The public sector has undergone extensive changes in recent years following the implementation of New Public Management. Studies on the subject are still retained in previous grounds made in other circumstantial prerequisites. Therefore, this study aims to increase the understanding of decision processes in public authorities to provide a nuanced picture of the phenomenon and further complement the established literature on decision-making theory. In doing so, we answer the question of how and why and it is decided which educational course an employee at a Swedish governmental agency attends.Through the use of a snowball sample approach, we reversed tracked the decision process and examined the underlying incentives of the process. By using both interviews with identified relevant actors in combination with related documents, we achieved a triangulation effect of our data. The results demonstrated a variety of applicable approaches to the decision made by the different actors throughout the decision process in their contextually dependent circumstances. Moreover, the results indicate that previous decision-making literature is insufficient on its own. Instead, we claim that a broad understanding is required to grasp decision-making behavior and advocate for a combinatorial and holistic approach which adhere to the varying decision-making behavior.

Master of Science / Department of Landscape Architecture, Regional and Community Planning / Stephanie Rolley / The City of Emerado, North Dakota, population 414, located in northeast North Dakota is the subject of a Social Network Analysis (SNA), conducted prior to it being the subject of a University of North Dakota Center for Community Engagement, Community Connect Forum. The SNA was developed based on the results of 25 interviews conducted with local residents, elected officials and business owners, using snowball sampling and following grounded theory methods. The interview results were coded and memos were written to aid in the analysis. Social Network data was entered into the Sentinel Visualizer software (FMS Advanced Systems Group) to develop a visual image of the network, including nodes (people, organizations or businesses) and links to illustrate the relationships between nodes. The SNA helps to frame the relationships in terms of bridging and bonding social capital. The SNA provides the ability to mathematically determine the most important nodes to the community social network, using calculations to determine levels of degree centrality, betweenness centrality, closeness centrality, Eigenvalue, and network density. After calculating these elements, categorical descriptions of the top ten individuals for each category are provided. The networks of five individuals are reviewed in depth to aid in comprehending the process of incrementally expanding networks.