Date of Award

5-2023

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Business Administration

First Advisor

Jeffrey Keisler

Second Advisor

Ehsan Elahi

Third Advisor

Amit Patel

Abstract

Public policy decision-making is challenging for several reasons. First, the outcomes of pulling a public policy lever are often deeply uncertain because of the complexity of the social and physical systems involved. Second, even if outcomes can be predicted, there are multiple points of view to consider, and the same outcome can be viewed anywhere from very positively to very negatively by different stakeholders. Because of this, public policy decisions should be both robust and just. Robustness helps with the uncertainty in outcomes and justice helps with differences in worldview. In this dissertation, I employ system dynamics and agent-based simulation modeling techniques to assist decision-making in two public policy contexts: COVID-19 non-pharmaceutical interventions and police funding. I also develop a framework in which both robustness and justice can be handled simultaneously in complex public policy problems.

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