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Simulation Modelling as a Theory Building Tool: The Formation of Risk Perceptions

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This paper presents a computer based simulation model which analyses the dynamics of public perceptions of risk using Bovine Spongiform Encephalopathy (BSE) ('mad cow disease') in the UK as a case study. The model is based upon a theoretically-derived understanding of the concept of perception of risk, and employs Cultural Theory and the archetypes it identifies as distinctive forms of social organization and cultural bias in the formation of perceptions. Cultural Theory is used as a theoretical lens for understanding the different interpretations of the risk associated with BSE/nvCJD, the subsequent risk amplification by the media, and the effect of trust and reliance in science and government in their construction. The analysis helps achieve a better understanding of the dynamics of public perceptions of risk, and it is therefore of interest both for academics and policy makers. In particular, the model allows exploring the influence that the occurrence of risk-related events, their media coverage, and trust in government responses has in the process by which people construct their risk perceptions.

Suggested Citation

  • Mercedes Bleda & Simon Shackley, 2012. "Simulation Modelling as a Theory Building Tool: The Formation of Risk Perceptions," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-2.
  • Handle: RePEc:jas:jasssj:2011-8-2
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    File URL: http://jasss.soc.surrey.ac.uk/15/2/2/2.pdf
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    1. Hanneman & Anthony Patrick, 1997. "On the Uses of Computer-Assisted Simulation Modeling in the Social Sciences," Sociological Research Online, Sociological Research Online, vol. 2(2), pages 1-5.
    2. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    3. Ulrich Frank & Klaus G. Troitzsch, 2005. "Epistemological Perspectives on Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-7.
    4. Karolina SafarzyƄska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    5. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    6. Janssen, Marco & de Vries, Bert, 1998. "The battle of perspectives: a multi-agent model with adaptive responses to climate change," Ecological Economics, Elsevier, vol. 26(1), pages 43-65, July.
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    Cited by:

    1. Sara McPhee-Knowles, 2015. "Growing Food Safety from the Bottom Up: An Agent-Based Model of Food Safety Inspections," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-9.

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