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The role of translations of verbal into numerical probability expressions in risk management: a meta-analysis

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  • Michael Theil

Abstract

Translations of verbal into numerical probability expressions play a central role in risk management, for instance when assessing risks or when choosing appropriate measures to handle them. Despite the fact that the issue of probability translations has been widely studied in the past, results have remained quite isolated. The present work sets out to provide a meta-analysis of previous work, focussing on the most frequently used expressions. It turns out that the numerical ratings for verbal expressions differ considerably between studies. Subsequent analysis is devoted to distances between the results and to differences in methodology. Although there is significant disagreement on which figure represents a particular verbal probability best, methodology was not found to be a decisive factor. The study clearly shows that there is no consensus about probability translations and that attempts to codify word-number-pairs come too early. For such general purposes, the present study helps to distinguish between similarly versus inconsistently rated expressions instead.

Suggested Citation

  • Michael Theil, 2002. "The role of translations of verbal into numerical probability expressions in risk management: a meta-analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 5(2), pages 177-186, April.
    • Handle: RePEc:taf:jriskr:v:5:y:2002:i:2:p:177-186
    DOI: 10.1080/13669870110038179
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    Citations

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    Cited by:

    1. Marie Juanchich & Karl Halvor Teigen & Am'elie Gourdon, 2013. "Top scores are possible, bottom scores are certain (and middle scores are not worth mentioning): A pragmatic view of verbal probabilities," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 8(3), pages 345-364, May.
    2. Teigen, Karl Halvor & Juanchich, Marie & Løhre, Erik, 2022. "What is a “likely” amount? Representative (modal) values are considered likely even when their probabilities are low," Organizational Behavior and Human Decision Processes, Elsevier, vol. 171(C).
    3. Fischer, Caroline, 2018. "Beraten statt archivieren. Wie öffentlich Beschäftigte ihr Wissen am Arbeitsplatz teilen," OSF Preprints gx6d3, Center for Open Science.
    4. Robert N. Collins & David R. Mandel, 2019. "Cultivating credibility with probability words and numbers," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(6), pages 683-695, November.
    5. Ahti Salo & Edoardo Tosoni & Juho Roponen & Derek W. Bunn, 2022. "Using cross‐impact analysis for probabilistic risk assessment," Futures & Foresight Science, John Wiley & Sons, vol. 4(2), June.
    6. Riege, Anine H. & Teigen, Karl Halvor, 2013. "Additivity neglect in probability estimates: Effects of numeracy and response format," Organizational Behavior and Human Decision Processes, Elsevier, vol. 121(1), pages 41-52.
    7. repec:cup:judgdm:v:8:y:2013:i:3:p:345-364 is not listed on IDEAS
    8. Boman, Mattias, 2009. "To pay or not to pay for biodiversity in forests - What scale determines responses to willingness to pay questions with uncertain response options?," Journal of Forest Economics, Elsevier, vol. 15(1-2), pages 79-91, January.
    9. Vivianne H. M. Visschers & Ree M. Meertens & Wim W. F. Passchier & Nanne N. K. De Vries, 2009. "Probability Information in Risk Communication: A Review of the Research Literature," Risk Analysis, John Wiley & Sons, vol. 29(2), pages 267-287, February.
    10. repec:cup:judgdm:v:14:y:2019:i:6:p:683-695 is not listed on IDEAS

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