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Setting Risk Priorities: A Formal Model

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  • Jun Long
  • Baruch Fischhoff

Abstract

This article presents a model designed to capture the major aspects of setting priorities among risks, a common task in government and industry. The model has both design features, under the control of the rankers (e.g., how success is evaluated), and context features, properties of the situations that they are trying to understand (e.g., how quickly uncertainty can be reduced). The model is demonstrated in terms of two extreme ranking strategies. The first, sequential risk ranking, devotes all its resources, in a given period, to learning more about a single risk, and its place in the overall ranking. This strategy characterizes the process for a society (or organization or individual) that throws itself completely into dealing with one risk after another. The other extreme strategy, simultaneous risk ranking, spreads available resources equally across all risks. It characterizes the most methodical of ranking exercises. Given ample ranking resources, simultaneous risk ranking will eventually provide an accurate set of priorities, whereas sequential ranking might never get to some risks. Resource constraints, however, may prevent simultaneous rankers from examining any risk very thoroughly. The model is intended to clarify the nature of ranking tasks, predict the efficacy of alternative strategies, and improve their design.

Suggested Citation

  • Jun Long & Baruch Fischhoff, 2000. "Setting Risk Priorities: A Formal Model," Risk Analysis, John Wiley & Sons, vol. 20(3), pages 339-352, June.
  • Handle: RePEc:wly:riskan:v:20:y:2000:i:3:p:339-352
    DOI: 10.1111/0272-4332.203033
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    Cited by:

    1. Riccardo Minciardi & Roberto Sacile & Eva Trasforini, 2009. "Resource Allocation in Integrated Preoperational and Operational Management of Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 29(1), pages 62-75, January.
    2. J. S. Busby & B. Green & D. Hutchison, 2017. "Analysis of Affordance, Time, and Adaptation in the Assessment of Industrial Control System Cybersecurity Risk," Risk Analysis, John Wiley & Sons, vol. 37(7), pages 1298-1314, July.
    3. Hong Yao & Xin Qian & Hong Yin & Hailong Gao & Yulei Wang, 2015. "Regional Risk Assessment for Point Source Pollution Based on a Water Quality Model of the Taipu River, China," Risk Analysis, John Wiley & Sons, vol. 35(2), pages 265-277, February.
    4. Simon J. T. Pollard & Ray V. Kemp & Mark Crawford & Raquel Duarte‐Davidson & James G. Irwin & Roger Yearsley, 2004. "Characterizing Environmental Harm: Developments in an Approach to Strategic Risk Assessment and Risk Management," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1551-1560, December.
    5. Meredith Frances Dobbie & Rebekah Ruth Brown, 2014. "A Framework for Understanding Risk Perception, Explored from the Perspective of the Water Practitioner," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 294-308, February.
    6. Susana Freiria & Alexandre O. Tavares & Rui Pedro Julião, 2015. "The Multiscale Importance of Road Segments in a Network Disruption Scenario: A Risk‐Based Approach," Risk Analysis, John Wiley & Sons, vol. 35(3), pages 484-500, March.
    7. Cameron A. MacKenzie, 2014. "Summarizing Risk Using Risk Measures and Risk Indices," Risk Analysis, John Wiley & Sons, vol. 34(12), pages 2143-2162, December.

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