This book provides a comprehensive demonstration of risk analysis as a distinct science covering risk understanding, assessment, perception, communication, management, governance and policy. It presents and discusses the key pillars of this science, and provides guidance on how to conduct high-quality risk analysis. The Science of Risk Analysis seeks to strengthen risk analysis as a field and science by summarizing and extending current work on the topic. It presents the foundation for a distinct risk field and science based on recent research, and explains the difference between applied risk analysis (to provide risk knowledge and tackle risk problems in relation to for example medicine, engineering, business or climate change) and generic risk analysis (on concepts, theories, frameworks, approaches, principles, methods and models to understand, assess, characterise, communicate, manage and govern risk). The book clarifies and describes key risk science concepts, and builds on recent foundational work conducted by the Society for Risk Analysis in order to provide new perspectives on science and risk analysis. The topics covered are accompanied by cases and examples relating to current issues throughout. This book is essential reading for risk analysis professionals, scientists, students and practitioners, and will also be of interest to scientists and practitioners from other fields who apply risk analysis in their work.
Risk, Surprises and Black Swans provides an in depth analysis of the risk concept with a focus on the critical link to knowledge; and the lack of knowledge, that risk and probability judgements are based on. Based on technical scientific research, this book presents a new perspective to help you understand how to assess and manage surprising, extreme events, known as ‘Black Swans’. This approach looks beyond the traditional probability-based principles to offer a broader insight into the important aspects of uncertain events and in doing so explores the ways to manage them. This book recognises the fundamental issues surrounding risk assessment and risk management to help you to understand and prepare for black swan events. Complete with international examples to illustrate ideas and concepts Integrates risk management and resilience based thinking Suitable for a variety of applications including engineering, finance and security.
Everyday we face decisions that carry an element of risk anduncertainty. The ability to analyze, predict, and prepare for thelevel of risk entailed by these decisions is, therefore, one of themost constant and vital skills needed for analysts, scientists andmanagers. Risk analysis can be defined as a systematic use of informationto identify hazards, threats and opportunities, as well as theircauses and consequences, and then express risk. In order tosuccessfully develop such a systematic use of information, thoseanalyzing the risk need to understand the fundamental concepts ofrisk analysis and be proficient in a variety of methods andtechniques. Risk Analysis adopts a practical, predictiveapproach and guides the reader through a number ofapplications. Risk Analysis: Provides an accessible and concise guide to performing riskanalysis in a wide variety of fields, with minimal prior knowledgerequired. Adopts a broad perspective on risk, with focus on predictionsand highlighting uncertainties beyond expected values andprobabilities, allowing a more flexible approach than traditionalstatistical analysis. Acknowledges that expected values and probabilities couldproduce poor predictions - surprises may occur. Emphasizes the planning and use of risk analyses, rather thanjust the risk analysis methods and techniques, including thestatistical analysis tools. Features many real-life case studies from a variety ofapplications and practical industry problems, including areas suchas security, business and economy, transport, oil & gas and ICT(Information and Communication Technology). Forms an ideal companion volume to Aven’s previous Wileytext Foundations of Risk Analysis. Professor Aven’s previous book Foundations of RiskAnalysis presented and discussed several risk analysisapproaches and recommended a predictive approach. This new textexpands upon this predictive approach, exploring further the riskanalysis principles, concepts, methods and models in an appliedformat. This book provides a useful and practical guide todecision-making, aimed at professionals within the risk analysisand risk management field.
A practical guide to the varied challenges presented in the ever-growing field of risk analysis. Risk Analysis presents an accessible and concise guide to performing risk analysis, in a wide variety of field, with minimal prior knowledge required. Forming an ideal companion volume to Aven's previous Wiley text Foundations of Risk Analysis, it provides clear recommendations and guidance in the planning, execution anduse of risk analysis. This new edition presents recent developments related to risk conceptualization, focusing on related issues on risk assessment and their application. New examples are also featured to clarify the reader's understanding in the application of risk analysis and the risk analysis process. Key features: Fully updated to include recent developments related to risk conceptualization and related issues on risk assessments and their applications. Emphasizes the decision making context of risk analysis rather than just computing probabilities Demonstrates how to carry out predictive risk analysis using a variety of case studies and examples. Written by an experienced expert in the field, in a style suitable for both industrial and academic audiences. This book is ideal for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and physical sciences. Managers facing decision making problems involving risk and uncertainty will also benefit from this book.
We all face risks in a variety of ways, as individuals, businesses and societies. The discipline of risk assessment and risk management is growing rapidly and there is an enormous drive for the implementation of risk assessment methods and risk management in organizations. There are great expectations that these tools provide suitable frameworks for obtaining high levels of performance and balance different concerns such as safety and costs. The analysis and management of risk are not straightforward. There are many challenges. The risk discipline is young and there area a number of ideas, perspectives and conceptions of risk out there. For example many analysts and researchers consider it appropriate to base their risk management policies on the use of expected values, which basically means that potential losses are multiplied with their associated consequences. However, the rationale for such a policy is questionable. A number of such common conceptions of risk are examined in the book, related to the risk concept, risk assessments, uncertainty analyses, risk perception, the precautionary principle, risk management and decision making under uncertainty. The Author discusses these concepts, their strenghts and weaknesses, and concludes that they are often better judged as misconceptions of risk than conceptions of risk. Key Features: Discusses common conceptions of risk with supporting examples. Provides recommendations and guidance to risk analysis and risk management. Relevant for all types of applications, including engineering and business. Presents the Author’s overall conclusions on the issues addressed throughout the book. All those working with risk-related problems need to understand the fundamental ideas and concepts of risk. Professionals in the field of risk, as well as researchers and graduate sutdents will benefit from this book. Policy makers and business people will also find this book of interest.
Quantitative risk assessments cannot eliminate risk, nor can they resolve tradeoffs. They can, however, guide principled risk management and reduction - if the quality of assessment is high and decision makers understand how to use it. This book builds a unifying scientific framework for discussing and evaluating the quality of risk assessments and whether they are fit for purpose. Uncertainty is a central topic. In practice, uncertainties about inputs are rarely reflected in assessments, with the result that many safety measures are considered unjustified. Other topics include the meaning of a probability, the use of probability models, the use of Bayesian ideas and techniques, and the use of risk assessment in a practical decision-making context. Written for professionals, as well as graduate students and researchers, the book assumes basic probability, statistics and risk assessment methods. Examples make concepts concrete, and three extended case studies show the scientific framework in action.
Risk science is becoming increasingly important as businesses, policymakers and public sector leaders are tasked with decision-making and investment using varying levels of knowledge and information. Risk Science: An Introduction explores the theory and practice of risk science, providing concepts and tools for understanding and acting under conditions of uncertainty. The chapters in this work cover the fundamental concepts, principles, approaches, methods and models for how to understand, assess, communicate, manage and govern risk. These topics are presented and examined in a way which details how they relate, for example, how to characterize and communicate risk with particular emphasis on reflecting uncertainties; how to distinguish risk perception and professional risk judgments; how to assess risk and guide decision-makers, especially for cases involving large uncertainties and value differences; and how to integrate risk assessment with resilience-based strategies. The text provides a variety of examples and case studies that relate to highly visible and relevant issues facing risk academics, practitioners and non-risk leaders who must make risk-related decisions. Presenting both the foundational and most recent advancements in the subject matter, this work particularly suits students of risk science courses at college and university level. The book also provides broader key reading for students and scholars in other domains, including business, engineering and public health.
Enterprise Risk Management: Advances on its Foundation and Practice relates the fundamental enterprise risk management (ERM) concepts and current generic risk assessment and management principles that have been influential in redefining the risk field over the last decade. It defines ERM with a particular focus on understanding the nexus between risk, uncertainty, knowledge and performance. The book argues that there is critical need for ERM concepts, principles and methods to adapt to the latest and most influential risk management developments, as there are several issues with outdated ERM theories and practices; problems include the inability to effectively and systematically balance both opportunity and downside performance, or relying too much on narrow probability-based perspectives for risk assessment and decision-making. It expands traditional loss-based risk principles into new and innovative performance-risk frameworks, and presents fundamental risk principles that have recently been developed by the Society for Risk Analysis (SRA). All relevant statistical and risk concepts are clearly explained and interpreted using minimal mathematical notation. The focus of the book is centered around ideas and principles, more than technicalities. The book is primarily intended for risk professionals, researchers and graduate students in the fields of engineering and business, and should also be of interest to executive managers and policy makers with some background in quantitative methods such as statistics.
This book provides a comprehensive demonstration of risk analysis as a distinct science covering risk understanding, assessment, perception, communication, management, governance and policy. It presents and discusses the key pillars of this science, and provides guidance on how to conduct high-quality risk analysis. The Science of Risk Analysis seeks to strengthen risk analysis as a field and science by summarizing and extending current work on the topic. It presents the foundation for a distinct risk field and science based on recent research, and explains the difference between applied risk analysis (to provide risk knowledge and tackle risk problems in relation to for example medicine, engineering, business or climate change) and generic risk analysis (on concepts, theories, frameworks, approaches, principles, methods and models to understand, assess, characterise, communicate, manage and govern risk). The book clarifies and describes key risk science concepts, and builds on recent foundational work conducted by the Society for Risk Analysis in order to provide new perspectives on science and risk analysis. The topics covered are accompanied by cases and examples relating to current issues throughout. This book is essential reading for risk analysis professionals, scientists, students and practitioners, and will also be of interest to scientists and practitioners from other fields who apply risk analysis in their work.
Quantitative risk assessments cannot eliminate risk, nor can they resolve trade-offs. They can, however, guide principled risk management and reduction - if the quality of assessment is high and decision makers understand how to use it. This book builds a unifying scientific framework for discussing and evaluating the quality of risk assessments and whether they are fit for purpose. Uncertainty is a central topic. In practice, uncertainties about inputs are rarely reflected in assessments, with the result that many safety measures are considered unjustified. Other topics include the meaning of a probability, the use of probability models, the use of Bayesian ideas and techniques, and the use of risk assessment in a practical decision-making context. Written for professionals, as well as graduate students and researchers, the book assumes basic probability, statistics and risk assessment methods. Examples make concepts concrete, and three extended case studies show the scientific framework in action.
This book presents a risk management framework designed to achieve better decisions and more desirable outcomes. It presents an in-depth discussion of some fundamental principles of risk management related to the use of expected values, uncertainty handling, and risk acceptance criteria. Several examples from the offshore petroleum industry are included to illustrate the use of the framework, but it can also be applied in other areas.
Risk is a popular topic in many sciences - in natural, medical, statistical, engineering, social, economic and legal disciplines. Yet, no single discipline can grasp the full meaning of risk. Investigating risk requires a multidisciplinary approach. The authors, coming from two very different disciplinary traditions, meet this challenge by building bridges between the engineering, the statistical and the social science perspectives. The book provides a comprehensive, accessible and concise guide to risk assessment, management and governance. A basic pillar for the book is the risk governance framework proposed by the International Risk Governance Council (IRGC). This framework offers a comprehensive means of integrating risk identification, assessment, management and communication. The authors develop and explain new insights and add substance to the various elements of the framework. The theoretical analysis is illustrated by several examples from different areas of applications.
This book explores the syntactic structures of Mainland Scandinavian, a term that covers the Northern Germanic languages spoken in Denmark, Norway, Sweden, and parts of Finland. The continuum of mutually intelligible standard languages, regional varieties, and dialects stretching from southern Jutland to eastern Finland share many syntactic patterns and features, but also present interesting syntactic differences. In this volume, Jan Terje Faarlund discusses the main syntactic features of the national languages, alongside the most widespread or typologically interesting features of the non-standard varieties. Each topic is illustrated with examples drawn from reference grammars, research literature, corpora of various sorts, and the author's own research. The framework is current generative grammar, but the volume is descriptive in nature, with technical formalities and theoretical discussion kept to a minimum. It will hence be a valuable reference for students and researchers working on any Scandinavian language, as well as for syntacticians and typologists interested in Scandinavian facts and data without necessarily being able to read Scandinavian.
The Nile today plays a crucial role in the economics, politics and cultural life of ten countries and their more than 300 million inhabitants. No other international river basin has a longer, more complex and eventful history than the Nile. In telling the detailed story of the hydropolitics of the Nile valley in a period during which the conceptualisation, use and planning of the waters were revolutionised, and many of the most famous politicians of the twentieth century Churchill, Mussolini, Eisenhower, Eden, Nasser and Haile Selassie played active parts in the Nile game, this work will stand as a case study of a much more general and acute question: the political ecology of trans-national river basins.
Risk science is becoming increasingly important as businesses, policymakers and public sector leaders are tasked with decision-making and investment using varying levels of knowledge and information. Risk Science: An Introduction explores the theory and practice of risk science, providing concepts and tools for understanding and acting under conditions of uncertainty. The chapters in this work cover the fundamental concepts, principles, approaches, methods and models for how to understand, assess, communicate, manage and govern risk. These topics are presented and examined in a way which details how they relate, for example, how to characterize and communicate risk with particular emphasis on reflecting uncertainties; how to distinguish risk perception and professional risk judgments; how to assess risk and guide decision-makers, especially for cases involving large uncertainties and value differences; and how to integrate risk assessment with resilience-based strategies. The text provides a variety of examples and case studies that relate to highly visible and relevant issues facing risk academics, practitioners and non-risk leaders who must make risk-related decisions. Presenting both the foundational and most recent advancements in the subject matter, this work particularly suits students of risk science courses at college and university level. The book also provides broader key reading for students and scholars in other domains, including business, engineering and public health.
Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.
Enterprise Risk Management: Advances on its Foundation and Practice relates the fundamental enterprise risk management (ERM) concepts and current generic risk assessment and management principles that have been influential in redefining the risk field over the last decade. It defines ERM with a particular focus on understanding the nexus between risk, uncertainty, knowledge and performance. The book argues that there is critical need for ERM concepts, principles and methods to adapt to the latest and most influential risk management developments, as there are several issues with outdated ERM theories and practices; problems include the inability to effectively and systematically balance both opportunity and downside performance, or relying too much on narrow probability-based perspectives for risk assessment and decision-making. It expands traditional loss-based risk principles into new and innovative performance-risk frameworks, and presents fundamental risk principles that have recently been developed by the Society for Risk Analysis (SRA). All relevant statistical and risk concepts are clearly explained and interpreted using minimal mathematical notation. The focus of the book is centered around ideas and principles, more than technicalities. The book is primarily intended for risk professionals, researchers and graduate students in the fields of engineering and business, and should also be of interest to executive managers and policy makers with some background in quantitative methods such as statistics.
Foundations of Risk Analysis presents the issues core to risk analysis – understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems. The author provides the readers with the knowledge and basic thinking they require to successfully manage risk and uncertainty to support decision making. This updated edition reflects recent developments on risk and uncertainty concepts, representations and treatment. New material in Foundations of Risk Analysis includes: An up to date presentation of how to understand, define and describe risk based on research carried out in recent years. A new definition of the concept of vulnerability consistent with the understanding of risk. Reflections on the need for seeing beyond probabilities to measure/describe uncertainties. A presentation and discussion of a method for assessing the importance of assumptions (uncertainty factors) in the background knowledge that the subjective probabilities are based on A brief introduction to approaches that produce interval (imprecise) probabilities instead of exact probabilities. In addition the new version provides a number of other improvements, for example, concerning the use of cost-benefit analyses and the As Low As Reasonably Practicable (ALARP) principle. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.
Everyday we face decisions that carry an element of risk and uncertainty. The ability to analyse, communicate and control the level of risk entailed by these decisions remains one of the most pressing challenges to the analyst, scientist and manager. This book presents the foundational issues in risk analysis ? expressing risk, understanding what risk means, building risk models, addressing uncertainty, and applying probability models to real problems. The principal aim of the book is to give the reader the knowledge and basic thinking they require to approach risk and uncertainty to support decision making. Presents a statistical framework for dealing with risk and uncertainty. Includes detailed coverage of building and applying risk models and methods. Offers new perspectives on risk, risk assessment and the use of parametric probability models. Highlights a number of applications from business and industry. Adopts a conceptual approach based on elementary probability calculus and statistical theory. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.
A comprehensive up-to-date presentation of some of the classical areas of reliability, based on a more advanced probabilistic framework using the modern theory of stochastic processes. This framework allows analysts to formulate general failure models, establish formulae for computing various performance measures, as well as determine how to identify optimal replacement policies in complex situations.
The field of risk science continues to learn from the long history of events to develop principles and practices that enable individuals, organizations, and societies to understand and manage future risk. Reflecting on these histories reminds us that risk and uncertainty are prevalent, yet it remains important to consider what is on the horizon: the possibility of future events, the consequences of those events, our vulnerability to those events, and how to recover from those events. Decoding Black Swans and Other Historic Risk Events offers a guide to understanding risk events and how to act before they occur. This book explores past risk events and analyzes how risk science principles apply to those events and studies whether current risk science concepts and approaches could potentially have avoided, reduced the impact, or supported recovery following the risk event. New insights are obtained by applying recent research progress in understanding and managing risk, considering aspects including quality of evidence, information, and misinformation in risk studies. The analysis results are used to identify how risk science approaches contribute to the overall management of risk and societal safety, and where improvements can be obtained, allowing the reader to possess a toolkit for identifying and planning for unsafe events. This title will be a critical read for professionals in the fields of occupational health and safety, risk management, civil engineering, mechanical engineering, energy, marine engineering, environmental engineering, business and management, and healthcare.
Quantitative risk assessments cannot eliminate risk, nor can they resolve trade-offs. They can, however, guide principled risk management and reduction - if the quality of assessment is high and decision makers understand how to use it. This book builds a unifying scientific framework for discussing and evaluating the quality of risk assessments and whether they are fit for purpose. Uncertainty is a central topic. In practice, uncertainties about inputs are rarely reflected in assessments, with the result that many safety measures are considered unjustified. Other topics include the meaning of a probability, the use of probability models, the use of Bayesian ideas and techniques, and the use of risk assessment in a practical decision-making context. Written for professionals, as well as graduate students and researchers, the book assumes basic probability, statistics and risk assessment methods. Examples make concepts concrete, and three extended case studies show the scientific framework in action"--
Risk is the single most prevalent and enduring factor that influences every individual, organization, and society. People often seek protection from negative risk events, but also seek to take advantage of opportunities arising from positive risk events. We may feel overwhelmed by messages encountered in daily interactions with media and society, contributing to a sense of ambiguity over how to act in response to risk-related information and misinformation. We seek to leverage evidence and reason to find our own balance between both positive and negative outcomes in an uncertain world. This groundbreaking book delivers practical concepts and tools that empower readers to leverage innovations in risk science to improve their abilities to interpret, assess, communicate, and handle risk. It provides a practical non-quantitative approach to understanding the risk and making better decisions involving risk. Think RISK covers several key themes in risk science: a) the main goals and strategies for understanding and managing risk; b) how readers can inform their risk stances by considering their own individual values and mission; c) the difference between risk and safety, and how that difference is critical for managing the risk; d) the role of psychological factors when understanding and managing the risk; e) the role of communication when understanding and managing the risk; and f) the general importance and incentives for effectively understanding and managing the risk. Written for business professionals in all private and public sectors, this book will also be relevant to non-business professionals such as medical practitioners and policymakers and would be an ideal fit for executive education and seminar-style courses in universities, corporate book clubs, and training seminars. Because it’s based on foundational and scientifically accepted ideas and principles, the book should remain relevant for many years.
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