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Nuclear emergency decision support: A behavioural OR perspective

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  • Argyris, Nikolaos
  • French, Simon

Abstract

Operational researchers, risk and decision analysts need consider many behavioural issues. Despite many OR applications in nuclear emergency decision support, the literature has not paid sufficient attention to behavioural matters. In working on designing decision support processes for nuclear emergency management, we have encountered many behavioural issues. In this paper we synthesise the findings in the literature with our experience and identify a number of behavioural challenges to nuclear emergency decision support. In addition to challenges in model-building and interaction, we pay attention to a behavioural issue that is often neglected: the analysis itself and the communication of its implications may have behavioural consequences. We introduce proposals to address these challenges. First, we propose the use of models relying on incomplete preference information, outlining a framework and illustrating it with data from a previous decision analysis for the Chernobyl Project. Moreover, we reflect on the responsibility that rests on the analyst in addressing behavioural issues sensitively in order to lessen the effects on public stress. In doing so we make a distinction between System 1 Societal Deliberation and System 2 Societal Deliberation and discuss how this can help structure societal deliberation in the context of nuclear emergencies.

Suggested Citation

  • Argyris, Nikolaos & French, Simon, 2017. "Nuclear emergency decision support: A behavioural OR perspective," European Journal of Operational Research, Elsevier, vol. 262(1), pages 180-193.
  • Handle: RePEc:eee:ejores:v:262:y:2017:i:1:p:180-193
    DOI: 10.1016/j.ejor.2017.03.059
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    2. Yang Zou & Shuliang Zou & Changming Niu, 2018. "The Optimization of Emergency Evacuation from Nuclear Accidents in China," Sustainability, MDPI, vol. 10(8), pages 1-7, August.
    3. Wenxin Su & Linyan Chen & Xin Gao, 2022. "Emergency Decision Making: A Literature Review and Future Directions," Sustainability, MDPI, vol. 14(17), pages 1-25, September.
    4. Caballero, William N. & Lunday, Brian J., 2019. "Influence modeling: Mathematical programming representations of persuasion under either risk or uncertainty," European Journal of Operational Research, Elsevier, vol. 278(1), pages 266-282.
    5. Raboun, Oussama & Chojnacki, Eric & Duffa, Céline & Insua, David Rios & Tsoukiàs, Alexis, 2020. "Spatial risk assessment in case of multiple nuclear release scenarios," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    6. Simon French & Nikolaos Argyris, 2018. "Decision Analysis and Political Processes," Decision Analysis, INFORMS, vol. 15(4), pages 208-222, December.
    7. Zhiying Wang & Xiaodi Liu & Shitao Zhang, 2019. "A New Decision Method for Public Opinion Crisis with the Intervention of Risk Perception of the Public," Complexity, Hindawi, vol. 2019, pages 1-14, July.

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