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Supplementing quantitative risk assessments with a stage addressing the risk understanding of the decision maker

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  • Aven, Terje

Abstract

A quantitative probabilistic risk assessment produces a conditional risk description given the knowledge of the analysts (formulated to a large extent through assumptions). However, important aspects of the risk may be concealed in the background knowledge of the analyst and the assumptions. This paper discusses this issue, the main purpose being to present a two-stage risk assessment approach where the second stage addresses the risk understanding of the decision maker. This second-stage is to a large extent qualitative. The approach is novel with its separation between the analysts׳ conditional risk descriptions using probability judgments, and the decision maker׳s risk understanding. The approach aims at improving the use of risk assessment in practical decision making by ensuring that the results of the risk assessments are properly interpreted and the key aspects of risk, uncertainty and knowledge are brought to attention for the decision makers. Examples are used to illustrate the approach.

Suggested Citation

  • Aven, Terje, 2016. "Supplementing quantitative risk assessments with a stage addressing the risk understanding of the decision maker," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 51-57.
    • Handle: RePEc:eee:reensy:v:152:y:2016:i:c:p:51-57
    DOI: 10.1016/j.ress.2016.03.003
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    References listed on IDEAS

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    1. Aven, Terje, 2008. "A semi-quantitative approach to risk analysis, as an alternative to QRAs," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 790-797.
    2. Aven, Terje, 2015. "On the allegations that small risks are treated out of proportion to their importance," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 116-121.
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    Cited by:

    1. Terje Aven, 2017. "Improving the foundation and practice of reliability engineering," Journal of Risk and Reliability, , vol. 231(3), pages 295-305, June.
    2. Deyun Zhou & Yongchuan Tang & Wen Jiang, 2017. "An Improved Belief Entropy and Its Application in Decision-Making," Complexity, Hindawi, vol. 2017, pages 1-15, March.
    3. Terje Aven, 2018. "An Emerging New Risk Analysis Science: Foundations and Implications," Risk Analysis, John Wiley & Sons, vol. 38(5), pages 876-888, May.
    4. Carpitella, Silvia & Certa, Antonella & Izquierdo, Joaquín & La Fata, Concetta Manuela, 2018. "A combined multi-criteria approach to support FMECA analyses: A real-world case," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 394-402.
    5. Abroon Qazi & Mecit Can Emre Simsekler & Steven Formaneck, 2023. "Supply chain risk network value at risk assessment using Bayesian belief networks and Monte Carlo simulation," Annals of Operations Research, Springer, vol. 322(1), pages 241-272, March.
    6. Qazi, Abroon, 2023. "Exploring Global Competitiveness Index 4.0 through the lens of country risk," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

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