Date of Award
Master of Science in Engineering Management
Department of Systems Engineering and Management
Amy M. Cox, PhD
Nearly one third of the Air Force acquisition system’s large programs are over cost and half are over budget; performance must improve. This research applies a systems perspective to this challenge and frames the acquisition system as a complex system of systems. It is a system composed of people in multiple organizations; organizations interacting with one another to develop, acquire and sustain weapon programs. The system’s performance is an emergent behavior of its components (people), structure and processes. Communication networks are a view of a system’s structure, revealing the flows and interactions between components (people) as the system accomplishes its functions. Literature demonstrates that these networks are key to the effective performance of various system functions (ex. innovation). Further, established methods in organization behavior literature allow for characterization of these networks. Yet, limits to existing methods reduce their utility. This research validates a method to characterize communication networks within large technical organizations. This research compares communication network mapping with two separate data sources: interviews (existing) and archival e-mail log files (new). Ego-centric networks for five volunteers are characterized with both data sources and compared via case study methods. This research makes three contributions. First, it demonstrates the effect of archival data inclusion on the observed network completeness. Second, it compares the content of the networks observed with both data sources. Third, it compares established network measures obtained with both data sources. Future research can leverage this method validation to explore the use of e-mail-based network characterization to improve organizational performance.
Flaxington, Taylor F., "Preliminary Study of Communication Network Characterization Towards Improved Organizational Behavior" (2020). Theses and Dissertations. 3235.