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Peak-avoidance has been suggested as a strategy to ease congestion and improve the travel experience in the road traffic system. However, commuters’ trade-offs when choosing whether to avoid the peak in the context of subway use have not yet been explored. In highly concentrated megacities, high demand during peak hours in the subway leads to long queues waiting to enter stations or platforms, as well as crowded trains, which yields highly negative externalities. This paper contextualizes and incorporates commuters’ perceived value as a theoretical basis to explain how perceived benefits and perceived sacrifices affect commuters’ intentions to avoid the peak in subway systems. A hybrid model was constructed to incorporate the perceived benefits and perceived sacrifices as latent variables to understand peak-avoidance behavior. Social norms, previous habits, and personal subjective feelings have significant impacts on subway commuters’ peak-avoidance decisions. In addition, our combined model improved the explanatory power compared to a traditional ordered logit model. The framework can be used as a theoretical basis for further development of behavioral research into commuters’ decision-making. Finally, these findings provide meaningful guidance for the government and subway companies to encourage travelers to avoid rush hours effectively.

Considering that most working adults spend nearly half their waking time at work, creating a supportive built environment around workplaces could be a feasible approach to maintain adequate levels of physical activity. However, the extent to which the built environment around workplaces influences walking behaviors in working adults remains unclear. Using survey data of 1009 full-time employees in Shanghai, China, this study assessed the nonlinear relationships between the built environment characteristics around workplaces and three domains of walking behaviors (commuting, utilitarian, and recreational walking). Using gradient boosting decision trees, our results showed that the built environment around workplaces is crucial for higher levels of walking behaviors, but built environment features tended to have distinctive associations with different domains of walking behaviors. Specifically, the number of physical activity facilities was positively associated with all three domains of walking behaviors, while a high floor area ratio was negatively associated with different domains of walking behaviors to some extent. Furthermore, several built environment characteristics, such as land use entropy, street view greenery, distance from home to the city center, and distance between the city center and workplaces had distinctive associations with different domains of walking behaviors. The findings of this study could provide nuanced guidance for creating pedestrian-friendly environments around workplaces to promote walking behaviors and overall physical activity levels in the working population.

This paper reports on the effects of an e-cycling stimulation program on travel satisfaction in the province of North-Brabant, the Netherlands. The program was designed to stimulate car-commuters to shift to e-bike in daily commuting, earning a monetary incentive for each kilometre e-cycled. With a longitudinal design, this study shows a significant increase in travel satisfaction when switching from car to e-bike. Starting from an average slightly positive satisfaction with car commuting, participants reported an extremely positive expected travel satisfaction by e-bike. Although a bit less than expected, the experienced travel satisfaction with e-cycling was high after a period of a month and even increased in the following period of half a year. Where the participants can be sub-divided into car-only and multi-modal car-commuters, this distinction does not show in the experienced travel satisfaction with e-cycling. Our study indicates that the hedonic treadmill mechanism does not automatically apply to the satisfaction with e-cycling. Multivariate analyses suggest that the increase in the travel satisfaction is affected by self-reported health, car ownership, urbanization degree, whether car use and e-cycling are experienced as strenuous, congestion on the route and the attractiveness of the cycle route.

In this paper, we argue that the current focus on cycling must not neglect the need to improve public transport services for the large number of people who do not want to or are unable to cycle. An ...

Although interest in the concept of tradable driving credits (TDC) has increased in recent years, empirical research into the potential effects of such a measure is scarce. The study reported in this paper employed an activity-based approach to investigate drivers’ responses to two distance-based TDC scenarios. Three hundred and eight Dutch frequent car commuters participated in an online stated adaptation experiment in which they recorded their car use for 7 days and, in response to the TDC scenarios, had the opportunity to reorganise their car use pattern, if desired. This paper investigates adaptation behaviours at the trip level. The results show that approximately 30% of trips made for maintenance and leisure-oriented activities were subject to change. In cases of change, a travel mode change was the most preferred adaptation strategy. A mixed logit modelling framework is used to test the effect of a variety of activity/trip attributes, TDC scenario attributes, and individual characteristics on the preference for adaptation alternatives.

There is increasing interest in the concept of tradable driving credits (TDC) as an alternative road pricing measure. To a considerable extent, this interest is inspired by the belief that TDC will address some major equity-related concerns, which are often raised in the case of traditional road pricing, because the measure is revenue-neutral, offers an opportunity for individuals to gain, and guarantees a minimum amount of ‘free’ travel through the allocation of personal credit allowances. This study investigates the acceptability of a proposed kilometre-based TDC scheme for personal car use. By analysing data from the Netherlands and China (Beijing), opinions towards TDC and its determinants are studied in two different cultural, societal and institutional contexts. Acceptability was much higher in Beijing: 67% compared to 22% in the Netherlands. We relate this difference to higher congestion levels in Beijing and the city’s current license plate-based driving restriction policy, compared to which TDC is evaluated to be more effective and fair by a majority of the participants. Having a higher income was positively related with acceptability in both countries, as were expected effectiveness and fairness. The effect of perceived fairness was particularly strong in Beijing.

Facing serious challenges of traffic congestion and air pollution, Beijing has implemented a series of traffic polices. In this paper, we first investigate the effectiveness of existing traffic measures in Beijing and analyse the underlying factors from the perspective of drivers, which provide insights for the traffic regulations in other cities worldwide. While the car ownership restriction has effectively limited the total number of vehicle in Beijing, the effect of the car use restriction only lasts for a short period. A survey on drivers’ opinions and attitudes towards the traffic situation and a potential measure, i.e., tradable driving credit (TDC), is conducted. Although traffic data shows that congestion improved and traffic was slightly congested in recent years in Beijing, most respondents believe congestion is still serious in Beijing. However, they think the impact of traffic congestion on their personal car use is relatively low, which could partly explain why so many travellers still depend on driving given the relative convenient transit facilities in Beijing. In addition, a large proportion of respondents treat personal cars as a representation of social status and think driving bring them pleasures, which indicates that it may be hard to further decrease the share of car trips in Beijing. According to their attitudes and social-economical characters, respondents’ willingness on their changes of travel behaviours under TDC is investigated. The results show that individuals’ social-economic characters such as income level, education and family size and the symbolic meaning of personal cars have significant influence on respondents’ willingness to switch to other transport modes.

Commuting imposes opportunity costs on travelers since those with long commutes have less time to participate in other activities. This paper examines how commute duration is associated with activity patterns. It utilizes a two-day time use survey administered in the United Kingdom in 2014 and 2015. Focusing on full-time employees and controlling for socio-demographic characteristics, we regress time spent engaging in 22 different activities on commute duration using OLS and Cragg two-part hurdle modeling. We separately test the effects of commute duration on activity participation for men versus women and for single persons versus persons in couples. We also report the subjective well-being (SWB), specifically the hedonic affect, associated with these activities as determined by using fixed-effects panel regression. The estimations suggest that commutes are associated with time constraints and entail trade-offs, with longer commutes being associated with significantly less time engaging in most of our activities including sleep, cooking, housework, shopping/accessing services, arts/entertainment activities, TV/music time, computer games and other computer use, visiting with others, sports/exercise/outdoor activities, hobbies, volunteering, and non-work travel. Those with longer commutes are found to tend to engage in more of two activities: work and eating out. The activities those with longer commutes tend to forego run the gamut from high-SWB to low-SWB. Given that the lowest-SWB activity in our sample is commuting itself, it appears as if the substitution of nearly any activity for commuting may bring emotional benefits. In all, the results suggest that longer commutes are associated with significant emotional costs.

This paper reports on the effects of an e-cycling incentive program in the province of North-Brabant, The Netherlands, in which commuters could earn monetary incentives when using their e-bike. The study used a longitudinal design allowing to observe behaviour change and mode shifts. The program appeared to be highly effective in stimulating e-bike use, as one month after the start of the program, the share of commute trips made by e-bike increased from 0% to 68%, with an increase up to 73% after half a year of participating. The environmental, congestion and health benefits of this shift are however mixed. Half of the e-bike trips substitute car trips, with positive effects on environment, congestion and health. The other half substitutes conventional cycling trips, implying fever health benefits. Our analyses further suggest that distance is an important factor for adopting e-cycling, where e-bike has a larger acceptable distance than a conventional bike. Nevertheless, we observed that the likelihood to use the e-bike decreased as commuting distance increased. Multivariate analyses suggest that a shift to e-cycling is affected by age, gender, physical condition, car ownership and household composition. Our study did find support for the hypothesis that having a strong car-commuting habit decreases the probability of mode shift to a new mode alternative. In contrast, multimodality may increase the likelihood of e-bike use as a result of openness to other travel options and a more deliberate mode choice. Lastly, dissatisfaction with the current travel mode positively influences mode shift towards the e-bike. Our results imply that stimulating e-cycling may be a promising way of stimulating physical activity, but that it will be most effective if targeted at specific groups who are not currently engaging in active travel.

With the continuous advancement of (mobile) ICT devices and applications, their impact on travel, activities and time use becomes more diverse. This holds in particular for apps developed for mobile devices (smartphones). In this paper, we argue that the effect of ICT on travel and activities should be analysed at the level of a single specific device or application, rather than for broad classes of ICT devices. We propose activity theory as a framework to analyse the impact of smartphone apps on travel and activities. Activity theory describes how subjects apply tools (such as apps) to work on an object and achieve an outcome that is in line with the subject’s motive. The application of the tool is embedded in an activity system which includes a community, formal and informal rules and in which a division of labour exists. We apply activity theory to analyse the effects of Whatsapp and travel feedback apps, based on existing literature about these apps. The analyses suggest that the activity systems of each app differ greatly in terms of object, motive, outcomes, community and rules, with implications for their use and impact. Both apps have an impact on travel, but differ with respect to whether this effect is intentional. For both apps contradictions in the activity system can be identified, which may give rise to further development of the activity system. These seem, however, to be largest for travel feedback apps. Based on our exploration, we argue that quantitative research on the impact of apps should be complemented by qualitative research based on activity theory. In particular, activity theory may help to gain a better understanding of underlying mechanism by which apps influence travel, to strengthen the theoretical underpinning and interpretation of the results of quantitative research and to explore changes in the development and use of apps and their impact on travel behaviour.

The impact of spatial characteristics on well-being has received increasing attention over the past decade. In most studies, however, the emphasis has been on either cognitive well-being (life satisfaction) or mental health. In addition, studies differ in terms of using objective or subjective characteristics, and in terms of the spatial scale of spatial variables (neighbourhood vs. the wider urban environment). This paper first discusses these differences from a theoretical point of view, and then compares model estimates based on different well-being conceptualisations and using objective and subjective spatial variables. To this end, a survey was held in the Utrecht province in the Netherlands that focused on this issue. We find that significant differences in cognitive and affective wellbeing and mental health are observed between neighbourhoods, which can be explained from both neighbourhood characteristics and personal characteristics of the inhabitants. We find that life satisfaction and affective well-being are more affected by subjective spatial variables, and mental health more by objective variables. In particular, life satisfaction and affective well-being are mostly affected by neighbourhood attractiveness and social safety, whereas mental health is positively associated with a newer housing stock. In general neighbourhood characteristics appear to have greater impact on different forms of well-being than accessibility variables on the urban level.

Introduction: Travel behavior research has only started to address how travel affects emotional wellbeing. The development of measurement methods is an important goal of this research.Methods: A re ...

A considerable amount of studies have indicated that people to some extent select themselves in specific neighbourhoods allowing them to travel in their desired way. Although a lot of studies analysed the degree to which travel preferences affect the residential location choice, few studies looked at the effect of a residential relocation on people's travel behaviour and attitudes. A new residential context has the potential to disrupt previous travel choices and could potentially change people's attitudes. This study – using 1539 recently relocated residents in the city of Ghent (Belgium) – analyses self-reported changes in mode frequency and travel attitudes after a relocation, and uses a cohort approach to look at mode frequency and attitudes at different times after the relocation took place. Results suggest that (i) travel attitudes often influence the residential location choice, and (ii) both travel attitudes and travel mode choice change after a relocation, albeit in different ways depending on the current (urban versus suburban) and previous residential neighbourhood (more/equally/less urbanised). This study also suggests that a (possible) dissonance between travel attitudes and the residential neighbourhood is partly a temporal situation, as attitudes can gradually change in accordance with the new residential environment.

This paper investigates the spatial structure of students’ leisure trips and to what extent locational characteristics of social network partners influence decisions about their joint leisure activities and travel. To this end a survey was held among university students asking them about details of their last leisure trip made with a friend. Cluster analysis suggests that four typical leisure trip patterns can be derived. Three clusters seem to be determined by the residential locations of ego and alter. Depending on the residential distance between ego and alter, leisure trip distances are either short for ego and alter (if residential distance is very short), somewhat longer for both (if residential distance is slightly longer) or long for at least one partner (if residential distance is large). A fourth cluster includes cases with long leisure trips for both partners, independent of residential distance, representing cases where specific destinations are visited. A more detailed analysis of travel distance suggests that travel distance depends on size of the residential municipality, residential distance and objective and perceived quality of leisure facilities such as cafes, bars and restaurants. Overall, our study provides support for the idea that leisure trip decisions should be understood on the level of social network ties (i.e. ego and alter) rather than based on individual characteristics only. Also, it provides support for the idea that a focus on single ties, rather than on the structure of social networks as a whole, increases our insight in leisure trip decision making.Keywords: Social network links, Social-recreational travel, Spatial context, Students

Recent research suggests that travellers’ anticipated trip utility may differ from the utility they actually experience when making the trip. This implies that it is important to investigate not only the factors underlying trip decision making, but also the actual experience of the trip. To that end, this paper presents an empirical test of the satisfaction with travel scale (STS) that was developed to measure travellers’ satisfaction with travel. STS measures travel satisfaction in terms of two affective (positive activation versus negative de-activation and positive de-activation versus negative activation) and one cognitive dimension. The STS was applied in the Netherlands in a survey of car users. The results suggest that the reliability of the measurement scales is satisfactory to good, and that they are indicative of an overarching concept of travel satisfaction. Regression analyses carried out with the three STS dimensions as dependent variables show that STS is influenced by experienced traffic safety, annoyance with other road users, the trip being tiring, being distracted by billboards, and lack of freedom to choose speed and lane. In addition, travel purpose and personal characteristics play a role. Overall, the findings provide support for the validity of the STS as a tool to measure satisfaction with travel. It is concluded that using tools such as STS may provide relevant insights into how qualitative and design-related factors influence the attractiveness of trips made by car or other travel modes.

Multi-day activity-based models of travel demand are receiving increasing interest recently as successors of existing single-day activity-based models. In this article, we argue that predicting activity location choice-sets can no longer be ignored when multi-day time frames are adopted in these models. We develop a model to predict activity location choice-sets and choices from these sets conditionally upon varying activity schedule contexts. We propose a method to estimate parameters of the involved utility functions that do not require observations or imputation of choice-sets. This is achieved by using Bayes’ method to transform the likelihood of chosen locations into a likelihood of attribute profiles of chosen locations. An application of the method using a national travel diary dataset illustrates the approach.

This paper explores the usefulness of cumulative prospect theory (CPT), an inductive–descriptive model for how people make choices with a priori unknown consequences, in the context of travelers’ coping with unreliable transport networks through the estimation of coefficients characterizing CPT’s value and weighting functions. Attention is directed toward employed parents’ trips to collect their child(ren) from the nursery at the end of workday because of parents’ strong sensitivity to the possibility of late arrivals there. Analysis of a stated response experiment about parents’ coping with unreliable transport networks en route to the nursery provides further evidence for a series of violations of the axioms underlying expected utility theory (EUT) – a deductive–normative model of decision-making under uncertainty that is widely used in transportation studies. The results also show that linkages exist between respondents’ everyday life and their responses in the stated response experiment and, by implication, the shape of CPT’s value function. It is therefore concluded that analytical frameworks for describing activity-travel behavior in situations of unreliability, variability and uncertainty should be both psychologically and socially realistic.

This article investigates the influence of both mobility events and household events on modal shift decision for bicycle commuting using data collected from a retrospective survey in the Netherlands. The results from a mixed-logit analysis illustrate the influence of several life events on commute modal shifts in addition to changes in commute time and sociodemographic variables. Job characteristics such as changes in work status and employer, mobility resource, long-term mobility events, and household events are seen to influence commuting decision by bicycle.

Objectives This paper proposes a conceptual model of the complex relationships between travel behaviour and health. In addition it gives a research agenda providing an overview of challenges for future research. Methods We review the relevant literature in the areas of public health, land use and transportation that address issues related to health and travel and their underlying mechanisms. We do not aim to give a full review of the literature but to underpin the conceptual model. Results and conclusions We conclude that research can easily come to the ‘wrong’ conclusions if the complex causal relationships that exist between relevant factors are overlooked. In particular, ignoring contradictory effects for specific socio-demographic groups, (residential) self-selection effects, substitutions of different forms of activity, and reverse causalities may lead to overestimation of the effect of policies. For example, travel-related physical activity might interact with other physical activity, self-selection effects may influence the complex relationships between travel behaviour and health, and people׳s health may influence their walking or cycling behaviour. Based on the conceptual model we present a research agenda. A first research challenge is to explore the combined effect of travel behaviour related determinants for health effects (physical activity, air pollution intake, injuries, and subjective well-being) on health. A second challenge is exploring the interactions between travel-related physical activity and other physical activity. Thirdly, the importance of attitudes and attitude formation, specifically health-related attitudes and self-selection processes related to travel behaviour, is an important research topic. Fourthly, it is important to explore the relationship between cycling levels and injury risks, because risks seem to be correlated with cycling levels: the more people cycle, the lower the injury risks. Fifthly, we think it is important to study the relevance of walking and cycling related self-selection effects. A sixth challenge relates to transport innovations.

Research has recently questioned the commonly held opinion that travel time is valued as negative, arguing that engagement in activities during travel may make these trips more enjoyable or productive. Satisfaction with travel has to date been assessed using utility-based models or measures of productivity of the trip. The present study is the first to assess the influence of activities performed during travel on public transport users’ subjective well-being. To this end, a survey was conducted in Sweden in 2010 in which activities during the work commute by public transport were recorded and subjective well-being during travel was measured retrospectively using the Satisfaction with Travel Scale (STS). Results show that talking to other passengers has the strongest positive effect on STS, whereas activities related to entertainment and relaxation lead to lower STS, possibly since engaging in these activities reflect unsuccessful attempts to abate boredom. In addition, it is found that activities during travel may have a more positive effect on the commute back home, suggesting that the mindset related to the destination influences travel satisfaction.

Leisure travel makes up a very significant part of daily travel and therefore needs to be considered in any travel demand management or general land use and transportation policy. Yet, research into leisure mobility has tended to ignore important aspects of leisure travel, such as its joint character, i.e. its dependence on the participation of other people and the important part played by characteristics of the sites where leisure activities are conducted, as well as the link between leisure activities and the dynamics in people’s social networks. This paper introduces a relational approach to leisure activities and travel, which studies joint leisure activities and travel within the webs of relations – the assemblages of people, artefacts, as well as ideas, emotions and other immaterial phenomena – in which they are situated. Two such webs deserve particular attention: the social ties that people have with others and particular configurations of elements (buildings, infrastructure, nature, people, etc.) that collectively make up ‘places’. A key idea of our approach is that two-way connections exists between single instances of leisure and the longer term, structural phenomena of the social tie and place. We expand the relational approach in relation to the decision whether or not to engage in joint leisure and the location choice. For each dimension, we review relevant literature and elaborate the relational approach in terms of the relations among people, artefacts, other forms of materiality and the ideas, norms, affects that hold them together and circulate between them.

In this paper we develop and explore an approach to estimate dynamic models of activity generation on one-day travel-diary data. Dynamic models predict multi-day activity patterns of individuals taking into account dynamic needs as well as day-varying preferences and time-budgets. We formulate an ordered-logit model of dynamic activity-agenda-formation decisions and show how one-day observation probabilities can be derived from the model as a function of the model’s parameters and, with that, how parameters can be estimated using standard loglikelihood estimation. A scale parameter cannot be identified because information on within-person variability is lacking in one-day data. An application of the method to data from a national travel survey illustrates the method. A test on simulated data indicates that, given a pre-set scale, the parameters can be identified and that estimates are robust for a source of heterogeneity not captured in the model. This result indicates that dynamic activity-based models of the kind considered here can be estimated from data that are less costly to collect and that support the large sample sizes typically required for travel-demand modeling. We conclude therefore that the proposed approach opens up a way to develop large-scale dynamic activity-based models of travel demand.

In order to investigate how public transport should be improved to appear attractive to car users, this study develops and tests an internet-based experimental simulation of travel mode choice dependent on the complexity of daily activity agendas. The results for 75 students taking part in the experimental simulation are compared to the results of a survey of another 69 students taking part in a pilot study. Students in both groups were frequent car users. The results of the survey showed that higher costs of car use and greater perceived difficulty to use public transport decreased intention to use the bus for the commute to the university. In the experimental simulation high access to bus stops increased bus use and reduced car use but less for a busy daily activity agenda when the car-use costs are low. The results highlight the importance of focusing on tradeoffs between increasing car-use costs and improvement of public transport.

Previous research demonstrates an impact on subjective well-being (SWB) of affect associated with routine performance of out-of-home activities. A primary aim of the present study is to investigate whether satisfaction with daily travel has a positive impact on SWB, either directly or indirectly through facilitating the performance of out-of-home activities. A secondary aim is to determine whether emotional-symbolic or instrumental reasons for car use results in higher satisfaction with daily travel than other travel modes. A survey of a population-based sample of 1,330 Swedish citizens included measures of car access and use, satisfaction with daily travel, satisfaction with performance of out-of-home routine activities, and affective and cognitive SWB. The results confirmed that the effect on affective and cognitive SWB of satisfaction with daily travel is both direct and indirect via satisfaction with performance of activities. Percent weekly car use had a small effect on satisfaction with daily travel and on affective SWB, although fully mediating the effect of satisfaction with performance of the activities. This suggests that car use plays a minor role for satisfaction with daily travel and its effect on SWB. This role may be larger if investigated after a forced reduced car use.

The advance of information and communication technologies (ICTs) has changed travellers’ appreciation of travel distance in various ways. In the context of telecommuting, ICT increasingly allows us to work from home one or more days per week. One hypothesis that has been put forward is that because ICTs reduce the frequency of commuting, it allows workers to accept longer commute distances, implying that telecommuters have a different valuation of travel distance than regular commuters and would also favour more peripheral residential locations. The question can be raised, however, whether telecommuters can be regarded as a homogeneous group with respect to their valuation of commute distance and residential preferences. To investigate the heterogeneity of commuters’ and telecommuters’ preferences, latent class discrete choice models of workers’ intended relocation probability and preferred residential environment were estimated. The results suggest that telecommuting is not a factor that can be used to identify segments with different residential preferences. However, within the group of telecommuters, two different classes can be identified, which can be characterised as being sensitive and insensitive to commute distance.

Analysis of household activity scheduling has to date been limited to one-day periods. This paper extends the study of household task allocation to a one-week period. Using a one-week time use survey held under couples in The Netherlands in 2003, the paper proposes indicators for measuring task allocation on a daily and weekly scale and investigates to what extent role expectations, work status and indicators of time pressure influence task allocation patterns. The outcomes suggest that egalitarian role expectations and higher female work status lead to a more balanced allocation of work and households tasks between spouses. More traditional role views and increased time pressure lead to more specialisation and inequality between spouses. Interestingly, households under time pressure apply day-to-day specialisation to arrive at balanced weekly allocation totals.

This paper develops a model of activity and trip scheduling that combines three elements that have to date mostly been investigated in isolation: the duration of activities, the time-of-day preference for activity participation and the effect of schedule delays on the valuation of activities. The model is an error component discrete choice model, describing individuals’ choice between alternative workday activity patterns. The utility function is formulated in a flexible way, applying a bell-shaped component to represent time-of-day preferences for activities. The model was tested using a 2001 data set from the Netherlands. The estimation results suggest that time-of-day preferences and schedule delays associated with the work activity are the most important factors influencing the scheduling of the work tour. Error components included in the model suggest that there is considerable unobserved heterogeneity with respect to mode preferences and schedule delay.

We argue that people think more about the short-term individual benefits of personal motorized travel than the long-term societal costs. One explanation is that people are more concerned about their own wellbeing and the wellbeing of their close relatives than the well-being of unknown others. Another explanation is that people have less knowledge of the long-term societal costs than of the short-term individual benefits. Research findings documenting long-term societal costs may increase this knowledge if accurately conveyed by governments, mass media, producers and providers of travel services, and opinion leaders. We identify several obstacles to such an accurate dissemination of research findings that need to be removed.

Before you lies the 2006 TRB (Transportation Research Board) Special Issue of Transportation comprising selected papers presented at the 2006 Annual Meeting of the TRB in sessions sponsored by the Travel Behavior and Values committee on activity-travel decision processes. We are pleased to serve as editors of this Special Issue. The Special Issue is the outcome of a partnership between Transportation and the TRB, a division of the National Research Council, which serves the National Academy of Sciences and the National Academy of Engineering in the United States. This partnership builds on TRB’s commitment to build bridges that help disseminate cutting edge research and state-of-the-art solutions in transportation to a worldwide audience. It involves two standing committees of TRB’s Division A (Technical Activities): the Committee on Traveler Behavior and Values ABD10) and the Committee on Travel Demand Forecasting (ADB40).

A negative effect of congestion that tends to be overlooked is travel time uncertainty. Travel time uncertainty causes scheduling costs due to early or late arrival. The negative effects of travel time uncertainty can be reduced by providing travellers with travel time information, which improves their estimate of the expected travel time, thereby reducing scheduling costs. In order to assess the negative effects of uncertainty and the benefits of travel time information, this paper proposes a conceptual model of departure time choice under travel time uncertainty and information. The model is based on expected utility theory, and includes the variation in travel time, the quality of travel time information and travellers’ perception of the travel time. The model is illustrated by an application to the case of the A2 motorway between Beesd and Utrecht in the Netherlands.

This paper introduces a first step towards analyzing tourist travel choice in situations where tourists may: (i) temporally separate their choice of different components of the travel package, e.g. tourists may choose travel destination before accommodation, and (ii) face a structure of constraints that limits their choice options, e.g. tourists may be restricted by school holidays when choosing the period in which to travel. Theoretical insights with regard to tourist travel, destination and activity choices are reviewed as a basis for the proposed conceptual framework. An exploratory empirical study of the proposed framework is given and implications are discussed.

The aim of this paper is to compare two congestion management schemes road-pricing and peak avoidance rewarding and their impact on commuter behaviour, based on two studies that were conducted in the Netherlands. The road-pricing study is based on stated preference data, whereas the study involving rewards was conducted in the context of a longitudinal field experiment. Given the substantial differences in data sources and analytical techniques applied beforehand, the comparison is made at an indicative level. It can be cautiously concluded that, as psychological theory predicts, rewarding is more effective in diverting commuters from peak periods. In both cases, the most popular alternative to peak-driving is off-peak driving. Most of the change in behaviour is attributed to introducing the new measure, whereas the impact of different price/reward levels is marginally decreasing in sensitivity and effectiveness. The short-term and long-term policy implications of these findings on the implementation of both measures are further discussed. (C) 2012 Elsevier Ltd. All rights reserved.

Spitsmijden, peak avoidance in Dutch, is the largest systematic effort to date to study, in the field, the potential of rewards as a policy mean for changing commuter behavior. A 13 week field study was organized in The Netherlands with the purpose of longitudinally investigating the impacts of rewards on commuter behavior. Different levels and types of rewards were applied and behavior was tracked with state-of-the art detection equipment. Based on the collected data, which included also pre and post-test measurements, a mixed discrete choice model was estimated. The results suggest that rewards can be effective tools in changing commuting behavior. Specifically rewards reduce the shares of rush-hour driving, shift driving to off-peak times and increase the shares of public transport, cycling and working from home. Mediating factors include socio-demographic characteristics, scheduling constraints and work time flexibility, habitual behavior, attitudes to commuting alternatives, the availability of travel information and even the weather. The success of this study has encouraged adoption of rewards, as additional policy tools, to alleviate congestion, especially during temporary road closures.

Subjective well-being (SWB) that includes individuals' cognitive and affective evaluations of life in general is proposed to be a more appropriate measure capturing the benefits individuals derive from travel improvements. We develop and test a measure of travel-related SWB, the nine item self-report satisfaction with travel scale (STS). In a survey of 155 undergraduates, STS, mood ratings, and ratings of SWB were collected for three hypothetical weekdays differing in travel mode, travel time, access to bus stops, and daily activity agenda. The results showed that STS is reliable and differentiates between changes in travel conditions. STS, mood, and to some extent SWB were shown to be affected by travel mode (bus vs. car), travel time, access to bus stops, and the number of activities in the daily agenda.

In a 13-week field study conducted in The Netherlands, participants were provided with daily rewards – monetary and in-kind, in order to encourage them to avoid driving during the morning rush-hour. Participants could earn a reward (money or credits to keep a Smartphone handset), by driving to work earlier or later, by switching to another mode or by teleworking. The collected data, complemented with pre and post measurement surveys, were analyzed using longitudinal techniques and mixed logistic regression. The results assert that the reward is the main extrinsic motivation for discouraging rush-hour driving. The monetary reward exhibits diminishing sensitivity, whereas the Smartphone has endowment qualities. Although the reward influences the motivation to avoid the rush-hour, the choice how to change behavior is influenced by additional factors including education, scheduling, habitual behavior, attitudes, and travel information availability.

A potential effect of ICTs is that they alleviate the traditional space-time constraints of paidwork activities and allow for the decomposition of work into multiple segments of subtasks, which can be performed at different times and/or locations. Such separation of activities into discrete pieces is commonly termed the fragmentation of activity. Regrettably, only limited empirical evidence is available on the fragmentation of work activity and the factors that contribute to it. The goal of this paper is to extend the previous work in the activity fragmentation arena in three ways: (i) to operationalize measures of spatial fragmentation and reformulate some of the temporal fragmentation measures for the specific purpose of investigating the fragmentation of the work activity; (ii) to analyse fragmentation not only in terms of the individual indicators, but also as a multi-dimensional construct including all dimensions of spatial and temporal fragmentation collectively; (iii) to test a detailed set of ICT-related, workrelated, and sociodemographic variables to identify the factors that are crucial in the occurrence of the fragmentation of the work activity. The study shows that there is heterogeneity in the fragmentation of work. Three internally homogenous patterns of fragmentation, which diverge in the degree of fragmentation, are identified: (1) a less temporally and spatially fragmented work pattern; (2) a less spatially and more temporally fragmented work pattern; (3) a more spatially and temporally fragmented work pattern. The multiple discriminant analysis suggests that ICT variables and work-related variables as well as personal-household attributes are associated with the fragmentation of work. However, the degree of association differs considerably among representative patterns of fragmentation.

It is argued that utility theory that underpins current cost-benefit analyses of daily travel needs to be complemented. An alternative theoretical framework is to this end proposed which applies subjective well-being (SWB) to travel behaviour analysis. It is posited in this theoretical framework that participation in goal-directed activities, facilitated or hindered by travel, contributes to SWB, that the degree of travel-related stress in participating in these activities reduces SWB, and that positive affect associated with travel in itself has an impact on SWB.

Although positive incentives have been successfully applied in various domains to influence behavior, they have received limited attention in transportation. This paper reports on the Dutch 'Spitsmijden' ('Peak Avoidance') project, in which travelers received positive incentives if they avoided travelling in the peak by car. Incentives could be financial (3 to 7 EURO per day) or credits to earn a smartphone at the end of the experiment. Travelers' responses were measured using electronic detection equipment and travel diaries. The results of the study indicate that positive incentives are able to reduce the amount of peak traffic of the participants by about 60%. Travelers mainly responded to the incentives by shifting their car trips to the periods before and after the peak period. Although the experiment was intended to achieve a structural change in travel behavior, we observed that travelers returned to the peak period when the incentives ended. © 2010 J. Ross Publishing, Inc.

This paper deals with the potential participation in a reward scheme to avoid peak hour driving. Using rewards in the context of congestion is novel compared to the attention received by road pricing. Psychological research emphasizes the importance of incentives such as rewards in promoting long term behavior changes. In the Netherlands, reward schemes have been tested as part of the ‘Spitsmijden’ project. This study analyzes participation based on a survey of non-participants. Ordered Logit (OL) and mixed ordered logit discrete choice models were specified. The results show that participation is linked to working time flexibility, constraints in the household and the workplace and especially to personal motivations. These results provide critical insights in the formulation of a more coherent and flexible policy on transportation demand management and the development of a more robust tool kit for the inducement of large-scale behavioral changes.

Existing microscopic traffic models have often neglected departure time change as a possible response to congestion. In addition, they lack a formal model of how travellers base their daily travel decisions on the accumulated experience gathered from repetitively travelling through the transport network. This paper proposes an approach to account for these shortcomings. A micro-simulation approach is applied, in which individuals base their consecutive departure time decisions on a mental model. The mental model is the outcome of a continuous process of perception updating according to principles of reinforcement learning. Individuals’ daily travel decisions are linked to the traffic simulator SIAS-PARAMICS to create a simulation system in which both individual decision-making and system performance (and interactions between these two levels) are adequately represented. The model is applied in a case study that supports the feasibility of this approach.

Confirmatory factor analyses are used to examine the psychometric properties of the satisfaction with travel scale (STS), including tests of measurement invariance across urban areas and travel modes (car, public transport and slow modes). The data set consists of questionnaire responses from random samples of residents of Sweden’s three largest urban areas. A theoretically supported, one-factor second-order measurement model with three separate constructs received empirical support in analyses of satisfaction with daily travel in general, satisfaction with the commute to work, and satisfaction with the commute from work in the different urban areas and with different travel modes. On the three first-order factors, high loadings were as expected obtained on scales involving cognitive evaluations (e.g. ‘‘low vs. high standard’’) and affective evaluations with respect to positive deactivation (e.g. ‘‘relaxed vs. stressed’’) and positive activation (e.g. ‘‘alert vs. tired’’). Satisfaction with daily travel in general differed significantly in the largest urban area from the medium- large urban area and the smallest urban area. The results also revealed that commuters travelling by bicycle or on foot are more satisfied with their work commute than people using other travel modes.

Agent-based approaches to simulating long-term location and mobility decisions and short-term activity and travel decisions of households and individuals are receiving increasing attention in land-use and transportation interaction (LUTI) models to predict land-use changes and travel behaviour in mutual interaction. Social interactions between households and between individuals potentially have an influence on a wide range of the long-term and short-term choices involved in these systems. In this paper we identify the areas in which social interactions play a role and address the question how these influences can be modelled in the context of agent-based LUTI models. We distinguish impacts on activity participation (joint activity participation, support-and-help activities) and impacts on decision making (information exchange, social adaptation of preferences and aspirations) as the two main areas of social influence. A prototype of a LUTI model is proposed that accounts for impacts of the social network on longer-term mobility decision making through information exchange and social adaptation of preferences and aspirations. The model is demonstrated in a numerical simulation.

Existing theories and models in economics and transportation treat households’ decisions regarding allocation of time and income to activities as a resource-allocation optimization problem. This stands in contrast with the dynamic nature of day-by-day activity-travel choices. Therefore, in the present paper we propose a different approach to model activity generation and allocation decisions of individuals and households that acknowledges the dynamic nature of the behavior. A dynamic representation of time and money allocation decisions is necessary to properly understand the impact of new technologies on day to day variations in travel and activity patterns and on performance of transportation systems. We propose an agent-based model where agents, rather than acting on the basis of a resource allocation solution for a given time period, make resource allocation decisions on a day-by-day basis taking into account day-varying conditions and at the same time respecting available budgets over a longer time horizon. Agents that share a household interact and allocate household tasks and budgets among each other. We introduce the agent-based model and formally discuss the properties of the model. The approach is illustrated on the basis of simulation of behavior in time and space.

The widespread adoption of information and communication technologies (ICT) and flexible work arrangements have enabled people to schedule their work activities in more flexible ways. New forms of working have already emerged. However, research about flexible work schedules is still scarce. The aim of this study is to determine the factors impacting the propensity to adopt a flexible work schedule, and establish how and to what extent the timing of work is influenced by ICTs, work, and sociodemographic characteristics. The analysis suggests that work-related characteristics and ICT usage seem to be more important for work-schedule flexibility than sociodemographic characteristics are.

This paper investigates travel time attributed to non-work stops in multi-purpose commuting trips. Travel time is explained by socio-demographics and spatial attributes, mode shift is also included to analyze the extra travel time, and its trade-off with activity time for four types of non-work stops—eating out, shopping, leisure/social activities, and family/personal/other. Data come from the “Daily Activity and Travel Survey of Beijing 2012”. Descriptive analysis shows that almost 20% of the multi-purpose commuting trips include a mode shift toward a more motorized transport mode than their direct counterparts. Regression results indicate that extra travel time due to detours is significantly related to the activity durations. Regardless of the activity type, longer work duration reduces the travel time. Furthermore, the interaction terms between personal/trip/spatial factors and activities durations show the impacts differ across the activity types. Gender difference is found only for eating out, which suggests that male commuters travel longer for the same amount of activity time. Concerning spatial factors, a greater mix of facilities near workplaces helps to reduce the extra travel time invested for a time unit of shopping and family/personal/other activities. Compared with public transit users, active mode users have shorter travel time for eating out. Timing, work duration and commuting duration as time-budget-related variables show negative impacts on the extra travel time for eating-out, shopping and family/personal/other activities. However, mode shift does not show any significant impact as the hypothesis proposed. Instead of rebalancing the trade-off between travel and activity time, commuters may relocate activity with an expanded opportunity choice set given by a higher mobility level.