Public Service-Function Types and Interlocal Agreement Network Structure

A Longitudinal Study of Iowa

Victor G. Hugg (University of Illinois at Chicago)

Faced with enduring partisan gridlock and ever-tightening financial constraints, public administrators are increasingly turning to cooperative arrangements with local institutions and organizations to provide public goods and services. Over time, networks of governance have emerged from an assortment of both formal and informal agreements. Recognizing the prevalence of these collaborative efforts, researchers have started to seriously examine these agreement networks in a bid to understand the factors the predict interlocal collaboration.

In my Urban Affairs Review research note, I find that there is a distinction to be made between collaborations aimed at providing system maintenance services (e.g., streets and roads; public transit; and water systems) and collaborations that provide lifestyle services (e.g., parks and recreation; education; and public housing). Over time, organizations that decide to join an interlocal agreement are more inclined to do so for system maintenance services relative to lifestyle services and prefer to form relationships with already-connected, central participants.

Augmenting our knowledge of the relationships between the structure and composition of different public service networks would allow us to better explain why local governments decide to cooperate with one another, nonprofit organizations, and private actors. Further, understanding the associations between service-function type and network structure is of interest to scholars and public officials alike because of the potentially-important practical implications a hypothesized connection between network structure and improved performance might have. If, all else equal, certain network structures lead to more optimal public service outcomes, policymakers would be intent on examining any factor that could be predictive of network structure.

The nascent governance network literature includes several studies that consider the role service-function type plays in the decision-making process for joining an interlocal service network. However, these analyses are rather narrow in scope: they usually examine a single service type within an individual metropolitan region, rely on survey data composed of small sample sizes that omit non-governmental organizations, or only observe a single point in time. My analysis replicates and extends the empirical findings of prior work by incorporating an array of both governmental and nongovernmental organizations providing 17 service-functions (allowing for comparisons between different public service-function networks) across the entire state of Iowa (improving geographic generalizability) over 25 years (enabling inferences about relationships over time).

Given that my study finds a relationship between service-function type and network structure, an obvious next step for future research to take would be to investigate the effects that governance network structures have on policy outcomes, controlling for the characteristics of participant governments and the demographics of those living within those governments' jurisdictions. Although public administration network scholars have made initial advances toward understanding network performance, the subject remains a centrally unanswered question in the field. If structure is found to affect outcomes, this work could have important normative implications by establishing the groundwork for studies that ultimately connect network composition and structure to the performance of collaborations within a specific policy or service area.

Read the UAR article here.


Victor G. Hugg received his PhD from the Department of Public Administration at the University of Illinois at Chicago in 2020. He holds a Master's Degree in political science from the University of Illinois at Urbana-Champaign. His research primarily focuses on intergovernmental management and collaborative governance, with an emphasis on understanding network formation and performance.

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