Mobility as a Service

Christiaanse, Rob

doi:10.1145/3308560.3317050

Cited by 8 publications

(3 citation statements)

References 25 publications

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“…General attitudinal aspects like privacy [33,34], environmental concern [35,36], lifestyle [36], healthrelated habits [29,37,38], innovativeness and techsavviness [39] have been found to be all critical factors to realise how concerned people are towards the adoption of MaaS. Lifestyle is affected by age, gender, education, and income [40][41][42].…”

Section: Attitudes and Habits Of The Travellersmentioning

confidence: 99%

MaaS modelling: a review of factors, customers’ profiles, choices and business models

Cisterna,

Madani,

Bandiera

et al. 2023

Eur. Transp. Res. Rev.

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Mobility-as-a-Service (MaaS) system 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 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. To successfully deploy MaaS to reach the intended goals, it is critical to develop feasible and sustainable models that capture the diverse needs of customers as well as the diverse and often competing objectives of service providers. This paper aims to provide a general modelling framework and a critical and descriptive analysis of the relevant literature relating all main actors in the MaaS ecosystem, and identify and discuss all factors that are considered relevant, focusing on the actor’s decision-making processes and their correlations. This review shows the large variety and interaction of factors influencing MaaS adoption and their impact on forecasting MaaS appeal. It is also observed that current travel behaviour and multi-modal transport models are not fully capturing the diverse travel needs and choices of potential MaaS users. Recent advancements in agent-based simulation and discrete choice modelling offer potential solutions to address this gap, and future research should aim in that direction. Finally, the review analyses the interaction between MaaS actors, including customers, service providers, the government, and the MaaS Broker, highlighting the complexity of the modelling process comprising all actors of the MaaS ecosystem. Therefore, it is recommended to prioritise future research in exploring these areas.

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Section: Attitudes and Habits Of The Travellersmentioning

confidence: 99%

MaaS modelling: a review of factors, customers’ profiles, choices and business models

Cisterna,

Madani,

Bandiera

et al. 2023

Eur. Transp. Res. Rev.

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“…No doubt that clean air is a common pool resource. Car sharing services like MAAS [11] use resources like gasoline in fulfilling transport services by bringing customers from A to B. Customers pay a fare for this service in some currency.…”

Section: The Governance Of Common Pool Resourcesmentioning

confidence: 99%

Human Centric Design in Smartcity Technologies

Christiaanse¹

2022

Companion Proceedings of the Web Conference 2022

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“…It has caused huge economic losses, especially in the Japanese tourism industry (Kabadayi et al, 2020;Alashhab et al, 2021). MaaS (Mobility as a Service) provides a seamless passenger experience using multiple modes of transport from the beginning until the end of a journey, and its developments have attracted keen interest from the industry in recent years (Christiaanse, 2019;Hensher et al, 2020). MaaS can be applied as a solution to deal with the current situation by considering the social distance (Bothos et al, 2019;Georgakis et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

User Welfare in Cryptocurrency Transaction Markets: An Empirical Study on EIP-1559

Ai,

Wu,

Shang

et al. 2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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MaaS (Mobility as a Service) itself has come into common use, and these developments have attracted keen interest from the industry in recent years. MaaS can be applied as a solution to deal with the current situation by considering the social distance. However, due to the time-share mechanism, personal assets are monopolized by specific users for a long time that cannot be shared with other users at the same time. Thus, the sharing economy companies in the tourism industry (e.g., Airbnb Experience and Huber) are in a dilemma of low productivity and high cost. In this research, we propose a new travel guide sharing service that considers the concept of social distance and user preferences. The user side only needs to select simple conditions such as travel time and the number of POIs (Point of Interest) that she/he plans to visit, meanwhile, the guide side simply inputs the POIs that she/he can guide. Furthermore, by analyzing these basic information, our proposed system can recommend the tour guides, scenic spots, and route planning to provide a real-time tour guide plan, which addressed the user's preferences and reduced the face-to-face communication to users in advance. To verify the effectiveness of our proposed method, we also ask 68 users to evaluate our system and analyze the results of questionnaires.

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Mobility as a Service

Cited by 8 publications

References 25 publications

MaaS modelling: a review of factors, customers’ profiles, choices and business models

MaaS modelling: a review of factors, customers’ profiles, choices and business models

Human Centric Design in Smartcity Technologies

User Welfare in Cryptocurrency Transaction Markets: An Empirical Study on EIP-1559

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