The Effect of Group Level Factors on Affective Convergence in Teams: An agent Based Model.

摘要

Previous research supports the idea that affective convergence occurs in teams The phenomenon of group affect has been well documented, however the group level conditions through which affective convergence emerges has received very little research. The current study helps to fill this gap by using agent-based modeling to examine affective convergence under varying group conditions. Agent-based modeling is a recently developed approach to research that uses the power of computers to model individual level behaviors and examine group level emergent constructs. The current study examined display rule presence, display rule breadth, social influence, interdependence, and team size on affective convergence. Results demonstrate support for the influence of group level factors on the latency and variance of affective convergence. Latency of affective convergence was shortest for small teams; teams with greater interdependence; teams with strong social influence; teams with no display rules; and teams with narrow display rules. Variance in team affect over time was influenced by interdependence, social influence processes and team size. Limitations, contributions and future research are discussed.