Affiliation:
1. Sloan School of Management Massachusetts Institute of Technology
2. Department of Computer Science Purdue University
3. Department of Computer and Information Science University of Pennsylvania
4. The Annenberg School of Communication University of Pennsylvania
5. Operations, Information, and Decisions Department University of Pennsylvania
Abstract
AbstractAs 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.
Funder
Alfred P. Sloan Foundation
Subject
Artificial Intelligence,Cognitive Neuroscience,Human-Computer Interaction,Linguistics and Language,Experimental and Cognitive Psychology
Cited by
2 articles.
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