Task dynamics in self-organising task groups: Expertise, motivational, and performance differences of specialists and generalists

Kees Zoethout*, Wander Jager, Eric Molleman

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

9 Citaten (Scopus)

Samenvatting

Multi-agent simulation is applied to explore how different types of task variety cause workgroups to change their task allocation accordingly. We studied two groups, generalists and specialists. We hypothesised that the performance of the specialists would decrease when task variety increases. The generalists, on the other hand, would perform better in a high task variety condition. The results show that these hypotheses were only partly supported because both learning and motivational effects changed the task allocation process in a much more complex way. We conclude that although no task variety leads to specialisation and high task variety leads to generalisation, in general, performance is better when task variety is low. Further, in case of no task variety, specialists outperform generalists. In case of moderate variety the opposite is true. With high task variety, since there is no space for any expertise and motivational development, the behaviour of specialists and generalists becomes more similar, and, consequently also their performance.

Originele taal-2English
Pagina's (van-tot)75-94
Aantal pagina's20
TijdschriftAutonomous Agents and Multi-Agent Systems
Volume16
Nummer van het tijdschrift1
DOI's
StatusPublished - feb.-2008

Vingerafdruk

Duik in de onderzoeksthema's van 'Task dynamics in self-organising task groups: Expertise, motivational, and performance differences of specialists and generalists'. Samen vormen ze een unieke vingerafdruk.

Citeer dit