IDEAS home Printed from https://ideas.repec.org/a/inm/ordeca/v13y2016i2p128-152.html
   My bibliography  Save this article

Validating the Contribution-Weighted Model: Robustness and Cost-Benefit Analyses

Author

Listed:
  • Eva Chen

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • David V. Budescu

    (Department of Psychology, Fordham University, Bronx, New York 10458)

  • Shrinidhi K. Lakshmikanth

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Barbara A. Mellers

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Philip E. Tetlock

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

Abstract

We use results from a multiyear, geopolitical forecasting tournament to highlight the ability of the contribution weighted model [Budescu DV, Chen E (2015) Identifying expertise to extract the wisdom of crowds. Management Sci. 61(2):267–280] to capture and exploit expertise. We show that the model performs better when judges gain expertise from manipulations such as training in probabilistic reasoning and collaborative interaction from serving on teams. We document the model’s robustness using probability judgments from early, middle, and late phases of the forecasting period and by showing its strong performance in the presence of hypothetical malevolent forecasters. The model is highly cost-effective: it operates well, even with random attrition, as the number of judges shrinks and information on their past performance is reduced.

Suggested Citation

  • Eva Chen & David V. Budescu & Shrinidhi K. Lakshmikanth & Barbara A. Mellers & Philip E. Tetlock, 2016. "Validating the Contribution-Weighted Model: Robustness and Cost-Benefit Analyses," Decision Analysis, INFORMS, vol. 13(2), pages 128-152, June.
    • Handle: RePEc:inm:ordeca:v:13:y:2016:i:2:p:128-152
    DOI: 10.1287/deca.2016.0329
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/deca.2016.0329
    Download Restriction: no
    File URL: https://libkey.io/10.1287/deca.2016.0329?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
    ---><---

    Citations

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


    Cited by:

    1. David R. Mandel & Daniel Irwin, 2021. "Tracking accuracy of strategic intelligence forecasts: Findings from a long‐term Canadian study," Futures & Foresight Science, John Wiley & Sons, vol. 3(3-4), September.
    2. Patrick Afflerbach & Christopher Dun & Henner Gimpel & Dominik Parak & Johannes Seyfried, 2021. "A Simulation-Based Approach to Understanding the Wisdom of Crowds Phenomenon in Aggregating Expert Judgment," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 329-348, August.
    3. Yuyu Fan & David V. Budescu & David Mandel & Mark Himmelstein, 2019. "Improving Accuracy by Coherence Weighting of Direct and Ratio Probability Judgments," Decision Analysis, INFORMS, vol. 16(3), pages 197-217, September.
    4. Ying Han & David Budescu, 2019. "A universal method for evaluating the quality of aggregators," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(4), pages 395-411, July.
    5. Karvetski, Christopher W. & Meinel, Carolyn & Maxwell, Daniel T. & Lu, Yunzi & Mellers, Barbara A. & Tetlock, Philip E., 2022. "What do forecasting rationales reveal about thinking patterns of top geopolitical forecasters?," International Journal of Forecasting, Elsevier, vol. 38(2), pages 688-704.
    6. repec:cup:judgdm:v:14:y:2019:i:4:p:395-411 is not listed on IDEAS

    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:inm:ordeca:v:13:y:2016:i:2:p:128-152. 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.

    We have no bibliographic references for this item. You can help adding them by using 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.