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School bus transport service strategies’ policy-making mechanism – An evolutionary game approach

Author

Listed:
  • Gu, Tianqi
  • Xu, Weiping
  • Liang, Hua
  • He, Qing
  • Zheng, Nan

Abstract

School transport services are essential to the society. As more families drive their children to school, stakeholders such as the school operators and policy-makers should work together to provide child-friendly and sustainable services like school bus transport. Given that this is a multi-stakeholder problem, it is complex to balance the objectives, for example when it comes to deciding the operators and the school bus service strategies. Currently, there is rather limited knowledge on the relevant policy-making mechanism, and the impact of public transport services used as school transport. To address this, this paper proposes a novel evolutionary game-based approach to reflect the “game” nature of this school transport operation problem and simulate the policy-making procedure, where positive external benefits, as well as intangible school benefits from green and child friendly transport are included. Essentially, the proposed approach should lead to an “equilibrium point” in term of cost-benefits and decision-makings for the involved operators. In this paper, two game players, i.e. schools and governments, are considered. It is found that (1) if both players offer services, i.e. competing, the schools tend to be conservative and stop offering services; (2) if some critical decision-making parameters such as the profit thresholds can be altered, the schools and the government can jointly operate services at “equilibrium” and maintain it sustainably. “Altering” such profit thresholds are possible via policy interventions or service designs, such as service advertisement and quality supervision.

Suggested Citation

  • Gu, Tianqi & Xu, Weiping & Liang, Hua & He, Qing & Zheng, Nan, 2024. "School bus transport service strategies’ policy-making mechanism – An evolutionary game approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
  • Handle: RePEc:eee:transa:v:182:y:2024:i:c:s0965856424000624
    DOI: 10.1016/j.tra.2024.104014
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    References listed on IDEAS

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    1. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, December.
    2. Masi, Barbara, 2018. "A ticket to ride: The unintended consequences of school transport subsidies," Economics of Education Review, Elsevier, vol. 63(C), pages 100-115.
    3. Qian, Xiaodong & Niemeier, Deb, 2019. "High impact prioritization of bikeshare program investment to improve disadvantaged communities' access to jobs and essential services," Journal of Transport Geography, Elsevier, vol. 76(C), pages 52-70.
    4. Trajkovski, Samantha & Zabel, Jeffrey & Schwartz, Amy Ellen, 2021. "Do school buses make school choice work?," Regional Science and Urban Economics, Elsevier, vol. 86(C).
    5. Verhoef, Erik T., 1999. "Time, speeds, flows and densities in static models of road traffic congestion and congestion pricing," Regional Science and Urban Economics, Elsevier, vol. 29(3), pages 341-369, May.
    6. Li-cai Lei & Shang Gao & En-yu Zeng, 2020. "Regulation strategies of ride-hailing market in China: an evolutionary game theoretic perspective," Electronic Commerce Research, Springer, vol. 20(3), pages 535-563, September.
    7. Zhang, Wei & Li, Guoxiang & Guo, Fanyong, 2022. "Does carbon emissions trading promote green technology innovation in China?," Applied Energy, Elsevier, vol. 315(C).
    8. Dorota Kleszczewska & Joanna Mazur & Jens Bucksch & Anna Dzielska & Catherina Brindley & Agnieszka Michalska, 2020. "Active Transport to School May Reduce Psychosomatic Symptoms in School-Aged Children: Data from Nine Countries," IJERPH, MDPI, vol. 17(23), pages 1-12, November.
    9. Friedman, Daniel, 1991. "Evolutionary Games in Economics," Econometrica, Econometric Society, vol. 59(3), pages 637-666, May.
    10. Ting Wang & Kaiyi Li & Defu Liu & Yang Yang & Dong Wu, 2022. "Estimating the Carbon Emission of Construction Waste Recycling Using Grey Model and Life Cycle Assessment: A Case Study of Shanghai," IJERPH, MDPI, vol. 19(14), pages 1-16, July.
    11. Beaudoin, Justin & Farzin, Y. Hossein & Lin Lawell, C.-Y. Cynthia, 2015. "Public transit investment and sustainable transportation: A review of studies of transit's impact on traffic congestion and air quality," Research in Transportation Economics, Elsevier, vol. 52(C), pages 15-22.
    12. Waygood, E.O.D. & Friman, Margareta & Olsson, Lars E. & Taniguchi, Ayako, 2017. "Children's incidental social interaction during travel international case studies from Canada, Japan, and Sweden," Journal of Transport Geography, Elsevier, vol. 63(C), pages 22-29.
    13. Ellen Haug & Otto Robert Frans Smith & Jens Bucksch & Catherina Brindley & Jan Pavelka & Zdenek Hamrik & Joanna Inchley & Chris Roberts & Frida Kathrine Sofie Mathisen & Dagmar Sigmundová, 2021. "12-Year Trends in Active School Transport across Four European Countries—Findings from the Health Behaviour in School-Aged Children (HBSC) Study," IJERPH, MDPI, vol. 18(4), pages 1-15, February.
    14. Gu, Tianqi & Kim, Inhi & Currie, Graham, 2019. "To be or not to be dockless: Empirical analysis of dockless bikeshare development in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 122-147.
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