In Case of Emergency, Don’t Break Glass: The Emergency Management Organizational Field as a Glassy Regime
- Author(s): Phillips, Nolan Edward;
- Advisor(s): Butts, Carter T;
- et al.
The way that relations between organizations and their environments affect their structures important features of organizations. These relations can potentially induce conformity, and their environments can potentially maintain differences. Organizations dependent on a leading organization for resources are theorized to structure themselves more like the leading organization. Conversely, organizations that function in divergent social contexts are expected to structure themselves divergently. While social network analyses have offered insights into this domain, previous work typically compares organizational structures and not the mechanisms that generate them. The advent of exponential family random graph models enables the examination of the underlying mechanisms, or social forces, that produce networks such as organizational structures. However, the tools to evaluate the adequacy or assess the fit of these models have opened up new questions regarding model evaluation and adequacy assessment. The first chapter of this dissertation introduces several new methods for evaluating the adequacy of exponential random graph models using labeled rather than topological features. The second chapter advances a within-sample model validation algorithm to assess the fit of a model. These tools were used to develop exponential random graph models that are used in the third chapter, which analyzes the generative features of states’ emergency operations plans. I build a new dataset from primary source documents that delineate the organizations assigned to a standardized set of emergency support functions. I then evaluate the historical contingency of the realized emergency management networks within each state through simulation studies. These studies build upon previous work and facilitate a virtual "rerunning of history" to assess whether states form similar networks due to exogenous pressures from the federal government or whether the social substrate within each state drives observable differences. From these analyses, I postulate an interorganizational continuum that is analogous to the physical states of matter to explain the observed differences and similarities. As such, this dissertation makes several valuable contributions to both the network analytic methodology and theories of interorganizational relations.