Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

The research presented in this thesis considers the question of whether individual-level risk preferences are consistent or inconsistent across decision domains. For example, do people make the same decisions with respect to work, health and finance? Some previous authors have suggested that risk preferences are inconsistent, e. g. Kahneman and Tversky (1979), while others have put forward the idea that people have generalised tendencies to take or avoid risks, e. g. Sitkin and Pablo (1992). The work of Sitkin and Pablo was drawn upon to develop hypotheses concerning the conceptualisation and construction of risk propensity. Risk propensity was operationalised as the degree of consistency of cross-domain risk preferences. It was proposed that a propensity to take or avoid risks is associated with whether individuals have consistent tendencies across different decision domains, that personality will be a key predictor of risk propensity, and that inconsistent cross-domain risk preferences will be associated with risk domain-specific cognitive and emotional aspects of decision making. A survey measure was developed to assess risk and decision preferences both across and within the domains of work, health and finance. Biographical and personality factors were also measured. The sample comprised 360 participants drawn from five sample groups chosen to capture a range of risk preferences. The results showed that risk propensity can be conceptualised and measured in terms of the consistency of cross-domain risk preferences. People who were consistent in their risk preferences were characterised by the personality traits of emotional stability, low extroversion, low openness and high agreeableness. Additionally, consistent risk preferences were associated with relative consistency of attention to situational information and perceived risk. The majority of participants, however, had different risk preferences in different domains, and showed variability in their decision preferences. The implications of the research for understanding risk propensity and risk management are discussed.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 155-171).

This thesis examines the use of precision agriculture data, specifically yield maps, for makingsite-specific economic decisions for improved farm management. The adoption of precisionagriculture on farms has allowed producers to collect a greater quantity and more specificinformation about production than ever before. With such information, site-specific decisions canbe made. Incorporating economic data with yield map data, two primary decision examples aredeveloped: defining areas of production and nonproduction and managing temporal risk spatiallyacross a field. Included with the production/ nonproduction decision are the effects that landtenure arrangements and risk aversion levels have on the decision. The risk maps are developedusing break-even analysis, the coefficient of variation, and a mean-variance framework, all based ona twenty year average of temporal net returns, measured spatially. The risk maps are repeatedincorporating a crop insurance option, a commonly used risk management tool. Results show thatdeveloping these maps can be used by agricultural producers to help with their decision making. Byincorporating these maps into the decision-making process, decisions can be made to increase farmprofitability.

Thesis (M.A.)--University of North Carolina at Wilmington, 2007. / Includes bibliographical references (leaves [38]-43)

The development of suitable long term flood risk intervention strategies is a challenge. Climate change alone is a significant complication but in addition complexities exist trying to identify the most appropriate set of interventions, the area with the highest economical benefit and the most opportune time for implementation. All of these elements pose difficulties to decision makers. Recently, there has been a shift in the current practice for appraising potential strategies and consideration is now being given to ensure flexible, adaptive strategies to account for the uncertain climatic conditions. Real Options in particular is becoming an acknowledged approach to account for the future uncertainties inherent in a flood risk investment decision. Real Options facilitates adaptive strategies as it enables the value of flexibility to be explicitly included within the decision making process. Opportunities are provided for the decision maker to modify and update investments when knowledge of the future state comes to light. In this thesis the use of Real Options in flood risk management is investigated as a method to account for the uncertainties of climate change. Each Intervention strategy is purposely designed to capture a level of flexibility and have the ability to adapt in the future if required. A state of the art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time. In addition to Real Options, this thesis also explores the use of evolutionary optimisation algorithms to aid the decision making process when identifying the most appropriate long term strategies. Although the risk analysis tool is capable of quantifying the potential benefits attributed to a strategy, it is not necessarily able to identify the most appropriate. Methods are required which can search for the optimal solutions according to a range of performance metrics. Single and multi-objective genetic algorithms are investigated in this thesis as a method to search for the most appropriate long term intervention strategies. The Real Options concepts are combined with the evolutionary multiobjective optimisation algorithm to create a decision support methodology which is capable of searching for the most appropriate long term economical yet robust intervention strategies which are flexible to future change. The methodology is applied to two individual case studies, a section of the Thames Estuary and an area on the River Dodder. The results show the inclusion of flexibility is advantageous while the outputs provide decision makers with supplementary knowledge which previously has not been considered.

The operational management of Water Distribution Systems (WDS), particularly under failure conditions when the behaviour of a WDS is not well understood, is a challenging problem. The research presented in this thesis describes the development of a methodology for risk-based diagnostics of failures in WDS and its application in a near real-time Decision Support System (DSS) for WDS’ operation. In this thesis, the use of evidential reasoning to estimate the likely location of a burst pipe within a WDS by combining outputs of several models is investigated. A novel Dempster-Shafer model is developed, which fuses evidence provided by a pipe burst prediction model, a customer contact model and a hydraulic model to increase confidence in correctly locating a burst pipe. A new impact model, based on a pressure driven hydraulic solver coupled with a Geographic Information System (GIS) to capture the adverse effects of failures from an operational perspective, is created. A set of Key Performance Indicators used to quantify impact, are aggregated according to the preferences of a Decision Maker (DM) using the Multi-Attribute Value Theory. The potential of distributed computing to deliver a near real-time performance of computationally expensive impact assessment is explored. A novel methodology to prioritise alarms (i.e., detected abnormal flow events) in a WDS is proposed. The relative significance of an alarm is expressed using a measure of an overall risk represented by a set of all potential incidents (e.g., pipe bursts), which might have caused it. The DM’s attitude towards risk is taken into account during the aggregation process. The implementation of the main constituents of the proposed risk-based pipe burst diagnostics methodology, which forms a key component of the aforementioned DSS prototype, are tested on a number of real life and semi-real case studies. The methodology has the potential to enable more informed decisions to be made in the near real-time failure management in WDS.

Flood events have caused detrimental impacts to humans' lives and anthropogenic climate change is anticipated to exacerbate the impact. It has been recognized that a long-term planning through risk-based optimization of flood defence will lead to a cost-effective solution for managing flood risk, but the prevailing assumption of stationarity may lead to an erroneous solution. In attempt to investigate the potential impact of the uncertain underlying statistical characteristics of extreme flow series to flood protection decisions, this research explores risk-based flood protection decisions in the context of climatic variability and change. In particular, the implications of persistence series and nonstationarity were investigated through hypothetical and real case studies. Monte Carlo simulation approach was adopted to capture the uncertainty due to the natural variability. For persistence model, AR(1) was integrated with the GEV model to simulate extreme flow series with persistence. To test the effects of nonstationary, GEV models with a linear location parameter and time as covariate were adopted. Rational decision makers' behaviours were simulated through a designed decision analysis framework. One of the main findings from the research is that the traditional stationary assumption should remain the basic assumption due to insignificant difference of the decisions' economic performance. However, exploration of the nonstationarity assumption enabled identification of options that are robust to climate uncertainties. It is also found that optimized protection of combined measures of flood defence and property-level protection may provide a cost-effective solution for local flood protection. Overall, the simulation and case studies enlighten practitioners and decision makers with new evidence, and may guide to practical enhancement of long term flood risk management decision making.

The main aim of this research is to develop a conceptual model that describes the way managers make decisions about internationalizing. It also tries to explain under what conditions managers will be risk-seekers and under what conditions they will be risk-averse, and as a result which groups of strategies and tools they will choose to use when internationalizing. This investigation focuses on the field of behavioural economics in opposition to leading paradigms in the IB field that concentrate on the neoclassical economic theory. This research uses an interdisciplinary approach that combines the behavioural economics approach and theories drawn from the field of entrepreneurship, IB, market relations, industrial organization, RBV and institutional theory, in order to develop a comprehensive theoretical framework that can explain from the senior manager's perspective when and why s/he chooses certain variables and not others. The findings link the manager's perception of his position vis-à-vis his industry reference point (IRP are defined as any variable that highlights a particular objective, seems capable of establishing a reference point, and as a result, creates a framework for organizational/individual decision making) and his decision making in the area of risk management, learning, and product adaption and development. The findings indicate that managers below their IRP display innovation when developing new marketing/distribution channels, and share their knowledge with partners. Nevertheless, they demonstrate low awareness of risk management. In contrast, managers above their IRP focus on the organization's existing technology and marketing and distribution channels and avoid adjusting their products to the market needs and sharing knowledge with distributors. On the other hand, they adopt an active risk management strategy.Additionally we link between the manager's perceptions of his position vis-à-vis his IRP and his choice of entry mode strategy. The findings indicate that a number of differences exist between managers below their IRP and managers above their IRP. Managers below their IRP use positioning strategies but use TCA or institutional strategies very little. In contrast, managers above their IRP use TCA or institutional strategies but will hardly use positioning strategies at all. The two types of managers use network strategy and RBV, but each group uses different factors within the theories. The research makes a number of important contributions to study of the IB sphere, particularly to the fields of research relating to the internationalization of BG companies, which is a relatively new field of knowledge. Today there is no comprehensive theoretical framework explaining the way BG companies internationalize and the reasons they choose one strategy or tool over another when entering foreign markets. The present research attempts to establish a conceptual model that describes the way managers make internationalization decisions. It does so by importing a new discipline from the field of behavioural economics into the IB field, which is deeply wedded to the tradition of neo-classical economics and integrates it with existing strategies in the field to create a conceptual model that mediates between traditional IB research and the BG research stream.