ELABORATIONS ON MULTIATTRIBUTE UTILITY THEORY DOMINANCE By David L. Vairo A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University, 2019. Major Director: Dissertation director’s name, Dr. Jason Merrick, Supply Chain Management and Analytics Multiattribute Utility Theory (MAUT) is used to structure decisions with more than one factor (attribute) in play. These decisions become complex when the attributes are dependent on one another. Where linear modeling is concerned with how factors are directly related or correlated with each other, MAUT is concerned with how a decision maker feels about the attributes. This means that direct elicitation of value or utility functions is required. This dissertation focuses on expanding the types of dominance forms used within MAUT. These forms reduce the direct elicitation needed to help structure decisions. Out of this work comes support for current criticisms of gain/loss separability that is assumed as part of Prospect Theory. As such, an alternative to Prospect Theory is presented, derived from within MAUT, by modeling the probability an event occurs as an attribute.

Safety risk assessment forms an integral part of the design and development of Safety Critical Systems. Conventionally in these systems, standards and policies have been developed to prescribe processes for safety risk assessment. These standards provide guidelines, references and structure to personnel involved in the risk assessment process. However, in some of these standards, the prescribed methods for safety decision making were found to be deficient in some respects. Two such deficiencies have been addressed in this thesis. First, when different safety metrics are required to be combined for a safety related decision, the current practices of using safety risk matrices were found to be inconsistent with the axioms of decision theory. Second, in the safety risk assessment process, when multiple experts are consulted to provide their judgment on the severity and/or likelihood of hazards, the standards were lacking detailed guidelines for aggregating experts' judgements. Such deficiencies could lead to misconceptions pertaining to the safety risk level of critical hazards. These misconceptions potentially give rise to inconsistent safety decisions that might ultimately result in catastrophic outcomes. This thesis addresses both these concerns present in SRM processes. For the problem of combining safety metrics, three potential approaches have been proposed. Normative Decision Analysis tools such as Utility Theory and Multi-attribute Utility Theory were proposed in the first and second approaches. The third approach proposes the use of a Multi-Objective Optimization technique - Pareto Analysis. For problems in Expert Aggregation, behavioral and mathematical solutions have been explored and the implications of using these methods for Safety Risk Assessment have been discussed. Two standard documents that contain the Safety Risk Management Processes of the Federal Aviation Agency (FAA) and the U.S. Navy were used to structure the case studies. This thesis has two main contributions. First, it evaluates the use of decision analysis in safety decision process of Safety Critical Systems. It provides guidelines to decision makers on how to meaningfully use and/or combine different safety metrics in the decision process. Second, it identifies the best practices and methods of aggregating expert assessments pertaining to safety decision making. / Master of Science / Safety risk assessment forms an important part of the design and development of Safety Critical Systems. Safety Critical Systems are those systems whose failure could potentially result in the loss of human life. Commonly in these systems, standards and policies have been developed to prescribe processes for safety risk assessment. These standards provide guidelines, references and structure to personnel involved in the risk assessment process. However, in some of these standards, the prescribed methods for safety decision making were found to be deficient in some respects. Two such deficiencies have been addressed in this thesis. First, when different safety metrics are required to be combined to provide information for a safety related decision, the current practices of the safety risk assessment do not yield consistent recommendations. Second, in the safety risk assessment process, often multiple experts are consulted to provide their judgment on the criticality of a potential safety risk of the system. The standards and policies that are currently being used, do not provide clear instructions on how to synthesize the judgements of multiple experts. This lack of clear guidelines could potentially lead to an incorrect final judgement on the criticality of the risk and ultimately result in choosing an improper method to reduce the safety risk. This thesis addresses both these concerns present in safety risk assessment process of Safety Critical Systems. For the problem of combining safety metrics, three approaches have been proposed. Two of the proposed approaches make use of normative decision analysis practices and therefore the recommendations reached using these methods will be consistent with the safety objective of the decision maker. The third approach makes use of a traditional concept called -Pareto Analysis which provides a visual method to analyze the advantages and drawbacks of a given safety concern for a system. For problems in combining the judgements of multiple experts a variety of methods was studied. The methods include group consensus and mathematical techniques and the implications of using these methods in safety risk assessment was discussed. The FAA and the U.S. Navy's standard documents and policies were used to frame the discussions. This thesis has two main contributions. First, it evaluates the use of Normative Decision Analysis methods in safety decision process of Safety Critical Systems. It provides guidelines to decision makers on how to meaningfully use and/or combine different safety metrics in the decision process. Second, it identifies the best practices and methods of aggregating expert assessments pertaining to safety decision making.

Nutrients are the number one water pollution problem for U.S. lakes, reservoirs, and ponds. Excessive nutrients, such as nitrogen and phosphorus, lead to eutrophication, a condition that can include low oxygen levels, noxious algal blooms, and fish kills. Since eutrophication is a condition that manifests itself differently in different systems, there is not a criterion variable with a clear threshold that can be used to set the criterion level. This dissertation presents an approach to address the question: How should States and Tribes choose nutrient criteria to determine eutrophication-related impairments of the designated use? To address this question I used a combination of water quality modeling and decision analysis to determine the optimal nutrient criterion variables and levels. To choose criterion variables that are predictive of the designated use, I utilized statistical models (structural equation models, multiple regression, and binomial regression model) to link the measured water quality variables to expert elicited categories of eutrophication and the designated uses. These models were applied successfully to single waterbodies, the Kissimmee Chain-of-Lakes region, and the State of North Carolina to assess which candidate criterion variables were the most predictive. Additionally, the models indicated that the variables that were most predictive of eutrophication were also the most predictive of the designated use. Using the predictive nutrient criteria variables, I applied a decision-analytic approach to nutrient criteria setting in North Carolina. I developed a nutrient criteria value model that included two submodels, a water quality model and a multiattribute value model. The submodels were parameterized using a combination of water quality data, expert elicitation data, and utility assessments. The outcome of the nutrient criteria value model is the overall expected value for a criterion level choice; the optimal criterion level would be the choice that maximized the expected value. Using the preferences of North Carolina environmental decision-makers and a total phosphorus criterion variable, the optimal criterion level was between 0.03 mg/L and 0.07 mg/L. Ultimately, I hope this research will establish methodology used to set appropriate water quality criteria. / Dissertation

An ongoing objective in healthcare is the development of tools to improve patient decision-making and surgical outcomes for patients with breast cancer that have undergone or plan to undergo breast reconstruction. In keeping with the bioethical concept of autonomy, these decision models are patient-oriented and expansive, covering a range of different patient decision-makers. In pursuit of these goals, this dissertation contributes to the development of a prototype shared decision support system that will guide patients with breast cancer and their physicians in making decisions about breast reconstruction. This dissertation applies principles in decision analysis to breast reconstruction decision-making. In this dissertation, we examine three important areas of decision-making: (1) the options available to decision-makers, (2) the validity of probabilistic information assessed from reconstructive surgeons, and (3) the feasibility of applying multiattribute utility theory. In addition, it discusses the influences of breast aesthetics and proposes a measure for quantifying such influences. The dissertation concludes with a fictional case study that demonstrates the integration of the findings and application of decision analysis in patient-oriented shared breast reconstruction decision-making. Through the implementation of decision analysis principles, cognitive biases and emotion may be attenuated, clearing the decision-maker’s judgment, and ostensibly leading to good decisions. While good decisions cannot guarantee good outcomes at the individual level, they can be expected to improve outcomes for patients with breast cancer as a whole. And regardless of the outcome, good decisions yield clarity of action and grant the decision-maker a measure of peace in an otherwise uncertain world. / text

Como em qualquer outra organização, as empresas de engenharia química vêm cada vez mais utilizando ferramentas de Tomadas de Decisão para escolhas de soluções técnicas para projetos, operações, desenvolvimento, dentre tantas. A tomada de decisão é o processo de responder a um problema, utilizando um conjunto de técnicas qualitativas e quantitativas para selecionar a solução ou ação, dentre várias alternativas que seja mais adequada para a resolução daquele problema. Dentre estas ferramentas, as mais utilizadas são a MAUT, do inglês Multiattribute Utility Theory (Teoria de Utilidade Multiatributos) e a AHP, do inglês Analytic Hierarchy Process (Processo de Análise Hierárquica).Neste trabalho, estes dois métodos são aplicados num mesmo problema de engenharia química: a seleção de um sistema para tratamento de compostos orgânicos voláteis durante o carregamento de navios que transportam petróleo e derivados. Para isto é realizada, em primeiro lugar, a descrição detalhada de cada método, a conceituação de composto orgânico volátil, a legislação pertinente e a descrição de cada alternativa como solução para controle deste tipo de emissão. Os resultados apontados pelos métodos MAUT e AHP são então comparados a fim de verificar se ambos conduzem a mesma solução. Pretende-se também observar o grau de influencia das diferentes áreas de atuação de uma organização na escolha final da tomada de decisão e verificar as percepções dos profissionais sobre cada método aplicado. Percebeu-se, entretanto, que as metodologias não conduziram, neste trabalho, a soluções idênticas, devido à influência das características de cada método, e que profissionais de uma mesma área de atuação tendem a tomarem o mesmo tipo de decisão

Como em qualquer outra organização, as empresas de engenharia química vêm cada vez mais utilizando ferramentas de Tomadas de Decisão para escolhas de soluções técnicas para projetos, operações, desenvolvimento, dentre tantas. A tomada de decisão é o processo de responder a um problema, utilizando um conjunto de técnicas qualitativas e quantitativas para selecionar a solução ou ação, dentre várias alternativas que seja mais adequada para a resolução daquele problema. Dentre estas ferramentas, as mais utilizadas são a MAUT, do inglês Multiattribute Utility Theory (Teoria de Utilidade Multiatributos) e a AHP, do inglês Analytic Hierarchy Process (Processo de Análise Hierárquica).Neste trabalho, estes dois métodos são aplicados num mesmo problema de engenharia química: a seleção de um sistema para tratamento de compostos orgânicos voláteis durante o carregamento de navios que transportam petróleo e derivados. Para isto é realizada, em primeiro lugar, a descrição detalhada de cada método, a conceituação de composto orgânico volátil, a legislação pertinente e a descrição de cada alternativa como solução para controle deste tipo de emissão. Os resultados apontados pelos métodos MAUT e AHP são então comparados a fim de verificar se ambos conduzem a mesma solução. Pretende-se também observar o grau de influencia das diferentes áreas de atuação de uma organização na escolha final da tomada de decisão e verificar as percepções dos profissionais sobre cada método aplicado. Percebeu-se, entretanto, que as metodologias não conduziram, neste trabalho, a soluções idênticas, devido à influência das características de cada método, e que profissionais de uma mesma área de atuação tendem a tomarem o mesmo tipo de decisão