Experts, despite their importance and value, can be double-edged swords. They can make valuable contributions from their deep base of knowledge, but those contributions may also contain their own biases and pet theories. Therefore, selecting experts, eliciting their opinions, and aggregating their opinions must be performed and handled carefully, with full recognition of the uncertainties inherent in those opinions.
Elicitation of Expert Opinions for Uncertainty and Risks illuminates those uncertainties and builds a foundation of philosophy, background, methods, and guidelines that helps its readers effectively execute the elicitation process. Based on the first-hand experiences of the author, the book is filled with illustrations, examples, case studies, and applications that demonstrate not only the methods and successes of expert opinion elicitation, but also its pitfalls and failures.
Studies show that in the future, analysts, engineers, and scientists will need to solve ever more complex problems and reach decisions with limited resources. This will lead to an increased reliance on the proper treatment of uncertainty and on the use of expert opinions. Elicitation of Expert Opinions for Uncertainty and Risks will help prepare you to better understand knowledge and ignorance, to successfully elicit expert opinions, to select appropriate expressions of those opinions, and to use various methods to model and aggregate opinions.
Elicitation of Expert Opinions for Uncertainty and Risks| Bilal M. Ayyub (Author)| CRC Press
Table of Contents
Chapter 1: Knowledge and ignorance
Information abundance and ignorance, The nature of knowledge, Basic terminology and definitions, Absolute reality and absolute knowledge, Historical developments and perspectives, Knowledge, information, and opinions, Cognition and cognitive science, Time and its asymmetry, Defining ignorance in the context of knowledge, Human knowledge and ignorance, Classifying ignorance, Ignorance hierarchy, Exercise problems.
Chapter 2: Information-based system definition
Introduction, System definition models, Perspectives for system definition, Requirements and work breakdown structure, Process modeling method, Black-box method, State-based method, Component integration method, Decision analysis method, Hierarchical definitions of systems, Introduction, Knowledge and information hierarchy, Models for ignorance and uncertainty types, Mathematical theories for ignorance types, Information uncertainty in engineering systems, System complexity, Exercise problems.
Chapter 3: Experts, opinions, and elicitation methods
Introduction, Experts and expert opinions, Historical background, Delphi method, Scenario analysis, Scientific heuristics, Rational consensus, Elicitation methods, Indirect elicitation, Direct method, Parametric estimation, Standards for educational and psychological testing, Methods of social research, Focus groups, Exercise problems.
Chapter 4: Expressing and modeling expert opinions
Introduction, Set theory, Sets and events, Fundamentals of classical set theory, Fundamentals of fuzzy sets and operations, Fundamental of rough sets, Monotone measures, Definition of monotone measures, Classifying monotone measures, Evidence theory, Probability theory, Possibility theory, Exercise problems.
Chapter 5: Consensus and aggregating expert opinions
Introduction, Methods of scoring of expert opinions, Self scoring, Collective scoring, Uncertainty measures, Types of uncertainty measures, Nonspecificity measures, Entropy-like measures, Fuzziness measure, Other measures, Combining expert opinions, Consensus combination of opinions, Percentiles for combining opinions, Weighted combinations of opinions, Uncertainty-based criteria for combining expert opinions, Opinion aggregation using interval analysis and fuzzy arithmetic, Opinion aggregation using Dempster's rule of combination, Demonstrative examples of aggregating expert opinions, Exercise problems.
Chapter 6: Guidance on expert-opinion elicitation
Introduction and terminology, Theoretical bases, Terminology, Classification of issues, study levels, experts, and process outcomes, Process definition, Need identification for expert-opinion elicitation, Selection of study level and study leader, Selection of peer reviewers and experts, Selection of peer reviewers, Identification and selection of experts, Items needed by experts and reviewers before the expert-opinion elicitation meeting, Identification, selection, and development of technical issues, Elicitation of opinions, Issue familiarization of experts, Training of experts, Elicitation and collection of opinions, Aggregation and presentation of results, Group interaction, discussion, and revision by experts, Documentation and communication, Exercise problems.
Chapter 7: Applications of expert-opinion elicitation
Introduction, Assessment of occurrence probabilities, Cargo elevators onboard ships, Navigation locks, Economic consequences of floods, Background, The Feather River Basin, Example issues and results.
Bibliography
Index
LINK FOR THE BOOK
