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.

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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.

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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.@en

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.@en

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.

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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.

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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.

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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.@en

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.@en

The European Union strives to align research and innovation to the values, needs and expectations of society to address societal challenges. To support this alignment the European Union endeavours to make Responsible Research and Innovation (RRI) part of the governmental policies on science and technology of its member states. If the European Union is effective in this endeavour, then principles that are common in the field of RRI should play a significant role in the perspectives that belong to the member states’ policy officers for research and innovation. In this paper we empirically check this by conducting a Q-method study on Dutch policy officers working on quantum technology-related policies. In this study we found four perspectives on innovation among these policy officers. In all these perspectives some of the RRI principles are present in merely a weak manner, or even absent, casting substantial doubts on whether RRI has become part of the EU member state governmental policies on science and technology.@en

This study investigates whether the decline in public transit ridership is a temporary phenomenon or indicative of a structural shift in travel patterns and attitudes. We estimate a latent class trajectory model using data from a comprehensive and large-scale survey administered by the Dutch national train operator conducted at eight different points in time after the onset of the pandemic. Six latent trajectories in train use and stated future intentions to use the train are revealed, showing different ‘recovery’ pathways. Whereas low-educated frequent commuters travel almost as much as before, highly educated frequent commuters and mixed-purpose travellers still travel much less, even in the last wave when all restrictions are lifted. The results indicate that travellers belonging to these classes have structurally changed their behaviour. The shift to working from home is more pronounced than the shift to private car use.

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Policies to increase the amount of time people spend working from home were widely used during the COVID-19 pandemic. Since research suggests that the resulting increase in working from home will outlast these policies themselves, policymakers want to understand the relations between working from home and travel behaviour. We apply longitudinal modelling techniques to estimate the relations between working from home and travel behaviour using panel data from the Netherlands Mobility Panel spanning the years 2017 through 2021. This allows us to separate between-persons and within-persons relations and effects and to see whether these effects changed during the pandemic. We find a negative effect of working from home on commute travel time both before and during the pandemic and a positive effect on leisure travel time only before the pandemic. The sizes of these effects remained roughly similar during the pandemic, although the extent to which working from home affected commute travel time increased during the pandemic. The net effect of working from home on travel time is negative, indicating that working from home policies could be used to reduce travel time. The results also show that some of the relationships between working from home and travel behaviour have changed during the pandemic. As a result, policymakers and transport operators should be careful when estimating future travel demand based on extrapolations of relationships found only before or during the pandemic.@en

In mobility panels, respondents may use a strategy of soft-refusal to lower their response burden, e.g. by claiming they did not leave their house even though they actually did. Soft-refusal leads to poor data quality and may complicate research, e.g. focused on people with actual low mobility. In this study we develop three methods to detect the presence of soft-refusal in mobility panels, based on respectively (observed and predicted) out-of-home activity, straightlining and speeding. For each indicator, we explore the relation with reported immobility and panel attrition. The results show that speeding and straightlining in a questionnaire is strongly related to reported immobility in a (self-reported) travel diary. Using a binary logit model, respondents who are predicted to leave their home but report no trips are identified as possible soft refusers. To reveal different patterns of soft-refusal and assess how these patterns influence the probability to drop out of the panel, a latent transition model is estimated. The results show four behavioral patterns with respect to soft-refusal ranging from a large class of reliable respondents who score positive on all three soft-refusal indicators, to a small ‘high-risk’ class of respondents who score poorly on all indicators. This ‘high-risk’ group also reports the highest immobility and has the highest attrition rate. The model also shows that respondents who do not drop out of the panel, tend to stay in the same behavioral pattern over time. The amount of soft-refusal expressed by a respondent therefore seems to be a stable behavioral trait.

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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.@en

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.@en

Background: The COVID-19 outbreak early 2020 was followed by an unprecedented package of measures. The relative calmness of the pandemic early 2022 provides a momentum to prepare for various scenarios. Objectives: As acceptance of COVID-19 measures is key for public support we investigated citizens’ preferences towards imposing measures in four scenarios: 1) spring/summer scenario with few hospitalizations; 2) autumn/winter scenario with many hospitalizations; 3) a new contagious variant, the impact on hospitalizations is unclear; 4) a new contagious variant, hospitalizations will substantially increase. Methods: Study 1 comprised a Participatory Value Evaluation (PVE) in which 2011 respondents advised their government on which measures to impose in the four scenarios. Respondents received information regarding the impact of each measure on the risk that the health system would be overloaded. To triangulate the results, 2958 respondents in Study 2 evaluated the acceptability of the measures in each scenario. Results: Measures were ranked similarly by respondents in Study 1 and 2: 1) the majority of respondents thought that hygiene measures should be upheld, even in the spring/summer; 2) the majority supported booster vaccination, working from home, encouraging self-testing, and mandatory face masks from scenario 2 onwards; 3) even in scenario 4, lockdown measures were not supported by the majority. Young respondents were willing to accept more risks for the health system than older respondents. Conclusion: The results suggest that policies that focus on prevention (through advising low-impact hygiene measures) and early response to moderate threats (by scaling up to moderately restrictive measures and boostering) can count on substantial support. There is low support for lockdown measures even under high-risk conditions, which further emphasizes the importance of prevention and a timely response to new threats. Our results imply that young citizens’ concerns, in particular, should be addressed when restrictive COVID-19 measures are to be implemented.@en

Academics are often environmentally-minded, and they often travel internationally to share their research. Are they prone to attitude-behaviour gap? We collected data from 104 academics in Europe regarding attitudes towards online conferences, flight shame and carbon offsetting, and analysed their trip-making and mode choices in hypothetical conference travel situations. We find that while respondents and their social environments are conscious of the environmental impacts of flying, travel time considerations dominate their travel choices. Respondents are willing to buy a € 5 more expensive ticket or extend their travel by train by 30 seconds to reduce 1 kg of CO2.@en

Within moral psychology, theories focusing on the conceptualization and empirical measurement of people’s morality in terms of general moral values –such as Moral Foundation Theory- (implicitly) assume general moral values to be relevant concepts for the explanation and prediction of behavior in everyday life. However, a solid theoretical and empirical foundation for this idea remains work in progress. In this study we explore this relationship between general moral values and daily life behavior through a conceptual analysis and an empirical study. Our conceptual analysis of the moral value-moral behavior relationship suggests that the effect of a generally endorsed moral value on moral behavior is highly context dependent. It requires the manifestation of several phases of moral decision-making, each influenced by many contextual factors. We expect that this renders the empirical relationship between generic moral values and people’s concrete moral behavior indeterminate. Subsequently, we empirically investigate this relationship in three different studies. We relate two different measures of general moral values -the Moral Foundation Questionnaire and the Morality As Cooperation Questionnaire- to a broad set of self-reported morally relevant daily life behaviors (including adherence to COVID-19 measures and participation in voluntary work). Our empirical results are in line with the expectations derived from our conceptual analysis: the considered general moral values are poor predictors of the selected daily life behaviors. Furthermore, moral values that were tailored to the specific context of the behavior showed to be somewhat stronger predictors. Together with the insights derived from our conceptual analysis, this indicates the relevance of the contextual nature of moral decision-making as a possible explanation for the poor predictive value of general moral values. Our findings suggest that the investigation of morality’s influence on behavior by expressing and measuring it in terms of general moral values may need revision.@en

Cities around the world make efforts to reduce car use and its negative consequences but even in cycling cities, mobility behaviour is still dominated by car use. This paper examines the effect of life events, changed resources and attitude-behaviour incongruency on changes in people's mobility style. The paper is based on a longitudinal survey including people who participated 2–3 times within a 2.5-year period. Applying latent transition analysis based on participants' mobility attitudes and behaviour, we identified 5 distinct mobility classes: one functional and one enthusiastic car user class; one car-prone and one car-aversive cycling class and a public transport class. Free-floating car sharing subscription had an effect on initial class membership but not on transition probability. However, shifts were significantly related to age and gender, changes in income and place of residence. Yet, most effects disappeared when car ownership was included in the latent transition model. Once people end up in car-centred mobility styles, a voluntary transition back seems difficult to achieve.

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