Date of Award
Master of Science in Systems Engineering
Department of Systems Engineering and Management
Marcelo Zawadzki, PhD
In December 2018, the United States Federal Government began what would become the longest government shutdown in U.S. history. This was the 21st shutdown since the adoption of the current appropriations process and 4th of the last decade. These shutdowns occur after government departments and agencies submit budget requests to Congress and the legislature is unable to come to an agreement to pass an appropriations bill. There is no clear solution to this problem. But this study hypothesizes that government departments and agencies could benefit from considering the political viability of their own budget requests prior to submitting them to Congress. In the field of decision analysis, no prior research was found for assessing the political viability of alternatives. This work theorizes and tests a novel methodology for vote forecasting using the results of a multi-objective decision analysis and comparing alternatives against the status quo. A model scenario is set forth of Customs and Border Protection submitting a funding request for additional technologies to secure the United States-Mexico border. The funding request is sent to a voting body of 20 decision makers from 2 different political parties. A total of 20 funding proposal alternatives are assessed according to the individual preferences of 20 decision makers and votes are forecasted using the results. The experiment with the model scenario made a clear distinction between alternatives with higher and lower levels of political viability. The study contributes a repeatable methodology that can be used for future research in real-life scenarios.
Crandall, Connor G., "Vote Forecasting Using Multi-Objective Decision Analysis" (2020). Theses and Dissertations. 3229.