Urban regime theory has been the predominant approach used to describe how the membership structure of collaborative decision-making networks directly impact how the network behaves, particularly in selecting policies. However, it provides a limited explanation for how the membership structure of the collaborative matters for policy. I argue that there are three network-level properties (total number of central actors, actor homogeneity, and network size) that shape the context under which individual actors are capable of exerting influence and directing development policy toward their own goals. The total number of actors measure is applied to examine the distribution of power and influence. The level of actor homogeneity and network size indicate the range of organizations and policy interests that are present within the network and must be overcome by central actors. The purpose of the dissertation is to move beyond descriptions of "who governs" by establishing a conceptual framework that offers a more complete explanation of the relationship between network structure and behavior. By developing more detailed descriptions of the governance structures, scholars can formulate more solid and testable predictions about the policies used by structurally distinct decision-making networks. This framework was tested using a sample of small to large American cities (n = 523) that responded to the 2004 International City/County Management Association's Economic Development Survey. A three-part quantitative analysis was conducted. Hierarchical cluster analysis was employed to empirically identify structurally distinct local economic development decision-making networks. Descriptive statistical tests were used to construct structural profiles for each decision-making network. Based on the composition of the networks, hypotheses regarding policy use were developed. Several binomial logistic regression models were estimated to test the effect of network structure on the likelihood of cities using several different development policies. This statistical method was also utilized to explore the effect of several social, economic, political, and geographic variables on the type of decision-making network that exists in a city. Three structurally distinct local economic development decision-making networks were identified: municipal, local government-chambers of commerce, and broad public-private partnerships. Decision-making network type was a significant predictor of how likely cities were to use several different policies: community development corporations, microenterprise programs, nongovernmental organization partnerships, other local government partnerships, tax abatements, and one-stop permit issuance.
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