Modelling activity-travel behaviour dynamics with panel data: The state-of-the-art

The field of travel behaviour dynamics represented a vibrant research area in the 1980s and the 1990s (Golob & Meurs, 1987; Golob, Kitamura, & Long, 1997; Kitamura, 1990), but has since, probably due to lack of mobility panel data, received relatively little attention by transportation researchers. Nevertheless, through the use of panel data (repeated measures of the same individuals) many new insights may be gained with respect to travel behaviour, insights that are fundamentally different from those that can possibly be gained from cross-sectional data

Revealing transition patterns between mono- and multimodal travel patterns over time: A mover-stayer model

Recent empirical evidence suggests that travellers are becoming increasingly multimodal. Coinciding with this trend, a growing interest can be observed in the transport literature to study the concept of multimodality. Most studies, in this regard, have focused on assessing the determinants of multimodal travel behaviour. While it is interesting to know which factors, at a certain moment in time, affect the membership of mono/multimodal travel patterns, one general omission in the current literature relates to the questions how and why travellers switch between the mono/multimodal travel patterns over time. This study aims to fill this knowledge gap. To this end, a mixture latent Markov model is specified and estimated using data from the German mobility panel. Our mixture latent Markov models consist of latent travel patterns as well as latent mobility styles. To acquire insights on changes in travel behaviour various model specifications are tested. The travel data is best explained by a model consisting of five latent travel patterns and three mobility styles. The five travel patterns are can be conceived as (1) strict car users, (2) public transport and occasional car users, (3) car passengers, (4) car and bicycle users and (5) bicycle and occasional public transport users, and the three underlying mobility styles are identified as (1) habitual travellers, who stay in their respective pattern for three consecutive years, (2) car (in)dependent choice travellers, who switch within car and non-car patterns, and (3) car users with an alternative mode preference, who switch between car and noncar patterns. Overall, it is concluded that mixture latent Markov models are effective to reveal (heterogeneity in) transition patterns

The effects of weather and climate change on cycling in northern Norway

Weather is identified as one of many factors that influence the demand for cycling. Weather patterns will change due to expected climate change. The aim of this article is to study the extent to which climate change influences the cycling frequency. The analysis in this article is conducted using an econometric model based on data spanning over four years on weather indicators and the cycling frequency in the Norwegian city of Bodø, which is located north of the Arctic Circle. According to the projections for climate change, both temperature and quantity of precipitation are expected to increase in this area during the next century. An important consequence of changes in the climate in the studied region is the reduced duration of what can be characterised as the winter season. However, this consequence is highly uncertain. When using Norway’s middle projections for climate change by 2050, the analysis shows a moderate increase in cycling frequency of 6.2%. For the reduced winter period, the cycle rate might be two and three times higher in 2050 compared to the current level. Both estimates assume that every other potential impact on cycling rates remain equal

Buying-off privacy concerns for mobility services in the Internet-of-things era: A discrete choice experiment on the case of mobile insurance

Internet-of-things technologies will enable collecting vast amounts of mobility data from car owners. Such connected car services can be value-adding but also create new privacy hazards. This paper studies whether and how privacy concerns of car owners can be compensated by offering monetary benefits. We study the case of usage based car insurance services for which the insurance fee is adapted to measured mileage and driving behaviour. A conjoint experiment shows that consumers prefer their current insurance products to usage based car insurance. However, when offered a minor financial compensation, they are willing to give up their privacy to car insurers. Consumers find privacy of behaviour and action more valuable than privacy of location and space. The study is a first to compare different forms of privacy in the acceptance of connected car services. Hereby, we contribute to more fine-grained understanding of privacy concerns in the acceptance of digital services, which will become more important than ever in the upcoming Internet-of-things era

Editorial: Driving, cycling and flying: trends in planning and operational transportation research in Europe

In this special issue we present three papers selected from the 18th meeting of the EURO Working Group on Transportation (EWGT) which was held in July 2015 in Delft, the Netherlands, organized by Delft University of Technology. The selected contributions reflect the diversity of topics that were addressed in this conference, which is dedicated to mathematical modeling of transportation problems. We are happy to have a small but representative sample in which three different modes of transportation are in focus: the bicycle, the car and the airplane. The editors are very grateful for all the work that authors and referees have put in creating interesting research papers in this broad field of transportation research. This editorial first explains what the EWGT is and how the EWGT conference was organized. The three contributions are then presented and put into the perspective of the Dutch edition of the EWGT conference

From welcome culture to welcome limits? Uncovering preference changes over time for sheltering refugees in Germany

Europe recently experienced a large influx of refugees, spurring much public debate about the admission and integration of refugees and migrants into society. Previous research based on cross-sectional data found that European citizens generally favour asylum seekers with high employability, severe vulnerabilities, and Christians over Muslims. These preferences and attitudes were found to be homogeneous across countries and socio-demographic groups. Here, we do not study the general acceptance of asylum seekers, but the acceptance of refugee and migrant homes in citizens' vicinity and how it changes over time. Based on a repeated stated choice experiment on preferences for refugee and migrant homes, we show that the initially promoted "welcome culture" towards refugees in Germany was not reflected in the views of a majority of a sample of German citizens who rather disapproved refugee homes in their vicinity. Their preferences have not changed between November 2015, the peak of "welcome culture," and November 2016, after political debates, media reporting and public discourse had shifted towards limiting admission of immigrants. A minority of one fifth of the sample population, who were initially rather approving of refugee and migrant homes being established in their vicinity, were more likely to change their preferences towards a rather disapproving position in 2016. Experience of contact with refugees and migrants, higher education, and general pro-immigration attitudes explain acceptance of refugee and migrant homes as well as preference stability over time. Country of origin and religion of refugees and migrants are considered less important than decent housing conditions and whether refugee and migrants arrive as families or single persons. In this respect our results highlight the importance of humanitarian aspects of sheltering and integration of refugees and other migrants into society

Automated Vehicles: Changes in expert opinions over time

Innovations in transportation can contribute to reaching relevant societal objectives (e.g. reduce emissions, congestion levels and/or risks). To determine which innovations to stimulate (and which not) it is important for policy makers to assess their effects on beforehand. Expert judgement is an often-used method for this purpose. Although expert opinions can provide useful input for decision-making, these judgement are potentially subject to change, for example, due to new information becoming available or because the (academic) discussion about the innovation in question takes a new turn. Studies that explicitly study stability and change in expert judgements are rare, but highly relevant to determine the reliability of experts’ assessments. To address this gap, this study assesses experts’ judgments at multiple points in time focusing on the effects of a transport innovation with potentially widespread societal implications, namely Automated Vehicles (AVs). To this end a survey was administrated to a group of experts involved in the WISE-ACT project. The results indicate that expert opinions towards this innovation are generally favorable; AVs are believed to reduce congestion delays, greenhouse gas emissions and traffic accidents. Although the consulted experts are generally quite stable in their opinions, they are becoming less optimistic about these positive effects over time. A Q-factor analysis additionally reveals two clusters of experts, one with a positive and one a negative outlook on AVs. The latter group beliefs that AVs will lower the value of travel time, thereby increasing travel demand, and, in turn, emission and congestion levels. Overall, the changing and diverging opinions among experts indicate that the transition to AVs is not necessarily regarded as a desirable one

A measurement model for general noise reaction in response to aircraft noise

In this paper a measurement model for general noise reaction (GNR) in response to aircraft noise is developed to assess the performance of aircraft noise annoyance and a direct measure of general reaction as indicators of this concept. For this purpose GNR is conceptualized as a superordinate latent construct underlying particular manifestations. This conceptualization is empirically tested through estimation of a second-order factor model. Data from a community survey at Frankfurt Airport are used for this purpose (N = 2206). The data fit the hypothesized factor structure well and support the conceptualization of GNR as a superordinate construct. It is concluded that noise annoyance and a direct measure of general reaction to noise capture a large part of the negative feelings and emotions in response to aircraft noise but are unable to capture all relevant variance. The paper concludes with recommendations for the valid measurement of community reaction and several directions for further research.Infrastructures, Systems and ServicesTechnology, Policy and Managemen