The Effect of Emergent Team Roles on Team Performance: A Computational Network Model

Shairoz A. Evegroen, Yagel Schoonderbeek, Jan Treur*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Abstract

Much research has been done into the role of different team members through team problem-solving processes, though less research has been done into an optimal combination of members and the influence of their dominance on the team's performance. Therefore, in this paper it is addressed what is the most effective combination of team members and whether dominance can increase team performance. For this purpose, an adaptive computational network model has been designed for a problem-solving team process. Different scenarios were simulated including a respectively homogeneous team and the representation of different dominant roles carried out by several team members. From these simulations, it can be concluded that heterogeneous teams perform better than homogeneous teams. Additionally, this study's results showed that dominance can have both negative and positive effects on team performance. Moreover, the results suggest that in particular, only dominance by the procedural facilitator-role delivers these positive effects.
Original languageEnglish
Title of host publicationComputational Collective Intelligence
Subtitle of host publication13th International Conference, ICCCI 2021, Rhodos, Greece, September 29 – October 1, 2021, Proceedings
EditorsNgoc T. Nguyen, L. Iliadis, I. Maglogiannis, B. Trawiński
PublisherSpringer Nature Switzerland AG
Pages111-125
Number of pages15
ISBN (Electronic)9783030880811
ISBN (Print)9783030880804
DOIs
Publication statusPublished - Nov 2021
Event13th International Conference on Computational Collective Intelligence, ICCCI 2021 - Virtual, Online
Duration: 29 Sep 20211 Oct 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12876 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Computational Collective Intelligence, ICCCI 2021
CityVirtual, Online
Period29/09/211/10/21

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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