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The Governance of Risks in Ridesharing: A Revelatory Case from Singapore

Author

Listed:
  • Yanwei Li

    () (Department of Public Administration, Nanjing Normal University, Nanjing 210023, China)

  • Araz Taeihagh

    () (Lee Kuan Yew School of Public Policy, National University of Singapore, 469B Bukit Timah Road, Li Ka Shing Building, Singapore 259771, Singapore)

  • Martin De Jong

    () (Faculty of Technology, Policy and Management, Delft University of Technology, 2600 GA Delft, The Netherlands
    School of International Relations and Public Affairs, Fudan University, Shanghai 200433, China)

Abstract

Recently we have witnessed the worldwide adoption of many different types of innovative technologies, such as crowdsourcing, ridesharing, open and big data, aiming at delivering public services more efficiently and effectively. Among them, ridesharing has received substantial attention from decision-makers around the world. Because of the multitude of currently understood or potentially unknown risks associated with ridesharing (unemployment, insurance, information privacy, and environmental risk), governments in different countries apply different strategies to address such risks. Some governments prohibit the adoption of ridesharing altogether, while other governments promote it. In this article, we address the question of how risks involved in ridesharing are governed over time. We present an in-depth single case study on Singapore and examine how the Singaporean government has addressed risks in ridesharing over time. The Singaporean government has a strong ambition to become an innovation hub, and many innovative technologies have been adopted and promoted to that end. At the same time, decision-makers in Singapore are reputed for their proactive style of social governance. The example of Singapore can be regarded as a revelatory case study, helping us further to explore governance practices in other countries.

Suggested Citation

  • Yanwei Li & Araz Taeihagh & Martin De Jong, 2018. "The Governance of Risks in Ridesharing: A Revelatory Case from Singapore," Energies, MDPI, Open Access Journal, vol. 11(5), pages 1-21, May.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1277-:d:146782
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Yanwei Li & Liang Ma, 2019. "What drives the governance of ridesharing? A fuzzy-set QCA of local regulations in China," Policy Sciences, Springer;Society of Policy Sciences, vol. 52(4), pages 601-624, December.
    2. Yuchen Gao & Jingrui Chen, 2019. "The Risk Reduction and Sustainable Development of Shared Transportation: The Chinese Online Car-hailing Policy Evaluation in the Digitalization Era," Sustainability, MDPI, Open Access Journal, vol. 11(9), pages 1-21, May.
    3. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    4. Ye Ma & Biying Yu & Meimei Xue, 2018. "Spatial Heterogeneous Characteristics of Ridesharing in Beijing–Tianjin–Hebei Region of China," Energies, MDPI, Open Access Journal, vol. 11(11), pages 1-21, November.

    More about this item

    Keywords

    risk; ridesharing; transport; governance; innovative technologies; case study; Singapore;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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