Risk communication helps companies, governments and institutions minimise disputes, resolve issues and anticipate problems before they result in an irreversible breakdown in communications. Without good risk communication and good risk management, policy makers have no roadmap to guide them through unforeseen problems, which frequently derails the best policies and results in a breakdown in communications and a loss of trust on behalf of those they are trying hardest to persuade. Most policy makers still use outdated methods - developed at a time before health scares like BSE, genetically modified organisms and dioxin in Belgian chicken feed eroded public confidence in industry and government - to communicate policies and achieve their objectives. Good risk communication is still possible, however. In this book, through the use of a host of case studies from four countries, the author identifies a series of methods that are set to work in a post trust society.

The growing centrality of risk management in pro-market governance raises important questions regarding how risks are produced, and why? Who and what is included in, and excluded from, risk management, and why? And, what is the relationship between the rise of risk management and neoliberalism? Drawing on various political economy approaches, this volume addresses these questions by examining - both analytically and empirically - diverse meanings and practices of risk management across a range of scales and themes ranging from austerity to climate change to housing and debt. The authors investigate the relationship between shifts in contemporary capitalism and the ways in which neoliberal forms of risk management have emerged, been reproduced and normalized, and, transformed historically.

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.

This collection of essays deals with the situated management of risk in a wide variety of organizational settings - aviation, mental health, railway project management, energy, toy manufacture, financial services, chemicals regulation, and NGOs. Each chapter connects the analysis of risk studies with critical themes in organization studies more generally based on access to, and observations of, actors in the field. The emphasis in these contributions is upon the variety of ways in which organizational actors, in combination with a range of material technologies and artefacts, such as safety reporting systems, risk maps and key risk indicators, accomplish and make sense of the normal work of managing risk - riskwork. In contrast to a preoccupation with disasters and accidents after the event, the volume as whole is focused on the situationally specific character of routine risk management work. It emerges that this riskwork is highly varied, entangled with material artefacts which represent and construct risks and, importantly, is not confined to formal risk management departments or personnel. Each chapter suggests that the distributed nature of this riskwork lives uneasily with formalized risk management protocols and accountability requirements. In addition, riskwork as an organizational process makes contested issues of identity and values readily visible. These 'back stage/back office' encounters with risk are revealed as being as much emotional as they are rationally calculative. Overall, the collection combines constructivist sensibilities about risk objects with a micro-sociological orientation to the study of organizations.

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 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.

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.

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.

Classes of socio-technical hazards allow a characterization of the risk in technology innovation and clarify the mechanisms underpinning emergent technological risk. Emerging Technological Risk provides an interdisciplinary account of risk in socio-technical systems including hazards which highlight: * How technological risk crosses organizational boundaries, * How technological trajectories and evolution develop from resolving tensions emerging between social aspects of organisations and technologies and * How social behaviour shapes, and is shaped by, technology. Addressing an audience from a range of academic and professional backgrounds, Emerging Technological Risk is a key source for those who wish to benefit from a detail and methodical exposure to multiple perspectives on technological risk. By providing a synthesis of recent work on risk that captures the complex mechanisms that characterize the emergence of risk in technology innovation, Emerging Technological Risk bridges contributions from many disciplines in order to sustain a fruitful debate. Emerging Technological Risk is one of a series of books developed by the Dependability Interdisciplinary Research Collaboration funded by the UK Engineering and Physical Sciences Research Council.

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.