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Travel-related attitudes are believed to affect the connections between the built environment and travel behaviour. Previous studies found supporting evidence for the residential self-selection hypothesis which suggests that the impact of the built environment on travel behaviour could be overestimated when attitudes are not accounted for. However, this hypothesis is under scrutiny as the reverse causality hypothesis, which implies a reverse direction of influence from the built environment towards attitudes, is receiving increased attention in recent research. This study tests both directions of influence by means of cross-sectional and longitudinal structural equation models. GPS tracking is used to assess changes in travel behaviour in terms of car kilometres travelled. The outcomes show stronger reverse causality effects than residential self-selection effects and that land-use policies significantly reduce car kilometres travelled. Moreover, the longitudinal models show that the built environment characteristics provide a better explanation for changes in car kilometres travelled than the travel-related attitudes. This contradicts the cross-sectional analysis where associations between car kilometres travelled and travel-related attitudes were stronger. This highlights the need for more longitudinal studies in this field.

The importance of attitudes in the relationship between travel behaviour (TB) and the built environment (BE) has been the subject of debate in the literature for about two decades. In line with the Theory of Planned Behaviour, attitudes – which affect behaviour – are generally assumed to be constant. However, it is plausible that attitudes can change, both directly, or indirectly, through the impact of the built environment on travel behaviour, a process which is referred to as reverse causality (RC). Based on literature from social psychology, this paper provides a conceptual model for the explanation of attitude changes. It also reviews the literature in the area of BE and TB concluding that two explanations dominate: a change in attitudes due to new experiences which can be underpinned by learning theories, and a change in attitudes due to mismatches between attitudes and behaviour which can be explained by cognitive dissonance theories. The literature also suggests a few additional explanations, while we also suggest explanations not provided in travel behaviour literature. Finally, we present an agenda for future research.

In this paper we propose the concept of ‘substitutability’, which we define as the extent to which the preferred travel alternative can be substituted by other initially less preferred alternatives. This is particularly of interest when the preferred alternative is no longer available, e.g. due to labour strikes, weather conditions, power failures, etc. Travel alternatives in this context can comprise of activities, modes, time of day, and routes. We argue that substitutability is a promising new concept, which is relevant for travel behaviour research. In particular, substitutability is relevant from an accessibility perspective, as well as from the perspective of ‘freedom of choice’. In this paper we conceptualise the concept of substitutability, present a mathematical expression for it and discuss its relationships with other related concepts in the travel behaviour research field, such as the freedom of choice, accessibility, and robustness/reliability. We illustrate the concept of substitutability using a case study, where we look at the extent to which airports can be substituted by other airports, and by high-speed railway stations, conditional on a given destination, namely the cities of Paris, London and Frankfurt. Finally, we present a research agenda.

Travel-related attitudes and dissonance between attitudes and the characteristics of the residential built environment are believed to play an important role in the effectiveness of land use policies that aim to influence travel behaviour. To date, research on the nature and directions of causality of the links between these variables has been hindered by the lack of longitudinal approaches. This paper takes such an approach by exploring how people across different population groups adjust their residential environments and attitudes over time. Two latent class transition models are used to segment a population into consonant and dissonant classes to reveal differences in their adjustment process. Interactions between (1) the distance to railway stations and travel-mode-related attitudes and (2) the distance to shopping centres and the importance of satisfaction with these distances are modelled. The models reveal mixed patterns in consonant and dissonant classes at different distances from these destinations. These patterns remain relatively stable over time. People in more dissonant classes generally do not have a higher probability of switching to more consonant classes. People adjust their built environments as well as their attitudes over time and these processes differ between classes. Implications for policies are discussed.

In this paper, we present the case that traditional transport appraisal methods do not sufficiently capture the social dimensions of mobility and accessibility. However, understanding this is highly relevant for policymakers to understand the impacts of their transport decisions. These dimensions include the distribution of mobility and accessibility levels over particular areas or for specific population groups, as well as how this may affect various social outcomes, including their levels of participation, social inclusion and community cohesion. In response, we propose a method to assess the socially relevant accessibility impacts (SRAIs) of policies in some of these key dimensions. The method combines the use of underlying ethics principles, more specifically the theories of egalitarianism and sufficientarianism, in combination with accessibility-based analysis and the Lorenz curve and Gini index. We then demonstrate the method in a case study example. Our suggestion is that policymakers can use these ethical perspectives to determine the equity of their policies decisions and to set minimum standards for local transport delivery. This will help them to become more confident in the development and adoption of new decision frameworks that promote accessibility over mobility and which also disaggregate the costs and benefits of transport policies over particular areas or for specific under-served population groups.

Urban form is often assumed to influence travel distance. However, as this is no travel choice in itself, but the consequence of other decisions, this paper tests, consistent with the activity-based approach, a causal model that does not relate urban form directly with daily travel distance, but indirectly through a series of decisions. A structural equation model was developed with urban form measures for both the residential and the work environment. The model demonstrates that indirect effects can steer a total effect in another direction, indicating that the apparent effects of one variable on another can be the trade-off of opposite effects. Effects from residential density suggest that people in a dense residential environment travel a little less, although this effect is partly cancelled out by extra activities. Workplace density/mix increases total daily distances, but decreases distances by car.

This paper analyses whether the decision to commute by car is influenced by built environment characteristics of residential neighbourhoods and, more especially, of work locations, taking into account interdependencies between household partners. It shows that the residential environment only affects car use among single-earners. Conversely, for all commuters, but in particular for dual-earners, characteristics of the work location affect whether they commute by car. Even in dual-earner households with two cars, work environment plays a role. We found that in cases of dual-earners with only one car, the partners with the longest commuting distances and the lowest density work locations are most likely to commute by car. Moreover, in households with young children, men are more inclined to leave the car at home. Other features relating to work also affect car commuting, including work flexibility and, especially, possession of a company car. We conclude that future policies aimed at reducing car use should place greater focus on work factors. © 2009 Elsevier Ltd. All rights reserved

This chapter contributes to the improvement of GPS-based travel surveying by introducing a combined method of GPS, GIS and web-based user interaction, which has been applied in large- scale fieldwork in the netherlands. With over 1000 participants, as far as we know, this is the first time that a GPS-based method that measures travel mode choice as well as the location and type of destinations that are visited has been used on such a large scale. The chapter focuses in particular on the identification of travel modes and destinations, which is still an under-researched issue. Our approach concentrates on the issue of deriving and validating the purpose of trip destinations and travel modes, while also allowing reliable multi-day data collection. The method consists of an interpretation process and a validation process. The interpretation process uses spatial data (e.g. railways, shops) and characteristics of the respondents (e.g. home address, possession of cars) to interpret data from the logs. The travel behaviour data that result from this interpretation round can be adjusted and added to by the respondents in a validation application. The link between both processes is interactive; when new individual characteristics (e.g. the address of a friend’s house) are entered by the respondents, these characteristics will be used for further interpretation of the data. The remainder of this chapter is structured as follows. The following section gives an overview of the advantages and drawbacks of current GPS-based data collection methods that are suitable for measuring choice of travel mode and/or trip destinations. The subsequent section describes the GPS-based method that we developed and in section four the value of our method is evaluated by presenting the results of the fieldwork we recently undertook. The results are compared with results from an internet survey that was carried out at an earlier date and also with the Dutch Travel Survey (DTS) that uses paper diaries. The chapter ends with conclusions on the use of GPS-based methods for the collection of travel behaviour data and a discussion of future possibilities., Research in Urbanism Series, Vol. 1 (2008): Urbanism on Track: Application of tracking technologies in urbanism

Increasing the number of people cycling to work brings a number of benefits: it can lead to reductions in air pollution and traffic jams, and increases people’s physical activity levels. We investigated the extent to which work-related factors influence (1) whether an individual decides to cycle to work, and (2) whether an individual cycles to work every day. It is anticipated that the office culture and colleagues’ and employers’ attitudes would significantly influence both decisions. These factors are expected to impact the provision of cycling facilities and financial compensation schemes in the workplace. We conducted an Internet survey in 4 Dutch municipalities, gathering data from over 4,000 respondents. The results suggest that the following factors increase the likelihood of being a commuter cyclist: having a positive attitude towards cycling; colleagues’ expectations that an individual will cycle to work; the presence of bicycle storage inside; having access to clothes changing facilities; and needing a bicycle during office hours. The presence of facilities for other transport modes, an increase in the commute distance, and the need to transport goods, in turn, reduces the chance that an individual will cycle. Cycling frequency is negatively affected, meanwhile, by an increase in commute distance, a free public transport pass or car parking provided by the employer. These results indicate that an individual’s working situation affects the commuting cycling behaviour. The findings also indicate that (partly) different variables influence an individual’s decision to cycle to work, and their decision to cycle every day.