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Risk aggregation: What does it really mean?

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  • Bjørnsen, Kjartan
  • Aven, Terje

Abstract

Risk aggregation is a common concept in risk management contexts. Overall, it relates to the process of summing and showing the interaction between single or individual risks, to see the bigger picture. However, its meaning and use are not clear when looking more closely into the concept and comparing various applications. In this paper, we will provide an in-depth study of the aggregation concept, using as a basis a general way of defining and understanding risk (in line with the Glossary from the Society for Risk Analysis), which includes most common perspectives on risk. The aim of the paper is to provide new insight into the concept, in order to strengthen the foundation of risk management and in particular the communication about risk issues.

Suggested Citation

  • Bjørnsen, Kjartan & Aven, Terje, 2019. "Risk aggregation: What does it really mean?," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:reensy:v:191:y:2019:i:c:s0951832018307932
    DOI: 10.1016/j.ress.2019.106524
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    References listed on IDEAS

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    1. Vinnem, Jan Erik, 2010. "Risk analysis and risk acceptance criteria in the planning processes of hazardous facilities—A case of an LNG plant in an urban area," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 662-670.
    2. Bernard, Carole & Jiang, Xiao & Wang, Ruodu, 2014. "Risk aggregation with dependence uncertainty," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 93-108.
    3. Ides Boone & Yves Van der Stede & Jeroen Dewulf & Winy Messens & Marc Aerts & Georges Daube & Koen Mintiens, 2010. "NUSAP: a method to evaluate the quality of assumptions in quantitative microbial risk assessment," Journal of Risk Research, Taylor & Francis Journals, vol. 13(3), pages 337-352, April.
    4. Aven, Terje, 2012. "The risk concept—historical and recent development trends," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 33-44.
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    Cited by:

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    5. Yin, Xuanpeng & Xu, Xuanhua & Pan, Bin, 2021. "Selection of Strategy for Large Group Emergency Decision-making based on Risk Measurement," Reliability Engineering and System Safety, Elsevier, vol. 208(C).

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