Understanding the complexity of project team member selection through agent-based modeling

•This study utilizes computational modeling to understand the complexity of project team selection.•Three project team selection orientations were compared through developed model.•Real data for model validation was collected from 116 construction projects for the period from 2009 to 2011.•The simulation results provided valuable references to decision makers for team selection.

Previous research has recognized the significance of a team's work capacity and suggested the selection of team members based on individual skills and performance in alignment with task characteristics. However, work teams are complex systems with interdependence between workers and the social environment, and exhibit surprising, nonlinear behavior. This study utilizes Agent-Based Modeling (ABM) to understand the complexity of project team member selection and to examine how the functional diversity of teams and worker interdependence affect team performance in different economic conditions. Data for model validation was collected from 116 construction projects for the period from 2009 to 2011. The results show that teams with higher functional diversity can enhance the overall firm performance when the economy is in a downturn. This study suggests managers using knowledge of worker interdependence to protect higher-performing workers by minimizing disruption of interdependence in team member selection for improving firm performance.