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  6. Convergence to consensus in heterogeneous groups and the emergence of informal leadership
Details

Convergence to consensus in heterogeneous groups and the emergence of informal leadership

Date Issued
July 14, 2016
Author(s)
Gavrilets, Sergey  
Auerbach, Jeremy David  
van Vugt, Mark
DOI
10.1038/srep29704
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/17043
Abstract

When group cohesion is essential, groups must have efficient strategies in place for consensus decisionmaking. Recent theoretical work suggests that shared decision-making is often the most efficient way for dealing with both information uncertainty and individual variation in preferences. However, some animal and most human groups make collective decisions through particular individuals, leaders, that have a disproportionate influence on group decision-making. To address this discrepancy between theory and data, we study a simple, but general, model that explicitly focuses on the dynamics of consensus building in groups composed by individuals who are heterogeneous in preferences, certain personality traits (agreeability and persuasiveness), reputation, and social networks. We show that within-group heterogeneity can significantly delay democratic consensus building as well as give rise to the emergence of informal leaders, i.e. individuals with a disproportionately large impact on group decisions. Our results thus imply strong benefits of leadership particularly when groups experience time pressure and significant conflict of interest between members (due to various between-individual differences). Overall, our models shed light on why leadership and decision-making hierarchies are widespread, especially in human groups.

Subjects

leadership

decision-making

group dynamics

behavioral evolution

mathematical modeling...

Disciplines
Anthropology
Applied Mathematics
Behavior and Ethology
Social Psychology
Submission Type
Publisher's Version
File(s)
Thumbnail Image
Name

leader.pdf

Size

605.5 KB

Format

Adobe PDF

Checksum (MD5)

f7b545db8278db77be613c80b3b0bdf1


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