Date of Completion


Embargo Period



multi-team systems, dynamic centrality, distributed situational awareness, resilience, coordination, cohesion, dynamic equilibrium, CATA, sociometric badge, event system theory

Major Advisor

Dr. John Mathieu

Associate Advisor

Dr. Lucy Gilson

Associate Advisor

Dr. Travis Grosser

Associate Advisor

Dr. Andrew Hill

Field of Study

Business Administration


Doctor of Philosophy

Open Access

Campus Access


My study used a multi-method approach toward generating an understanding of how complex systems adapt effectively to dynamic environmental challenges. I synthesized events systems theory with multi-dimensional network approaches to model how multi-team systems (MTSs) respond to, and manage, environmental challenges. I sampled three different MTSs who engage in ten-day 24-hour exercises that mimic real-life operations in Army Tactical Operations Centers (TOCs). I employed qualitative research techniques including semi-structured interviews and observations with the first two samples to identify critical variances and processes, and to develop appropriate measures and indices, respectively. Based on these insights, I gathered subject matter experts’ observations, and a vast array of digital traces that captured all interactions throughout the system for the entire duration of the exercise. These indices were used to longitudinally model environmental challenges and system adaptation in the form of dynamic network properties, as related to the effectiveness of both subunits and the overall system. Specifically, environmental events constituted the level of analysis of my design and were time-dependent longitudinal measures at both the component team and MTS levels of analysis. In each case, there were event parameters (antecedents) and outcomes (effectiveness indices). Component team features (e.g., cohesion and coordination) were nested in MTS emergent states (MTS resiliency and distributed situation awareness) and network configurations (adaptive processes). The frequency and variety of events, the ten-day 24-hour timeframe, and the magnitudes of effects within- and between-teams, and over time, afforded sufficient power to test my hypotheses. Testing hypothesized relationships at the system and team level produced cautionary results, which underscores the complexity of dynamic network research. However, event duration enhanced MTS resiliency while overlapping events detracted from it, indicating that given time and non-competing priorities, system resiliency was bolstered. As the criticality of events increased, distributed situational awareness suffered, which indicates the teams may resort to automatic information processing and internal processes at the detriment of between team collaboration. Similarly, system level coordination in response to events negatively impacted team performance, indicating that consequence management efforts at the MTS level detracted from team proximal goals.