Unpublished conference/Abstract (Scientific congresses, symposiums and conference proceedings)MaaS modelling: a review of factors, customers’ profiles, choices and business models
Cisterna, Carolina; Negarsadat, Madani; Bandiera, Claudia et al.
2022 • 3rd International Conference on Mobility as a Service – ICoMaaS
No document available.
Abstract :
[en] Mobility-as-a-Service (MaaS) is regarded as one of the emerging solutions to
offer integrated, seamless, and flexible multi-modal mobility services as an
alternative to privately owned mobility resources. MaaS gathers collective services
such as public transport, shared solutions and other types of new mobility (e.g.,
on-demand ride services) and ancillary services (e.g., discounted parking) in
bundles, accessed via monthly subscriptions. The key distinction between this
system and traditional multi-modal systems managed by independent service
providers is that payment for services is done through a single digital platform.
MaaS is expected to change the way users will choose their modes of transport
to reach their daily activities, and how service providers will generate profits,
cooperate, and compete. From a wider perspective, MaaS is expected to favour a
decline in car ownership and foster sustainable mobility, especially if the services
increase the efficiency and utilisation of mass transit. To that aim, it is critical to
obtain a thorough grasp of feasible and sustainable business models that suit the
diverse needs of customers as well as the diverse and often competing objectives
of service providers. In contrast, traditional transportation planning models
typically assess solutions in a limited period of time (i.e., the peak hour) and use
different simplifying assumptions (e.g., single trip-based choices, no interaction
between service providers). This paper aims to provide a general modelling
framework relating all main actors in the MaaS ecosystem and identify and
discuss all factors that are considered relevant to define customers’ profiles and
business models based on a comprehensive review of the literature. Gaps and
challenges from the current studies are highlighted and future research directions
are recommended.