Group Discussions Improve Competence Calibration: Making Self-Perceived Competence Valuable When Harnessing the Wisdom of Crowds

Goedde-Menke, Michael; Diecidue, Enrico; Jacobs, Andreas; Langer, Thomas

Research article (journal) | Peer reviewed

Abstract

This paper experimentally demonstrates that group discussions can serve as an instrument to improve competence calibration, which in turn allows getting more wisdom out of the crowd through competence weighting. While the alignment of individuals’ estimation accuracy and self-perceived competence is typically poor and competence-weighted aggregates do not even match the accuracy of simple averaging, we find that preceding group discussions on unrelated judgment problems enhance competence calibration. Consequently, the subsequent performance of competence-weighted aggregation schemes raises to and beyond prediction market levels, suggesting an easy-to-implement approach for effectively exploiting crowd wisdom.

Details about the publication

JournalManagement Science
Volumeforthcoming
Statusaccepted / in press (not yet published)
Release year2025 (24/10/2025)
Language in which the publication is writtenEnglish
DOI10.1287/mnsc.2022.03061
Keywordsestimation accuracy; wisdom of the crowd; calibration; competence weighting; prediction markets

Authors from the University of Münster

Goedde-Menke, Michael
Chair of Finance (Prof. Langer)
Langer, Thomas
Chair of Finance