Date of Award

4-2026

Degree Name

Doctor of Philosophy

Department

Evaluation

First Advisor

Daniela Schröter, Ph.D.

Second Advisor

Vincent Reitano, Ph.D.

Third Advisor

Pedro Mateu, Ph.D.

Fourth Advisor

Michael Harnar, Ph.D.

Keywords

Demand, economics, evaluation, federal government, hierarchical linear modeling, mixed methods

Abstract

This dissertation examines the factors that influence demand for evaluation in the federal government of the United States. Although evaluation has become a central element of evidence-based policymaking, limited empirical research explains what drives variation in evaluation activity across federal agencies. The study addresses this gap through a sequential exploratory mixed-methods design that integrates qualitative document analysis with quantitative hierarchical (panel) data modeling. Hierarchical linear modeling (HLM) was employed to analyze longitudinal data from 23 federal agencies (2008–2024), accounting for both within- and between-agency variation over time and providing more accurate estimates of factors influencing evaluation demand.

In the qualitative phase, federal evaluation policies, guidance documents, and agency evaluation plans were systematically analyzed to identify factors influencing evaluation demand. Findings from this phase revealed four overarching domains - economic, institutional, policy, and operational - that shape the conditions under which federal agencies commission evaluations. These qualitative insights informed the quantitative phase, which modeled evaluation demand across 23 federal agencies from 2008 to 2024 using procurement expenditure data. The quantitative analysis demonstrates that evaluation demand in the federal government is driven primarily by institutional and organizational forces rather than economic constraints. Specifically, the number of policy mandates significantly predicts increases in evaluation spending, while organizational complexity also contributes positively to evaluation demand. In contrast, evaluation prices and agency budgets show no significant relationship with evaluation activity, indicating that federal evaluation functions more as a compliance-driven governance mechanism than as a market-based activity.

These findings contribute to theory and practice by advancing understanding of mandated demand within public administration. The study proposes an institutional compliance model of evaluation demand that distinguishes between discretionary and mandated evaluation behavior in government contexts. The research documents a 7.56-fold increase in evaluation spending between 2008 and 2024, indicating that evaluation has become progressively institutionalized within federal governance. Implications extend to policy, practice, and social change. For policymakers, the evidence shows that institutional mechanisms, such as legislative requirements, organizational infrastructure, and accountability systems, are more effective in strengthening evaluation capacity than economic incentives. For practitioners, the study underscores the need to embed evaluation within organizational structures and decision processes to ensure sustainability. The findings also support positive social change by informing strategies to improve government effectiveness, transparency, and accountability through evidence-based policy and evaluation use. This dissertation provides the first systematic empirical contribution to understanding federal evaluation demand within the U.S. federal government.

Access Setting

Dissertation-Open Access

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