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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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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To inform policies aimed at more sustainable travel behaviour, previous research has investigated the concept of multimodality. The notion underlying this line of research is that increasing the degree of multimodality will lead to less car dependence and therefore more sustainable travel behaviour. This paper investigates multimodality by inferring modality styles and revealing their response to exogenous variation in the form of the weather. The main idea of this paper is that travellers with a more multimodal modality style are more sensitive to exogenous variation, and that they are therefore more likely to resort to the use of the car when ‘car-favouring’ conditions present themselves. The results show that the effects of weather conditions on mode choices do indeed differ between three modality styles. The identified modality styles can be summarised as (1) bike + car; (2) car mostly and (3) multimodal. For the third class, which has the highest degree of multimodality, the use of the sustainable modes is more strongly affected by weather conditions when compared to the first, less multimodal, class. The least multimodal second class meanwhile is least affected by a change in weather conditions. More multimodal travellers thus seem to be more susceptible to exogenous variation, which might prevent the formation of sustainable travel habits or patterns. Based on these results, the claim that a higher degree of multimodality will lead to more sustainable behaviour and that policy makers should aim to realise a shift towards more multimodal modality styles needs to be nuanced. Policy makers should instead focus directly on increasing the attractiveness of sustainable travel modes, which will inadvertently lead to more multimodal modality styles.

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Mobility is an important part of daily life. With modern mobility systems, people have access to a range of transport modes allowing them to basically reach any destination they want. Although people often have multiple options to choose from, personal mobility is dominated by motorized road transport in many countries and cities, also in the Netherlands, owing to the ease of use and high level of flexibility. This popularity poses challenges for governments to keep their countries and cities accessible, attractive, safe and liveable since motorized road transport comes with several negative effects such as increased congestion, damage to the environment, negative effects on human health due to emissions, inefficient use of space and reduced liveability of cities. This thesis consists of studies on several mechanisms behind travel behaviour change towards sustainable travel modes, based on a large-scale longitudinal travel survey; the Netherlands Mobility Panel (MPN). As this panel has been operating for several years and collects a wide range of relevant information from its respondents, it allows studying numerous aspects of travel behaviour (change). This thesis will help policy makers understand how travel behaviour changes and provide them with knowledge to promote travel behaviour change towards a more sustainable mobility system. The focus is on four topics that are imperative to achieve this goal: the effects of life events on travel behaviour, new technologies to promote a mode shift away from car (in this case, the e-bike), the links between personal health and active travel and effects of the COVID-19 pandemic on mobility. To correctly study these topics, longitudinal data is needed, as we want to infer the direction of effects from the data rather than making assumption on this direction, with the risk of drawing wrong conclusions (e.g., we do not know whether active travel has an effect on personal health or that the effect runs from personal health to active travel). While these longitudinal data are ideally suited to study travel behaviour changes, it is crucial that the data quality is guaranteed. To address one possible cause of low data quality, the thesis includes a fifth study focused on the notion of soft-refusal, which describes the tendency of some respondents to use a strategy to lower their response burden, e.g. by claiming they did not leave their house even though they actually did. @en

In recent years, there has been a resurgence of interest in the ‘disagreement’ or dissonance between travel attitudes and behaviours. This has shown that when people experience travel-related dissonance they are less satisfied with their travel experience. However, what remains unclear is whether people experiencing dissonance are more likely to change their travel attitude or their behaviour, so that they are more closely aligned. Moreover, it is unclear whether and how life events, such as having a child, interact with creating or reducing travel-related dissonance. Using data from a large and well-designed longitudinal study, this paper addresses these two gaps in the literature on travel-related cognitive dissonance through an exploratory study. The findings suggest that dissonant travellers are more likely to change their segment membership than consonant travellers. Furthermore, in line with the theory of cognitive dissonance, people may adjust either their attitudes or behaviours to achieve a state of consonance. This suggests that policymakers should not only focus on subtle nudges aimed at changing attitudes (and subsequently behaviours) in desirable directions but also on implementing policies aimed at directly influencing behaviours, assuming that attitudes will follow.@en

In recent years, the e-bike has become increasingly popular in many European countries. With higher speeds and less effort needed, the e-bike is a promising mode of transport to many, and it is considered a good alternative for certain car trips by policy-makers and planners. A major limitation of many studies that investigate such substitution effects of the e-bike, is their reliance on cross-sectional data which do not allow an assessment of within-person travel mode changes. As a consequence, there is currently no consensus about the e-bike’s potential to replace car trips. Furthermore, there has been little research focusing on heterogeneity among e-bike users. In this respect, it is likely that different groups exist that use the e-bike for different reasons (e.g. leisure vs commute travel), something which will also influence possible substitution patterns. This paper contributes to the literature in two ways: (1) it presents a statistical analysis to assess the extent to which e-bike trips are substituting trips by other travel modes based on longitudinal data; (2) it reveals different user groups among the e-bike population. A Random Intercept Cross-Lagged Panel Model is estimated using five waves of data from the Netherlands Mobility Panel. Furthermore, a Latent Class Analysis is performed using data from the Dutch national travel survey. Results show that, when using longitudinal data, the substitution effects between e-bike and the competing travel modes of car and public transport are not as significant as reported in earlier research. In general, e-bike trips only significantly reduce conventional bicycle trips in the Netherlands, which can be regarded an unwanted effect from a policy-viewpoint. For commuting, the e-bike also substitutes car trips. Furthermore, results show that there are five different user groups with their own distinct behaviour patterns and socio-demographic characteristics. They also show that groups that use the e-bike primarily for commuting or education are growing at a much higher rate than groups that mainly use the e-bike for leisure and shopping purposes.

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Introduction: It has been estimated that physical inactivity accounts for roughly 10% of premature mortality globally in any given year. Active travel (walking and cycling) has been promoted as an effective means to stimulate physical activity. However, many of the available studies on the relation between active travel and health are based on cross-sectional data and are therefore unable to determine the direction of causation. This study aims to unravel the bidirectional relationships between active travel measured by the active modes bicycle, e-bike and walking, on the one hand, and two health outcomes, namely body-mass index (BMI) and self-rated health (SRH), on the other. Methods: To provide an initial assessment of the relationship between active travel and the two health outcomes, multivariate regression models are estimated. To study the direction of causation, Random-Intercept Cross-Lagged Panel Models (RI-CLPM) are estimated using three waves of the Netherlands Mobility Panel (MPN). Active travel is measured as travelled distances and trips with the bicycle, e-bike and walking. BMI is calculated based on weight and height, SRH is measured with a single question. Results: The regression models show that a higher BMI and lower SRH are associated with less walking and cycling, while being obese is associated with more e-bike use. The results of the RI-CLPM indicate that cycling distance has a positive effect on SRH. Furthermore, walking distance has a negative effect on BMI and BMI has a negative effect on bicycle use among people without obesity. No relationships between BMI and active travel are found for people with obesity. Conclusion: The results highlight the importance of longitudinal analyses when estimating the relationship between active travel and health. In addition, the results suggest that, relatively speaking, the increasing overweight and obesity rates may result in a decrease of bicycle use.

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COVID-19 has massively affected the lives of people all over the world. This paper presents first insights in current and potential future effects of the virus and the Dutch government's ‘intelligent lockdown’ on people's activities and travel behaviour. Findings are based on a representative sample of about 2500 respondents from the Netherlands Mobility Panel (MPN). We show that approximately 80% of people reduced their activities outdoors, with a stronger decrease for older people. 44% of workers started or increased the amount of hours working from home and 30% have more remote meetings. Most of these workers report positive experiences. Students and school pupils, however, are mostly not happy with following education from home. Furthermore, the amount of trips and distance travelled dropped by 55% and 68% respectively when compared to the fall of 2019. So-called ‘roundtrips’ (e.g. a walking or cycling tour) gained in popularity. People are currently more positive towards the car and far more negative towards public transport. Changes in outdoor activities seem to be temporal, with over 90% of people who currently reduced their outdoor activities not expecting to continue this behaviour in the future after corona. However, 27% of home-workers expect to work from home more often in the future. In addition, 20% of people expect to cycle and walk more and 20% expect to fly less in the future. These findings show that the coronavirus crisis might result in structural behavioural changes, although future longitudinal analyses are needed to observe these possible structural effects.@en