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Risk Analysis and Risk Management in an Uncertain World

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  • Howard Kunreuther

Abstract

The tragic attacks of September 11 and the bioterrorist threats with respect to anthrax that followed have raised a set of issues regarding how we deal with events where there is considerable ambiguity and uncertainty about the likelihood of their occurrence and their potential consequences. This paper discusses how one can link the tools of risk assessment and our knowledge of risk perception to develop risk management options for dealing with extreme events. In particular, it suggests ways that the members of the Society for Risk Analysis can apply their expertise and talent to the risks associated with terrorism and discusses the changing roles of the public and private sectors in dealing with extreme events.

Suggested Citation

  • Howard Kunreuther, 2002. "Risk Analysis and Risk Management in an Uncertain World," Risk Analysis, John Wiley & Sons, vol. 22(4), pages 655-664, August.
    • Handle: RePEc:wly:riskan:v:22:y:2002:i:4:p:655-664
    DOI: 10.1111/0272-4332.00057
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    References listed on IDEAS

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    1. Kunreuther, Howard & Novemsky, Nathan & Kahneman, Daniel, 2001. "Making Low Probabilities Useful," Journal of Risk and Uncertainty, Springer, vol. 23(2), pages 103-120, September.
    2. Neil D. Weinstein & Kathryn Kolb & Bernard D. Goldstein, 1996. "Using Time Intervals Between Expected Events to Communicate Risk Magnitudes," Risk Analysis, John Wiley & Sons, vol. 16(3), pages 305-308, June.
    3. Fischhoff, Baruch, 1994. "What forecasts (seem to) mean," International Journal of Forecasting, Elsevier, vol. 10(3), pages 387-403, November.
    4. Howard Kunreuther & Geoffrey Heal, 2002. "Interdependent Security: The Case of Identical Agents," NBER Working Papers 8871, National Bureau of Economic Research, Inc.
    5. Hsee, Christopher K & Kunreuther, Howard C, 2000. "The Affection Effect in Insurance Decisions," Journal of Risk and Uncertainty, Springer, vol. 20(2), pages 141-159, March.
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    Citations

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    Cited by:

    1. Munan Li & Alan L. Porter, 2018. "Facilitating the discovery of relevant studies on risk analysis for three-dimensional printing based on an integrated framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 277-300, January.
    2. Jing Zeng & Jiuchang Wei & Dingtao Zhao & Weiwei Zhu & Jibao Gu, 2017. "Information-seeking intentions of residents regarding the risks of nuclear power plant: an empirical study in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 739-755, June.
    3. Canhoto, Ana Isabel, 2021. "Leveraging machine learning in the global fight against money laundering and terrorism financing: An affordances perspective," Journal of Business Research, Elsevier, vol. 131(C), pages 441-452.
    4. Jingyu Liu & Walter W. Piegorsch & A. Grant Schissler & Susan L. Cutter, 2018. "Autologistic models for benchmark risk or vulnerability assessment of urban terrorism outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 803-823, June.
    5. Bruno Spilak & Wolfgang Karl Härdle, 2022. "Tail-Risk Protection: Machine Learning Meets Modern Econometrics," Springer Books, in: Cheng-Few Lee & Alice C. Lee (ed.), Encyclopedia of Finance, edition 0, chapter 92, pages 2177-2211, Springer.
    6. Raymond A. Zilinskas & Bruce Hope & D. Warner North, 2004. "A Discussion of Findings and Their Possible Implications from a Workshop on Bioterrorism Threat Assessment and Risk Management," Risk Analysis, John Wiley & Sons, vol. 24(4), pages 901-908, August.
    7. Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
    8. Beverly Cigler, 2009. "Post-Katrina Hazard Mitigation on the Gulf Coast," Public Organization Review, Springer, vol. 9(4), pages 325-341, December.
    9. Ajita Atreya & Susana Ferreira, 2015. "Seeing is Believing? Evidence from Property Prices in Inundated Areas," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 828-848, May.
    10. Max Resende & Alexandre Ferreira, 2021. "A machine learning approach to risk disclosure reporting," Economics Bulletin, AccessEcon, vol. 41(2), pages 234-251.
    11. Gregory Levitin & Liudong Xing & Hong‐Zhong Huang, 2019. "Security of Separated Data in Cloud Systems with Competing Attack Detection and Data Theft Processes," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 846-858, April.
    12. Walter W. Piegorsch, 2010. "Translational benchmark risk analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 13(5), pages 653-667, July.
    13. Wesley E Highfield & Sarah A Norman & Samuel D Brody, 2013. "Examining the 100‐Year Floodplain as a Metric of Risk, Loss, and Household Adjustment," Risk Analysis, John Wiley & Sons, vol. 33(2), pages 186-191, February.
    14. Bridget M. Hutter & Clive J. Jones, 2007. "From government to governance: External influences on business risk management," Regulation & Governance, John Wiley & Sons, vol. 1(1), pages 27-45, March.
    15. Walter W. Piegorsch & Susan L. Cutter & Frank Hardisty, 2007. "Benchmark Analysis for Quantifying Urban Vulnerability to Terrorist Incidents," Risk Analysis, John Wiley & Sons, vol. 27(6), pages 1411-1425, December.
    16. Michèle Marti & Michael Stauffacher & Jörg Matthes & Stefan Wiemer, 2018. "Communicating Earthquake Preparedness: The Influence of Induced Mood, Perceived Risk, and Gain or Loss Frames on Homeowners’ Attitudes Toward General Precautionary Measures for Earthquakes," Risk Analysis, John Wiley & Sons, vol. 38(4), pages 710-723, April.
    17. Luca Allodi & Fabio Massacci, 2017. "Security Events and Vulnerability Data for Cybersecurity Risk Estimation," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1606-1627, August.

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