Misconceptions of Risk

Description

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.Content: Chapter 1 Risk is Equal to the Expected Value (pages 1–16): Chapter 2 Risk is a Probability or Probability Distribution (pages 17–33): Chapter 3 Risk Equals a Probability Distribution Quantile (Value?at?Risk) (pages 35–41): Chapter 4 Risk Equals Uncertainty (pages 43–53): Chapter 5 Risk is Equal to an Event (pages 55–60): Chapter 6 Risk Equals Expected Disutility (pages 61–70): Chapter 7 Risk is Restricted to the Case of Objective Probabilities (pages 71–81): Chapter 8 Risk is the same as Risk Perception (pages 83–91): Chapter 9 Risk Relates to Negative Consequences Only (pages 93–96): Chapter 10 Risk is Determined by the Historical Data (pages 97–106): Chapter 11 Risk Assessments Produce an Objective Risk Picture (pages 107–113): Chapter 12 There are Large Inherent Uncertainties in Risk Analyses (pages 115–133): Chapter 13 Model Uncertainty should be Quantified (pages 135–144): Chapter 14 It is Meaningful and Useful to Distinguish between Stochastic and Epistemic Uncertainties (pages 145–148): Chapter 15 Bayesian Analysis is based on the use of Probability Models and Bayesian Updating (pages 149–165): Chapter 16 Sensitivity Analysis is a Type of Uncertainty Analysis (pages 167–178): Chapter 17 The Main Objective of Risk Management is Risk Reduction (pages 179–189): Chapter 18 Decision?Making under Uncertainty should be Based on Science (Analysis) (pages 191–213): Chapter 19 The Precautionary Principle and Risk Management cannot be Meaningfully Integrated (pages 215–226): Chapter 20 Conclusions (pages 227–237):