## 7 Review of Studies Related to Integration in the Context of Multi-Modal Mobility
### Review of Studies
Question: How to integrate one-to-many peer-to-peer ridesharing with public transit on a MaaS platform for morning commute? Results: The study [114] focuses on integrating one-to-many peer-to-peer ridesharing and public transit for morning commute. Due to the computational complexity to optimize matching, routing and scheduling for the users in a large scale network, a decision model for the integrated matching problem and an iterative distributed optimization algorithm based on decomposing the original problem into small sub-problems within clusters through an incremental approach were proposed. The results of experiments with real-world data show that the proposed algorithm is able to find quality solutions for MaaS systems while significantly reducing the users' vehicle miles travelled. 14. Question: What are the consumers' intention to subscribe to MaaS, preferences for bundling in MaaS and willingness to pay for extra features of MaaS? Results: In [116], a method to estimate the latent demand for MaaS based on a stated preference survey and a choice model was proposed. To study the effects of various factors such as service attributes, socio-demographics and transportation characteristics on the decision to subscribe MaaS, a binary mixed logit model was used. Based on the proposed model, the effects of transportation mode pricing schemes, the cross effects between transportation modes and the effects of individual characteristics on the choice of which transport modes to be included in the subscription were studied. The results show that consumers are not yet inclined to subscribe to MaaS. The subscription intention is affected by the service attribute characteristics, the subscription price, and the social influence variables. The most preferred transportation mode is public transportation. Socio-demographic profiles and individuals' transportation characteristics are critical factors influencing the decision to subscribe and the choice of which transport modes to be included in the bundle. 15. Question: How to evaluate added values of MaaS bundles for users with heterogeneous subscription willingness? Results: In [117], an integrated choice and latent variable model was developed to take into account the factors that influence user subscription to MaaS bundles and estimate the users' subscription willingness. Four bundles were considered in the study, Bus First, Metro Access, Value Taxi, and Ultra Access. By grouping the users with different subscription willingness to MaaS bundles, the added value of MaaS bundles for different group of users was evaluated. The proposed method was tested based on data collected from a stated preference survey. The findings of this study showed that the target users of Bus First and Metro Access bundles were similar. The target users of Value Taxi and UltraAccess bundles were also similar. In terms of the target users' subscription willingness, the Bus First and MetroAccess bundles were considerably higher than the other two bundles. The results showed that BusFirst bundle and Metro Access bundle were generally accepted by users. 16. Question: How do different MaaS bundling and pricing schemes contribute to sustainable transportation? Results: The study [118] assessed the influence of applying different bundling and pricing schemes in MaaS on sustainable transportation. A stated portfolio choice experiment was conducted to capture individuals' intended choice of MaaS. To study the bundles of transportation modes selected by individuals, a mixed logit model was used. The study explores the transportation modes that individuals prefer to include in the bundle, influence of pricing schemes on the bundle as well as the impact on sustainable transport caused by pricing schemes. The findings show that the MaaS's contribution to improvement of sustainable transport is a non-linear function of decreasing monthly subscription fees and/or increasing length of the subscription. 17.