The need for a deeper understanding of public policy instruments is well established in public administration literature. Growth in ethanol and alternative fuel policy instruments across the country and the importance of these policies to national energy security only adds urgency to this need. Policy instruments are defined as tools governments use to address public policy problems. Public policy scholars traditionally focus on processes of policy making or the policies, with little attention paid to how governments accomplish policy goals. This dissertation shifts the focus to policy instruments to fill this void in public administration scholarship. It examines factors that influence policy instruments chosen by policy makers in the fifty states. Using the lens of biofuel policies, it links three diverse public policy theories: Policy Instrument Theory, New Public Management (NPM) Theory, and Political Culture Theory, into a single model of policy instrument choice. The dependent variable is derived using cluster analysis methods and results in four distinct groups of states based on state level biofuel policy instrument characteristics. These groups are used to test proposed hypotheses regarding state level characteristics including levels of NPM reform, individual state political culture and elite political ideology as well as fundamental measures of state policy capacity of state wealth, impacts of economic sectors, and political interests. Multinomial logistic regression analysis is used to establish the likelihood of membership in one group of states versus other groups with specific instrument characteristics. The results conclude that policy makers in states make different instrument choices based on state level characteristics. Wealthy states choose policy instruments that rely upon changing citizen behavior rather than direct government intervention. The levels of agricultural and manufacturing employment influence instrument choice. Agricultural employment was the most influential variable introduced to the model. These economic sectors did not appear to receive favorable treatment as policy instrument theorists contend. Strong evidence was found for a connection between political ideology and policy instrument choice. States with liberal elite ideology choose different biofuel policy instruments than states with conservative elite ideology. The research offered initial evidence that NPM philosophies translate to policy instrument adoption.

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The Russian invasion of Ukraine in February 2022 has resulted in numerous civilian deaths, damage of transportation and power infrastructure, and forced millions of Ukrainians to seek safety, protection, and assistance abroad. The humanitarian crisis caused by war is beyond the normal capacity of any single agency, institution, or organization and requires collaboration and coordination of various public, private, and nonprofit organizations. Networks connect various organizations and agencies to share and accumulate resources, including financial, human, technological, knowledge, and information, necessary to respond to the changing and uncertain environment and to achieve goals that cannot be accomplished by a single organization. The collaboration of actors within a network is a crucial aspect for service delivery and assistance during the humanitarian crisis caused by war. Even though collaboration among network participants is desirable, the establishment of collaborative ties within the network remains a challenging task for various reasons. This study uses a mixed method approach to answer eight research questions: 1) What is the role of collaborative capacity within interorganizational networks? 2) How do organizations manage the process of collaboration in serving the impacted people in a constantly changing military environment? 3) What is the structure of the humanitarian response network in the response to the crisis caused by war in Ukraine? 4) What humanitarian response partners were involved and what were their roles and responsibilities? 5) What humanitarian response partners were involved and what were their roles and responsibilities? 6) What are the characteristics of the network aiming to respond to the humanitarian crisis? 7) How does network structure impact the collaborative capacity of an interorganizational network during a humanitarian crisis? 8) How do key environmental and organizational factors impact the collaborative capacity of a network during humanitarian crisis? Content analysis (n=229), social network analysis (SNA), and semi-structured interviews (n=14) were used to analyze network collaborative capacity in humanitarian response network in Ukraine. The findings suggest that the network collaborative capacity is influenced by common goals and shared visions, pre-existing ties and relationships between humanitarian response partners, organizational learning, and knowledge sharing. Power asymmetry can both facilitate and hinder network collaborative capacity. The strength of ties, communication, resource dependence, and environmental complexity were also found to play influential roles in building, developing and sustaining the network collaborative capacity. Powerful network members should consider developing better information system that reflects ongoing projects and allow participants to share data and report, and exchange ideas and feedback. Moreover, the efforts should be focused on involving Ukrainian nonprofit organizations in the response because currently they are excluded from the response due to the lack of experience and language barriers.

This grounded theory retrospective case study examined whether the development of the Tennessee Value-Added Assessment System (TVAAS) supported Lasswell's (1951) policy process framework and the ecological adaptation of Marshall, Mitchell and Wirt's policy actors model. The study was a retrospective case study employing semi-structured interviews, analysis of documents, and archival records. The following research questions guided the study: Did the policy process evolve linearly as in Lasswell's theoretical model? If it was different, how? With respect to Marshall, Mitchell, and Wirt's ecological model of policy actor behavior, how was this theory consistent with the evidence from this case study? How did the political culture affect the policy process? How did the selected participants interpret their roles in the different policy stages? What issues developed during the stages of the policy process? How has the Tennessee Value-Added Assessment System as a codified policy changed? The study concluded that the policy process evolved linearly, but took multiple cycles. The Small School Lawsuit precipitated events that suggest features of Punctuated Equilibrium and Multiple Streams theories during the agenda setting stage. The Advocacy Coalition Framework theory underscored many of the events that occurred in later stages. Policy actor behavior changed relative to actor proximity to the inner circle. The traditionalistic policy culture of Tennessee influenced the policy process largely through the elite's inclusion of the TVAAS policy in the omnibus Education Improvement Act (EIA) Bill. The interviewee/participant's roles during the policy process varied at the different policy process stages. Several issues (superintendent elections, teacher evaluation) with the omnibus EIA bill emerged during the policy process that threatened its passage; however, the bill passed due to the initial urgency of fiscal litigation concerns. Since its passage, TVAAS as a codified policy has not experienced any significant changes, except No Child Left Behind has necessitated changes to the types of assessments and indicators. This study may be very useful to policy analyses and policy-makers interested in state level policymaking. / Ed. D.