This dissertation examines the factors and combinations of factors that affect the performance of continuum of care homeless service networks, applying the configurational approach of contingency theory to data sets drawn from federal sources. The study accepts the two key assumptions from the theory: (1) that there are multiple paths to high performance and (2) key conditions have a joint influence on network performance. The data analysis in this study has two parts. The first employs OLS regression to examine the causal relationship between independent variables and the performance of permanent supportive housing (PSH) programs. This study also applies fuzzy set qualitative comparative analysis (fsQCA) to identify multiple combinations of factors that influence the performance of PSH programs. The results identify key factors and multiple combinations of factors that lead to high and low network performance. Federal CoC funding emerges as a core condition for high and low performance, but all relevant conditions can be critical factors depending on how they interact with other relevant conditions. This analysis helps expand the utility of existing contingency theory by using it to explain the dynamic interactions between factors in the context of public service networks. Ultimately, this dissertation confirms that fsQCA can be a useful method for evaluating the performance of public service networks and helping them provide more services more effectively.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc2257727 |
| Date | 12 1900 |
| Creators | Kim, Jintak |
| Contributors | Jang, Hee Soun, Andrew, Simon A., Shi, Yu Kelly |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Public, Kim, Jintak, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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