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Simulation of the Governance of Complex Systems (SimCo): Basic Concepts and Experiments on Urban Transportation



The current paper is positioned at the intersection of computer simulation, governance research, and research on infrastructure systems, such as transportation or energy. It proposes a simulation framework, “Simulation of the governance of complex systems†(SimCo), to study the governability of complex socio-technical systems experimentally by means of agent-based modelling (ABM). SimCo is rooted in a sociological macro-micro-macro model of a socio-technical system, taking into account the interplay of agents' choices (micro) and situational constraints (macro). The paper presents the conceptualization of SimCo, its elements and subsystems as well as their interactions. SimCo depicts the daily routines of users performing their tasks (e.g. going to work) by choosing among different technologies (e.g. modes of transportation), occasionally deciding to replace a worn-out technology. All components entail different dimensions that can be adjusted, thus allowing operators to purposefully intervene, for instance in the case of risk management (e.g. preventing congestion) or system transformation (e.g. towards sustainable mobility). Experiments with a basic scenario of an urban road transport system demonstrate the effects of different modes of governance (soft control, strong control and a combination of both), revealing that soft control may be the best strategy to govern a complex socio-technical system.

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  • Fabian Adelt & Johannes Weyer & Sebastian Hoffmann & Andreas Ihrig, 2018. "Simulation of the Governance of Complex Systems (SimCo): Basic Concepts and Experiments on Urban Transportation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(2), pages 1-2.
  • Handle: RePEc:jas:jasssj:2017-41-2

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    References listed on IDEAS

    1. Lopolito, A. & Morone, P. & Taylor, R., 2013. "Emerging innovation niches: An agent based model," Research Policy, Elsevier, vol. 42(6), pages 1225-1238.
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    3. Lämmer, Stefan & Gehlsen, Björn & Helbing, Dirk, 2006. "Scaling laws in the spatial structure of urban road networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 89-95.
    4. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
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    Cited by:

    1. Sebastian Hoffmann & Fabian Adelt & Johannes Weyer, 2020. "Modelling End-User Behavior and Behavioral Change in Smart Grids. An Application of the Model of Frame Selection," Energies, MDPI, vol. 13(24), pages 1-26, December.
    2. Raimbault, Juste & Le Néchet, Florent, 2021. "Introducing endogenous transport provision in a LUTI model to explore polycentric governance systems," Journal of Transport Geography, Elsevier, vol. 94(C).
    3. Sylvie Occelli & Simone Landini, 2021. "Thinking Together and Governance in Transport Planning: Can We Strengthen the Connections?," International Journal of E-Planning Research (IJEPR), IGI Global, vol. 10(4), pages 39-62, October.

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