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Wiley Handbooks in OPERATIONS RESEARCH AND MANAGEMENT SCIENCE
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Wiley Handbooks in OPERATIONS RESEARCH AND MANAGEMENT SCIENCE
by Eric R. Johnson, PhD, Steven N. Tani, PhD,, Terry Bresnick, MBA, Gregory S. Parn
Handbook of Decision Analysis
Cover
Wiley Handbooks in OPERATIONS RESEARCH AND MANAGEMENT SCIENCE
Title page
Copyright page
List of Figures
List of Tables
Foreword
This Handbook Is Timely
Decision Professionals: The Practitioner Perspective
Our Profession
The Biggest Challenge
Preface
Acknowledgments
Special Acknowledgments
Individual Acknowledgments
Chapter Acknowledgments
Handbook Chapter Reviewers
About the Authors
Acronyms
Chapter One: Introduction to Decision Analysis
1.1 Introduction
1.2 Decision Analysis Is a Socio-Technical Process
1.3 Decision Analysis Applications
1.4 Decision Analysis Practitioners and Professionals
1.5 Handbook Overview and Illustrative Examples
1.6 Summary
KEY TERMS
Chapter Two: Decision-Making Challenges
2.1 Introduction
2.2 Human Decision Making
2.3 Decision-Making Challenges
2.4 Organizational Decision Processes
2.5 Credible Problem Domain Knowledge
2.6 Behavioral Decision Analysis Insights
2.7 Two Anecdotes: Long-Term Success and a Temporary Success of Supporting the Human Decision-Making Process
2.8 Setting the Human Decision-Making Context for the Illustrative Example Problems
2.9 Summary
KEY TERMS
Chapter Three: Foundations of Decision Analysis
3.1 Introduction
3.2 Brief History of the Foundations of Decision Analysis
3.3 Five Rules: Theoretical Foundation of Decision Analysis
3.4 Scope of Decision Analysis
3.5 Taxonomy of Decision Analysis Practice
3.6 Value-Focused Thinking
3.7 Summary
KEY TERMS
ACKNOWLEDGMENTS
Chapter Four: Decision Analysis Soft Skills
4.1 Introduction
4.2 Thinking Strategically
4.3 Leading Decision Analysis Teams
4.4 Managing Decision Analysis Projects
4.5 Researching
4.6 Interviewing Individuals
4.7 Conducting Surveys
4.8 Facilitating Groups
4.9 Aggregating across Experts
4.10 Communicating Analysis Insights
4.11 Summary
KEY TERMS
Chapter Five: Use the Appropriate Decision Process
5.1 Introduction
5.2 What Is a Good Decision?
5.3 Selecting the Appropriate Decision Process
5.4 Decision Processes in Illustrative Examples
5.5 Organizational Decision Quality
5.6 Decision Maker’s Bill of Rights
5.7 Summary
KEY TERMS
Chapter Six: Frame the Decision Opportunity
6.1 Introduction
6.2 Declaring a Decision
6.3 What Is a Good Decision Frame?
6.4 Achieving a Good Decision Frame
6.5 Framing the Decision Opportunities for the Illustrative Examples
6.6 Summary
KEY TERMS
Chapter Seven: Craft the Decision Objectives and Value Measures
7.1 Introduction
7.2 Shareholder and Stakeholder Value
7.3 Challenges in Identifying Objectives
7.4 Identifying the Decision Objectives
7.5 The Financial or Cost Objective
7.6 Developing Value Measures
7.7 Structuring Multiple Objectives
7.8 Illustrative Examples
7.9 Summary
KEY TERMS
Chapter Eight: Design Creative Alternatives
8.1 Introduction
8.2 Characteristics of a Good Set of Alternatives
8.3 Obstacles to Creating a Good Set of Alternatives
8.4 The Expansive Phase of Creating Alternatives
8.5 The Reductive Phase of Creating Alternatives
8.6 Improving the Set of Alternatives
8.7 Illustrative Examples
8.8 Summary
KEY WORDS
Chapter Nine: Perform Deterministic Analysis and Develop Insights
9.1 Introduction
9.2 Planning the Model: Influence Diagrams
9.3 Spreadsheet Software as the Modeling Platform
9.4 Guidelines for Building a Spreadsheet Decision Model
9.5 Organization of a Spreadsheet Decision Model
9.6 Spreadsheet Model for the RNAS Illustrative Example
9.7 Debugging the Model
9.8 Deterministic Analysis
9.9 Deterministic Modeling Using Monetary Multidimensional Value Functions (Approach 1B)
9.10 Deterministic Modeling Using Nonmonetary Multidimensional Value Functions (Approach 1A)
9.11 Illustrative Examples
9.12 Summary
KEY TERMS
Chapter Ten: Quantify Uncertainty
10.1 Introduction
10.2 Structure the Problem in an Influence Diagram
10.3 Elicit and Document Assessments
10.4 Illustrative Examples
10.5 Summary
KEY TERMS
Chapter Eleven: Perform Probabilistic Analysis and Identify Insights
11.1 Introduction
11.2 Exploration of Uncertainty: Decision Trees and Simulation
11.3 The Value Dialogue
11.4 Risk Attitude
11.5 Illustrative Examples
11.6 Summary
KEY TERMS
Chapter Twelve: Portfolio Resource Allocation
12.1 Introduction to Portfolio Decision Analysis
12.2 Socio-Technical Challenges with Portfolio Decision Analysis
12.3 Single Objective Portfolio Analysis with Resource Constraints
12.4 Multiobjective Portfolio Analysis with Resource Constraints
12.5 Summary
KEY TERMS
Chapter Thirteen: Communicating with Decision Makers and Stakeholders
13.1 Introduction
13.2 Determining Communication Objectives
13.3 Communicating with Senior Leaders
13.4 Communicating Decision Analysis Results
13.5 Communicating Insights in the Illustrative Examples
13.6 Summary
KEY TERMS
Chapter Fourteen: Enable Decision Implementation
14.1 Introduction
14.2 Barriers to Involving Decision Implementers
14.3 Involving Decision Implementers in the Decision Process
14.4 Using Decision Analysis for Decision and Strategy Implementation
14.5 Illustrative Examples
14.6 Summary
KEY TERM
Chapter Fifteen: Summary of Major Themes
15.1 Overview
15.2 Decision Analysis Helps Answer Important Decision-Making Questions
15.3 The Purpose of Decision Analysis Is to Create Value for Shareholders and Stakeholders
15.4 Decision Analysis Is a Socio-Technical Process
15.5 Decision Analysts Need Decision-Making Knowledge and Soft Skills
15.6 The Decision Analysis Process Must Be Tailored to the Decision and the Organization
15.7 Decision Analysis Offers Powerful Analytic Tools to Support Decision Making
15.8 Conclusion
Appendix A Probability Theory
A.1 Introduction
A.2 Distinctions and the Clarity Test
A.3 Possibility Tree Representation of a Distinction
A.4 Probability as an Expression of Degree of Belief
A.5 Inferential Notation
A.6 Multiple Distinctions
A.7 Joint, Conditional, and Marginal Probabilities
A.8 Calculating Joint Probabilities
A.9 Dependent and Independent Probabilities
A.10 Reversing Conditional Probabilities: Bayes’ Rule
A.11 Probability Distributions
A.12 Combining Uncertain Quantities
Appendix B Influence Diagrams
B.1 Introduction
B.2 Influence Diagram Elements
B.3 Influence Diagram Rules
B.4 SUMMARY
Appendix C Decision Conferencing
C.1 Introduction
C.2 Conference Process and Format
C.3 Location, Facilities, and Equipment
C.4 Use of Group Processes
C.5 Advantages and Disadvantages
C.6 Best Practices
C.7 SUMMARY
KEY TERMS
Index
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