Making Hard Decisions with the DecisionTools Suite 3rd Edition by Robert Clemen, Terence Reilly ISBN 1285708348 9781285708348

Ch 1: Introduction to Decision Analysis

Introduction

Why Are Decisions Hard?

Why Study Decision Analysis?

Subjective Judgments and Decision Making

The Decision Analysis Process

Requisite Decision Models

Where Is Decision Analysis Used?

Where Does the Software Fit In?

Where Are We Going from Here?

Summary

Questions and Problems

Case Studies

References

Epilogue

Section 1: Modeling Decisions

Ch 2: Elements of Decision Problems

Introduction

Values and Objectives

Decisions to Make

Uncertain Events

Consequences

Summary

Questions and Problems

Case Studies

References

Epilogue

Ch 3: Structuring Decisions

Introduction

Structuring Values

Fundamental and Means Objectives

Getting the Decision Context Right

Structuring Decisions: Influence Diagrams

Influence Diagrams and the Fundamental Objectives Hierarchy

Using Arcs to Represent Relationships

Some Basic Influence Diagrams

Constructing an Influence Diagram

Structuring Decisions: Decision Trees

Decision Trees and the Objectives Hierarchy

Basic Decision Trees

Decision Trees and Influence Diagrams Compared

Decision Details: Defining Elements of the Decision

More Decision Details: Cash Flows and Probabilities

Defining Measurement Scales for Fundamental Objectives

Using PrecisionTree for Structuring Decisions

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 4: Making Choices

Introduction

Decision Trees and Expected Monetary Value

Solving Influence Diagrams: Overview

Risk Profiles

Dominance: An Alternative to EMV

Making Decisions with Multiple Objectives

Decision Analysis Using PrecisionTree

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 5: Sensitivity Analysis

Introduction

Sensitivity Analysis: A Modeling Approach

Problem Identification and Structure

One-Way Sensitivity Analysis: Sensitivity Graphs

One-Way Sensitivity Analysis: Tornado Diagrams

Dominance Considerations

Two-Way Sensitivity Analysis

Sensitivity to Probabilities

Sensitivity to Probabilities—House-hunting

Sensitivity Analysis in Action

Sensitivity Analysis: A Built-In Irony

Sensitivity Analysis Using Excel® and PrecisionTree

Summary

Exercises

Questions and Problems

Case Studies

References

Ch 6: Organizational Use of Decision Analysis

Introduction

The Decision-Making Process

Organizational Issues in Enhancing Creativity and Enabling Choices

Developing Alternatives: Understanding the Creative Process

Value-Focused Thinking for Creating Alternatives

Strategy Tables

Managing and Monitoring the Six-Step Decision Process

Summary

Questions and Problems

Case Study

References

Epilogue

Section 1 Cases

Section 2: Modeling Uncertainty

Ch 7: Probability Basics

Introduction

A Little Probability Theory

Venn Diagrams

More Probability Formulas

PrecisionTree® and Bayes’ Theorem

Uncertain Quantities

Oil Wildcatting

John Hinckley’s Trial

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 8: Subjective Probability

Introduction

Uncertainty and Public Policy

Probability: A Subjective Interpretation

Assessing Discrete Probabilities

Assessing Continuous Probabilities

Heuristics and Biases in Probability Assessment

Decomposition and Probability Assessment

Experts and Probability Assessment: Pulling It All Together

Constructing Distributions Using @RISK

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 9: Theoretical Probability Models

Introduction

The Binomial Distribution

The Poisson Distribution

The Exponential Distribution

The Triangular Distribution

The Beta Distribution

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 10: Using Data

Introduction

Using Data to Construct Probability Distributions

Using Data to Fit Theoretical Probability Models

Using @RISK to Fit Distributions to Data

Using Data to Model Relationships

The Regression Approach

Summary

Exercises

Questions and Problems

Case Study

References

Epilogue: Solar Trash Compactors

Ch 11: Simulation

Introduction

Mechanics of Simulation

Sampling from Probability Distributions

Simulation Models

Simulating the Model

Simulation vs. Decision Trees

Examples of Simulation Models

Simulating Spreadsheet Models Using @RISK

Correlations Among Random Variables

Sequential Simulations

Simulation, Decision Trees, and Influence Diagrams

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 12: Value of Information

Introduction

Value of Information: Some Basic Ideas

Expected Value of Perfect Information

Expected Value of Imperfect Information

Value of Information in Complex Problems

Value of Information, Sensitivity Analysis, and Structuring

Value of Information and Nonmonetary Objectives

Value of Information and Experts

Calculating EVPI and EVII with PrecisionTree

Summary

Exercises

Questions and Problems

Case Studies

References

Ch 13: Real Options

Introduction

Option Basics

Real Options

An Approach to Valuing Real Options

Optionality and Proteiz

Valuing the Abandon Option

Valuing the Scale-Up Option

Review of the Approach for Continuous Uncertainties

Comparison with Real Option Valuation from Financial Theory

What Discount Rate?

Finding Optimal Decision Values Using RISK Optimizer

Summary

Exercises

Questions and Problems

References

Section 2 Cases

Section 3: Modeling Preferences

Ch 14: Risk Attitudes

Introduction

Risk

Risk Attitudes

Investing in the Stock Market, Revisited

Expected Utility, Certainty Equivalents, and Risk Premiums

Keeping Terms Straight

Utility Function Assessment

Risk Tolerance and the Exponential Utility Function

Pitfalls in Utility Assessment: Biases in the CE, PE, and TO Methods

Modeling Preferences Using PrecisionTree

Decreasing and Constant Risk Aversion

Some Caveats

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 15: Utility Axioms, Paradoxes, and Implications

Introduction

Axioms for Expected Utility

Paradoxes

Hedonic Framing

Failure to Ignore Sunk Costs

Status Quo Bias

Implications

Implications for Utility Assessment

A Final Perspective

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 16: Conflicting Objectives I: Fundamental Objectives and the Additive Utility Function

Introduction

Objectives and Attributes

Trading Off Conflicting Objectives: The Basics

The Additive Utility Function

Assessing Individual Utility Functions

Assessing Weights

Biases and Inconsistencies in Weight Assessment

Keeping Concepts Straight: Certainty versus Uncertainty

An Example: Library Choices

Using Software for Multiple-Objective Decisions

Summary

Exercises

Questions and Problems

Case Studies

References

Epilogue

Ch 17: Conflicting Objectives II: Multiattribute Utility Models with Interactions

Introduction

Multiattribute Utility Functions: Direct Assessment

Independence Conditions

Determining Whether Independence Exists

Additive Independence

Substitutes and Complements

Assessing a Two-Attribute Utility Function

When Independence Fails

Multiattribute Utility in Action: BC Hydro

Summary

Exercises

Questions and Problems

Case Study

References

Epilogue

Section 3 Cases

Ch 18: Conclusion and Further Reading

Introduction

A Decision-Analysis Reading List

Author Index

Subject Index