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A Simplified Method for Value of Information Using Constructed Scales

Author

Listed:
  • Michael C. Runge

    (U.S. Geological Survey Eastern Ecological Science Center at the Patuxent Research Refuge, Laurel, Maryland 20708)

  • Clark S. Rushing

    (Warnell School of Forestry and Natural Resources, University of Georgia, Athens, Georgia 30602)

  • James E. Lyons

    (U.S. Geological Survey Eastern Ecological Science Center at the Patuxent Research Refuge, Laurel, Maryland 20708)

  • Madeleine A. Rubenstein

    (U.S. Geological Survey, National Climate Adaptation Science Center, Reston, Virginia 20192)

Abstract

The value of information is a central concept in decision analysis, used to quantify how much the expected outcome of a decision would be improved if epistemic uncertainty could be resolved prior to committing to a course of action. One of the challenges, however, in quantitative analysis of the value of information is that the calculations are demanding, especially in requiring predictions of outcomes as a function of alternative actions and sources of uncertainty. However, the concept of value of information is important in early framing of some decisions, before such predictions are available. We propose a novel measure of the value of information based on constructed scales (CVOI), grounded in the algebra of the expected value of perfect information (EVPI), but requiring less of experts and analysts. The CVOI calculation decomposes EVPI into a contribution representing the relevance of the uncertainty to the decision and a contribution representing the magnitude of uncertainty; constructed ratio scales are then proposed for each contribution. We demonstrate the use of CVOI to identify research priorities related to migratory bird management in the face of climate change.

Suggested Citation

  • Michael C. Runge & Clark S. Rushing & James E. Lyons & Madeleine A. Rubenstein, 2023. "A Simplified Method for Value of Information Using Constructed Scales," Decision Analysis, INFORMS, vol. 20(3), pages 220-230, September.
    • Handle: RePEc:inm:ordeca:v:20:y:2023:i:3:p:220-230
    DOI: 10.1287/deca.2023.0474
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    References listed on IDEAS

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    1. Hau L. Lee & Kut C. So & Christopher S. Tang, 2000. "The Value of Information Sharing in a Two-Level Supply Chain," Management Science, INFORMS, vol. 46(5), pages 626-643, May.
    2. Myles R. Allen & Peter A. Stott & John F. B. Mitchell & Reiner Schnur & Thomas L. Delworth, 2000. "Quantifying the uncertainty in forecasts of anthropogenic climate change," Nature, Nature, vol. 407(6804), pages 617-620, October.
    3. Andrew Speirs‐Bridge & Fiona Fidler & Marissa McBride & Louisa Flander & Geoff Cumming & Mark Burgman, 2010. "Reducing Overconfidence in the Interval Judgments of Experts," Risk Analysis, John Wiley & Sons, vol. 30(3), pages 512-523, March.
    4. Jeffrey M. Keisler & Zachary A. Collier & Eric Chu & Nina Sinatra & Igor Linkov, 2014. "Value of information analysis: the state of application," Environment Systems and Decisions, Springer, vol. 34(1), pages 3-23, March.
    5. Hanea, A.M. & McBride, M.F. & Burgman, M.A. & Wintle, B.C. & Fidler, F. & Flander, L. & Twardy, C.R. & Manning, B. & Mascaro, S., 2017. "I nvestigate D iscuss E stimate A ggregate for structured expert judgement," International Journal of Forecasting, Elsevier, vol. 33(1), pages 267-279.
    6. James C. Felli & Gordon B. Hazen, 1998. "Sensitivity Analysis and the Expected Value of Perfect Information," Medical Decision Making, , vol. 18(1), pages 95-109, January.
    7. Peck, Stephen C. & Teisberg, Thomas J., 1993. "Global warming uncertainties and the value of information: an analysis using CETA," Resource and Energy Economics, Elsevier, vol. 15(1), pages 71-97, March.
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