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Managing the social amplification of risk: a simulation of interacting actors

Author

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  • J S Busby

    (Lancaster University, Lancaster, UK)

  • S Onggo

    (Lancaster University, Lancaster, UK)

Abstract

A central problem in managing risk is dealing with social processes that either exaggerate or understate it. A longstanding approach to understanding such processes has been the social amplification of risk framework. But this implies that some true level of risk becomes distorted in social actors’ perceptions. Many risk events are characterised by such uncertainties, disagreements and changes in scientific knowledge that it becomes unreasonable to speak of a true level of risk. The most we can often say in such cases is that different groups believe each other to be either amplifying or attenuating a risk. This inherent subjectivity raises the question as to whether risk managers can expect any particular kinds of outcome to emerge. This question is the basis for a case study of zoonotic disease outbreaks using systems dynamics as a modelling medium. The model shows that processes suggested in the social amplification of risk framework produce polarised risk responses among different actors, but that the subjectivity magnifies this polarisation considerably. As this subjectivity takes more complex forms it leaves problematic residues at the end of a disease outbreak, such as an indefinite drop in economic activity and an indefinite increase in anxiety.

Suggested Citation

  • J S Busby & S Onggo, 2013. "Managing the social amplification of risk: a simulation of interacting actors," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(5), pages 638-653, May.
  • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:5:p:638-653
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    Citations

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    Cited by:

    1. Christopher D. Wirz & Michael A. Xenos & Dominique Brossard & Dietram Scheufele & Jennifer H. Chung & Luisa Massarani, 2018. "Rethinking Social Amplification of Risk: Social Media and Zika in Three Languages," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2599-2624, December.
    2. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.
    3. Hoa Nguyen & An Nguyen, 2020. "Covid-19 Misinformation and the Social (Media) Amplification of Risk: A Vietnamese Perspective," Media and Communication, Cogitatio Press, vol. 8(2), pages 444-447.
    4. Comrie, E.L. & Burns, C. & Coulson, A.B. & Quigley, J. & Quigley, K.F., 2019. "Rationalising the use of Twitter by official organisations during risk events: Operationalising the Social Amplification of Risk Framework through causal loop diagrams," European Journal of Operational Research, Elsevier, vol. 272(2), pages 792-801.

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