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Delivering mobility as a service (MaaS) through a broker/aggregator business model

Author

Listed:
  • Yale Z. Wong

    (University of Sydney Business School)

  • David A. Hensher

    (University of Sydney Business School)

Abstract

Mobility as a service (MaaS) promises a bold new future where bundled public transport and shared mobility options (carsharing, ridesharing, bikesharing and microtransit) will provide consumers with seamless mobility on par with and exceeding that of private vehicle ownership. Whilst there is a growing body of work examining the market and end user demand for MaaS, there remains a limited understanding of the supply-side around new business models for delivering these integrated mobility services. Mobility broker/aggregator models have been proposed, but to date there exists no quantitative evidence to empirically test the conditions around which interested businesses might invest or supply in this new entrepreneurial model. In this paper, the idea of mode-agnostic mobility contracts [first proposed in Wong et al. (in: 40th Australasian Transport Research Forum (ATRF), Darwin, 2018)] are tested as the interface for bringing together specialised businesses as part of a future transport ecosystem. Data is collected from 202 organisations across 28 countries and mixed logit models estimated to identify the importance of contract attributes like modal mix, role of government, return on investment expectations, branding and equity contribution on respondent interest to partake in a MaaS business. Willingness-to-pay estimates are then devised to identify the potential value proposition of a mobility broker/aggregator to the business community.

Suggested Citation

  • Yale Z. Wong & David A. Hensher, 2021. "Delivering mobility as a service (MaaS) through a broker/aggregator business model," Transportation, Springer, vol. 48(4), pages 1837-1863, August.
    • Handle: RePEc:kap:transp:v:48:y:2021:i:4:d:10.1007_s11116-020-10113-z
    DOI: 10.1007/s11116-020-10113-z
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    References listed on IDEAS

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    Cited by:

    1. Hensher, David A. & Nelson, John D. & Mulley, Corinne, 2022. "Electric car sharing as a service (ECSaaS) – Acknowledging the role of the car in the public mobility ecosystem and what it might mean for MaaS as eMaaS?," Transport Policy, Elsevier, vol. 116(C), pages 212-216.
    2. Bushell, James & Merkert, Rico & Beck, Matthew J., 2022. "Consumer preferences for operator collaboration in intra- and intercity transport ecosystems: Institutionalising platforms to facilitate MaaS 2.0," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 160-178.
    3. Antonella Franco & Antonino Vitetta, 2023. "Preference Model in the Context of Mobility as a Service: A Pilot Case Study," Sustainability, MDPI, vol. 15(6), pages 1-14, March.
    4. Dalenogare, Lucas Santos & Le Dain, Marie-Anne & Benitez, Guilherme B. & Ayala, Néstor F. & Frank, Alejandro G., 2022. "Multichannel digital service delivery and service ecosystems: The role of data integration within Smart Product-Service Systems," Technological Forecasting and Social Change, Elsevier, vol. 183(C).

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    More about this item

    Keywords

    Mobility as a service (MaaS); Intelligent mobility; Service delivery; Broker/aggregator; Public transport contract; Stated choice experiment; Willingness-to-pay;
    All these keywords.

    JEL classification:

    • D2 - Microeconomics - - Production and Organizations
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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