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Modeling a Simulation for Sociotechnical Resilience

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  • Fredy Tantri
  • Sulfikar Amir

Abstract

This paper proposes a conceptual model to simulate the response of sociotechnical systems to crisis. The model draws on a concept of “sociotechnical resilience” as the theoretical framework, which underscores the hybrid nature of sociotechnical systems. Revolving around the notion of transformability, the concept considers sociotechnical resilience to be constitutive of three fundamental attributes, namely, informational relations, sociomaterial structures, and anticipatory practices. Our model aims to capture the complex interactions within a sociotechnical system during a recovery process by incorporating these core attributes in the operational units embedded in a multilevel directed acyclic graph, information networks, and recovery strategies. Furthermore, the model emphasizes specifically the role of informational configuration during a disruption. We introduce two recovery strategies in our simulation, namely, random recovery and informed recovery. The former represents the unprepared responses to crisis, while the latter incorporates the reporting process to support the command centre in making optimum decisions. The simulation results suggest the importance of system flexibility to allow structural reconfiguration at the organizational level. Our proposed model complements the theoretical principles of sociotechnical resilience while laying a practical foundation of sociotechnical modeling for resilience enhancement in real-world settings.

Suggested Citation

  • Fredy Tantri & Sulfikar Amir, 2019. "Modeling a Simulation for Sociotechnical Resilience," Complexity, Hindawi, vol. 2019, pages 1-11, December.
    • Handle: RePEc:hin:complx:7950629
    DOI: 10.1155/2019/7950629
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    References listed on IDEAS

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    1. Almoghathawi, Yasser & Barker, Kash & Albert, Laura A., 2019. "Resilience-driven restoration model for interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 12-23.
    2. Alexei Sharpanskykh & Sybert H. Stroeve, 2011. "An agent-based approach for structured modeling, analysis and improvement of safety culture," Computational and Mathematical Organization Theory, Springer, vol. 17(1), pages 77-117, March.
    3. Benedikte Bjerge & Nathan Clark & Peter Fisker & Emmanuel Raju, 2016. "Technology and Information Sharing in Disaster Relief," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-20, September.
    4. Yossi Sheffi, 2005. "The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262693496, April.
    5. Sulfikar Amir & Vivek Kant, 2018. "Sociotechnical Resilience: A Preliminary Concept," Risk Analysis, John Wiley & Sons, vol. 38(1), pages 8-16, January.
    6. Adjetey-Bahun, Kpotissan & Birregah, Babiga & Châtelet, Eric & Planchet, Jean-Luc, 2016. "A model to quantify the resilience of mass railway transportation systems," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 1-14.
    7. Preece, Gary & Shaw, Duncan & Hayashi, Haruo, 2013. "Using the Viable System Model (VSM) to structure information processing complexity in disaster response," European Journal of Operational Research, Elsevier, vol. 224(1), pages 209-218.
    8. Justyna Tasic & Fredy Tantri & Sulfikar Amir, 2019. "Modelling Multilevel Interdependencies for Resilience in Complex Organisation," Complexity, Hindawi, vol. 2019, pages 1-23, February.
    9. Daniel A. Eisenberg & Jeryang Park & Thomas P. Seager, 2017. "Sociotechnical Network Analysis for Power Grid Resilience in South Korea," Complexity, Hindawi, vol. 2017, pages 1-14, October.
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    Cited by:

    1. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

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