Buch, Englisch, 456 Seiten, Format (B × H): 178 mm x 254 mm
Decision Making Under Uncertainty
Buch, Englisch, 456 Seiten, Format (B × H): 178 mm x 254 mm
ISBN: 978-1-041-37094-9
Verlag: CRC Press
Risk analysis has become an essential tool for addressing complex problems in fields ranging from engineering, public health, food safety, environmental management, national security, finance, and business. Yet many professionals still struggle with the central challenge of the discipline—not estimating risk, but making sound decisions under uncertainty. This third edition of Principles of Risk Analysis: Decision Making Under Uncertainty presents a practical, integrated framework for using risk analysis to support better decisions rather than simply producing better analyses.
Blending theory with decades of professional practice, Charles Yoe guides readers through the complete risk analysis process, including risk assessment, risk management, risk communication, governance, quantitative modeling, probability, uncertainty analysis, Monte Carlo simulation, sensitivity analysis, decision making, risk perception, and communication. Throughout, the emphasis remains on identifying the uncertainties that matter, understanding their implications, and translating technical analyses into decisions that are robust, transparent, and defensible.
Key features:
- A decision-centered approach that integrates risk assessment, management, communication, and governance.
- Practical methods for characterizing, quantifying, and communicating uncertainty.
- Step-by-step guidance for developing quantitative risk assessment models using probability and Monte Carlo simulation.
- Modern approaches to scenario analysis, sensitivity analysis, adaptive decision making, and robust decisions.
- Strategies for communicating uncertainty through effective messages, visualizations, and storytelling.
- Numerous examples, case studies, figures, and practical guidance drawn from real-world applications.
Written for graduate students, researchers, analysts, consultants, regulators, and decision makers across a wide range of disciplines, this book provides both a comprehensive introduction and a practical reference for anyone seeking to make better decisions in the face of uncertainty.
Zielgruppe
Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Preface Acknowledgements Part I: Introduction-What Is Risk Analysis? Chapter 1: A Quick Start 1.0 The Reason for Risk 1.1 Two Kinds of Uncertainty 1.2 A Working Vocabulary (For Now) 1.3 Organization of This Book 1.4 Three Things to Remember Chapter 2. The Basics 2.1 Risk 2.2 The Language Is Messy 2.3 Beyond Definitions: The Context and Dimensions of Risk 2.4 What Is Risk Analysis? 2.5 Risk Management 2.6 Risk Assessment 2.7 Risk Communication 2.8 Risk Governance 2.9 Why Do Risk Analysis? 2.10 A Brief Historical Perspective on Risk Analysis 2.11 Revisiting Figure 2.1 2.11 Three Things to Remember 2.12 References Chapter 3. Risk Management 3.1 Introduction 3.2 The Model 3.3 Identifying Risks 3.4 Risk Estimation 3.4 Risk Evaluation 3.5 Risk Control 3.6 Risk Monitoring 3.7 Risk Communication 3.8 Risk Management Models 3.9 Three Things to Remember 3.10 References Chapter 4: Risk Assessment 4.1 Introduction 4.2 Risk Assessment Defined 4.3 Risk Assessment Activities 4.4 Risk Assessment Models 4.5 Three Things to Remember 4.6 References Chapter 5: Risk Communication 5.1 Introduction 5.2 Definitions 5.3 Internal Risk Communication 5.4 External Risk Communication 5.5 Three Things to Remember 5.6 References Chapter 6: Risk Governance 6.1 Introduction 6.2 Consent 6.3 Risk Governance at a Glance 6.4 The Core Parts of Risk Governance 6.5 How Consideration of Consent Changes the Risk Manager’s Job 6.6 Three Things to Remember 6.7 References Chapter 7: Enterprise Risk Management 7.1 Introduction 7.2 What Is Enterprise Risk Management? 7.3 Why ERM Emerged 7.4 The Evolution of Enterprise Risks 7.5 Core ERM Concepts 7.6 Risk Appetite and Decision Making 7.7 ERM Governance and Risk Culture 7.8 ISO 31000 Risk Management Guidelines 7.9 COSO Enterprise Risk Management Framework 7.10 ERM in Practice 7.11 Strengths, Challenges and Limitations of ERM 7.12 ERM Beyond the Private Sector 7.13 Three Things to Remember 7.14 References Part II: Foundations-Thinking Well Under Uncertainty Chapter 8: Uncertainty 8.1 Introduction 8.2 The 3:17 p.m. Call 8.3 Separating What We Know from What We Do Not Know 8.4 Three Levels of Uncertainty 8.5 Two Types of Uncertainty 8.6 Deep Uncertainty 8.7 Types of Uncertainty 8.8 Being Intentional about Uncertainty 8.9 Three Things to Remember 8.10 References Chapter 9: Human Judgment Under Uncertainty 9.1 Introduction 9.2 Two Modes of Thinking 9.3 Distorting Reality 9.4 Thinking Lazily 9.5 Misjudging Probability 9.6 Rushing to Closure 9.7 Why Risk Analysis Matters 9.8 The Challenge of Thinking Differently 9.9 Three Things to Remember 9.10 References Chapter 10: Probability and Statistics Review for Risk Assessors 10.1 Introduction 10.2 Probability as a Decision Input 10.3 Two Schools of Thought 10.4 Expressing Probability 10.5 How Probabilities Are Obtained in Practice 10.6 Examples of Each Probability 10.7 Working with Probabilities 10.8 Why You Need to Know These Probability Rules 10.9 Statistics as Evidence for Decision Making 10.10 Describing Data 10.11 Revealing Variability and Uncertainty 10.12 Confidence Intervals: Quantifying What We Don't Know 10.13 Hypothesis Testing: How Strong Is the Evidence? 10.14 Regression and Correlation 10.15 Prediction Uncertainty 10.16 Three Things to Remember 10.17 References Chapter 11: Characterizing Uncertainty Through Expert Elicitation 11.1 Introduction 11.2 Personal Opinion, Professional Opinion, and Expert Judgment 11.3 What Kinds of Uncertain Values? 11.4 Subjective Probability Distributions 11.5 The Elicitation Protocol 11.6 Eliciting Subjective Probability Distributions 11.7 Combining Expert Judgments 11.8 Cognitive Biases and Behavioral Effects in Expert Elicitation 11.9 Supportive Roles for AI in Elicitation 11.10 Three Things to Remember 11.11 References Chapter 12: Choosing A Probability Distribution: A Structured Selection Process 12.1 Introduction 12.2 Foundations 12.3 Selecting a Distribution 12.4 Example of a Judgment Driven Parametric Distribution 12.5 Example of Distribution Choice with Some Data 12.6 A Dozen Useful Probability Distributions for Risk Assessors 12.7 Three Things to Remember 12.8 References Chapter 13: Economics of Risk Management 13.1 Introduction 13.2 Economics for Risk Managers 13.3 Economics and Decision Making 13.4 Economic Analysis 13.5 Think Like an Economist 13.6 Three Things to Remember 13.7 References Part III: The Risk Assessor’s Toolbox-Conducting Risk Assessments That Improve Decisions Chapter 14: From Risk Identification to Quantitative Model 14.1 Introduction 14.2 Types of Models Used in Risk Analysis 14.3 Decision Example 14.4 How to Build a Quantitative Model 14.5 Simulation Models 14.6 Building Risk Models in Spreadsheets 14.7 Three Things to Remember 14.8 References Chapter 15: (Probabilistic) Scenario Analysis 15.1 Introduction 15.2 Core Structural Scenarios 15.3 Types of Scenario Analysis 15.4 Scenario Comparisons 15.5 Tools for Constructing Scenarios 15.6 Adding Probability to Scenarios 15.7 An Example 15.8 Value of Scenarios 15.9 Three Things to Remember 15.10 References Chapter 16: Monte Carlo Process 16.1 Introduction 16.2 Why Simulate? 16.3 Background 16.4 A Two-Step Process 16.5 How Many Iterations? 16.6 Sampling Method 16.7 An Illustration 16.8 Interpreting Monte Carlo Output 16.9 Common Misuses of Monte Carlo 16.10 Summary and Look Forward 16.11 References Chapter 17: Sensitivity Analysis 17.1 Introduction 17.2 Global vs. Local Sensitivity Analysis—What's the Difference and Why It Matters 17.3 Qualitative Sensitivity Analysis 17.4 Quantitative Sensitivity Analysis 17.5 Sensitivity to Model Structure (Model-Form Sensitivity) 17.6 Pitfalls of Sensitivity Analysis 17.7 Three Things to Remember 17.8 References Chapter 18: Choosing the Right Risk Assessment Tool 18.1 Introduction 18.2 Understand the Right Problem 18.3 Understand How Things Fail 18.4 Imagine Futures 18.5 Estimate Consequences 18.6 Compare Alternatives 18.7 Three Things to Remember Part IV: Deciding and Communicating—Making Risk Analysis Matter Chapter 19: Presenting and Using Assessment Results 19.1 Introduction 19.2 Understand Your Assessment Output Data Before You Explain It 19.3 Examine the Quantities 19.4 Examine the Probabilities 19.5 Examine Relationships 19.6 Data Visualizations 19.7 Common Misinterpretations of Risk Graphics and Numbers 19.8 Three Things to Remember 19.9 References Chapter 20: Using Uncertainty to Make Better Decisions 20.1 Introduction 20.2 Decision Makers Struggle With Uncertainty 20.3 From Fixed to Adaptive Decisions 20.4 Establishing the Acceptable Level of Risk 20.5 Using Data to Decide 20.6 From Prediction to Robustness 20.7 Risk Management as a Tool to Improve Outcomes 20.8 Operationalize Adaptive Decisions 20.9 Decision Making Without Probability 20.10 Robust and Adaptive Decision Making 20.11 Three Things to Remember 20.12 References Chapter 21: Risk Perception: Social, Cultural, and Psychological Contexts of Risk 21.1 Introduction 21.2 Why Risk Perception Matters for Decision Making Under Uncertainty 21.3 Psychological Foundations of Risk Perception 21.4 Cultural and Social Perspectives on Risk 21.5 Risk Perception and Risk Governance 21.6 Implications for Risk Communication 21.7 Bridge to Communication 21.8 Three Things to Remember 21.9 References Chapter 22: Risk Message Development 22.1 Introduction 22.2 How People Actually Process Risk Messages 22.3 A Risk Message Development Process 22.4 Know Your Intended Audience 22.5 Begin with the Desired Action 22.6 Framing Risk Communication 22.7 Preparing Risk Messages in Advance 22.8 The 27/9/3 Rule 22.9 Communicating Uncertainty 22.10 Using AI Wisely for Risk Message Development 22.11 Three Things to Remember 22.12 References Chapter 23: From Using Uncertainty to Telling the Story 23.1 Introduction 23.2 Story: The Bridge from Reports to Decisions 23.3 The Problem with Reports 23.4 What Do We Mean by a “Story”? 23.5 The Core Idea: Stories Provide Structure for Uncertainty 23.6 How to Write a Good Risk Story 23.7 What Makes a Good Story? Illustrated by Snow White 23.8 RIDM Stories 23.9 Beyond the Written Word 23.10 Three Things to Remember 23.11 References
