Institute for Software Research
School of Computer Science, Carnegie Mellon University
Human and Organizational Risk Modeling:
This thesis advances the study of critical personnel risks in network organizations by using Dynamic Network Analysis. Dynamic Network analysis is a methodology that incorporates both social network analysis and multi-agent simulation to represent structure and process the evolutionary nature of network organizations. Advances are made on two fronts. First, theory is developed about three dynamic risks related to critical personnel: intermittent availability, individual redundancy and shifts of critical personnel. These theories are built by using a reasoned computational approach that first validates the multi-agent simulation model and then creates forward grounded theory. Empirical data from two different network organizations are used to validate the model and build theory.
Second, the foundations for a Dynamic Network Analytic Theory of Network Organization Leadership are established. Leadership is a subset of critical personnel and the specific risks of network organization leadership need studied as well. But traditional leadership theory has limited applicability to high velocity contexts and network organizations. Consequently, there has been a call for a paradigm shift in leadership theory. The effective study of risks associated with network organization leadership will require a relevant paradigm and theory. This research developed a relevant paradigmatic framework and provided basic insight for a theory of network organization leadership.