Thesis (Ph. D.)--Auburn University, 2008. / Abstract. Vita. Includes bibliographical references (p. 64-65).

Thesis (M.S.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains vii, 64 p. Vita. Includes abstract. Includes bibliographical references (p. 33).

Diss.-- European Business School, 2009. / Includes bibliographical references.

Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 2004. / Includes bibliographical references.

Mannheim, Universität, Thesis (doctoral), 2001.

Thesis (doctoral)--Universität St. Gallen, 1997.

Value of information (VOI) is the amount a decision maker is willing to pay for information to better understand the uncertainty surrounding a decision, prior to making the decision. VOI is a key part of decision analysis (DA). Especially in this age of information explosion, evaluating information value is critical. VOI research tries to derive generic conclusions regarding VOI properties. However, in most cases, VOI properties rely on the specific decision context, which means that VOI properties may not be generalizable. Thus, instead, VOI properties have been derived for typical or representative decisions. In addition, VOI analysis as a method of DA has been successfully applied to practical decision problems in a variety of industries. This approach has also been adopted as the basis of a heuristic algorithm in the latest research in simulation and optimization. Portfolio Decision Analysis (PDA), rooted in DA, is a body of theories, methods, and practices that seek to help decision makers with limited budget select a subset of candidate items through mathematical modeling that accounts for relevant constraints, preferences, and uncertainties. As one of the main tools for resource allocation problems, its successful implementation, especially in capital-intensive industries such as pharmaceuticals and oil & gas, has been documented (Salo, Keisler and Morton 2011). Although VOI and PDA have been extensively researched separately, their combination has received attention only recently. Resource allocation problems are ubiquitous. Although significant attention has been directed at it, less energy has been focused on understanding the VOI within this setting, and the role of VOI analysis to solve resource allocation problems. This belief motivates the present work. We investigate VOI properties in portfolio contexts that can be modeled as a knapsack problem. By further looking at the properties, we illustrate how VOI analysis can derive portfolio management insights to facilitate PDA process. We also develop a method to evaluate the VOI of information portfolios and how the VOI will be affected by the correlations between information sources. Last, we investigate the performance of a widely implemented portfolio selection approach, the benefit-cost ratio (BCR) approach, in PDA practice. / text

In many data sets, a mixture distribution formulation applies when it is known that each observation comes from one of the underlying categories. Even if there are no apparent categories, an implicit categorical structure may justify a mixture distribution. This thesis concerns the modeling of extreme values in such a setting within the peaks-over-threshold (POT) approach. Specifically, the traditional POT modeling using the generalized Pareto distribution is augmented in the sense that, in addition to threshold exceedances, data below the threshold are also modeled by means of the mixture exponential distribution. In the first part of this thesis, the conventional frequentist approach is applied for data modeling. In view of the mixture nature of the problem, the EM algorithm is employed for parameter estimation, where closed-form expressions for the iterates are obtained. A simulation study is conducted to confirm the suitability of such method, and the observation of an increase in standard error due to the variability of the threshold is addressed. The model is applied to two real data sets, and it is demonstrated how computation time can be reduced through a multi-level modeling procedure. With the fitted density, it is possible to derive many useful quantities such as return periods and levels, value-at-risk, expected tail loss and bounds for ruin probabilities. A likelihood ratio test is then used to justify model choice against the simpler model where the thin-tailed distribution is homogeneous exponential. The second part of the thesis deals with a fully Bayesian approach to the same model. It starts with the application of the Bayesian idea to a special case of the model where a closed-form posterior density is computed for the threshold parameter, which serves as an introduction. This is extended to the threshold mixture model by the use of the Metropolis-Hastings algorithm to simulate samples from a posterior distribution known up to a normalizing constant. The concept of depth functions is proposed in multidimensional inference, where a natural ordering does not exist. Such methods are then applied to real data sets. Finally, the issue of model choice is considered through the use of posterior Bayes factor, a criterion that stems from the posterior density. / published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

Not available / text

This PHD project aims to develop a service design system which has a customer-centric view and delivers a balance between profit and value for both customers and service providers. The system will enable designers to assess the design and provide decision support and rationale at an early service design development stage. Also during the lifecycle of the service it would provide a better cost estimation for the service provider to support its future decisions. The two first chapters give an overview of the service field and the research area. Chapter 1, the introduction, states the aim and objectives of this research along with setting the field of the rationale behind the motivation and scope. Chapter 2, the literature review, gives a thorough overview of the service design area mentioning the theories, techniques, methodologies and methods that have been used directly or indirectly for service modeling/design. Chapter 3, the research methodology, states the rationale behind the decisions to conduct this research in terms of purpose, design, strategy and data collection techniques. Moreover an analysis of the current methodology structure which was based on the adaptation of the aforementioned decisions is provided. In Chapter 4 there is a comparison among three different methods (Service Explorer (SE), Integrated Service CAD and Life cycle simulator (ISCL) and Service Blueprinting (SB)) as identified from the literature, which have been developed specifically for service design. The comparison looks at the dynamic features of each method. A dynamic feature is a property of a service method that has the ability to capture specific elements of the service design process which are subject to continuously change within a specific timeframe. At first, there is a brief discussion on how each method is applied and what the output as a generic process is. It starts with identifying generic key concepts of the service design approach by applying all methods to a rental service scenario. Following that, we create a virtual service of a rental machine scenario and map the previously identified key concepts into specific elements of the rental service. We test all methods against these service concepts to identify how well and in what scope each one performs. A merging process of the service concepts is then carried out to form 4 categories which form the specific dynamic features. We test all methods against these features. In particular we find that, SB lacks dynamic capability. SE does well on prioritising individual customer requirements but provides neither a modular design process nor the ability to deal with changes during the service lifecycle. ISCL can provide a process for generating models by combining previously established building blocks and a life-cycle service simulation. However the resources are fixed and there is no prioritisation on the requirements. A pragmatic service deployment requires a service environment that is subject to change, which in turn is not provided by the current methods we compared. The purpose of Chapter 5 is to demonstrate an open source agent-based simulation language that could be used for service design and to simulate the Emergent Synthesis (ES) methodology. This methodology was identified from the literature search as a potential solution to the research gap presented in Chapter 4. That would act as a validation of using the proposed method in the service design area. For this reason a service market is being used as a modelling example. First the area of agent-based modelling is introduced. Certain modifications take place according to the modelling language needs. Next step is the justification and discussion about these changes. The Systems Modelling Language (SySML) is being introduced as a diagrammatic notation method according to which the altered service market model is being represented. The purpose of Chapter 6 is to provide a new approach for accurate design of a service by combining and developing a unified modelling system which covers all important key aspects of a service scenario. To demonstrate the applicability and the output of the system, a case study has been selected. The rest of this chapter is structured as follows. Then there is the introduction and investigation of the service case study. Also the purpose of that choice is stated. Next step is the full breakdown of the system, the current data flow and how the combination of the individual methods has been implemented. Results of each method are produced while visualising the connections between each input-output. A comparison takes place to show the difference of using each method individually and how the emergence of the system as a result of the combination process affects the output. Last step is the validation and the analysis of the results. The penultimate chapter is the discussion, where the outcome based on the results of each chapter is discussed. In Chapter 4, we discuss the outcome of the comparative analysis process. In Chapter 5 we give the analysis and discussion of the service market modelling output and in Chapter 6 we place a discussion based on the system’s output. Last chapter is the conclusion where there is a brief restatement of the whole research work leading to major contribution points. The major contribution of the developed system is the integration of three major methods and methodologies (SE, ISCL, ES) in order to provide answers to the inherent limitations of current techniques (representation of social behaviours in an environment that is subject to change) in the service design domain.