DEVS simulation of Belbin's team roles for collaborative team dynamics

Other authors

Universitat Politècnica de Catalunya. Departament de Ciències de la Computació

Universitat Politècnica de Catalunya. ALBCOM - Algorísmia, Bioinformàtica, Complexitat i Mètodes Formals

Publication date

2025



Abstract

Belbin's team role theory identifies nine behavioral roles that, when combined, support effective collaboration. Configuring teams based on these roles is often manual, costly, and inflexible. This article presents an individual-oriented simulation model using the DEVS formalism to emulate group interactions shaped by Belbin roles. Each team member is modeled as an atomic entity with behavior defined by a combination of two roles. This enables controlled experimentation with different team compositions, interaction timings, and communication sequences. Simulations were conducted using synthetic data, defined under plausible assumptions based on Belbin's framework. The model enables exploration of how different configurations affect communication flow and task distribution, supporting the identification of team structures that promote balance and efficiency. Results demonstrate the potential of integrating behavioral theories with formal modeling approaches to improve team design. This work offers a flexible and extensible simulation-based method for analyzing and optimizing team dynamics.


This research was partially supported by the Fondecyt de Iniciación grant No. 11230961 from ANID, Chile; by the Natural Sciences and Engineering Research Council of Canada (NSERC); and by the Escuela de Ingeniería Informática, Universidad de Valparaíso, Chile, through the REXE grant No. 4054/2022. Diego Monsalves acknowledges support from the National Doctoral Scholarship of ANID, Chile, exempt resolution No. 4402/2023.


Peer Reviewed


Postprint (author's final draft)

Document Type

Conference report

Language

English

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Related items

https://ieeexplore.ieee.org/abstract/document/11338914

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Open Access

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E-prints [72263]