Description : Provides undergraduates in surveying and property professionals with a clear practical explanation of the various management techniques to improve their property development decisions.
Description : Most decisions in life are based on incomplete information and have uncertain consequences. To successfully cope with real-life situations, the nervous system has to estimate, represent and eventually resolve uncertainty at various levels. A common tradeoff in such decisions involves those between the magnitude of the expected rewards and the uncertainty of obtaining the rewards. For instance, a decision maker may choose to forgo the high expected rewards of investing in the stock market and settle instead for the lower expected reward and much less uncertainty of a savings account. Little is known about how different forms of uncertainty, such as risk or ambiguity, are processed and learned about and how they are integrated with expected rewards and individual preferences throughout the decision making process. With this Research Topic we aim to provide a deeper and more detailed understanding of the processes behind decision making under uncertainty.
Description : Uncertainty in Policy Making explores how uncertainty is interpreted and used by policy makers, experts and politicians. It argues that conventional notions of rational, evidence-based policy making - hailed by governments and organisations across the world as the only way to make good policy - is an impossible aim in highly complex and uncertain environments; the blind pursuit of such a 'rational' goal is in fact irrational in a world of competing values and interests. The book centres around two high-profile and important case studies: the Iraq war and climate change policy in the US, UK and Australia. Based on three years' research, including interviews with experts such as Hans Blix, Paul Pillar, and Brian Jones, these two case studies show that the treatment of uncertainty issues in specialist advice is largely determined by how well the advice fits with or contradicts the policy goals and orientation of the policy elite. Instead of allowing the debates to be side-tracked by arguments over whose science or expert advice is 'more right', we must accept that uncertainty in complex issues is unavoidable and recognise the values and interests that lie at the heart of the issues. The book offers a 'hedging' approach which will enable policy makers to manage rather than eliminate uncertainty.
Description : Introduction and basic concepts; Models and probability; Choices and preferences; Preference assessment procedures; Behavioral assumptions and limitations of decision analysis; Risk sharing and incentives; Choices with multiple attributes.
Description : Decision Making Under Uncertainty in Electricity Markets provides models and procedures to be used by electricity market agents to make informed decisions under uncertainty. These procedures rely on well established stochastic programming models, which make them efficient and robust. Particularly, these techniques allow electricity producers to derive offering strategies for the pool and contracting decisions in the futures market. Retailers use these techniques to derive selling prices to clients and energy procurement strategies through the pool, the futures market and bilateral contracting. Using the proposed models, consumers can derive the best energy procurement strategies using the available trading floors. The market operator can use the techniques proposed in this book to clear simultaneously energy and reserve markets promoting efficiency and equity. The techniques described in this book are of interest for professionals working on energy markets, and for graduate students in power engineering, applied mathematics, applied economics, and operations research.
Description : How to improve decision-making skills in realistic situations and do it in a reasonably nonmathematical fashion. Develops practical techniques for deciding upon the best strategies in a variety of situations. Provides methods for reducing complex problems to easily-drawn decision diagrams (trees), supported by real-world examples. Includes detailed cases that employ the methods described in the text. Each chapter contains illustrative examples and exercises.
Description : In every decision context there are things we know and things we do not know. Risk analysis uses science and the best available evidence to assess what we know—and it is intentional in the way it addresses the importance of the things we don’t know. Principles of Risk Analysis: Decision Making Under Uncertainty lays out the tasks of risk analysis in a straightforward, conceptual manner that is consistent with the risk models of all communities of practice. It answers the questions "what is risk analysis?" and "how do I do this?" Distilling the common principles of the many risk tribes and dialects into serviceable definitions and narratives, the book provides a foundation for the practice of risk analysis and decision making under uncertainty for professionals from all walks of life. In the first part of the book, readers learn the language, models, and concepts of risk analysis and its three component tasks—risk management, assessment, and communication. The second part of the book supplies the tools, techniques, and methodologies to help readers apply the principles. From problem identification and brainstorming to model building and choosing a probability distribution, the author walks readers through the how-to of risk assessment. Addressing the critical task of risk communication, he explains how to present the results of assessments and how to develop effective messages. The book’s simple and straightforward style—based on the author’s decades of experience as a risk analyst, trainer, and educator—strips away the mysterious aura that often accompanies risk analysis. It describes the principles in a manner that empowers readers to begin the practice of risk analysis, to better understand and use the models and practice of their individual fields, and to gain access to the rich and sophisticated professional literature on risk analysis. Additional exercises as well as a free student version of the Palisade Corporation DecisionTools® Suite software and files used in the preparation of this book are available for download.
Description : This book is devoted to investment decision-making under uncertainty. The book covers three basic approaches to this process: a) The stochastic dominance approach, developed on the foundation of von Neumann and Morgenstern' expected utility paradigm. 2 b) The mean-variance approach developed by Markowitz on the foundation of von-Neumann and Morgenstem's expected utility or simply on the assumption of a utility function based on mean and variance. c) The non-expected utility approach, focusing on prospect theory and its modi fied version, cumulative prospect theory. This theory is based on an experi mental finding that subjects participating in laboratory experiments often violate expected utility maximization: They tend to use · subjective probability beliefs that differ systematically from the objective probabilities and to base their decisions on changes in wealth rather than on total wealth. The above approaches are discussed and compared in this book. W e also discuss cases in which stochastic dominance rules coincide with the mean-variance rule and cases in which contradictions between these two approaches may occur. We then discuss the relationship between stochastic dominance rules and prospect theory, and establish a new investment decision rule which combines the two and which we call prospect stochastic dominance. Although all three approaches are discussed, most of the book is devoted to the stochastic dominance paradigm.
Description : Covering the prediction of outcomes for engineering decisions through regression analysis, this succinct and practical reference presents statistical reasoning and interpretational techniques to aid in the decision making process when faced with engineering problems. The author emphasizes the use of spreadsheet simulations and decision trees as important tools in the practical application of decision making analyses and models to improve real-world engineering operations. He offers insight into the realities of high-stakes engineering decision making in the investigative and corporate sectors by optimizing engineering decision variables to maximize payoff.
Description : Mathematical modelling has become in recent years an essential tool for the prediction of environmental change and for the development of sustainable policies. Yet, many of the uncertainties associated with modelling efforts appear poorly understood by many, especially by policy makers. This book attempts for the first time to cover the full range of issues related to model uncertainties, from the subjectivity of setting up a conceptual model of a given system, all the way to communicating the nature of model uncertainties to non-scientists and accounting for model uncertainties in policy decisions. Theoretical chapters, providing background information on specific steps in the modelling process and in the adoption of models by end-users, are complemented by illustrative case studies dealing with soils and global climate change. All the chapters are authored by recognized experts in their respective disciplines, and provide a timely and uniquely comprehensive coverage of an important field.