IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2011-8-2.html
   My bibliography  Save this article

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

Author

Abstract

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
    as

    Download full text from publisher

    File URL: https://www.jasss.org/15/2/2/2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Eve Seguin, 2000. "The UK BSE crisis: Strengths and weaknesses of existing conceptual approaches," Science and Public Policy, Oxford University Press, vol. 27(4), pages 293-301, August.
    3. Horst Hanusch & Andreas Pyka (ed.), 2007. "Elgar Companion to Neo-Schumpeterian Economics," Books, Edward Elgar Publishing, number 2973.
    4. R. Hanneman & S. Patrick, 1997. "On the Uses of Computer-Assisted Simulation Modeling in the Social Sciences," Sociological Research Online, , vol. 2(2), pages 65-70, June.
    5. 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.
    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.
    7. Karolina Safarzyńska & 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sujeetha Selvakkumaran & Erik O. Ahlgren, 2018. "Model-Based Exploration of Co-Creation Efforts: The Case of Solar Photovoltaics (PV) in Skåne, Sweden," Sustainability, MDPI, vol. 10(11), pages 1-23, October.
    2. Branden B. Johnson & Brendon Swedlow, 2021. "Cultural Theory's Contributions to Risk Analysis: A Thematic Review with Directions and Resources for Further Research," Risk Analysis, John Wiley & Sons, vol. 41(3), pages 429-455, March.
    3. 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.
    4. M. Aenne Schoop & Marco Verweij & Ulrich Kühnen & Shenghua Luan, 2020. "Political disagreement in the classroom: testing cultural theory through structured observation," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 623-643, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giovanni Dosi & Andrea Roventini, 2017. "Agent-Based Macroeconomics and Classical Political Economy: Some Italian Roots," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 261-283, November.
    2. Friederike Wall, 2016. "Agent-based modeling in managerial science: an illustrative survey and study," Review of Managerial Science, Springer, vol. 10(1), pages 135-193, January.
    3. Karolina Safarzyńska & 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.
    4. Ernesto Carrella & Richard M. Bailey & Jens Koed Madsen, 2018. "Indirect inference through prediction," Papers 1807.01579, arXiv.org.
    5. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Beyond replicator dynamics: Innovation-selection dynamics and optimal diversity," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 229-245, May.
    6. G. Fagiolo & A. Roventini, 2009. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 6.
    7. G. Fagiolo & C. Birchenhall & P. Windrum, 2007. "Empirical Validation in Agent-based Models: Introduction to the Special Issue," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 189-194, October.
    8. Francesco Lamperti, 2015. "An Information Theoretic Criterion for Empirical Validation of Time Series Models," LEM Papers Series 2015/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Almas Heshmati & Flávio Lenz-Cesar, 2015. "Policy simulation of firms’ cooperation in innovation," Research Evaluation, Oxford University Press, vol. 24(3), pages 293-311.
    10. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    11. Latynskiy, Evgeny & Berger, Thomas, 2015. "UTZ certification for groups of smallholder coffee farmers: Hype of hope?," 2015 Conference, August 9-14, 2015, Milan, Italy 229069, International Association of Agricultural Economists.
    12. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    13. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    14. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
    15. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
    16. Hepburn, Cameron & Mealy, Penny, 2017. "Transformational Change: Parallels for addressing climate and development goals," INET Oxford Working Papers 2019-02, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, revised May 2019.
    17. Jiang, Guoyin & Shang, Jennifer & Liu, Wenping & Feng, Xiaodong & Lei, Junli, 2020. "Modeling the dynamics of online review life cycle: Role of social and economic moderations," European Journal of Operational Research, Elsevier, vol. 285(1), pages 360-379.
    18. J. Farmer & Cameron Hepburn & Penny Mealy & Alexander Teytelboym, 2015. "A Third Wave in the Economics of Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 329-357, October.
    19. Seri, Raffaello & Martinoli, Mario & Secchi, Davide & Centorrino, Samuele, 2021. "Model calibration and validation via confidence sets," Econometrics and Statistics, Elsevier, vol. 20(C), pages 62-86.
    20. Bauermann, Tom, 2020. "Governmental policies to reduce unemployment during recessions: Insights from an ABM," Ruhr Economic Papers 847, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jas:jasssj:2011-8-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Francesco Renzini (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.