Social learning strategies modify the effect of network structure on group performance

Daniel Barkoczi () and Mirta Galesic
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Daniel Barkoczi: Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development
Mirta Galesic: Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development

Nature Communications, 2016, vol. 7, issue 1, 1-8

Abstract: Abstract The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.

Date: 2016
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DOI: 10.1038/ncomms13109

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