Mobility-as-a-Service for university communities: how would you value it?

The mobility of people in cities is changing rapidly. In recent years, many European urban areas have witnessed the increasing integration of road and rail public transport services, the emergence of real-time information systems for travelers, and the widespread deployment of shared mobility services, whether provided by cars, mopeds, bicycles, and scooters. These are enabling users to meet their mobility needs by resorting to a wide range of transportation options. In an urban mobility context increasingly characterized by capillary, competing and therefore more accessible and affordable transportation services, the concept of Mobility-as-a-Service (MaaS) is gaining increasing attention as a means of providing integrated mobility solutions through a single digital platform (Matyas and Kamargianni, 2019). In this way, users would be able to plan, book, and pay for these services through a single account and a single digital interface, choosing from time to time among the different options those that best meet their needs and preferences (Reck and Axhausen, 2020) (Matyas and Kamargianni, 2021). Thus, MaaS could allow users to travel effortlessly by seamlessly combining different transportation services and paying integrated fares overall more conveniently (Polydoropoulou et al., 2020 a) (Caiati et al., 2020). However, the successful implementation of a MaaS platform requires a thorough understanding of the interest and willingness-to-pay of potential users (Polydoropoulou et al., 2020 b) (Ho et al., 2020). In this study, we investigate the interest and willingness-to-pay of the university community of the Politecnico di Milano in Italy for a MaaS platform using a discrete choice modeling approach. To achieve this objective, a Revealed Preference/Stated Preference survey has been conducted among students, academic and technical-administrative staff of the university to collect data on their habits, travel behaviors, mobility preferences and stated intentions for MaaS. The data collected were first analyzed with descriptive statistics, in order to have a profiling of potential users, and then used to estimate behavioral choice models, with the aim of identifying the factors that most affect the interest and willingness-to-pay for a MaaS platform. Results show that some demand segments of the university community of the Politecnico di Milano are very interested in MaaS platform and have a high willingness-to-pay for a bundle that integrates local public transport subscription with vehicle-sharing services. Key factors that most influence interest and willingness-to-pay are the frequency of the home-university commute, modes of transportation habitually used, place of origin and destination, any current difficulties with the first and last leg of the travel (e.g., to make access or egress from train and subway stations), but also personal attitudes. This study contributes to the literature on MaaS adoption by providing insights into the interest and willingness-to-pay of a specific university community. The findings have implications for transportation policy, highlighting the potential for MaaS to enhance sustainable transportation options in university communities, but can be easily extended to other organizations as well.