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Coordination Game in Online Ride-Hailing Market of Smart City

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1283))

Abstract

Objective: analyze the modes of interest coordination and development of online ride-hailing market of smart city. Method: systematic and comprehensive analysis was made in this paper about the coordination game between smart city’s government, enterprise and car owner in the online ride-hailing market to establish a system evolutionary game model, say the government - enterprise evolutionary game model and enterprise - car owner evolutionary game model. Results: the use of this model enabled the study of dynamic government- enterprise game evolution process under four situations and dynamic enterprise-car owner evolution process under six situations, sequentially to obtain a condition model, where the online ride-hailing market system converged to a non-supervision/non-monitor/coordination mode. Conclusion: the government must make proper regulation in the evolutionary process to develop appropriate regulations and policies, and guide the market participants to adopt healthy and sustainable strategies.

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Acknowledgements

This research was financially supported by China Central Public-interest Scientific Institution Basal Research Fund (Grant No.: 552018Y-5930 & 552019Y-6660).

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Authors and Affiliations

  1. China National Institute of Standardization, Beijing, 100191, China

    Qi Duan

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  1. Qi Duan
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Correspondence to Qi Duan .

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Editors and Affiliations

  1. David Goldman Informatics Centre, University of Sunderland, Sunderland, UK

    John MacIntyre

  2. University of Shanghai for Science and Technology, Shanghai, China

    Jinghua Zhao

  3. Shenzhen University, Shenzen, Guangdong, China

    Xiaomeng Ma

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Duan, Q. (2021). Coordination Game in Online Ride-Hailing Market of Smart City. In: MacIntyre, J., Zhao, J., Ma, X. (eds) The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIOT 2020. Advances in Intelligent Systems and Computing, vol 1283. Springer, Cham. https://doi.org/10.1007/978-3-030-62746-1_81

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