BACKGROUND: Long-term noise annoyance can be expected to have worse outcomes than short-term annoyance. This study investigates noise annoyance over time, its association with personality traits and potential reciprocal effects between health outcomes and noise annoyance. METHODS: Firstly, we conducted a Longitudinal Latent Class Analysis to identify noise annoyance profiles. We further analysed the effect of Big Five personality traits on the likelihood of belonging to these annoyance profiles. Secondly, we used Cross-lagged Panel Models to analyse whether changes in noise annoyance precede changes in health outcomes or vice versa. For both analyses, we used 8 years of data from the Dutch Longitudinal Internet Studies for the Social Sciences (LISS) panel. Between 2708 and 11,068 subjects were included (this varies between models). RESULTS: We found three profiles of noise annoyance, namely, chronically, occasionally and never annoyed. Among all participants, 12% were chronically annoyed by neighbour noise and 6% by street noise. Extraversion and emotional stability decreased the chance of belonging to the cluster of chronically annoyed, while openness had the opposite effect. Chronic noise annoyance showed a significant effect on self-reported heart complaints and sleeping problems, while the effects of noise annoyance profiles on high blood pressure and heart attacks were insignificant. Some potential indications for a reverse effect from health outcomes on noise annoyance were found. CONCLUSION: Noise annoyance was relatively stable over time possibly because of its correlation with personality traits. Noise had a small negative effect on health outcomes, and some health outcomes affected noise annoyance. Further research should be conducted to collect dedicated panel data.

A biased preference for the status quo could explain the increased support for policies following their implementation. However, the influence of status quo bias on support for transport policies has been analysed to a limited extent only. The counterfactual test serves as a potential method to empirically explore this influence by framing policies as the existing or alternative situation. This paper employs the counterfactual test to ascertain whether individuals disproportionately favour the status quo. To this end, we have designed separate experiments focusing on three transport policies: road pricing, speed limits, and train ticket fare differentiation. The results indicate that status quo bias does indeed influence support for transport policies. Participants prefer each policy option when framed as the status quo. In contrast, support for the same policy option declines when presented as the alternative situation. These findings underscore the irrational tendency to adhere to the status quo, which may stem from psychological commitments or cognitive misperceptions. Therefore, politicians, policymakers, and practitioners should anticipate a bias towards the status quo when introducing controversial transport policies.

A lack of accessibility can lead to social exclusion and lower quality of life. While research has shown that objective accessibility measures influence well-being, few studies have examined the role of perceived accessibility. In this study, we test the notion that activity participation might play a mediating role in the relationship between perceived accessibility and well-being. In addition, we hypothesize that perceived accessibility may also directly influence well-being, assuming that a sense of residing in an accessible place has intrinsic value to people. Using data from the 2022 Netherlands Mobility Panel (n = 4,222), we test these chain relationships: perceived accessibility-activity participation-life satisfaction. The results of the structural equation modeling show that higher perceived accessibility by cars and bicycles directly enhances life satisfaction, while perceived accessibility by walking influences life satisfaction only indirectly, through increased activity participation. Accessibility by public transport, however, has no direct/indirect significant effect on well-being.

To address transport injustice and social exclusion, the needs and perceptions of different groups of individuals seem indispensable. Consequently, perceived accessibility has received a growing interest in recent years. While it is well established that transport and social disadvantages cause transport poverty and perceived inaccessibility, only recently the relevance of geographical disadvantages has been addressed. This paper explores the idea that an individual is more likely to experience inaccessibility if they face transport, social, or geographical disadvantages in at least two of these dimensions of transport poverty. For instance, while living in a rural area or lacking the ownership of a car may not translate into low perceived access on themselves, the combination of the two might lower perceived access. To empirically assess whether and which disadvantages indeed lower perceived accessibility further, the effect of combinations of disadvantages on perceived accessibility in rural and urban areas of the Netherlands are systematically explored using a regression analysis. Data is retrieved from the Dutch National Travel Survey. This survey includes a 1-day travel diary, measures both objective and subjective accessibility, and is administered among a representative sample of the Dutch population. In total, a large and representative sample of 22,742 participants is included in the analysis. Results highlight that rural-living individuals only perceive inaccessibility if they indeed encounter one or more transport and/or social disadvantages as well. Also, not possessing a driver's license determines perceived inaccessibility to a larger extent than a lack of car ownership. Lastly, possessing an e-bike is beneficial for the elderly in both rural and urban Dutch areas. The research findings may support policymakers and practitioners in tailoring policy interventions towards the needs of individuals who suffer from multiple disadvantages.

Many studies have investigated how digital engagement, new ways of working, and automated vehicles (AVs), are reshaping travel behaviour. However, their findings are frequently divergent or inconclusive. This work proposes that three emerging time-use patterns (TUPs) – multitasking, flexibility and fragmentation of activities – can help to explain the divergent results. To assess this notion, we systematically investigate the mediating role of TUPs in the relationship between digital engagement/telework/AVs and four key travel outcomes (trip frequency, travel distance, mode choice, and value of travel time). Using empirical data from 2019 to 2024, we find that TUPs can be seen as a mediator in shaping travel outcomes. For instance, when digital activities or telework increase activity fragmentation, they are associated with increased trip frequency. When digital activities or telework have been shown to increase flexibility, that has resulted in lower trip frequency. We notice that a potential reason for divergent results is that different configurations of digital engagement, telework, and AVs correspond to distinct TUPs, leading to opposite travel effects. We recommend that future studies integrate TUPs into assessments of travel behaviour change to better interpret causal relationships and address inconclusive findings.

In theory, the unidirectional relationship between perception and behavior has been well established. In this line, the relationship between perceived accessibility and travel behavior has also gained traction in the transport domain. There is, however, less knowledge regarding the dynamic of bidirectional effects between these two variables and (in)consistency over time. Employing the Netherlands Mobility Panel data, we investigate the direction of the (causal) effect between perceived accessibility and travel behavior/travel preference. Using a two-wave cross-lagged panel model, we test how this theory works among urban travelers (n = 4,946). The findings show that the relationship between perceived accessibility and travel-related decisions varies depending on the transport mode and whether it is about travel behavior or preference. The effects might show bidirectionality, unidirectionality, or neither. Findings highlight that the perception-behavior theory is primarily consistent with revealed travel behavior as opposed to stated preferences. We find a bidirectional perception-(travel) behavior relationship. Unlike conventional wisdom and commonly used theoretical links, we find that travel mode use has a larger impact on perceived mode-specific accessibility than the reverse effect (the more expected link). Travel behavior also shows consistently lower levels of perception-behavior dissonance than preferences do. The study finds that perception consistently influences public transport use and preferences, unlike for cars and bicycles. Policy-wise, this implies that efforts aimed at correcting misperceptions about the accessibility of public transport could still have a positive impact on individuals’ decisions to choose public transport.

The last decade denoted a growing interest in perceived accessibility, yet the link between perceived and objective accessibility measures is understudied. This paper aims to address accessibility poverty by identifying groups with different levels of perceived accessibility. To achieve this aim, we develop a latent class model that relates perceived accessibility patterns to social, transport, and geographical conditions encountered by individuals. To support the specification of the latent class model, we develop a theoretical framework that links transport, social, and geographical conditions with perceived inaccessibility. Data is obtained from the Dutch National Travel Survey, which includes information on travel patterns and preferences. In total, 20,020 participants are included in the analysis. The latent class model identified six social groups with varying levels of perceived accessibility. Notably, while 89% of the individuals perceive excellent accessibility, a minority of 11% experiences different forms of inaccessibility. In addition, the latent class model showed that social rather than transport or spatial conditions encountered by individuals determine perceived inaccessibility. The results lend support to tailored policies aimed at reducing accessibility poverty and social exclusion for specific segments of the population.

Bert van Wee, professor in Transport Policy at Delft University of Technology, the Netherlands, faculty Technology, Policy and Management, is retiring. Given his large contributions to EJTIR as Editor-in-Chief, editorial board member, author and reviewer, this Editorial Note is dedicated to his work for EJTIR. Over 25 years, van Wee published 18 papers and 1 book review in EJTIR covering a wide range of topics from road pricing to urban rail transport, vehicle automation and port throughput. What his studies have in common is that they explore how transport policies affect land-use and travel behaviour, as well as the economic and wider societal impacts of those policies. Bert van Wee’s generalist view on the transport system is rare, but, given the rising complexity of the system, increasingly needed to indeed be able to address the future challenges.

As claimed by the aviation industry, sustainable aviation fuels offer significant environmental benefits, yet their impact on travel behavior remains underexplored. The current study investigates potential shifts in travel behavior in response to the introduction of zero-emission flights. A stated choice experiment using a sample from the UK general public evaluates preferences for flights, trains, and cars based on travel time, cost, and carbon emissions. Covariates, such as attitudes towards zero-emission flights, flight-shaming norms, and sociodemographic factors, are incorporated into a latent class choice model. Results reveal heterogeneity in zero-emission flight preferences, with subgroups showing high sensitivity to travel cost and distance. Overall, travel choices remain stable even with longer zero-emission flight durations, highlighting ticket price as a primary concern. A group with less sustainable choices, characterized by unfavorable attitudes and flight shame norms, leans towards cars if zero-emission flights are costly for short-haul journeys. Notably, this subgroup with limited preference for zero-emission flights, predominantly male and high-income, shifts strongly to zero-emission flights for long-haul journeys, displaying the lowest price sensitivity.

Noise annoyance and its relation to health outcomes have been studied extensively. The vast majority of studies in this field use cross-sectional data. Such data does not allow investigation of temporal effects or the direction of these effects. It is reasonable to expect that the effects of noise on health build up over time. Moreover, noise may not only impact health outcomes, but health outcomes may also impact the sensitivity to noise – hence flipping the direction of the effect. Further adding to the complexity of the relationship between noise and health outcomes is the fact that personality traits may influence re-ported noise annoyance. This study aims to shed light on the accumulative effects of noise annoyance on health, as well as the bidirectional relationships between noise annoyance and health. To do so, we analyze eight years of data from the Dutch Longitudinal Internet Studies for the Social Sciences (LISS) panel. Specifically, we conduct a Longitudinal Latent Class Analysis to identify annoyance profiles and analyze the effect of Big Five personality traits on the likelihood of belonging to the different annoyance profiles. Furthermore, we use Cross-Lagged Panel Models to analyze whether changes in noise annoy-ance precede changes in health outcomes or vice versa. We find three different profiles of noise annoy-ance, namely chronically annoyed people, occasionally annoyed people, and people who are generally not annoyed. Noise annoyance was found to be relatively stable over time. Regarding personality traits, we find that extraversion and emotional stability decrease the chance of belonging to the cluster of chronically annoyed persons, while openness has the opposite effect. Finally, chronic annoyance shows a significant effect on self-reported heart complaints and sleeping problems, while the effects of noise annoyance profiles on high blood pressure and heart attacks are insignificant.

Gender violence encompasses a multitude of morally problematic psychological, physical, and sexual behaviors that, in most countries, constitute criminal offenses. In this study, we investigate the association between moral foundations (Care, Fairness, Loyalty, Authority, and Sanctity) and punitive responses to gender violence offenses. Our case study focuses on gender violence in Portugal, a country in which these offenses are a prevalent social problem. We collected data on gender violence legal cases decided in Portuguese courts between 2002 and 2022, and we used a latent class cluster analysis model to identify the complex patterns in the data and reduce such patterns to a distinct number of clusters. Four main clusters unravel latent relations between the foundations mapped in the legal narratives and corresponding punitive responses: (i) Affirmative with suspended prison time (moral rhetoric rooted in Authority); (ii) Mixed outcomes but no prison time (moral rhetoric rooted in Sanctity); (iii) Affirmative with lengthy prison time large compensation (moral rhetoric rooted in Loyalty and Care); and (iv) Affirmative with court fines (moral rhetoric rooted in Fairness). The moral foundations provide a valuable lens to understand the problem of gender violence, but further research is needed to establish the causal mechanisms between morality and punitive responses to gender violence.

Attitudes have been used as explanatory variables of travel behaviour for decades, typically under the assumption that there is a causal effect of attitudes on behaviour. However, recent research has shown that the relationship between attitudes and travel behaviour is bi-directional. In this study we use a longitudinal modelling technique on panel data to 1) separate within-person effects from between-person associations and 2) test whether the within-person effects changed during the COVID-19 pandemic. We find that the within-person effects were weaker during the pandemic than they were before the pandemic. In addition, the within-person effects were much smaller than would be expected based on methods that do not separate within-person effects from between-person associations. This means that researchers should be careful when basing policy recommendations on cross-sectional correlations between attitudes and behaviour for two reasons: first, the problem of endogeneity, and second, the highly relevant separation of within-person effects from between-person relations.

Automated vehicles (AVs) may transform not only our travel experience but our complete daily schedules. This study analyses the data from an interactive stated activity-travel survey using latent class cluster analysis to uncover the types and prevalence of schedule changes with AVs. The analysis reveals that the majority of respondents expected little to no changes in their schedules. Importantly however, these responses are correlated with low commitment to the survey, evident in unrealistically short response times to non-central survey parts and simpler representations of their current schedules. The remaining responses reveal significant and varied changes in activities on board and outside travel, and in commute departure times. We conclude that the prevalence of schedule changes may be underestimated in our and possibly other AV studies due to low survey commitment. Our findings also highlight diverse potential motivations behind schedule changes with AVs: while some travellers may desire to free up time for other activities during the day (time saving), others may satisfy an unmet activity need by engaging in on-board activities (time spending). Considering this heterogeneity is crucial in endeavours to quantify the total benefits and costs that automated vehicles will bring to their users.

Over the past years, aviation policies are more and more focussed on sustainability rather than connectivity, putting pressure on airlines to re-design the network. For this, evaluating air travellers their preferences on direct routing compared to lay-overs is needed to make well-informed design choices. This paper examines the preferences of air travellers on direct itineraries by applying a data-driven approach. To this end, a stated preference choice experiment is developed and implemented in an online survey. The results of the latent class choice model show two types of flyers with different preferences, labelled as time sensitive and price sensitive flyers. The model outcomes indicate that both are willing to pay for direct itineraries, while time sensitive flyers are willing to pay substantially more. Other flight characteristics also play an important role in air travellers’ route choice, such as the distance to the airport, travel time, and transfer time. Travel motive, ticket price compensation by the employer, and experience with layovers drive whether air travellers belong to the time or price sensitive flyers. The distinction between time and price sensitive flyers and their preferences is expected to yield more tailored transport policies than a distinction between, for instance, business and non-business. Future research should focus on the societal impact of a reduction in direct itineraries for air travellers, using insights gained in this study.

In light of growing environmental challenges, the need to reconsider how we approach personal transportation is becoming increasingly evident. A shift from a private car-focused mobility system towards a more sustainable and equitable transportation system is needed. Car sharing is considered a means to achieve this, however, its usage and its impact are not entirely understood, as many studies do not consider the motives of individuals to use this alternative, treating the population of users as a homogeneous group. This study aims to reveal distinct car sharing usage profiles to gain a thorough understanding of the various motivates behind car sharing and its relation with travel behaviour. Six user profiles are uncovered using a Latent Class Cluster Analysis (LCCA) based on station-based carsharing data of one company operating in the Netherlands gathered through an online survey (N = 1281). The results show significant diversity in car sharing motives. The identified user groups have different effects on travel behaviour. Environmentally motivated car sharers use the shared car as a complete replacement for their private car, causing a substantial decrease in car ownership and usage. For utilitarian car sharers, and especially formerly carless individuals, the decrease in car ownership is less substantial and even an increase in car use can be observed. Finally, it was found that car sharing is mostly complementary to public transport use. Ways to promote the use of both modes could be explored.

Car sharing contributes to reducing emissions, resource depletion, and land take, by promoting more efficient use of vehicles that on average sit idle 96% of the time. But consumer adoption remains limited. User segmentation studies can inform efforts to mobilize potential users to join car sharing, and to anticipate what their needs and usage characteristics will be. This paper proposes a comprehensive segmentation method based on socio-demographic variables, which reveals differences in preferences for car sharing platform type, usage characteristics and societal outcomes of car sharing use. To do so, we apply a three step Latent Cluster Analysis to a nationwide sample of active car sharing users. This method results in a set of user segments that reflect distinct life phases, with different needs in terms of the frequency and type of trips made by car sharing. This is reflected in different preferences for car sharing platform types, as the likelihood to use peer-to-peer car sharing as opposed to business-to-consumer car sharing differs by user segment. The segments do not differ substantially in their motivations for engaging with car sharing. Yet, environmental motivations for car sharing outrank financial motivations, while social motivations play no substantial role. The clusters do show substantial differences in the changes in car ownership that occur while being an active car sharing member as well as the likelihood to use car sharing in place of a private car rather than public transport or walking and biking. We conclude that a comprehensive segmentation method based on socio-demographic variables provides actionable insights for upscaling car sharing adoption, as well as targeting specific user segments in order to optimize societal outcomes from car sharing use.

The fast growth of e-commerce in urban areas has led to a surge in last-mile transportation demand and an associated increase of external effects: congestion, noise and visual pollution. This paper analyses a new urban freight transport service that has a potential to reduce this footprint: crowdshipping. Crowdshipping is a service where a package is delivered via a traveller who is already making a personal trip for other purposes. The decision of whether or not to use crowdshipping is known to be subject to various service, time and price conditions, including trust in a correct delivery. The effect of trust has not been investigated explicitly, however. We conduct a stated choice experiment and estimate a hybrid choice model with trust as a situation-specific latent variable. The research design allows us to explore how the relevant attributes influence service adoption via trust. We find a significant influence of established choice attributes on service adoption, except for the delivery company’s reputation and the possibility of damage. In addition, all attributes except delivery time have a significant influence on trust. We conclude that trust has a partially mediating effect on the adoption of the service except delivery time, and a fully mediating effect on adoption via reputation and damage.

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.

Research on the relationships between travel-related attitudes and travel behaviour has recently been reinvigorated by new theorizing as well as new empirical models. While traditional theories assume a rather static role of attitudes, i.e. acting as stable predispositions that cause behaviours in a unidirectional manner, recent models assume that attitudes and behaviours mutually influence each other over time. This study aims at better understanding attitude-behaviour dynamics by capitalizing on the circumstances presented by the ongoing COVID-19 pandemic. It assesses how the fear of COVID-19 infection and (the attitude towards) working-from-home influence train use as well as train use attitudes. To explore the (within-person) reciprocal relationships between these variables, random-intercept cross-lagged panel models were estimated using a 4-wave longitudinal dataset collected during the COVID-19 pandemic from a large panel of train travellers in the Netherlands. The results indicate that train use and the attitude towards train use reciprocally influence each other. Those with stronger fears of infection in one wave tend to use the train less in a subsequent wave, but higher use of the train in one wave also reduces the fear of infection in the next. We also found that working from home (WFH) and travelling by train operate as substitutes for one another. Moreover, people who work from home frequently become more fearful of infection. All the findings are consistent with cognitive dissonance theory that people develop attitudes that align with their behaviours. The paper concludes with several policy implications related to changing attitudes and promoting train use.