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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.

Incentive-based travel demand management strategies are gaining increasing attention because they are generally considered more acceptable by the traveling public and policy makers. This study presented a detailed analysis and modeling effort aimed at understanding how incentives affected traveler choices by using data collected from a reward-based experiment conducted in 2006 in the Netherlands. The incentive-based scheme analyzed in this study included monetary rewards or credit toward obtaining a smartphone with a view to motivating commuters to change their choice of departure time out of the peak period or to shift their mode of travel. The mixed panel multinomial logit modeling approach adopted in this study was able to isolate the impacts of incentives on behavioral choices while accounting for variations in such impacts across socioeconomic groups that might have been due to unobserved individual preferences and constraints. The model also shed light on the effects of behavioral inertia, in which individuals were prone to continue their past behavior even when it was no longer optimal. Finally, the study offered insights on the extent to which behavioral changes persisted after termination of the incentive period. In general, it was found that incentives were effective in changing behavior and overcame inertial effects; however, individuals largely reverted to their original behavior when the rewards were eliminated. This finding suggests that incentives need to be provided for a sustained period to bring about lasting change.

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.

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.

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.

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.

This paper investigates the travel time attributed to each activity in a trip chain by developing a travel-time price for multiple-purpose trips. Travel-time price is a ratio of the associated travel time of an activity to the activity duration. The travel-time price developed here has three characteristics. First, it accounts for the influence of sociodemographics and urban form characteristics on travel time. Second, it represents the intra-activity trade-off of travel time between activity duration and its associated travel time for different activity types. Third, it represents the interactivity trade-off of travel time between different types of activities. By using the data from the AMADEUS activity-travel diary collected in the Netherlands in 2000, a regression analysis was carried out for multiple-purpose trips stemming from one base, and the results were compared with those of an analysis of single-purpose trips from one base. The focus was on weekday, nonwork, out-of-home activities performed by heads of households. This daily activity behavior is interpreted as an outcome of the long-term decisions made about work and housing locations. The results indicated that, although multiple-purpose trips are not as common, they are more efficient than single-purpose trips. Sociodemographics and spatial characteristics were not statistically significant for the travel-time price of maintenance activities but were mostly significant for discretionary activities. In addition, nonwork out-of-home travel time is largely influenced by the duration of discretionary activities, gender, working hours, and the spatial setting.

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.

Traffic information is increasingly regarded as a tool to achieve a more efficient use of the road network. As traffic information is often applied in the context of routitine trips, the question arises how travellers integrate traffic information with the knowledge of travel conditions gained through daily experience. To describe this process, the paper proposes a model of perception updating of travel times in the context of departure time decisions. The model applies a CHAID-based classification algorithm to describe how travellers classify trips made under various conditions (departure time and presence of traffic information) into mental classes with comparable expectations in terms of travel time. Thus, it is assumed that the learning process depends on a set of conditions, one of which is the available travel time information. The model is tested through a series of numerical experiments. The results suggest that the model describes learning and adaptation behaviour in a plausible way. Through increased experience, perception of travel times is improved, and more departure time classes are distinguished. However, this does not seem to lead to shorter travel times or higher trip utilities. Also the presence of travel time information may be, depending on the history of trip outcomes, distinguished as a significant indicator of the expected travel time. We conclude that the nrodel provides a good starting point for the further development of learning and adaptation models in the context of lTS.

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.

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.

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.

Results are reported of a study that attempts to estimate marginal mental efforts of various operators (delete activity, insert activity, substitute activity) from activity rescheduling data by using sequence alignment as a measure of the amount of effort. The study makes several contributions to the literature on activity-based analysis and modeling. First, it is one of the few attempts to examine the decision process supposed to lead to the decision outcome, focusing on mental effort. Second, it adopts sequence alignment methodology not as a means of calculating the (dis)similarity between activity profiles, but as a measure of mental effort. A genetic algorithm is used to derive the weights of mental effort attached to each type of operator. Results, derived from a computer-based activity diary instrument, support the suggested approach in that observations can be successfully reproduced and that the estimated marginal mental efforts are consistent with general theory.

Contains fulltext : 67204.pdf (Publisher’s version ) (Closed access) An approach is presented to determine the effect of travel time uncertainty and traffic information on mode choice in general and on the potential patronage of park-and-ride (P&R) facilities in particular. An expected-utility approach is applied to model the effect of travel time uncertainty and traffic information on the utility derived from the various travel modes. Through a series of simulations, the potential effects of travel time uncertainty and information provision on the use of a P&R facility in the Nijmegen region in the Netherlands are assessed. The simulations suggest that providing travelers with travel time information increases the patronage of P&R facilities because use of the car is avoided in the case of heavy congestion. However, the effect of information provision is limited when compared with other factors such as the quality of the P&R alternative in terms of travel time, facilities, and costs.

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.