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Mobility as a Service (MaaS) is a promising concept which aims at offering seamless mobility to end users and providing economic, societal, transport-related and environmental benefits to the cities of the future. To achieve a successful future market take-up of MaaS it is important to develop prototype business models to offer high-value bundled mobility services to customers, as well as enable the MaaS operator and the involved actors to capture value. This paper aims at investigating the business perspective of MaaS by collecting qualitative data from workshops and in-depth interviews in three European metropolitan areas: Budapest, Greater Manchester and the city of Luxembourg. The analysis of the collected data contributed to the in-depth analysis of the MaaS business ecosystem and the identification of the champions of MaaS in the three areas. Prototype business models for MaaS are developed based on the Osterwalder's canvas, to describe how MaaS operators may create, deliver, and capture value. Our findings indicate that the MaaS ecosystem comprises of public and private actors who need to cooperate and compete in order to capture value. Although noticeable deviations among the study areas are observed, mobility service providers, public transport authorities and regional authorities were commonly indicated as the key actors in a MaaS partnership. In addition, viewed as a system, enablers and barriers to MaaS are identified based on the systems' of innovation approach. The analysis indicates that the regulatory framework of the cities, the lack of standardization and openness of the application programming interfaces and the need for transport-related investments constitute risks for the successful implementation of MaaS in the study areas. Trust between MaaS actors and cooperation in e-ticketing are key enablers in some of the study areas.

In this paper, we apply Bhat and Dubey's (2014) new multinomial probit (MNP)-based ICLV formulation to analyze children's travel mode choice to school. The new approach offered significant advantages, as it allowed us to incorporate three latent variables with a large data sample and with 10 ordinal indicators of the latent variables, and still estimate the ICLV model without any convergence problems. The data used in the empirical analysis originates from a survey undertaken in Cyprus in 2012. The results underscore the importance of incorporating subjective attitudinal variables in school mode choice modeling. The results also emphasize the need to improve bus and walking safety, and communicate such improvements to the public, especially to girls and women and high income households. The model application also provides important information regarding the value of investing in bicycling and walking infrastructure.

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The scope of this paper is to develop an advanced stated preferences (SP) survey customized to capture teenagers' behaviors and to estimate models of hybrid mode choices, in which the utilities depend on both the attributes of the mode and the latent variable willingness to walk or cycle. The SP scenarios include four alternative modes for the trip to school—car (escorted by parents), bus, bicycle, and walk—while the attributes are travel time; travel cost; walking time to the bus station; availability of bike paths, sidewalks, and parking places; and weather conditions. The data are drawn from a survey that took place in all the high schools of Cyprus in 2012. The sample consists of 4,174 teenagers (ages 12 to 18) and covers 8.7% of the total high school population. For the model estimations, 8,348 SP observations are used. It was found that the existence of bike paths and wide pavements significantly affect the choice of active transport. The latent variable enters significantly into the specification of the choice model to assure that unobserved variables should be implemented in the choice process. Willingness to walk and to cycle has a positive effect on the choice of those alternatives and a negative effect on the choice of a car. Moreover, parents' level of education and mode use patterns and habits influence the development of attitudes toward mode choice. The results of the study provide insights on policies and campaigns that may help the next generation develop greener travel behavior.