Segmenting the potential users of MaaS by combining latent class cluster analysis and structural equation modeling

• LCCA and SEM are combined to reveal potential users of MaaS. • Public transport and shared mobility users are potential adopters of MaaS. • Media reviews are essential for influencing the MaaS uptake. • Flexibility in traveling is important to escalate the adoption of MaaS among car users. To reduce problems caused by the excessive use of private vehicles, transportation planners have been actively looking for sustainable transport related solutions. Mobility as a Service (MaaS) is gaining popularity due to its capability to integrate transport opportunities into one platform. Studies on travelers’ acceptance of MaaS have been conducted, but there remains a gap in understanding heterogeneity regarding intentions of using MaaS particularly concerning attitudinal factors. Based upon the extension of the unified theory of acceptance and use of technology, we plan to reveal travelers’ segmentation by using latent class cluster analysis and to examine path heterogeneities in the identified traveler clusters by applying a structural equation modeling. The results confirm that the traveler clusters consider the importance of the relatives and media's viewpoints toward MaaS, while the car user cluster is more interested in adopting MaaS if the service could promise enough flexibility of traveling in terms of time and destination. The results related to the heterogeneity in transport mode choice are useful for constructing MaaS packages. This study could be advantageous for MaaS operators as it enables them to understand some attitudinal factors influencing willingness to take up MaaS thus realizing suitable, effective promotions.