Abstract
The main objective of the present study is to analyse the effect of a Travel Behaviour Change Program (TBCP) based on health improvement actions, in relation to a potential for an increase in walking and cycling, with reference to particular groups of people defined according to sociodemographics. A TBCP consisting of three persuasion actions based on health improvements was planned and executed in Valencia (Spain). A two-wave panel survey was used to study the effects of taking part in the TBCP. The panel survey collected data related to activity-travel scheduling process before and after the execution of the TBCP. To study the influence of participating in the TBCP, respondents were separated into two groups: those directly implicated in the TBCP and those who were not involved in any action (CG), which were formed on the basis of sociodemographic similarity. We developed descriptive and explanatory analyses and predictive models, to study the effect of the TBCP with reference to particular groups of people defined according to sociodemographics. Results indicate that being involved in the TBCP affects more males than females, those who share their household and do not live with their parents during weekdays, those with lower car availability, those willing to reduce car use and students. Several implications for research and transport policy are derived from these results.
Highlights
The extensive use of cars in urban areas significantly contributes to climate change, local air contamination, pedestrian accidents and cityscaping
A Probit model is used to evaluate the likelihood of participating in the Travel Behaviour Change Programs (TBCP) or control groups (CGs) group (Equation (1)) and the outcomes are saved to be used in the following step of the model
To evaluate the effects of being involved in the TBCP considering the sociodemographics of the participants, we introduce a new three-way interaction variable: yit = βi’xit + γizit + μ1ai + μ2wt + η1(aw)it + η2(aD)it + η3(wD)it + η4(awD)it + εit where, D represents the sociodemographic characteristic considered, η1, η2 and η3 represent the lower order effects. η4 designates the parameter associated with the three-way interaction variable awD
Summary
The extensive use of cars in urban areas significantly contributes to climate change, local air contamination, pedestrian accidents and cityscaping. The habitual use of cars to carry out most daily trips results in physical inactivity, which augments the danger of many chronic illnesses such as coronary heart disease, type 2 diabetes and cancer of the colon [1]. The promotion of the use of travel mode alternatives to cars, cycling and walking, to carry out habitual trips, could have positive effects on reducing pollution, accidents and increase the health of citizens. The key characteristic of these actions is that they can possibly accomplish better cost-effective results in reducing car use and increasing walking or cycling
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