A Decision Analysis Perspective on Multiple Response Robust Optimization

Decisions in which multiple objectives must be optimized simultaneously occur frequently in government, military, and industrial settings. One method a decision maker may use to assist in such decisions is the application of a desirability function. An informed specification of the desirability function\u27s parameters is essential to accurately describe the decision maker\u27s value trade-offs and risk preference. This thesis uses utility transversality to analyze the implicit trade-off and risk attitude assumptions attendant to the desirability function. The desirability function does not explicitly account for response variability. A robust solution takes not only the expected response into account, but also its variance. Assessing a utility function over desirability as a means to describe the decision maker\u27s risk attitude produces a robust operating solution consistent with those preferences. This thesis examines robustness as it applies to the desirability function in a manufacturing experiment example. Different levels of diplomatic, informational, military, and economic (DIME) instruments of national policy are investigated to examine their effect on the political, military, economic, social, infrastructure, and information (PMESII) systems of a nation. AFRL\u27s National Operational Environment Model (NOEM) serves as a basis for identifying a robust national policy in a scenario involving the Democratic Republic of Congo

Nuclear emergency decision support : a behavioural OR perspective

Operational researchers, risk and decision analysts need consider many behavioural issues. Despite many OR applications in nuclear emergency decision support, the literature has not paid sufficient attention to behavioural matters. In working on designing decision support processes for nuclear emergency management, we have encountered many behavioural issues. In this paper we synthesise the findings in the literature with our experience and identify a number of behavioural challenges to nuclear emergency decision support. In addition to challenges in model-building and interaction, we pay attention to a behavioural issue that is often neglected: the analysis itself and the communication of its implications may have behavioural consequences. We introduce proposals to address these challenges. First, we propose the use of models relying on incomplete preference information, outlining a framework and illustrating it with data from a previous decision analysis for the Chernobyl Project. Moreover, we reflect on the responsibility that rests on the analyst in addressing behavioural issues sensitively in order to lessen the effects on public stress. In doing so we make a distinction between System 1 Societal Deliberation and System 2 Societal Deliberation and discuss how this can help structure societal deliberation in the context of nuclear emergencies

Multiattribute analysis of alternatives for Hanford Tanks Remediation System

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 1997.Includes bibliographical references (leaves 137-140).by Florinel Morosan.Ph.D

Conflicting Objectives in Decisions

This book deals with quantitative approaches in making decisions when conflicting objectives are present. This problem is central to many applications of decision analysis, policy analysis, operational research, etc. in a wide range of fields, for example, business, economics, engineering, psychology, and planning. The book surveys different approaches to the same problem area and each approach is discussed in considerable detail so that the coverage of the book is both broad and deep. The problem of conflicting objectives is of paramount importance, both in planned and market economies, and this book represents a cross-cultural mixture of approaches from many countries to the same class of problem

A Conjoint Analysis of Wetland-Based Recreation: A Case Study of Louisiana Waterfowl Hunting.

Conjoint analysis is a recent evolution in mathematical psychology that has been employed extensively in the marketing environment. The technique is concerned with measuring the joint effect of two or more independent variables on the ordering of a dependent variable. Conjoint analysis relates an individual\u27s preferences to a set of prespecified attributes. The objective of conjoint analysis is to decomposed a set of responses to factorially designed stimuli in which the utility of each stimuli attribute can be inferred from the respondents\u27 evaluations of the stimuli. In addition, conjoint analysis and its economic foundations are developed in the context of conventional related market and non-market valuation approaches. Given the multiattribute nature of wetland based activities such as waterfowl hunting, conjoint analysis becomes an attractive approach in estimating the benefits and values derived from wetland based activities. An empirical and economic analysis is presented in which waterfowl hunters\u27 willingness-to-pay for various hunting trip attributes is derived from a rank-ordered logit specification of the indirect utility function. The hunting trip vignettes are developed according to seven different attributes with each attribute varying across three levels using a fractional factorial experiment. The data for the analysis were derived from questionnaires mailed to 7,500 randomly selected individuals who purchased 1990 Louisiana duck stamps. The statistical estimation technique employed in this research was rank-ordered logit via weighted least squares. Weighted least squares was chosen due to the presence of heteroskedasticity and uncertainty regarding the properties of the error term which masks the efficiency of the ordinary least squares regression. A Box-Cox transformation was also employed to test for specification of the functional form. The results indicated that the length of the hunting season, the daily duck bag limit, and the rate of congestion were three significant factors influencing waterfowl hunters\u27 trip rating preferences. In addition, conjoint analysis appears to be a viable technique for analysis of resource based multiattribute activities

Foundations for Value-Driven Delegated Design with Human Decision Makers

Value-Driven Design is a paradigm that argues that the goal of the engineering design process is to create a system with maximum value. However, the design of large, complex systems undoubtedly requires the efforts of many individuals, and it is naive to think these individuals will act to maximize value if their own values are not maximized along the way. This research focuses on building the foundational knowledge for incentivizing the many individuals in large system design to make design decisions toward maximizing system value. Specifically, this dissertation uses the mathematical framework of normative decision making to formulate and evaluate incentives. We formulate two promising incentive structures: the Piece Rate–where a marginal increase in system value yields a marginal increase in reward an individual will receive– and the Variable Ratio–where a marginal increase in system value yields a marginal increase in the probability of a reward to the individual. These incentive structures are evaluated twofold: (1) by how well they motivate an engineer to provide effort to search for an optimal design solution and (2) by how well they motivate an engineer to collaborate with other engineers to yield an optimal system design solution. We derive mathematical models of effort and collaboration provision for incentive evaluation. Mathematical analysis suggests that which incentive structure motivates greater search effort or collaboration is contextual. The effectiveness of one incentive over the other for effort provision is dependent, in part, on the risk preferences of the engineer. The effectiveness of one incentive over the other for collaboration provision is dependent, in part, on how the incentive structures are scaled with respect to the feasible system alternative space. Therefore, the analysis in this dissertation suggests that the greater information a system-level manager has over the people in the design process and the general characteristics of the system design alternative space, the greater her ability for choose between the Piece Rate and Variable Ratio incentive structures to induce search effort and collaboration to maximize system value

A methodology for probabilistic aircraft technology assessment and selection under uncertainty

The high degree of complexity and uncertainty associated with aerospace engineering applications has driven designers and engineers towards the use of probabilistic and statistical analysis tools in order to understand and design for that uncertainty. As a result, probabilistic methods have permeated the aerospace field to the extent that single point deterministic designs are no longer credible, particularly in systems analysis, performance assessment, technology impact quantification, etc. However, as statistics theory is not the primary focus of most aerospace practitioners, incorrect assumptions and flawed methods are often unknowingly used in design. A common assumption of probabilistic assessments in the field of aerospace is the independence of random variables. These random variables represent design variables, noise variables, technology impacts, etc., which can be difficult to correlate but do have underlying relationships. The justification for the assumed independence is usually not discussed in the literature even though this can have a substantial effect on probabilistic assessment and uncertainty quantification results. In other cases the dependence between random variables is acknowledged but intentionally ignored on the basis of difficulty in characterizing underlying random variable relationships, a strong bias towards methodological simplicity and low computational expense, and the expectation of modest strength in random variable dependence. Probabilistic assessments also yield large amounts of data which is not effectively used due to the sheer volume of data and poor traceability to the drivers of uncertainty. The literature shows optimization techniques are resorted to in order to select from competing alternatives in multiobjective spaces, however, these techniques generally do not handle uncertainty well. The motivating question is, how can improvements be made to the probabilistic assessment process for aircraft technology assessments that capture technology impact tradeoffs and dependencies, and ultimately enable decision makers to make an axiomatic and rational selection under uncertainty? This question leads to the research objective of this work which is to develop a methodology ``to quantify and characterize aviation's environmental impact, uncertainties, and the trade-offs and interdependencies among various impacts'' \cite{Council2010}, in order to assess and select future aircraft technologies. Copula theory is suggested to address the problem of assumed independence on the input side of probabilistic assessments in aerospace applications. Copulas are functions that can be used to define probabilistic relationships between random variables. They are well documented in the literature and have been used in many fields such as the statistics, finance, and insurance industries. They can be used to quantify complex relationships, even if that is only qualitatively or notionally understood. In this way a designer's knowledge regarding uncertainty can be better represented and propagated to system level metrics through the probabilistic assessment. Utility theory is proposed as a solution to the challenge of effectively using output data from probabilistic assessments. Utility theory is a powerful tool used in economics, marketing, psychiatry, etc., to express preferences among competing alternatives. Utility theory can provide combined valuation to each alternative in a multiobjective design space while incorporating the uncertainty associated with each alternative. This can enable designers to rationally and axiomatically make selections consistent with their preferences, between complex solutions with varying degrees of uncertainty. This work provides an introduction to copula and utility theories for the aerospace audience. It also demonstrates how these theories can be applied in canonical problems to bridge gaps currently found in the literature with regards to probabilistic assessments of aircraft technologies. The key contributions of this research are (1) an Archimedean copula selection tree enabling practitioners to rapidly translate their qualitative understanding of dependence into copula families that can represent it quantitatively (2) estimation of the quantified effect of using copulas to capture probabilistic dependence in three representative aerospace applications (3) an expected utility formulation for axiomatically ranking and selecting aircraft technology packages under uncertainty and (4) a strategic elicitation procedure for multiattribute utility functions that does not need assumptions of independence conditions on preferences between the attributes. The proposed FAAST methodology is shown as an encompassing framework for the aircraft technology assessment and selection problem that fills capability gaps from the literature and supports the decision maker in a rational and axiomatic manner.Ph.D

Essays in Behavioral Labor and Welfare Economics

In my dissertation, I study three questions in behavioral labor and welfare economics using experimental methods: what is the role of task difficulty on effort, how to measure ability and motivation in a more rigorous way, and what are the economic consequences of stochastic choice in a risk setting. In the first chapter, I study the effect of task difficulty on workers’ effort and compare it to the effect of monetary rewards in a tightly controlled laboratory experiment. I find that task difficulty has an inverse-U effect on effort, and that this effect is quantitatively large when compared to the effect of conditional rewards. Difficulty acts as an important mediator of monetary rewards: they are most effective at the medium level of difficulty. I show that the inverse-U pattern of effort response to difficulty is not consistent with the Expected Utility model but is consistent with the Rank-Dependent Utility (RDU) model that allows for probability weighting. I structurally estimate the RDU model and find that it fits the data well. These findings suggests that 1) task difficulty is a useful and costless tool to stimulate effort, 2) to elicit the maximum amount of effort, the task has to be reasonably challenging, and 3) the design of optimal incentive schemes for workers should take into account task difficulty. In the second chapter, I develop a novel method for estimating ability and motivation from the outcomes and response time on a cognitive test. The proposed method is based on a dynamic stochastic model of optimal effort choice that features a psychologically plausible mechanism of decision-making. In a laboratory experiment, I find substantial heterogeneity among subjects in terms of their estimated ability and motivation that is partially attributed to their demographic characteristics and preferences. Test scores turns out to be a very imprecise measure of true ability. The observed variation in test scores is mostly due to variation in motivation rather than ability. I find no association between estimated measures of ability and motivation and their self-reported counterparts. Looking at the relative importance of ability versus motivation on the success on a cognitive task, I find that motivation plays a slightly bigger role than ability. In the third chapter, which is a joint work with Dr. Glenn W. Harrison, Dr. Morten Lau and Dr. Don Ross, we study the welfare costs of stochastic choice. Theoretical work on stochastic choice mainly focuses on the sources of choice randomness, and less on its economic conse- quences. We attempt to close this gap by developing a method of extracting information about the monetary costs of noise from structural estimates of preferences and choice randomness. Our method is based on allowing a degree of noise in choices in order to rationalize them by a given structural model. To illustrate the approach, we consider risky binary choices made by a sample of the general Danish population in an artefactual field experiment. The estimated welfare costs are small in terms of everyday economic activity, but they are considerable in terms of the actual stakes of the choice environment. Higher welfare costs are associated with higher age, lower education, and lower income

Towards the formation and measurement of ethnic price perception

This research is the outcome of a preeminent interest in the topic of price perception. Pointedly, the perception of prices is part of the purchasing process, the same willingness to pay and the actual purchase behaviour, and is indubitably a perceptual construct. As such, perception is problematic to measure as it does not relate to an observable behaviour. On the other hand, pricing is regarded as an important variable in the marketing mix. This research contributes to theory by augmenting the current knowledge on the perception of prices including the methods used in the measurement of such perception. Moreover, this research addresses a gap in the understanding of how diverse ethnic groups perceive prices. The relationship set in this study between ethnicity and price perception is thought-provoking as it contributes to the current discussion around diversity in the marketplace. For example, the literature shows advances in areas such as multicultural and ethnic marketing and this research makes a significant contribution to these areas from price perception. Accordingly, this study involved a systematic review of the literature and presented a framework that suggested that the formation of price perception is affected by external factors such as culture and ethnicity. Furthermore, a qualitative study examined the formation of price perception around ethnic groups. Next, this research used a quantitative study that sought differences in price perception among ethnic groups. Thus, the quantitative study used a price perception scale (Lichtenstein et al., 1993) and a choice-based conjoint analysis. Also, the study adopted structural equation modelling (SEM) to measure differences among scales and the multinomial logit model to analyse the choice-based conjoint analysis. The findings of both the quantitative and the qualitative studies link to the systematic review and support the framework for the formation and measurement of price perception originally proposed