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.

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.

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.

Providing new knowledge on risk analysis and simulation for megaprojects, this book is essential reading for both academics and practitioners. Its focus is on technical descriptions of a newly developed dynamic systems approach to megaproject risk analysis and simulation. This is backed up by a discussion of the methodology as applied in a comprehensive case study on the Edinburgh Tram Network (ETN) project. The book informs both academic researchers and megaproject stakeholders with the latest information on risk as applied to megaprojects. As well as the complete case study, the book includes a general risk analysis framework for megaprojects, an analytic network process (ANP) method for risk quantification, a system dynamics (SD) method for risk simulation, and practical guides for the application of the dynamic systems approach in megaproject research and practice.

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.

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.

The Cold War Era left the major participants, the United States and the former Soviet Union (FSU), with large legacies in terms of both contamination and potential accidents. Facility contamination and environmental degradation, as well as the accident vulnerable facilities and equipment, are a result of weapons development, testing, and production. Although the countries face similar issues from similar activities, important differences in waste management practices make the potential environmental and health risks of more immediate concern in the FSU and Eastern Europe. In the West, most nuclear and chemical waste is stored in known contained locations, while in the East, much of the equivalent material is unconfined, contaminating the environment. In the past decade, the U.S. started to address and remediate these Cold War legacies. Costs have been very high, and the projected cost estimates for total cleanup are still increasing. Currently in Russia, the resources for starting such major activities continue to be unavailable."

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.

This book proposes a uniform logic and probabilistic (LP) approach to risk estimation and analysis in engineering and economics. It covers the methodological and theoretical basis of risk management at the design, test, and operation stages of economic, banking, and engineering systems with groups of incompatible events (GIE). This edition includes new chapters providing a detailed treatment of scenario logic and probabilistic models for revealing bribes. It also contains clear definitions and notations, revised sections and chapters, an extended list of references, and a new subject index, as well as more than a hundred illustrations and tables which motivate the presentation.

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.

Introduction This book includes terms of reference and offers an augmented volume of relevant work initiated within the comprehensive concept of "Knowledge Management and Risk Governance." The latter stood for the initial title of an ad-hoc meeting held in Ascona, Switzerland, organized by the Technological Risk Management Unit of the Joint Research Centre of the European Commission (JRC) and the KOVERS Centre of Excellence in Risk and Safety Sciences of the Swiss Federal Institute of Technology, ETH Zurich. Background Risk governance, in addition to the continuous interest of researchers, has recently attracted the attention of policy-makers and the media and the concern of the public. New and emerging risks in various fields and a number of risk-related issues increased the public interest and prompted for a new framework in dealing with risks. The Conference on Science and Governance organized by the European Commission in October 2000 is one of the international forums addressing this issue. Other recent events such as the establishment of the International Risk Governance Council outline the importance of the governance concept in relation to that of risk management (see www.irgc.org). At the same time noticeable progress has been made in Information Technologies and Decision Support, passing from the process of information PREFACE xvi to the process of knowledge. In this context new tools and methods became available, whose application in risk management may be beneficial.

This book presents a unique collection of contributions from some of the foremost scholars in the field of risk and reliability analysis. Combining the most advanced analysis techniques with practical applications, it is one of the most comprehensive and up-to-date books available on risk-based engineering. All the fundamental concepts needed to conduct risk and reliability assessments are covered in detail, providing readers with a sound understanding of the field and making the book a powerful tool for students and researchers alike. This book was prepared in honor of Professor Armen Der Kiureghian, one of the fathers of modern risk and reliability analysis.

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.

Information we receive from and create together with our social networks is becoming increasingly important. Social information has a great impact on our information behaviour and there are many possible angles and layers in studying social aspects in information science. This book presents some of these angles. Social Information Research, co-edited by Gunilla Widen and Kim Holmberg communicates current research looking into different aspects of social information as part of information behaviour research. There is a special emphasis on the new innovations supporting contemporary information behavior and the social media context within which it can sit. As a concept, social information has been studied in biology, psychology and sociology among other disciplines. This book is relevant for various actors in the library and information science field and will be useful for researchers, educators, and practitioners while coordinating empirical research on social information and providing an overview of some of the present research about social information.