Chapter 6 - Determinants of Transport Choices

Interrupting habitual car use: The importance of car habit strength and moral motivation for personal car use reduction

The influence of the built environment in the social impact of the low emission zones of Madrid (Spain)

Introduction: Mitigating private vehicle use can lead to improvements in physical health and reduce traffic-related emissions. Thus, influencing travel patterns and behaviors of individuals has become a focus for policy makers and researchers. This research provides a multilevel analysis on individual characteristics as well as area-level climate parameters that may influence an individual’s commuting mode choices across multiple Canadian cities. Methods: The study used individual data from the 2011 National Household Survey conducted by Statistics Canada. The city-level climate data were collected from Environmental Canada’s 1981-2010 Normals & Averages collection. Different multilevel models were fitted using MLwiN version 2.35 to investigate relationship between socioeconomic and climate variables and commuting mode choice (private, public and walking/cycling), using private vehicle as a reference. Results: Older age and higher income groups tend to prefer taking private vehicle in comparison to other modes. Educational and gender differences were also a significant determinant of mode choices. The climate variable indicate an increase in annual temperature encourages walking/cycling (OR=1.24, 95% CI: 1.03-1.48), but an increase in annual average summer temperature is associated with higher private transport use (OR=0.80, 95% CI: 0.69-0.92). Higher average winter temperature was significantly associated with higher odds of taking private vehicle compared to public transport. Conclusions: Individual characteristics can allow policy makers to identify target groups for promoting more sustainable modes of transportation. The climate variables indicate that temperature can affect travel decisions differently between locales with distinct climate condition, thus policies should be local. As climate change occurs, transportation policies should also consider heat threshold in which more individuals may switch to private vehicle use for more comfortable traveling.

This paper studies the willingness to change car use when commuting to a university campus. We estimated a hybrid discrete choice (HDC) model to test the hypothesis that, in addition to traditional tangible attributes, the willingness to change car use to more sustainable transportation modes also depends on the pro-environmental attitude and the perceived convenience of each transportation alternative. We found that teachers have better pro-environmental attitudes than students and administrative staff, but senior individuals and people who own an above-average priced car have negative effects on this attitude. We concluded that in addition to car ownership, the price of a car is also a decisive factor in the willingness to change car use. On-campus parking fees were identified as a key variable for reducing car use when commuting to campus and for financing more sustainable transportation modes. This paper contributes to the literature on sustainable mobility on university campuses and is the first based on an HDC modeling approach that integrates tangible attributes and latent variables into this context.

In this study, we focused on policies to promote reduction in the use of private vehicles that could be implemented in Bangkok during periods of severe PM2.5 levels, including a flat charge for use of private cars, private vehicle bans, and public transport fare subsidization. The objective was to investigate how these policies can be used to help convince private car users to shift their travel modes to rail transit, and, thus, reduce vehicle emissions that contribute to air pollution. We conducted a stated preference survey of 731 private car users in Bangkok, Thailand, where stated-choice scenarios were specified with respect to all possible combinations of the proposed policies that could lead to a reduction of PM2.5 concentration. A binomial logit model was used for the analysis. Our results suggest that the effectiveness of the travel demand management policies would vary across geographical areas of the city. Public transport fare subsidization would be effective in reducing car use among residents in the inner suburbs. A car ban would be an effective measure in outer suburbs, while the flat charge would be effective among populations in central Bangkok and the inner suburbs.

The increasing use of car in developing countries is an important reason for traffic congestion and pollution. Using a car may partly reflect a normative choice, but the majority of previous studies that used the Norm-Activation Model (NAM) to study pro-environmental transport behavior were conducted among the general public in high income and developed countries in Europe and Northern America. The present research aimed to examine the causal chain of the NAM theory and the role of the NAM dimensions as well as socio-demographic and situational characteristics for parental sustainable transport mode choice on their children’s school travels in an Iranian context. Among the three core NAM dimensions, awareness of consequences refers to how aware people are of the negative consequences of car use. Ascription of responsibility refers to whether individuals perceive themselves to be personally responsible for the consequences of car use, and personal norms are defined as a moral personal obligation to take action for collective benefit. In 2014, a self-completion questionnaire survey (n = 1,078) was carried out among parents of pupils (aged 7–9 years). Results (based on n = 733) showed that the NAM was not significantly associated with sustainable transport mode choice in the current study. However, the structural equation modeling showed that the underlying NAM system was supported by the data. Among the socio-demographic characteristics, parents in households who had more cars were less likely to choose sustainable transport modes. Also, accessibility to public transport had a positive effect on the choice of sustainable transport modes. A potential reason for the lack of empirical support for the behavioral link between the NAM causal chain and sustainable mode choice could have been due to that study area may be rather unsupportive of sustainable transport choices, and spatial factors may be more important precursors of mode use than normative processes. Overall, the current findings showed that demographic, household and situational characteristics were more important than the NAM dimensions in predicting sustainable transport mode choice in an Iranian sample. In order to promote sustainable transport mode use, it seems to be more feasible to focus on developing a safe infrastructure and to extend the availability of sustainable transport options in Iran.

Reduction of car use is one of the most effective ways to tackle congestion‐related problems. Using positive incentives to stimulate bicycle use is one possibility to reduce car use. Cycling is a sustainable transport mode that uses little space and is healthy. There is evidence that positive incentives may be more effective than punishing travellers for undesirable behaviour, and the emergence of mobile applications for delivering interventions has opened up new opportunities for influencing travellers. So far, few studies have focused on exploring the effectiveness of positive incentives on long‐term behavioural change. We used the SMART app to deliver positive incentives to more than 6000 travellers in the Dutch region of Twente. The app automatically tracks users and provides incentives such as challenges with rewards, feedback, and messages. This study covers the period from March 2017 to June 2018, in which more than 1000 SMART users participated in monthly challenges. We evaluated the effects of the challenges and rewards and found that the challenges did encourage cycling and reduced car use in the short term. There is also some evidence for behavioural change over a longer time period.

The Barcelona Metropolitan Area (AMB) has implemented various policies to reduce car use and promote more sustainable mobility. Initiatives such as superblocks, Low Emission Zones (LEZs), and the Bicivia network aim to transform the urban model in response to environmental and congestion challenges. However, the high reliance on private vehicles for intermunicipal travel, uneven infrastructure, and social resistance to certain changes remain significant issues. This study examines the evolution of mobility patterns and assesses the effectiveness of the above policies in fostering real and sustainable change. A mixed-methods approach was adopted, which combined an exploratory factor analysis (EFA) of 2011–2024 data, trend linear regression, and a comparative international analysis. The EFA identified four key structural dimensions: traditional transport infrastructure, active mobility and bus lines, public bicycles and mixed use, and transport efficiency and punctuality. The findings reveal a clear reduction in private car use and an increase in sustainable modes of transport. This indicates that there are prospects for future transformation. Nonetheless, challenges persist in intermunicipal mobility and the public acceptance of the measures. This study provides empirical and comparative evidence and emphasizes the need for integrated metropolitan governance to achieve a resilient and sustainable urban model.

Globally, the need for more sustainable modes of transport is rising. One of the main contenders of the car is the electrical bike (e-bike). To promote the use of e-bikes, pilots are being organised worldwide (e.g. in the USA, Norway, and the Netherlands). Studies have shown that providing a free e-bike to people for a limited period of time changes their mode choice behaviour during the pilot period. Only few studies have also investigated the long-term effects of these free e-bike trial periods, which show increase in e-bike use in general. However, these studies have failed to investigate why some participants of the trials change behaviour on the long-term, whereas others continued their former behaviour. This study aims to bridge this gap. A pilot with e-bikes was organised at Delft University of Technology, The Netherlands, with the goal of reducing car use for commuter trips towards the university. Data was collected at various moments during and after the trial period to evaluate the long-term changes in commuting behaviour and to identify potential reasons for these changes. A total of 82 participants are included in this study. Overall, car use for commuting decreased from 88% before the pilot to 63% three months after the pilot. E-bike use went up from 2% to 18% in the same time period. A binary logistic regression model shows that the most important variables to explain the decrease in car use are 1) purchase of an e-bike, 2) the participant's perception regarding e-bike safety, and 3) the aim of the participant to use the pilot to change their current behaviour. Besides that, the most important predictor of increase in e-bike use is the purchase of an e-bike. Furthermore, participants identify the investment costs of an e-bike as the strongest reason for not purchasing an e-bike and, thus, not changing their commuting behaviour. Future pilot programs could consider the potential of incrementally purchasing an e-bike over a longer period of time, instead of at once, to increase e-bike adoption rate.

Factors influencing car use for commuting and the intention to reduce it: A question of self-interest or morality?

The motives for car use and the personal norms for reducing car use have been studied to understand the motivational processes underlying car use. Motives have been classified as instrumental, symbolic and affective, while personal norms have been classified as introjected and integrated. The aim of this study is to validate scales measuring motives for car use and personal norms for car use reduction in Mexico City. Both scales were applied, together with a measure of car use, to a sample of 257 motorists. The results indicate a good fit for the three-factor model for the motives for car use scale and a good fit for the two-factor model for personal norms for car use reduction. A linear regression model was run, which showed that both constructs explain 21.3% of variance in car use, and the significant predictors are instrumental motives and integrated norms. Both scales show initial evidence of reliability, validity and parsimony.

Purpose – In this chapter, issues involved in trying to reduce car use in urban areas are examined, drawing on experience in Britain, and the possible lessons for China are considered. Methodology – The advantages and disadvantages of the car are considered to explain the growth in car use in Britain. The political difficulties of reducing urban car use are discussed. A variety of methods of reducing car use by changing travel behaviour are described, including charging for the use of the road, fuel pricing, control of car parking and alternative methods of accessing the car such as car clubs and car sharing. The evidence on the effectiveness of measures to reduce car use is examined. The potential for reducing car use in China is then considered. Findings – Most of the initiatives for reducing car use in Britain have focused on reducing congestion rather than actually reducing car use. The largest initiative to do this has been the London Congestion Charging scheme; this was successful, unlike proposals for some other cities, for a variety of reasons. However, while there have been many initiatives in Britain, there is little systematic evidence of their effectiveness. Practical implications – The chapter discusses some of the political difficulties involved in trying to reduce car use and then illustrates these, particularly for congestion charging using the example of London. Value of the chapter – The main value of this chapter is to illustrate the range of possible approaches to reducing car use, drawing upon evidence from various cities showing some of the ways of overcoming the barriers to implementation.

This study investigates which variables drive intention to reduce car use by modelling a stage of change construct with mechanisms in the Theory of Planned Behavior (TPB) and Norm Activation Model (NAM). Web questionnaires (n = 794) were collected via 11 workplaces. The socio-demographics, work commute, stage of change, attitudes to sustainable travel modes, social norms, perceived behavioral control, and personal norm were assessed. An initial descriptive analysis revealed that 19% of the employees saw no reason to reduce their car use; 35% would like to reduce their car use but felt it was impossible; 12% were thinking about reducing their car use but were unsure of how or when to do this; 12% had an aim to reduce current car use, and knew which journeys to replace and which modes to use; and 23% try to use modes other than a car for most journeys, and will maintain or reduce their already low car use in the coming months. A series of Ordered Logit Models showed that socio-demographic variables did not explain the stage of change. Instead, personal norms, instrumental and affective attitudes, and perceived behavioral control toward sustainable travel modes were all significant and explained 43% of the variance in stage of change. Furthermore, it was found that the significant relationships were not linear in nature. The analysis also showed an indirect effect of social norms on the stage of change through personal norms. Implications are discussed regarding the design of interventions aimed at influencing a sustainable work commute.

Sustainable transportation in Argentina: Values, beliefs, norms and car use reduction

A travel plan contains a package of site-specific measures that aim to manage car use and to encourage the use of more sustainable transport modes. In recent years, there has been increasing interest in using the land use planning and approvals process to secure travel plans for new developments. Although evaluations of travel plans tend to focus on outcomes such as reductions in car use, scant attention has been paid to evaluating the process through which they are developed. For this study, an assessment framework was developed to evaluate the quality of travel plans for new developments. With a case study from Victoria, Australia, the framework was applied to 31 travel plans. Results showed that most travel plans were prepared for residential and mixed use developments and contained measures that were focused primarily on information and infrastructure provision. Relevant background information and the selection of measures generally were covered by travel plans. However, the process for managing their implementation scored relatively low in the assessment in comparison with other elements. Overall, the framework developed provides a useful tool for assessing the relative merits and deficiencies of travel plans prepared for new developments and can be used to improve the quality of travel plans that are submitted through the planning process. Further work is required to refine the framework according to the collective views of travel planning practitioners.