IDEAS home Printed from https://ideas.repec.org/a/taf/jriskr/v15y2012i7p717-735.html
   My bibliography  Save this article

Making sense of uncertainty: advantages and disadvantages of providing an evaluative structure

Author

Listed:
  • Nathan F. Dieckmann
  • Ellen Peters
  • Robin Gregory
  • Martin Tusler

Abstract

In many decision contexts, there is uncertainty in the assessed probabilities and expected consequences of different actions. The fundamental goal for information providers is to present uncertainty in a way that is not overly complicated, yet sufficiently detailed to prompt decision-makers to think about the implications of this uncertainty for the decision at hand. In two experiments, we assess the pros and cons of providing an evaluative structure to facilitate the comprehension and use of uncertainty information and explore whether people who vary in numeracy perceive and use uncertainty in different ways. Participants were presented with scenarios and summary tables describing the anticipated consequences of different environmental-management actions. Our results suggest that different uncertainty formats may lead people to think in particular ways. Laypeople had an easier time understanding the general concept of uncertainty when an evaluative label was presented (e.g. uncertainty is High or Low). However, when asked about a specific possible outcome for an attribute, participants performed better when presented with numerical ranges. Our results also suggest that there appear to be advantages to using evaluative labels, in that they can highlight aspects of uncertainty information that may otherwise be overlooked in more complex numerical displays. However, the salience of evaluative labels appeared to cause some participants to put undue weight on this information, which resulted in value-inconsistent choices. The simplicity and power of providing an evaluative structure is a double-edged sword.

Suggested Citation

  • Nathan F. Dieckmann & Ellen Peters & Robin Gregory & Martin Tusler, 2012. "Making sense of uncertainty: advantages and disadvantages of providing an evaluative structure," Journal of Risk Research, Taylor & Francis Journals, vol. 15(7), pages 717-735, August.
  • Handle: RePEc:taf:jriskr:v:15:y:2012:i:7:p:717-735
    DOI: 10.1080/13669877.2012.666760
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13669877.2012.666760
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13669877.2012.666760?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andrea D. Gurmankin & Jonathan Baron & Katrina Armstrong, 2004. "The Effect of Numerical Statements of Risk on Trust and Comfort with Hypothetical Physician Risk Communication," Medical Decision Making, , vol. 24(3), pages 265-271, June.
    2. Ralph L. Keeney, 1982. "Feature Article—Decision Analysis: An Overview," Operations Research, INFORMS, vol. 30(5), pages 803-838, October.
    3. Nathan F. Dieckmann & Paul Slovic & Ellen M. Peters, 2009. "The Use of Narrative Evidence and Explicit Likelihood by Decisionmakers Varying in Numeracy," Risk Analysis, John Wiley & Sons, vol. 29(10), pages 1473-1488, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Robin Gregory & Nathan Dieckmann & Ellen Peters & Lee Failing & Graham Long & Martin Tusler, 2012. "Deliberative Disjunction: Expert and Public Understanding of Outcome Uncertainty," Risk Analysis, John Wiley & Sons, vol. 32(12), pages 2071-2083, December.
    2. Karl Halvor Teigen & Erik Løhre & Sigrid Møyner Hohle, 2018. "The boundary effect: Perceived post hoc accuracy of prediction intervals," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(4), pages 309-321, July.
    3. Takashi Ishida & Atsushi Maruyama & Shinichi Kurihara, 2022. "Risk Communication under Conflicting Information: The Role of Confidence in Subjective Risk Assessment," Journal of Food Research, Canadian Center of Science and Education, vol. 11(1), pages 1-1, January.
    4. Nathan F. Dieckmann & Ellen Peters & Robin Gregory, 2015. "At Home on the Range? Lay Interpretations of Numerical Uncertainty Ranges," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1281-1295, July.
    5. repec:cup:judgdm:v:13:y:2018:i:4:p:309-321 is not listed on IDEAS
    6. Robin Gregory & Ralph L. Keeney, 2017. "A Practical Approach to Address Uncertainty in Stakeholder Deliberations," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 487-501, March.
    7. Nathan F. Dieckmann & Robin Gregory & Ellen Peters & Robert Hartman, 2017. "Seeing What You Want to See: How Imprecise Uncertainty Ranges Enhance Motivated Reasoning," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 471-486, March.
    8. A. Berhaupt-Glickstein & W. K. Hallman, 2021. "An Investigation of the Contested Qualified Health Claims for Green Tea and Cancer," Journal of Consumer Policy, Springer, vol. 44(2), pages 259-277, June.
    9. Vivianne H.M. Visschers, 2017. "Judgments under uncertainty: evaluations of univocal, ambiguous and conflicting probability information," Journal of Risk Research, Taylor & Francis Journals, vol. 20(2), pages 237-255, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robin Gregory & Nathan Dieckmann & Ellen Peters & Lee Failing & Graham Long & Martin Tusler, 2012. "Deliberative Disjunction: Expert and Public Understanding of Outcome Uncertainty," Risk Analysis, John Wiley & Sons, vol. 32(12), pages 2071-2083, December.
    2. repec:cup:judgdm:v:4:y:2009:i:1:p:34-40 is not listed on IDEAS
    3. Yaniv Hanoch & Talya Miron-Shatz & Mary Himmelstein, 2010. "Genetic testing and risk interpretation: How do women understand lifetime risk results?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 5(2), pages 116-123, April.
    4. Nathan F. Dieckmann & Ellen Peters & Robin Gregory, 2015. "At Home on the Range? Lay Interpretations of Numerical Uncertainty Ranges," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1281-1295, July.
    5. Taillandier, F. & Sauce, G. & Bonetto, R., 2009. "Risk-based investment trade-off related to building facility management," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 785-795.
    6. Carland, Corinne & Goentzel, Jarrod & Montibeller, Gilberto, 2018. "Modeling the values of private sector agents in multi-echelon humanitarian supply chains," European Journal of Operational Research, Elsevier, vol. 269(2), pages 532-543.
    7. Fernández, Eduardo & Figueira, José Rui & Navarro, Jorge & Solares, Efrain, 2022. "Handling imperfect information in multiple criteria decision-making through a comprehensive interval outranking approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    8. Robert F. Bordley, 2023. "Lessons for Decision-Analysis Practice from the Automotive Industry," Interfaces, INFORMS, vol. 53(3), pages 240-246, May.
    9. William J. Burns & Ellen Peters & Paul Slovic, 2012. "Risk Perception and the Economic Crisis: A Longitudinal Study of the Trajectory of Perceived Risk," Risk Analysis, John Wiley & Sons, vol. 32(4), pages 659-677, April.
    10. Sironen, Susanna & Primmer, Eeva & Leskinen, Pekka & Similä, Jukka & Punttila, Pekka, 2020. "Context sensitive policy instruments: A multi-criteria decision analysis for safeguarding forest habitats in Southwestern Finland," Land Use Policy, Elsevier, vol. 92(C).
    11. Emilio Cerdá & Sonia Quiroga Gómez, 2009. "Economic Value of Weather Forecasting Systems Information: A Risk Aversion Approach," Working Papers 2009-04, FEDEA.
    12. Brandon Garrett & Gregory Mitchell, 2013. "How Jurors Evaluate Fingerprint Evidence: The Relative Importance of Match Language, Method Information, and Error Acknowledgment," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 10(3), pages 484-511, September.
    13. Paredes-Frigolett, Harold & Pyka, Andreas & Leoneti, Alexandre Bevilacqua, 2021. "On the performance and strategy of innovation systems: A multicriteria group decision analysis approach," Technology in Society, Elsevier, vol. 67(C).
    14. Tim H¨ofer & Rüdiger von Nitzsch & Reinhard Madlener, 2020. "Using Value-Focused Thinking and Multicriteria Decision Making to Evaluate Energy Transition Alternatives," Decision Analysis, INFORMS, vol. 17(4), pages 330-355, December.
    15. Rajshekhar G. Javalgi & Hemant K. Jain, 1988. "Integrating multiple criteria decision making models into the decision support system framework for marketing decisions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(6), pages 575-596, December.
    16. Mónica D. Oliveira & Inês Mataloto & Panos Kanavos, 2019. "Multi-criteria decision analysis for health technology assessment: addressing methodological challenges to improve the state of the art," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(6), pages 891-918, August.
    17. Jun Yao & Harmen Oppewal & Di Wang, 2020. "Cheaper and smaller or more expensive and larger: how consumers respond to unit price increase tactics that simultaneously change product price and package size," Journal of the Academy of Marketing Science, Springer, vol. 48(6), pages 1075-1094, November.
    18. Höfer, Tim & Madlener, Reinhard, 2020. "A participatory stakeholder process for evaluating sustainable energy transition scenarios," Energy Policy, Elsevier, vol. 139(C).
    19. Maria Giuffrida & Riccardo Mangiaracina & Umar Burki, 2021. "Cloud-Based Booking Platforms in Warehouse Operations," Sustainability, MDPI, vol. 13(20), pages 1-16, October.
    20. Isaac M. Lipkus & Ellen Peters & Gretchen Kimmick & Vlayka Liotcheva & Paul Marcom, 2010. "Breast Cancer Patients’ Treatment Expectations after Exposure to the Decision Aid Program Adjuvant Online: The Influence of Numeracy," Medical Decision Making, , vol. 30(4), pages 464-473, July.
    21. Yaniv Hanoch & Jonathan Rolison & Alexandra M. Freund, 2019. "Reaping the Benefits and Avoiding the Risks: Unrealistic Optimism in the Health Domain," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 792-804, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jriskr:v:15:y:2012:i:7:p:717-735. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RJRR20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.