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The Effects of Group Composition and Dynamics on Collective Performance.
- Source :
- Topics in Cognitive Science; Apr2024, Vol. 16 Issue 2, p302-321, 20p
- Publication Year :
- 2024
-
Abstract
- As organizations gravitate to group‐based structures, the problem of improving performance through judicious selection of group members has preoccupied scientists and managers alike. However, which individual attributes best predict group performance remains poorly understood. Here, we describe a preregistered experiment in which we simultaneously manipulated four widely studied attributes of group compositions: skill level, skill diversity, social perceptiveness, and cognitive style diversity. We find that while the average skill level of group members, skill diversity, and social perceptiveness are significant predictors of group performance, skill level dominates all other factors combined. Additionally, we explore the relationship between patterns of collaborative behavior and performance outcomes and find that any potential gains in solution quality from additional communication between the group members are outweighed by the overhead time cost, leading to lower overall efficiency. However, groups exhibiting more "turn‐taking" behavior are considerably faster and thus more efficient. Finally, contrary to our expectation, we find that group compositional factors (i.e., skill level and social perceptiveness) are not associated with the amount of communication between group members nor turn‐taking dynamics. In a pre‐registered experiment, we compare the effects of four widely studied attributes of group composition and find the group's average skill level, their skill diversity, and their social perceptiveness to be significant predictors of collective performance, with the predictive power of average skill level dominating other factors. [ABSTRACT FROM AUTHOR]
- Subjects :
- GROUP dynamics
COGNITIVE styles
SOCIAL skills
OVERHEAD costs
SWARM intelligence
Subjects
Details
- Language :
- English
- ISSN :
- 17568757
- Volume :
- 16
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Topics in Cognitive Science
- Publication Type :
- Academic Journal
- Accession number :
- 176535873
- Full Text :
- https://doi.org/10.1111/tops.12706