Transportation Research Interdisciplinary Perspectives (Jan 2025)
Modelling the mode choice behaviour of Mobility-as-a-Service (MaaS) users in the Solent of the UK
Abstract
Mobility-as-a-service (MaaS) offers a platform to integrate multiple transport modes into a single intuitive online booking and payment system. This paper aims to understand the factors affecting the mode choice of MaaS app users, with a focus on mode shift towards more sustainable transport modes rather than private cars. Thus, this research explores the transport mode choice of MaaS users between private transport, public/shared transport and active transport and how individual characteristics of users affect their mode choices. To achieve this aim, a revealed preference survey was distributed among Breeze MaaS app users in the Solent area, Southeast of England. A total of 2,022 valid responses were collected, and multinomial logistic regression (MLR) models were estimated. Factors such as car and bike ownership, travel-related impairment, education, profession, public transport pass ownership, and residential area type were found to be significant predictors of most frequent mode choice selection. Retired and employed users are less likely to select public/shared transport compared to private transport, indicating negative perceptions toward this mode. People with travel-related impairments are significantly more likely to choose other transport modes (i.e., taxi and wheelchair), indicating that current public/shared transport modes are not accessible and inclusive enough in the region. Possessing public transport passes seems to attract people towards public/shared transport modes. Some policy insights for successful implementation of MaaS programme; such as integrated shared modes with frequent public transport during morning and evening peak hours, inclusion of accessible taxis and rehabilitation buses, and stepwise discounted bundling system, are recommended. This study serves as a comprehensive guide to investigate the factors affecting the mode choice of MaaS users and provides a basis for future research to improve the understanding of factors for stakeholders to improve the operations of MaaS for successful implementations.
