Optimizing multi-team system behaviors: Insights from modeling team communication

To better manage behavioral operations in project management, we demonstrate the value of quantitative model-based approaches in examining behaviors and generating insights for managerial research and practice. We focus on organizational members' behaviors and interactions on large-scale projects using multi-team systems (MTS). While MTS invoke different behaviors than simpler team systems, research insights have lagged on MTS due to the complexity and resource intensity of capturing the multitude of behaviors and interactions by human subjects in real-world situations. Thus, MTS provides an apt context to demonstrate the mechanics of mathematically modeling human behavior and conducting virtual experiments via mixed-integer linear optimization to understand the way to meet operational objectives. Virtual experimentation is used to explore communication behaviors that unfold under different levels of project complexity and interdependence when time, cost, and quality operational objectives are considered independently or collectively. The results suggest that the type of communication plan set by project managers needs to change according to project attributes and objectives (maximize quality, minimize cost or minimize time). Moreover, this paper demonstrates the benefits of using operations research methods to assess behavioral patterns in an operational setting and establish propositions for targeted research in the field. In conclusion, benefits and limitations are put forth about the way Behavioral OR expands the traditional toolkit of human subject researchers in operations and beyond.