment to examine the impact of EV recharging technology on the V2G contract preferences. Two contexts have been designed: the current EV recharging time and fast recharging. Our results show that in the context of current recharging time, Dutch EV drivers in general prefer not to participate in V2G contracts, while the opposite is true in the context of fast recharging. With regard to specific V2G contract attributes, Dutch EV drivers are most concerned about ‘discharging cycles’. Also important to them is ‘the guaranteed minimum battery level’, but its importance drops significantly in the fast charging context. In addition, ‘monthly remuneration’ and ‘plug-in time’ also influence people's preferences for adopting V2G. From these findings, we draw the implications for the aggregator and policy makers.@en

Although Automated vehicles (AVs) are expected to have a major and positive effect on road safety, recent accidents caused by AVs tend to generate a powerful negative impact on the public opinion regarding safety aspects of AVs. Triggered by such incidents, many experts and policy makers now believe that paradoxically, safety perceptions may well prohibit or delay the rollout of AVs in society, in the sense that AVs will need to become much safer than conventional vehicles (CVs), before being accepted by the public. In this study, we provide empirical insights to investigate and explain this safety paradox. Using stated choice experiments, we show that there is indeed a difference between the weight that individuals implicitly attach to an AV-fatality and to a CV-fatality. However, the degree of overweighting of AV-fatalities, compared to CV-fatalities, is considerably smaller than what has been suggested in public opinions and policy reports. We also find that the difference in weighting between AV-fatalities and CV-fatalities is (partly) related to a reference level effect: simply because the current number of fatalities caused by AVs is extremely low, each additional fatality carries extra weight. Our findings suggest that indeed, AVs have to become safer—but not orders of magnitude safer—than CVs, before the general public will develop a positive perception of AVs in terms of road safety. Ironically, our findings also suggest that the inevitable occurrence of more AV-related road accidents will in time lead to a diminishing degree of overweighting of safety issues surrounding AVs.@en

In this study we extend recent work into the role of Weber’s law in discrete choice theory towards non-regret based models of (travel) choice behavior; and we provide an empirical exploration of the relevance of Weber’s law in the context of utility- and regret-based models of travel behavior.@en