The intention to use real-time multimodal information to change travel behaviour. The use of psychosocial variables for the market segmentation.

Advanced Traveller Information Systems (ATIS) have been developed to encourage citizens to make better choices by making their travel more efficient and reliable. Another goal is to make mobility more sustainable. More precisely, the deployment of ATIS, especially multimodal real-time information systems, aims to induce a modal shift from the car to public transports (PT) or soft modes. This Ph.D. thesis assesses the impact on travel behaviour of an ATIS, TUeTO, developed for the city of Torino within the European project Opticities. To reach this objective, a mixed method analysis has been adopted, allowing the use of both quantitative and qualitative data gathered before and after the test of TUeTO. Psychosocial constructs were defined to segment the market, together with socioeconomic and travel characteristics, to understand which variables can induce a change of travel habits towards sustainable mobility. To this end, an exploratory factor analysis (EFA) was conducted on two questionnaires (one designed for the ex-ante phase of the Opticities project and the second designed ad hoc within the thesis work) to find psychosocial constructs related to the sample of 76 participants out of the 150 recruited within the project. A cluster analysis was subsequently performed to define different categories of people according to their willingness to use real-time multimodal information system to change travel behaviour. In addition, the use of qualitative data gathered through focus group discussions before and after the test of the app made possible to complete statistical analysis and investigate the cognitive mechanisms related to the use of ATIS. The textual analysis was made to verify the coherence of the clusters and gain insight regarding the issues related to the use of ATIS. The innovative methodology of this thesis using both qualitative and quantitative data had for aim to validate, determine, and characterize the clusters created thanks to the cluster analysis method. The quantitative data from the cluster analysis defined reliable categories of people willing to use ATIS to change travel behaviour after the test period, while the use of qualitative data was successful in deepening the understandings of the issue, although it did not validate all clusters created so far. Segmentation better characterized the attitudes of people towards the use of ATIS. In contrast to the literature, the statistical analysis showed that people who had the intention to use TUeTO before the test, were not willing to change their travel behaviour after. On the other hand, although it was expected that people willing to use an ATIS would be mainly car users, the analysis pointed out that public transport users were more interested in using the information. However, the shift of mode from the car to more sustainable alternatives might be limited since a small amount of people willing to change travel behaviour for the most frequent trip use a car. Content analysis opened a new perspective regarding the deployment of ATIS as a policy to change travel behaviours. While some participants pointed out the need to improve the reliability of TUeTO, others would have preferred an improvement of the public transport infrastructure either along with or instead of the deployment of the ATIS.