Member variation, recognition of expertise, and group performance.
Abstract
The most effective method for aggregating the conflicting opinions of experts is a subject of active debate in the literature. Task differences are most often used to explain differing results among studies. Alternatively, we suggested that the characteristics of the interacting groups themselves determine whether they outperform or underperform their equivalent composites. Expert loan officers serving in ad hoc and practiced groups, on average, performed equally as well as did their composite and most influential individual. However, whether a particular group outperformed or underperformed its composite could be explained by variation in group members' performances and abilities to recognize differential expertise. These findings suggest the circumstances in which alternative social decision schemes are likely to be more effective. They also support the usefulness of conceptualizing group judgment as a weighted combination of the opinions of group members whereby the allocation of weights to members is the critical issue.
Cited by (3)
- Recognizing and Utilizing Expertise in Work Groups: A Status Characteristics PerspectiveBunderson, J. Stuart · 2003 · Administrative Science Quarterly
- Impact of highly and less job-related diversity on work group cohesion and performance: a meta-analysisWebber, Sheila Simsarian, Donahue, Lisa M. · 2001 · Journal of Management
- Something(s) old and something(s) new: Modeling drivers of global virtual team effectivenessMaynard, M. Travis, Mathieu, John E., Rapp, Tammy L., Gilson, Lucy L. · 2012 · Journal of Organizational Behavior
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Member variation, recognition of expertise, and group performance. https://app.cochat.ai/papers/10.1037//0021-9010.72.1.81
- The paper
- Libby, R., Trotman, K. T., & Zimmer, I. (1987). Member variation, recognition of expertise, and group performance. Journal of Applied Psychology. https://doi.org/10.1037//0021-9010.72.1.81
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.