Toward a better understanding of team decision processes: combining laboratory experiments with agent-based modeling - Iris Lorscheid; Matthias Meyer (Journal of Business Economics, 2021)
Despite advances in the field, we still know little about the socio-cognitive processes of team decisions, particularly their emergence from an individual level and transition to a team level. This study investigates team decision processes by using an agent-based model to conceptualize team decisions as an emergent property. It uses a mixed-method research design with a laboratory experiment providing qualitative and quantitative input for the model's construction, as well as data for an output validation of the model. First, the laboratory experiment generates data about individual and team cognition structures. Then, the agent-based model is used as a computational testbed to contrast several processes of team decision making, representing potential, simplified mechanisms of how a team decision emerges. The increasing overall fit of the simulation and empirical results indicates that the modeled decision processes can at least partly explain the observed team decisions. Overall, we contribute to the current literature by presenting an innovative mixed-method approach that opens and exposes the black box of team decision processes beyond well-known static attributes.
Keywords: C63; C92; D71; D91; M10; 650; Agent-based modeling; Zero-intelligence agents; Team decision; Group processes; Cognition; Laboratory experiment