## Advances in Decision Analysis: From Foundations to ApplicationsWard Edwards, Ralph F. Miles Jr., Detlof von Winterfeldt Decision analysis is a prescriptive theory that aids individuals or groups confronted with complex problems in a wide variety of contexts. By framing issues, identifying risks, eliciting stakeholder preferences, and suggesting alternative approaches, decision analysts can offer workable solutions in domains such as the environment, health and medicine, engineering and operations research, and public policy. This book is a mixture of historical and forward-looking essays on key topics in decision analysis. Part I covers the history and foundations of decision analysis. Part II discusses structuring decision problems, including the development of objectives and their attributes, and influence diagrams. Part III discusses probabilities and their elicitation and Bayes nets. Part IV discusses additive and multiplicative utilities, risk preferences, and 'option pricing' methods. Part V discusses risk analysis. Part VI puts decision analysis in a behavioral and organizational context. Part VII presents case studies of applications. |

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### Contents

1 | |

13 | |

3The Foundations of Decision Analysis Revisited | 32 |

A Personal Account of How It Got Started | 57 |

Reﬂections on the Contributions of Ward Edwards to Decision | 71 |

STRUCTURING DECISION PROBLEMS | 81 |

HORA College of Business and Economics University of Hawaii | 95 |

Developing Objectives and Attributes | 104 |

JIANMIN JIA Faculty of Business Administration The Chinese University | 286 |

The Engineering RiskAnalysis Method and Some Applications | 302 |

Health Risk Analysis for RiskManagement DecisionMaking | 325 |

DECISION ANALYSIS IN A BEHAVIORAL | 351 |

Decision Conferencing | 375 |

Resource Allocation Decisions | 400 |

From Decision Analysis to the Decision Organization | 419 |

Building Decision Competency in Organizations | 451 |

PROBABILITIES AND BAYES NETS | 129 |

Aggregating Probability Distributions | 154 |

Model Building with Belief Networks and Inﬂuence Diagrams | 177 |

A Bayesian Approach to Learning Causal Networks | 202 |

UTILITIES | 221 |

Extensions of the Subjective Expected Utility Model | 253 |

PARTV RISK ANALYSIS | 279 |

### Other editions - View all

Advances in Decision Analysis: From Foundations to Applications Ward Edwards,Ralph F. Miles Jr.,Detlof von Winterfeldt No preview available - 2007 |

Advances in Decision Analysis: From Foundations to Applications Ward Edwards,Ralph F. Miles Jr.,Detlof von Winterfeldt No preview available - 2007 |

### Common terms and phrases

alternatives applications approach assessment attribute Bayesian Bayesian networks Bayesian statistics behavior belief network beneﬁts biases Cambridge University Press causal network choice Clemen combination conﬂict consequences cost decision analysis decision conferences decision maker decision problem decision theory decision tree decision-analysis deﬁned deﬁnition developed difﬁcult discussion effects equivalent estimates evaluation example expected utility experts ﬁeld ﬁnancial ﬁnd ﬁrst ﬁve forecasts fractiles fundamental objectives game theory Howard identiﬁed individual inﬂuence diagram issues Journal judgments Kahneman Keeney linear Management Science mathematical Matheson measure methods multiattribute negotiation Neuroeconomics node nuclear Operations Research options organization organizational outage outcomes parameters plutonium preferences probabilistic probability distributions proﬁt Raiffa reactor reﬂect represent requires risk analysis risk aversion shown in Figure signiﬁcant speciﬁc statistics strategy structure subjective probability sufﬁcient tritium Tversky uncertainty utility function utility theory value functions value model variables weights Winkler Winterfeldt York

### Popular passages

Page 18 - The theory of chance consists in reducing all the events of the same kind to a certain number of cases equally possible, that is to say, to such as we may be equally undecided about in regard to their existence, and in determining the number of cases favourable to the event whose probability is sought.

Page 19 - BELIEF The subject of our inquiry is the logic of partial belief, and I do not think we can carry it far unless we have at least an approximate notion of what partial belief is, and how, if at all, it can be measured. It will not be very enlightening to be told that in such circumstances it would be rational to believe a proposition to the extent of f unless we know what sort of a belief in it that means. We must therefore try to develop a purely psychological method of measuring belief.

Page 20 - Research is a scientific method of providing executive departments with a quantitative basis for decisions regarding the operations under their control.

Page 18 - We state here explicitly: The rational concept of probability, which is the only basis of probability calculus, applies only to problems in which either the same event repeats itself again and again, or a great number of uniform elements are involved at the same time.