Netherlands Mobility Panel Research Articles

State-of-the-art of Longitudinal Travel Surveys – A Comparison of the MOP and MPN

Longitudinal travel surveys are needed to capture individual travel behaviour changes. Only two longitudinal tavel surveys of national relevance are currently in operation, the German Mobility Panel (MOP) since 1994 and the Netherlands Mobility Panel (MPN) since 2013. This paper provides an overview of both panels' differences and similarities in design and data collection. Furthermore, representativeness, diary fatigue and non-random attrition are assessed in both panels to show the challenges panel surveys have to deal with. Overall, this paper shows important aspects of a panel survey that should be considered when designing a new longitudinal travel survey.

Travel behavior changes due to life events: Longitudinal evidence from Dutch couple households

Despite increasing interest in how travel behavior changes over time, few studies have investigated how life events alter travel behavior, especially from a household perspective. This study examined the extent to which life events influenced changes in travel mode frequencies at the household level. We applied structural equation modeling based on the Netherlands Mobility Panel data for 2014 and 2016. For both partners, acquiring a household car significantly increased car use, and disposing of household cars decreased car use frequency. The number of household cars was inversely related to men’s train use. Childbirth in the household decreased both partners’ cycling frequency. Men’s job changes increased train use. These findings emphasize that life events can influence changes in travel behavior within household partners.

Commute mode switch and its relationship to life events, built-environment, and attitude change

Policies aimed at discouraging car commuting can be more effective when targeted at important determinants that inhibit or promote car use. However, evidence on what factors motivate commuters’ decision to start or stop car use is still limited. This study uses the Netherlands Mobility Panel data (MPN) data to examine how various factors, including life events, travel attitude, and the built-environment influence commuters to switch from non-car to car and car to non-car and whether commuters adjust their attitude following mode switch. Results show that beginning a new job and important life events such as childbirth or beginning to cohabitate are powerful triggers of mode switch. Various employer-provided car incentive programs strongly discourage car commuters from shifting to alternative modes. Travel attitude influences mode switch decision and attitude also changes following mode switch according to newly adopted travel behavior. Important policy implications informed by these findings are discussed.

The relations between working from home and travel behaviour: a panel analysis

AbstractPolicies 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.

Effects of life events and attitudes on vehicle transactions: A dynamic Bayesian network approach

Individual and household life events are interdependent and influence mobility-related decisions at different levels over time. This paper developed an integrated dynamic model to capture the interdependences among life events, with a special focus on vehicle transactions. Particular attention was paid to the inclusion of vehicles’ characteristics such as the age, fuel type, and size of cars, which are pertinent to emission forecast. A dynamic Bayesian network (DBN), containing individual and household characteristics and latent attitudes toward car ownership and use alongside life events, was employed to study the interdependences. The temporal relationships among life events and lead-lag effects were also captured in the DBN. The longitudinal survey data “the Netherlands Mobility Panel (MPN)” from 2013 to 2018 was used to train and test the DBN. The analysis results confirm the dynamic interdependences between vehicle transactions and other life events and reveal noticeable associations between attitudes and purchase decisions. It is found that several life events (e.g., “Birth of a baby”, “Marital status change”) have concurrent or varied lag-effects on vehicle transaction decisions. The validation indicates that the proposed DBN approach has a high predictive accuracy of vehicle transaction decisions and other life events.

Estimating post-pandemic effects of working from home and teleconferencing on travel behaviour

Like in many other countries, the Dutch government instructed people to work from home where possible during the COVID-19 pandemic to halt the transmission of the virus. This policy seems to have resulted in a structural increase in working from home and teleconferencing that will outlast the pandemic. However, the longer-term effects on travel behaviour are still unclear. Making use of panel data collected using the Netherlands Mobility Panel, this paper has two main aims. First, it analyses developments in working from home and teleconferencing since COVID-19. Second, it estimates the expected post-pandemic effects on travel behaviour. The results show that compared to before the pandemic, the average number of hours that people work from home has doubled and roughly two-thirds of respondents indicate that they teleconference more often. We estimate that structural, post-pandemic increases in working from home and teleconferencing will result in a negative effect on distances travelled by train (-3% to -9%), by bus, tram, and metro (-1% to -5%) and car (-1 to -5%). The estimated effect on the distance travelled by bicycle (-2% to 0%), and walking (0% to +1%) is smaller or even positive, due to people making more complementary trips for other purposes when working from home. When interpreting these results, we should keep in mind that due to various other factors, such as population growth, total travel demand will still grow in the near future.

A composite X-minute city cycling accessibility metric and its role in assessing spatial and socioeconomic inequalities – A case study in Utrecht, the Netherlands

The 15 min city (or “X-minute city” in general) concept aims to give people access to all essential services and daily needs (e.g., healthcare, education, etc.) within X minutes of active transportation, to improve transport equity, sustainability, and traffic safety. To date, there is a lack of methods and tools to assess to what degree cities currently, or after implementing policies, comply with the X-minute city concept. This research aims to develop a methodology for quantifying the X-minute city through a metric (CSx) that was developed based on an accessibility framework and tested for cycling mode in the Utrecht region in the Netherlands as a study area. Travel data from the Netherlands mobility panel were analysed to determine input characteristics of the metric, such as the weight of destination types. Standardized gravity-based 2-step floating catchment area (2SFCA) accessibility scores for all destination types were weighted and aggregated into a composite metric that shows relative scores as an X-minute city. The results of the analysis show that 100% of the population in the Utrecht region has access to at least one destination for all 9 destination types within 15 min, whereas this number reduces to 94% within a 10 min cycling threshold; indicating the status of Utrecht as a cycling city with cycling-friendly infrastructure. Furthermore, low-income groups do not have lower cycling accessibility to the services in the 15 min city in the study area, reinforcing the notion that cycling can be an effective solution to reduce transport inequalities. The developed metric can be used to assess cities on their way towards becoming X-minute city, prioritise neighbourhoods to develop, set quantifiable goals, and evaluate planning scenarios.

Multimodal travel behaviour, attitudes, and cognitive dissonance

Multimodal travel behaviour, also termed multimodality, refers to as the phenomenon of an individual using more than one mode of transport in a given period. Studies indicate that encouraging multimodality may provide a solution to induce modal shifts towards sustainable transport. In this research, we investigate the distribution of mode-specific attitudes and attitude-mode use incompatibilities across clusters and levels of multimodality using the Netherlands Mobility Panel. We find that the most positive attitude does not necessarily correspond to the mode with the highest level of use. Attitudes towards car use are most positive, independent of the cluster membership and levels of multimodality. We also find that multimodal public transport users (compared with car-dominant users) and those with a higher level of multimodality are more likely to be attitudinally incompatible with frequently-used modes and the composition of their existing mode sets of travelling. This suggests that multimodal individuals may tend to experience cognitive dissonance with their mode use. Our findings also help uncover the psychological mechanism underlying a recent important finding that multimodal individuals are inclined to change their mode use patterns over time.

Causal relations between body-mass index, self-rated health and active travel: An empirical study based on longitudinal data

IntroductionIt 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. MethodsTo 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. ResultsThe 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. ConclusionThe 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.

E-bike user groups and substitution effects: evidence from longitudinal travel data in the Netherlands

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.

Exploring the relationship between life events, mode preferences and mode use of young adults: A 3-year cross-lagged panel analysis in the Netherlands

This paper examines the impact of life events on transport mode preferences and the frequency of mode use of young adults in the Netherlands, using data from three waves (2014, 2015 and 2016) of the Netherlands Mobility Panel. The database used for this paper contains 1,180 young adults (18–39 years) who participated in all three waves. Cross-lagged structural equation panel models were estimated to examine the longitudinal relationship between life events (childbirth, moving home or a new job) and travel behaviour. We investigated the relationship between frequency of mode use and mode preference over time, and the impact of life events on mode preference and frequency of mode use. Young adults showed very stable behaviour over time: frequency of mode use and mode preference are good predictors of frequency of mode use and mode preference in the future. The results show that changes in the frequency of mode use have a stronger effect on changes in mode preferences than vice versa. In addition, young adults subjected to life events are more likely to change travel behaviour. Car use and car preference are found to increase significantly after childbirth. Bicycle use and preference for the bicycle were more likely to increase for young adults who moved home. Changing jobs showed a negative association with bicycle use. These life-changing moments could offer a window of opportunity for policymakers and other parties to create more awareness of alternative, more sustainable, modes of transport.

Early adopters of Mobility-as-a-Service in the Netherlands

The concept of Mobility-as-a-Service (MaaS) is rapidly gaining momentum. Parties involved are eager to learn more about its potential uptake, effects on travel behaviour, and users. We focus on the latter, as we attempt to reveal the profile of groups within the Dutch population that have a relatively high likelihood of adopting MaaS in the near future, apart from the actual supply side.MaaS is a transport concept integrating existing and new mobility services on a digital platform, providing customised door-to-door transportation options. Based on common denominators of MaaS as found in the literature, we have established five indicators to identify early adopters: innovativeness, being tech-savvy, needing travel information, having a multimodal mindset, and wanting freedom of choice. These five indicators are the building blocks of our Latent Demand for MaaS Index (LDMI), and were constructed using 26 statements and questions from a special survey conducted in 2018 among participants of the Netherlands Mobility Panel (MPN). The features derived from the MPN serve as independent variables in a regression analysis of the indicators used to ascertain the profile of early adopters.The results of our model indicate that early adopters are likely to be highly mobile, have a high socio-economic status, high levels of education and high personal incomes. Young people are more eager to adopt MaaS than older adults. Early adopters are healthy, active and frequent users of trains and planes. The characteristics of MaaS's early adopters overlap in numerous ways with those of innovative mobility services users and with the general characteristics of early adopters as found in innovation studies.

How COVID-19 and the Dutch ‘intelligent lockdown’ change activities, work and travel behaviour: Evidence from longitudinal data in the Netherlands

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.

Trip chain complexity: a comparison among latent classes of daily mobility patterns

This paper studies the relationship between trip chain complexity and daily travel behaviour of travellers. While trip chain complexity is conventionally investigated between travel modes, our scope is the more aggregated level of a person’s activity-travel pattern. Using data from the Netherlands Mobility Panel, a latent class cluster analysis was performed to group people with similar mode choice behaviour in distinct mobility pattern classes. All trip chains were assigned to both a travel mode and the mobility pattern class of the traveller. Subsequently, differences in trip chain complexity distributions were analysed between travel modes and between mobility pattern classes. Results indicate considerable differences between travel modes, particularly between multimodal and unimodal trip chains, but also between the unimodal travel modes car, bicycle, walking and public transport trip chains. No substantial differences in trip chain complexity were found between mobility pattern classes. Independently of the included travel modes, the distributions of trip chain complexity degrees were similar across mobility pattern classes. This means that personal circumstances such as the number of working hours or household members are not systematically translated into specific mobility patterns.

The experienced mode choice set and its determinants: Commuting trips in the Netherlands

Abstract Active modes take up an increasingly important place on the global policy-making agenda. In the Netherlands, a country that is well-known for its high shares of walking and cycling, the government aims at achieving a modal shift among 200,000 commuting car drivers towards using the bicycle. To this end, policy measures need to be introduced. When the aim is to achieve a modal switch over an enduring period of time, it is more relevant to know the likelihood of including or excluding a mode in the mode choice set, compared to choosing a mode for a single trip. Therefore, we investigate the formation of the experienced choice set (set of modes used over a long period of time), where the aim is to identify determinants that influence the inclusion or exclusion of a mode in this set. We estimate discrete choice models, based on survey data from the Netherlands Mobility Panel (MPN) and a complementary survey, where individuals were asked to report the frequency of using certain modes of transport for commuting trips over the course of half a year. This study shows that the experienced choice set for commuting is unimodal for the majority of the individuals, and remains constant over time for most individuals. Reimbursement by the employer for using a certain mode is the most important determinant influencing the experienced choice set, followed by ownership characteristics and urban density. We show that the mode choice set formation depends on more determinants than previously assumed.

Modal shift implications of e-bike use in the Netherlands: Moving towards sustainability?

This paper investigates the modal shift patterns of e-bike users in the Dutch context. We focus on the change in e-bikers’ travel behavior to assess whether this change benefits sustainability. Our study provides direct ecologically valid evidence on modal shift by using a longitudinal dataset from the Netherlands Mobility Panel survey. We examine e-bikers’ modal shift patterns before and after acquiring an e-bike. The findings indicate that after e-bike adoptions, conventional bike use reduces significantly, while car use reduces less strongly. Nonetheless, the share of car kilometers is much larger than that of conventional bikes at the baseline. Besides, the emission rate per passenger kilometer of an e-bike is several times lower than that of a car. These imply a net environmental gain after e-bike adoptions. The present study also sheds light on modal shifts at a disaggregated level by investigating those e-bikers who are more likely to drive less after e-bike adoption. The findings suggest that e-bikers younger than 50 and those around retirement age (60–69) seem more likely to step out of their cars. Additionally, people living in rural areas tend to be more likely to reduce their car use than their counterparts in highly urbanized areas. Based on our findings, we present policy recommendations for achieving a greener shift in mobility systems.

Linear, non-linear, bi-directional? Testing the nature of the relationship between mobility and satisfaction with life

Travel is one of the most important facilitators of life and has been widely acknowledged as a prerequisite for economic and social activity. Research developing in recent decades has found that limitations to mobility and accessibility can reduce satisfaction with life. To date, research in this field assumes a linear and one-way relationship between the two—i.e. that ‘more mobility’ results in ‘more life satisfaction’. Yet diminishing marginal returns on happiness are found in many related fields such as economics, and there is always the possibility that happier people travel more than unhappy people. To the authors’ knowledge, this paper presents the first attempt to look for evidence of a non-linear relationship between mobility (measured as trip-making) and life satisfaction, and the first to test the direction of causality between the two factors. It uses a sample of some 1500 adults in the Netherlands Mobility Panel. Linear and segmented regression models were used to associate trip-making with satisfaction with life, when controlling for income, age, self-rated health and other demographics. Counter to expectations, five different model specifications suggest that the relationship between trip-making and satisfaction with life is linear. Furthermore, a structural equation model found that the relationship between mobility and satisfaction could run in either direction. This study questions many of the assumptions made about the relationship between transport and subjective well-being. Given the increasing prominence of this topic, much research is needed to further explore these complex relationships.

Longitudinal changes in transport-related and recreational walking: The role of life events

Walking is a common form of physical activity and has a considerable impact on public health. Walking behavior may change over time due to life events, including residential relocation. Only a few studies based on longitudinal data have examined the impacts of life events on walking behavior. The present study investigated the extent to which life events lead to changes in transport-related and recreational walking duration, by analyzing longitudinal panel data from the Netherlands Mobility Panel (MPN) for the years 2013 and 2015. In total, 1185 respondents aged 18 or older who completed both survey waves were included in our sample. Multilevel mixed-effects Tobit regression models were fitted and showed that both childbirth and relocation to less urbanized areas were related to an increase in transport-related walking over time. No significant associations of life events with recreational walking were observed. Findings suggest that transport-related walking is more likely to be influenced by changes in the household composition and residential relocation than recreational walking. Further longitudinal research is needed to verify our findings and gain insight into the mechanisms underlying these relationships.

Do changes in travellers’ attitudes towards car use and ownership over time affect travel mode choice? A latent transition approach in the Netherlands

Abstract This paper examines how changes in travellers’ attitudes towards car use and ownership change over time and how these changes influence car use, based on the 2014 and 2016 waves of the Netherlands Mobility Panel (N = 1640). A latent transition model was estimated to investigate transitions between different segments based on travellers’ attitudes towards car use and ownership, and the latent transition probabilities were used to predict changes in mode use. Four latent classes were found to reflect the participants’ attitudes: cost-sensitive, car-minded, environmentally aware and social-conscious travellers. Most of the participants remained in the same class between 2014 and 2016, which suggests that attitudes towards car use and ownership are stable over time. Also, the results indicate that car use and car ownership may be less widespread among younger adults. Only when younger adults face life events, such as moving, starting a job or become parents, transitioning to more car-oriented profiles appears more likely. Changes in attitudes towards car use and car ownership do not significantly affect car use (number of trips per day), except for the social-conscious travellers who switched to the car-minded class. This suggests that, in most cases, a more positive or negative attitude towards car use and ownership does not directly affect the frequency of car use.

Travel mode attitudes, urban context, and demographics: do they interact differently for bicycle commuting and cycling for other purposes?

This study examined whether interactions between travel mode attitudes, urbanization level, and socio-demographics were different for bicycle commuting and cycling for other purposes. Data were obtained from the 2014 wave of the Netherlands mobility panel (MPN). In total, 2673 respondents (18 + years) who had recorded at least one trip on the days covered by the survey were included in the sample. Four outcomes were constructed, two of which concerned commuting-related cycling: any commuting-related bicycle usage (yes vs. no) and average cycling duration (in hours per weekday). Likewise, two similar outcome variables concerning cycling for other proposes were constructed. These outcomes were analyzed by means of Tobit regression models (cycling duration) and binary logistic models (any bicycle usage). Attitudinal factors concerning different travel modes, namely bus, car, cycling, and train, were constructed by means of factor analysis. The results showed that a positive attitude toward cycling was positively related to bicycle commuting duration, but this association was less strong among those with a positive attitude toward bus use. Having a positive cycling attitude had a weaker association with both bicycle commuting usage and duration in those who do not always have a car available. Regarding cycling for other purposes, cycling attitude had a stronger positive association with cycling duration among residents of very highly urbanized area, compared to residents of less urbanized areas. The available evidence, though limited, suggests that targeting attitudes can have a measurable impact on bicycling, but not to the same extend among all people.