MEMBERSHIP AND MOBILITY BUNDLES CHOICE IN MOBILITY-AS-A-SERVICE

The main contribution of this thesis is the development of a membership and bundle choice model within the context of a Mobility-as-a-Service (MaaS) system. This thesis proposes a comprehensive modeling framework that considers a broader range of interactions and the development of different building blocks for the MaaS ecosystem model. Following the framework, we propose agent-based simulation (ABM) as the most suitable method for capturing customers’ decision-making process in the MaaS system. ABM is capable of simulating the spatial and temporal distribution of individual users, as well as the dynamic availability of shared services included in the MaaS bundle (carsharing availability at the station may vary daily by time). Another advantage of ABM is the ability to dynamically adjust transport mode costs within the network, allowing users to experience the cost variations associated with various modes. While experimenting with new mobility options in the network, users strive to keep travel costs as low as possible. The decision-making process is simulated by embedding the MaaS bundle and its parameters as a possible travel option for potential MaaS members, as depicted in Figure 1.5. By incorporating and varying the MaaS bundle parameters in the ABM, analysts can create diverse experimental setups to capture key performance indicators (KPIs) that represent the MaaS system’s response to implemented variations. These KPIs encompass MaaS bundle users’ travel habits, the evaluation of a potential car policy in a context where the MaaS system becomes a viable mobility choice, and the MaaS Broker revenue. Moreover, the proposed model is flexible, allowing analysts to compare the KPIs in contexts with and without the MaaS system. The development of this thesis contributes to gaining insights into MaaS adoption and to the scientific debate and understanding of how new MaaS services will reshape the future of transportation and mobility systems.