In our high technology society, there is a growing demand for a better understanding of decision making in high risk situations in order to improve selection, training and operational performance. Decision Making Under Stress presents a state-of-the-art review of psychological theory, in research and practice, on decision making in high pressure and emergency situations. It focuses on the experienced decision makers who deal with such risks, principally on flight decks, at civil emergencies, in industrial settings and military environments. The 29 chapters cover a wide range of perspectives and applications from aviation, military, industry and the emergency services. The authors, all international invited experts in their field, are based in research centers and universities from Europe, North America and Australia. Their common interest is in the theories and methods of a new research domain called NDM (naturalistic decision making). This volume comprises the edited contributions to the Third International NDM conference, sponsored by the US Army Research Institute and the US Naval Air Warfare Center, which was held in Aberdeen, Scotland in September 1996. The NDM researchers are interested in decision making in situations characterised by high risk, time pressure, uncertain goals, ambiguous information and teamwork. The extent to which the NDM approach can explain and predict human performance in such settings is a central theme, discussed with many practical examples and applications. This book is essential reading for applied psychologists, pilots, emergency commanders, military officers, high hazard managers, safety and emergency response professionals.

Today's ever more complex world creates challenges for decision makers. This volume reviews the principles underlying complex decision making, the handling of uncertainties in dynamic environments, and the various modeling approaches. Beginning with a discussion of the underlying concepts, theories and empirical evidence, the book gives you a range of practical tools and techniques for decision making in complex environments and systems.

The purpose of Multiple Criteria Analysis in Strategic Siting Problems is to demonstrate how multiple criteria can be used in analysis of facility location problems. The book begins with an overview, explains the internationally most popular multiple objective analysis methods, and demonstrates their applications on real problems. Siting problems reviewed include nuclear waste disposal in the U.S., solid waste management in Finland, pipeline location in India, and pipeline location in Russia. Methods covered are multiattribute utility analysis, analytic hierarchy process, the ELECTRE outranking method, and verbal decision analysis. The book concludes with a comparative review of methods. The book uses the multi-attribute, multi-party framework of Kunreuther to present the decision context, to include parties with interests in the decisions, as well as the sequence of project events. This perspective is valuable in identifying the qualitative backgrounds of siting problems that need to be considered. The book demonstrates the importance of multiple criteria in hazardous facility site selection. It also shows how each of the four methodologies covered operate, both in terms of demonstration problems worked with numbers, and how these methods have been applied in the real applications. The real applications were taken from refereed journal documentation, with the exception of Russian pipeline analysis decisions in which Professor Larichev participated. The book is recommended for those interested in decision-making involving problems with social import. This includes environmental aspects, as well as international aspects of decision making.

This is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations. Including numerous application examples and illustrations with tables and figures and presenting the authors' latest research developments, it is a valuable resource for researchers and professionals in the fields of fuzzy mathematics, operations research, information science, management science and decision analysis.

This book presents the concept of the double hierarchy linguistic term set and its extensions, which can deal with dynamic and complex decision-making problems. With the rapid development of science and technology and the acceleration of information updating, the complexity of decision-making problems has become increasingly obvious. This book provides a comprehensive and systematic introduction to the latest research in the field, including measurement methods, consistency methods, group consensus and large-scale group consensus decision-making methods, as well as their practical applications. Intended for engineers, technicians, and researchers in the fields of computer linguistics, operations research, information science, management science and engineering, it also serves as a textbook for postgraduate and senior undergraduate university students.

Crisis events are increasingly common. Their impacts are greater--and they are more widely reported in the media--than ever before. They often symbolize tragedy and loss, but they are also the precipitating factors in radical, rapid, and frequently positive social change. Understanding the complex dynamics of these powerful events is imperative for both researchers and managers. Taking a broad view of organizational crisis, the authors synthesize a rich and diverse body of theory, research, and practice and apply it to every kind of crisis imaginable, from oil spills to nuclear disasters, airplane crashes, shuttle explosions, and corporate implosions such as Enron. The "organization" can be anything from a company to a federal bureaucracy or society. Organizational crisis is presented as a natural stage in organizational evolution, creating not only stress and threats but also opportunities for growth and development. Communication is viewed as the pivotal process in the creation and maintenance of organization, and its role is examined here at every stage, from incubation to avoidance, crisis management, and recovery. Researchers, crisis managers, and communications managers will find a wealth of applied theoretical orientations, including chaos theory, sensemaking, organizational learning theory, and more.

In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.

In Decision Modelling And Information Systems: The Information Value Chain the authors explain the interrelationships between the decision support, decision modelling, and information systems. The authors borrow from Porter's value chain concept originally set out in the organizational context and apply it to a corporate IS context. Thus data, information and knowledge is seen to be the progressive value added process leading to business intelligence. The book captures key issues that are of central interest to decision support researchers, professionals, and students. The book sets out an interdisciplinary and contemporary view of Decision Support System (DSS).

The first two parts of the book focus on the interdisciplinary decision support framework, in which mathematical programming (optimization) is taken as the inference engine. The role of business analytics and its relationship with recent developments in organisational theory, decision modelling, information systems and information technology are considered in depth. Part three of the book includes a carefully chosen selection of invited contributions from internationally-known researchers. These contributions are thought-provoking and cover key decision modelling and information systems issues.

These chapters include: Arthur Geoffrion on restoring transparency to computational solutions, Bill Inmon on the concept of the corporate information factory, Louis Ma and Efraim Turban on strategic information systems, and Erik Thomsen on information impact and its relationship to the value of information technology.

The final part of the book covers contemporary developments in the related area of business intelligence considered within an organizational context. The topics cover computing delivered across the web, management decision-making, and socio-economic challenges that lie ahead. It is now well accepted that globalisation and the impact of digital economy are profound; and the role of e-business and the delivery of decision models (business analytics) across the net lead to a challenging business environment. In this dynamic setting, decision support is one of the few interdisciplinary frameworks that can be rapidly adopted and deployed to so that businesses can survive and prosper by meeting these new challenges.

Gilboa and Schmeidler provide a new paradigm for modeling decision making under uncertainty. Case-based decision theory suggests that people make decisions by analogies to past cases: they tend to choose acts that performed well in the past in similar situations, and to avoid acts that performed poorly. The authors describe the general theory and its relationship to planning, repeated choice problems, inductive inference, and learning. They highlight its mathematical and philosophical foundations and compare it to expected utility theory as well as to rule-based systems.

This book provides a thorough development of the powerful methods of heavy traffic analysis and approximations with applications to a wide variety of stochastic (e.g. queueing and communication) networks, for both controlled and uncontrolled systems. The approximating models are reflected stochastic differential equations. The analytical and numerical methods yield considerable simplifications and insights and good approximations to both path properties and optimal controls under broad conditions on the data and structure. The general theory is developed, with possibly state dependent parameters, and specialized to many different cases of practical interest. Control problems in telecommunications and applications to scheduling, admissions control, polling, and elsewhere are treated. The necessary probability background is reviewed, including a detailed survey of reflected stochastic differential equations, weak convergence theory, methods for characterizing limit processes, and ergodic problems.

For this book, the editors invited contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000. The chapters contain contributions to identifying rare or hidden events and explaining their significance. The methods presented in this book are based on the interaction of human, machine, and humans living environment.

Problems with high stakes, involving human perceptions and judgements, and whose resolutions have long-term repercussions, call for a rational approach to their solution. Strategic Decision Making provides an effective, formal methodology that gives assistance to such strategic level decision making problems. Focusing on applying the AHP to decision-making problems in engineering, Strategic Decision Making explores the three main endeavours of human existence: business, defence and governance. Many years of successfully applying Strategic Decision Making in these domains have created extensive results covering many complex planning, resource, allocation and priority setting problems throughout industry and business. Case studies drawn from years of successful, practical application experience. Discusses applications of decision making for real life problems. Worked examples and solutions to problems throughout. The reader will gain comprehensive exposure to the extent of assistance that a formal methodology, such as AHP, can provide to the decision maker in evolving decisions in complex and varied domains. Decision makers, in business and industry around the world, will find this valuable for practical use as a working tool.

The present book fmds its roots in the International Conference on Methods and Applications of Multiple Criteria Decision Making held in Mons in May 1997. A small number of contributions to that conference were selected via a refereeing procedure and retained authors were requested to include in their final version their more recent results. This explains why some papers differ significantly from the original presentation. The introductory paper of Raynaud addresses the long range forecasts in Multiple Criteria Decision Making on the basis of a Delphi process that was run before and during the congress. In a second part, the French author explains how he and some of his partners could find the proof of an important conjecture : the iteration of a strongly monotonic choice function is not a strongly monotonic ranking function. The second part of the book covers methodological aspects of decision theory. The contribution of Bouyssou and Pirlot concerns the reformulation of classical conjoint measurement models that induce a complete and transitive preference binary relation on the set of alternatives which seem to be unrealistic when decision makers are asked to compare objects evaluated on several attributes. The authors propose to consider non transitive, non complete and non additive decomposable conjoint models. They define properties that characterize such models.

The book focuses on applications of belief functions to business decisions. Section I introduces the intuitive, conceptual and historical development of belief functions. Three different interpretations (the marginally correct approximation, the qualitative model, and the quantitative model) of belief functions are investigated, and rough set theory and structured query language (SQL) are used to express belief function semantics. Section II presents applications of belief functions in information systems and auditing. Included are discussions on how a belief-function framework provides a more efficient and effective audit methodology and also the appropriateness of belief functions to represent uncertainties in audit evidence. The third section deals with applications of belief functions to mergers and acquisitions; financial analysis of engineering enterprises; forecast demand for mobile satellite services; modeling financial portfolios; and economics.

Gallhofer and Saris examine the collective choice processes in different decision-making units leading to World Wars I and II as well as the Cuban Missile Crisis, colonial wars, and to major foreign policy decisions of a European government after World War II. In the unit relating to the European government, they find strong evidence for consensual decision-making. But when disagreements occurred among the participants, alternative procedures were employed, such as postponements in order to search for additional information, shifts from argumentation to find a compromise, and change from consensus to majority decision-making. How quickly these shifts were made depended on the group norms.

This book provides a theoretical framework to understand how different foreign-policy decision-making units or groups arrive at a collective choice. The qualitative and quantitative studies presented here are based on written records and deal with the choice process of four different decision-making units in situations that pertain to important foreign policy decisions. Germany's decision-making process under Hitler to initiate World War II exemplifies a group with a leader who is insensitive to advice, making the decisions himself and using the group only for acclamation. Kennedy's decision-making during the Cuban Missile Crisis is very different, as it shows a leader sensitive to advice where the group has the task of presenting different options and their consequences. The Austro-Hungarian cabinet's decision to initiate World War I exemplifies a homogeneous group with a dissenter, although it arrived at a collective decision quite quickly using persuasion, compromise, and some coercion. The bulk of the study deals with a heterogeneous unit in a great variety of decision situations, because most Western European governments are of this type. Where there is extreme conflict and time pressure, consensual decision-making is abandoned and a majority choice is hammered out.

As the first systematic documented study of collective decision-making, as it pertains to different decision units, this book will be of considerable importance to scholars and researchers investigating the decision-making process in government and international affairs.

Although interest in Spatial Decision Support Systems (SDSS) continues to grow rapidly in a wide range of disciplines, students, planners, managers, and the research community have lacked a book that covers the fundamentals of SDSS along with the advanced design concepts required for building SDSS. Filling this need, Spatial Decision Support Systems: Principles and Practices provides a comprehensive examination of the various aspects of SDSS evolution, components, architecture, and implementation. It integrates research from a variety of disciplines, including the geosciences, to supply a complete overview of SDSS technologies and their application from an interdisciplinary perspective. This groundbreaking reference provides thorough coverage of the roots of SDSS. It explains the core principles of SDSS, how to use them in various decision making contexts, and how to design and develop them using readily available enabling technologies and commercial tools. The book consists of four major parts, each addressing different topic areas in SDSS: 1. Presents an introduction to SDSS and the evolution of SDSS 2. Covers the essential and optional components of SDSS 3. Focuses on the design and implementation of SDSS 4. Reviews SDSS applications from various domains and disciplines -- investigating current challenges and future directions The text includes numerous detailed case studies, example applications, and methods for tailoring SDSS to your work environment. It also integrates sample code segments throughout. Addressing the technical and organizational challenges that affect the success or failure of SDSS, the book concludes by considering future directions of this rapidly emerging field of study.