A Decision Support System Including Feedback to Sensitize for Certainty Interval Size

  • Conference paper
  • First Online:
Operations Research Proceedings 2022 (OR 2022)

Part of the book series: Lecture Notes in Operations Research ((LNOR))

Included in the following conference series:

  • 435 Accesses

Abstract

In decision-making overconfidence and estimation biases can lead to sub-optimal outcomes and accuracy loss. A debiasing strategy presented in this work is to use feedback based on the error pattern of own previous absolute and 90% certainty (confidence) interval estimates. This is comprised in a decision support system (DSS) and applied in an experiment, where results indicate support for the key assumption that subjects are able to selectively reduce their overconfidence and their estimation bias, if present, with the help of the provided feedback.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 181.89
Price includes VAT (Germany)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
EUR 235.39
Price includes VAT (Germany)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Ancarani, A., Di Mauro, C., & D’Urso, D. (2016). Measuring overconfidence in inventory management decisions. Journal of Purchasing and Supply Management, 22(3), 171–180. https://doi.org/10.1016/j.pursup.2016.05.001.

    Article  Google Scholar 

  2. Klayman, J., Soll, J. B., Gonzalez-Vallejo, C., & Barlas, S. (1999). Overconfidence: It depends on How, What, and Whom you ask. Organizational Behavior and Human Decision Processes, 79(3), 216–247. https://doi.org/10.1006/obhd.1999.2847.

    Article  Google Scholar 

  3. Shipman, A. S., & Mumford, M. D. (2011). When confidence is detrimental: Influence of overconfidence on leadership effectiveness. The Leadership Quarterly, 22(4), 649–665. https://doi.org/10.1016/j.leaqua.2011.05.006.

    Article  Google Scholar 

  4. Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502–517. https://doi.org/10.1037/0033-295X.115.2.502.

    Article  Google Scholar 

  5. Ren, Y., & Croson, R. (2013). Overconfidence in newsvendor orders: An experimental study. Management Science, 59(11), 2502–2517. https://doi.org/10.1287/mnsc.2013.1715.

    Article  Google Scholar 

  6. Soll, J. B., & Klayman, J. (2004). Overconfidence in interval estimates. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(2), 299–314. https://doi.org/10.1037/0278-7393.30.2.299.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nathalie Balla .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Balla, N. (2023). A Decision Support System Including Feedback to Sensitize for Certainty Interval Size. In: Grothe, O., Nickel, S., Rebennack, S., Stein, O. (eds) Operations Research Proceedings 2022. OR 2022. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-24907-5_9

Download citation

Publish with us

Policies and ethics

Navigation