Socially Sustainable Mobility as a Service (MaaS): A practical MCDM framework to evaluate accessibility and inclusivity with application

Promoting socially sustainable mobility services for all social groups is one of the key elements for sustainable development according to the UN's sustainable development goals. Mobility as a Service (MaaS), a rapidly growing smart mobility concept, has the potential to achieve this goal. However, measuring societal impacts of MaaS considering vulnerable social groups' (elderly, disabled, low-income people) needs is still a question for scholars, practitioners, and policy makers. This paper presents a practical 3-stage framework to evaluate the accessibility and inclusion of MaaS systems based on a range of indicators, and a multi-criteria decision making (MCDM) method. A worldwide experts' view survey was conducted among transportation academics and practitioners with 105 valid responses to prioritise the main and sub-criteria in proving an accessible and inclusive MaaS system. The results of MCDM analysis show that accessible transport services, accessible MaaS platforms, and accessibility data collection have a share of 51 %, 29 %, and 20 %, respectively. The functionality of the proposed framework has been illustrated on a real-world multi-city MaaS implementation within the Solent area, in particular Portsmouth city located in Southeast England (UK). The policy recommendations proposed in this study shed light on guiding stakeholders and policymakers to select and implement an accessible and inclusive MaaS system. • Mobility as a Service (MaaS) has the potential to contribute to socially sustainable mobility in cities. • A 3-step MCDM framework and a set of indicators are developed to evaluate inclusivity and accessibility of MaaS. • A worldwide experts’ view survey was conducted among transportation academics and practitioners to rank criteria and sub-criteria. • Accessible transport services, accessible MaaS platforms, and accessibility data collection have a share of 51%, 29%, and 20%, respectively. • Functionality of the proposed framework is tested on a real-world MaaS project in the UK.