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Modelling a social dilemma of mode choice based on commuters' expectations and social learning

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  • Sunitiyoso, Yos
  • Matsumoto, Shoji

Abstract

This study attempts to apply an agent-based approach to modelling a social dilemma of travel mode choice considering psychological and sociological aspects. A traveller is modelled to have expectations, which shows the traveller's beliefs about the influence of other group members on his action, as decision-making rules. Social interaction using a group-based interaction is hypothesized to be important. We apply an imitation game based on social learning mechanisms to the model. Two kinds of mechanism are used: payoff-biased and conformist transmission. The model reveals the conditions that make cooperation as a possible outcome are optimistic bandwagon expectations, group-based interactions, and strong conformist transmissions.

Suggested Citation

  • Sunitiyoso, Yos & Matsumoto, Shoji, 2009. "Modelling a social dilemma of mode choice based on commuters' expectations and social learning," European Journal of Operational Research, Elsevier, vol. 193(3), pages 904-914, March.
    • Handle: RePEc:eee:ejores:v:193:y:2009:i:3:p:904-914
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    References listed on IDEAS

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    Cited by:

    1. Tian, Li-Jun & Huang, Hai-Jun, 2015. "Modeling the modal split and trip scheduling with commuters’ uncertainty expectation," European Journal of Operational Research, Elsevier, vol. 244(3), pages 815-822.
    2. Ronald, Nicole & Arentze, Theo & Timmermans, Harry, 2012. "Modeling social interactions between individuals for joint activity scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 276-290.
    3. Kočišová, J. & Horváth, D. & Brutovský, B., 2009. "The efficiency of individual optimization in the conditions of competitive growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3585-3592.
    4. Wei, Fangfang & Jia, Ning & Ma, Shoufeng, 2016. "Day-to-day traffic dynamics considering social interaction: From individual route choice behavior to a network flow model," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 335-354.
    5. Zhang, Guijie & Wei, Fangfang & Jia, Ning & Ma, Shoufeng & Wu, Yi, 2019. "Information adoption in commuters’ route choice in the context of social interactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 300-316.
    6. Busby, J.S. & Onggo, B.S.S. & Liu, Y., 2016. "Agent-based computational modelling of social risk responses," European Journal of Operational Research, Elsevier, vol. 251(3), pages 1029-1042.

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