Handbook of Decision Analysis.

By: Parnell, Gregory SContributor(s): Bresnick, Terry | Tani, Steven N | Johnson, Eric RMaterial type: TextTextSeries: Wiley Handbooks in Operations Research and Management Science SerPublisher: Somerset : John Wiley & Sons, Incorporated, 2013Copyright date: ©2013Edition: 1st edDescription: 1 online resource (430 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781118515846Subject(s): Decision makingGenre/Form: Electronic books.Additional physical formats: Print version:: Handbook of Decision AnalysisDDC classification: 658.403 LOC classification: HD30.23.H3542 2013Online resources: Click to View
Contents:
Cover -- Wiley Handbooks in OPERATIONS RESEARCH AND MANAGEMENT SCIENCE -- Title page -- Copyright page -- Contents -- List of Figures -- List of Tables -- Foreword -- Preface -- Acknowledgments -- 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 -- 1.3.1 Oil and Gas Decision Analysis Success Story: Chevron -- 1.3.2 Pharmaceutical Decision Analysis Success Story: SmithKline Beecham -- 1.3.3 Military Decision Analysis Success Stories -- 1.4 Decision Analysis Practitioners and Professionals -- 1.4.1 Education and Training -- 1.4.2 Decision Analysis Professional Organizations -- 1.4.3 Problem Domain Professional Societies -- 1.4.4 Professional Service -- 1.5 Handbook Overview and Illustrative Examples -- 1.5.1 Roughneck North American Strategy (RNAS) (by Eric R. Johnson) -- 1.5.2 Geneptin Personalized Medicine for Breast Cancer (by Sean Xinghua Hu) -- 1.5.3 Data Center Location and IT Portfolio (by Gregory S. Parnell and Terry A. Bresnick) -- 1.6 Summary -- Key Terms -- References -- Chapter Two: Decision-Making Challenges -- 2.1 Introduction -- 2.2 Human Decision Making -- 2.3 Decision-Making Challenges -- 2.4 Organizational Decision Processes -- 2.4.1 Culture -- 2.4.2 Impact of Stakeholders -- 2.4.3 Decision Level (Strategic, Operational, and Tactical) -- 2.5 Credible Problem Domain Knowledge -- 2.5.1 Dispersion of Knowledge -- 2.5.2 Technical Knowledge: Essential for Credibility -- 2.5.3 Business Knowledge: Essential for Success -- 2.5.4 Role of Experts -- 2.5.5 Limitations of Experts -- 2.6 Behavioral Decision Analysis Insights -- 2.6.1 Decision Traps and Barriers -- 2.6.2 Cognitive Biases -- 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 -- 2.8.1 Roughneck North American Strategy (by Eric R. Johnson) -- 2.8.2 Geneptin Personalized Medicine (by Sean Xinghua Hu) -- 2.8.3 Data Center Decision Problem (by Gregory S. Parnell) -- 2.9 Summary -- Key Terms -- References -- 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 -- 3.5.1 Terminology -- 3.5.2 Taxonomy Division: Single or Multiple Objectives -- 3.5.3 Single-Objective Decision Analysis -- 3.5.4 Multiple-Objective Decision Analysis -- 3.5.5 Taxonomy Division: Addressing Value Trade-Offs and Risk Preference Separately or Together? -- 3.5.6 Taxonomy Division: Nonmonetary or Monetary Value Metric? -- 3.5.7 Taxonomy Division: Degree of Simplicity in Multidimensional Value Function -- 3.6 Value-Focused Thinking -- 3.6.1 Four Major VFT Ideas -- 3.6.2 The Benefits of VFT -- 3.7 Summary -- Key Terms -- Acknowledgments -- References -- 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 -- 4.6.1 Before the Interview -- 4.6.2 Schedule/Reschedule the Interview -- 4.6.3 During the Interview -- 4.6.4 After the Interview -- 4.7 Conducting Surveys -- 4.7.1 Preparing an Effective Survey: Determine the Goals, Survey Respondents, and Means of Distributing and Collecting Survey Data -- 4.7.2 Executing a Survey Instrument: Developing the Survey Questions, Testing, and Distributing the Survey -- 4.8 Facilitating Groups -- 4.8.1 Facilitation Basics -- 4.8.2 Group Processes.
4.8.3 Focus Groups -- 4.9 Aggregating across Experts -- 4.10 Communicating Analysis Insights -- 4.11 Summary -- Key Terms -- References -- Chapter Five: Use the Appropriate Decision Process -- 5.1 Introduction -- 5.2 What Is a Good Decision? -- 5.2.1 Decision Quality -- 5.2.2 The Six Elements of Decision Quality -- 5.2.3 Intuitive versus Deliberative Decision Making -- 5.3 Selecting the Appropriate Decision Process -- 5.3.1 Tailoring the Decision Process to the Decision -- 5.3.2 Two Best Practice Decision Processes -- 5.3.3 Two Flawed Decision Processes -- 5.4 Decision Processes in Illustrative Examples -- 5.4.1 Roughneck North American Oil Strategy -- 5.4.2 Geneptin Personalized Medicine -- 5.4.3 Data Center -- 5.5 Organizational Decision Quality -- 5.6 Decision Maker's Bill of Rights -- 5.7 Summary -- Key Terms -- References -- 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 -- 6.4.1 Vision Statement -- 6.4.2 Issue Raising -- 6.4.3 Categorization of Issues -- 6.4.4 Decision Hierarchy -- 6.4.5 Values and Trade-Offs -- 6.4.6 Initial Influence Diagram -- 6.4.7 Decision Schedule and Logistics -- 6.5 Framing the Decision Opportunities for the Illustrative Examples -- 6.5.1 Roughneck North American Strategy (RNAS) -- 6.5.2 Geneptin Personalized Medicine -- 6.5.3 Data Center Decision -- 6.6 Summary -- Key Terms -- References -- Chapter Seven: Craft the Decision Objectives and Value Measures -- 7.1 Introduction -- 7.2 Shareholder and Stakeholder Value -- 7.2.1 Private Company Example -- 7.2.2 Government Agency Example -- 7.3 Challenges in Identifying Objectives -- 7.4 Identifying the Decision Objectives -- 7.4.1 Questions to Help Identify Decision Objectives -- 7.4.2 How to Get Answers to the Questions.
7.5 The Financial or Cost Objective -- 7.5.1 Financial Objectives for Private Companies -- 7.5.2 Cost Objective for Public Organizations -- 7.6 Developing Value Measures -- 7.7 Structuring Multiple Objectives -- 7.7.1 Value Hierarchies -- 7.7.2 Techniques for Developing Value Hierarchies -- 7.7.3 Value Hierarchy Best Practices -- 7.7.4 Cautions about Cost and Risk Objectives -- 7.8 Illustrative Examples -- 7.8.1 Roughneck North American Strategy (by Eric R. Johnson) -- 7.8.2 Geneptin (by Sean Xinghua Hu) -- 7.8.3 Data Center Location (by Gregory S. Parnell) -- 7.9 Summary -- Key Terms -- References -- 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 -- 8.7.1 Roughneck North American Strategy (by Eric R. Johnson) -- 8.7.2 Geneptin Personalized Medicine (by Sean Xinghua Hu) -- 8.7.3 Data Center Location (by Gregory S. Parnell) -- 8.8 Summary -- Key Words -- References -- 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 -- 9.4.1 Keep Inputs Separated from Calculations -- 9.4.2 Parameterize Everything -- 9.4.3 Use Range Names for Readability -- 9.4.4 Use Uniform Indexing for Rows and Columns of a Sheet -- 9.4.5 Manage the Model Configurations -- 9.5 Organization of a Spreadsheet Decision Model -- 9.5.1 Value Components -- 9.5.2 Decisions -- 9.5.3 Uncertainties -- 9.5.4 Business Units -- 9.5.5 Time.
9.5.6 Representation of Business Units, Value Components, and Time: P&L Calculation Sheet(s) -- 9.5.7 Inputs Sheet(s) -- 9.6 Spreadsheet Model for the RNAS Illustrative Example -- 9.6.1 Selectors -- 9.6.2 Inputs and Strategy Table Sheets -- 9.6.3 Calculations Sheets -- 9.7 Debugging the Model -- 9.8 Deterministic Analysis -- 9.8.1 Sources of Value -- 9.8.2 Deterministic Sensitivity Analysis -- 9.8.3 Scenario Analysis -- 9.9 Deterministic Modeling Using Monetary Multidimensional Value Functions (Approach 1B) -- 9.10 Deterministic Modeling Using Nonmonetary Multidimensional Value Functions (Approach 1A) -- 9.10.1 The Additive Value Function -- 9.10.2 Single-Dimensional Value Functions -- 9.10.3 Swing Weights -- 9.10.4 Swing Weight Matrix -- 9.10.5 Scoring the Alternatives -- 9.10.6 Deterministic Analysis -- 9.11 Illustrative Examples -- 9.11.1 Geneptin -- 9.11.2 Data Center Location -- 9.12 Summary -- Key Terms -- References -- Chapter Ten: Quantify Uncertainty -- 10.1 Introduction -- 10.2 Structure the Problem in an Influence Diagram -- 10.3 Elicit and Document Assessments -- 10.3.1 Heuristics and Biases -- 10.3.2 Reference Events -- 10.3.3 Assessment Protocol -- 10.3.4 Assessing a Continuous Distribution -- 10.3.5 Conditioning Cases -- 10.3.6 The Reluctant Expert -- 10.4 Illustrative Examples -- 10.4.1 Geneptin -- 10.5 Summary -- Key Terms -- References -- Chapter Eleven: Perform Probabilistic Analysis and Identify Insights -- 11.1 Introduction -- 11.2 Exploration of Uncertainty: Decision Trees and Simulation -- 11.2.1 Decision Trees -- 11.2.2 Simulation -- 11.2.3 Choosing between Monte Carlo Simulation and Decision Trees -- 11.2.4 Software for Simulation and Decision Trees -- 11.3 The Value Dialogue -- 11.3.1 P&L Browsers -- 11.3.2 Total Value and Value Components -- 11.3.3 Cash Flow over Time -- 11.3.4 Direct EV Tornado Diagram.
11.3.5 Delta EV Tornado Diagram.
Summary: A ONE-OF-A-KIND GUIDE TO THE BEST PRACTICES IN DECISION ANALYSIS Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet most training materials on the subject overlook the soft skills that are essential for success in the field. This unique resource fills this gap in the decision analysis literature and features both soft personal/interpersonal skills and the hard technical skills involving mathematics and modeling. Readers will learn how to identify and overcome the numerous challenges of decision making, choose the appropriate decision process, lead and manage teams, and create value for their organization. Performing modeling analysis, assessing risk, and implementing decisions are also addressed throughout. Additional features include: Key insights gleaned from decision analysis applications and behavioral decision analysis research Integrated coverage of the techniques of single- and multiple-objective decision analysis Multiple qualitative and quantitative techniques presented for each key decision analysis task Three substantive real-world case studies illustrating diverse strategies for dealing with the challenges of decision making Extensive references for mathematical proofs and advanced topics The Handbook of Decision Analysis is an essential reference for academics and practitioners in various fields including business, operations research, engineering, and science. The book also serves as a supplement for courses at the upper-undergraduate and graduate levels.
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Cover -- Wiley Handbooks in OPERATIONS RESEARCH AND MANAGEMENT SCIENCE -- Title page -- Copyright page -- Contents -- List of Figures -- List of Tables -- Foreword -- Preface -- Acknowledgments -- 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 -- 1.3.1 Oil and Gas Decision Analysis Success Story: Chevron -- 1.3.2 Pharmaceutical Decision Analysis Success Story: SmithKline Beecham -- 1.3.3 Military Decision Analysis Success Stories -- 1.4 Decision Analysis Practitioners and Professionals -- 1.4.1 Education and Training -- 1.4.2 Decision Analysis Professional Organizations -- 1.4.3 Problem Domain Professional Societies -- 1.4.4 Professional Service -- 1.5 Handbook Overview and Illustrative Examples -- 1.5.1 Roughneck North American Strategy (RNAS) (by Eric R. Johnson) -- 1.5.2 Geneptin Personalized Medicine for Breast Cancer (by Sean Xinghua Hu) -- 1.5.3 Data Center Location and IT Portfolio (by Gregory S. Parnell and Terry A. Bresnick) -- 1.6 Summary -- Key Terms -- References -- Chapter Two: Decision-Making Challenges -- 2.1 Introduction -- 2.2 Human Decision Making -- 2.3 Decision-Making Challenges -- 2.4 Organizational Decision Processes -- 2.4.1 Culture -- 2.4.2 Impact of Stakeholders -- 2.4.3 Decision Level (Strategic, Operational, and Tactical) -- 2.5 Credible Problem Domain Knowledge -- 2.5.1 Dispersion of Knowledge -- 2.5.2 Technical Knowledge: Essential for Credibility -- 2.5.3 Business Knowledge: Essential for Success -- 2.5.4 Role of Experts -- 2.5.5 Limitations of Experts -- 2.6 Behavioral Decision Analysis Insights -- 2.6.1 Decision Traps and Barriers -- 2.6.2 Cognitive Biases -- 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 -- 2.8.1 Roughneck North American Strategy (by Eric R. Johnson) -- 2.8.2 Geneptin Personalized Medicine (by Sean Xinghua Hu) -- 2.8.3 Data Center Decision Problem (by Gregory S. Parnell) -- 2.9 Summary -- Key Terms -- References -- 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 -- 3.5.1 Terminology -- 3.5.2 Taxonomy Division: Single or Multiple Objectives -- 3.5.3 Single-Objective Decision Analysis -- 3.5.4 Multiple-Objective Decision Analysis -- 3.5.5 Taxonomy Division: Addressing Value Trade-Offs and Risk Preference Separately or Together? -- 3.5.6 Taxonomy Division: Nonmonetary or Monetary Value Metric? -- 3.5.7 Taxonomy Division: Degree of Simplicity in Multidimensional Value Function -- 3.6 Value-Focused Thinking -- 3.6.1 Four Major VFT Ideas -- 3.6.2 The Benefits of VFT -- 3.7 Summary -- Key Terms -- Acknowledgments -- References -- 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 -- 4.6.1 Before the Interview -- 4.6.2 Schedule/Reschedule the Interview -- 4.6.3 During the Interview -- 4.6.4 After the Interview -- 4.7 Conducting Surveys -- 4.7.1 Preparing an Effective Survey: Determine the Goals, Survey Respondents, and Means of Distributing and Collecting Survey Data -- 4.7.2 Executing a Survey Instrument: Developing the Survey Questions, Testing, and Distributing the Survey -- 4.8 Facilitating Groups -- 4.8.1 Facilitation Basics -- 4.8.2 Group Processes.

4.8.3 Focus Groups -- 4.9 Aggregating across Experts -- 4.10 Communicating Analysis Insights -- 4.11 Summary -- Key Terms -- References -- Chapter Five: Use the Appropriate Decision Process -- 5.1 Introduction -- 5.2 What Is a Good Decision? -- 5.2.1 Decision Quality -- 5.2.2 The Six Elements of Decision Quality -- 5.2.3 Intuitive versus Deliberative Decision Making -- 5.3 Selecting the Appropriate Decision Process -- 5.3.1 Tailoring the Decision Process to the Decision -- 5.3.2 Two Best Practice Decision Processes -- 5.3.3 Two Flawed Decision Processes -- 5.4 Decision Processes in Illustrative Examples -- 5.4.1 Roughneck North American Oil Strategy -- 5.4.2 Geneptin Personalized Medicine -- 5.4.3 Data Center -- 5.5 Organizational Decision Quality -- 5.6 Decision Maker's Bill of Rights -- 5.7 Summary -- Key Terms -- References -- 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 -- 6.4.1 Vision Statement -- 6.4.2 Issue Raising -- 6.4.3 Categorization of Issues -- 6.4.4 Decision Hierarchy -- 6.4.5 Values and Trade-Offs -- 6.4.6 Initial Influence Diagram -- 6.4.7 Decision Schedule and Logistics -- 6.5 Framing the Decision Opportunities for the Illustrative Examples -- 6.5.1 Roughneck North American Strategy (RNAS) -- 6.5.2 Geneptin Personalized Medicine -- 6.5.3 Data Center Decision -- 6.6 Summary -- Key Terms -- References -- Chapter Seven: Craft the Decision Objectives and Value Measures -- 7.1 Introduction -- 7.2 Shareholder and Stakeholder Value -- 7.2.1 Private Company Example -- 7.2.2 Government Agency Example -- 7.3 Challenges in Identifying Objectives -- 7.4 Identifying the Decision Objectives -- 7.4.1 Questions to Help Identify Decision Objectives -- 7.4.2 How to Get Answers to the Questions.

7.5 The Financial or Cost Objective -- 7.5.1 Financial Objectives for Private Companies -- 7.5.2 Cost Objective for Public Organizations -- 7.6 Developing Value Measures -- 7.7 Structuring Multiple Objectives -- 7.7.1 Value Hierarchies -- 7.7.2 Techniques for Developing Value Hierarchies -- 7.7.3 Value Hierarchy Best Practices -- 7.7.4 Cautions about Cost and Risk Objectives -- 7.8 Illustrative Examples -- 7.8.1 Roughneck North American Strategy (by Eric R. Johnson) -- 7.8.2 Geneptin (by Sean Xinghua Hu) -- 7.8.3 Data Center Location (by Gregory S. Parnell) -- 7.9 Summary -- Key Terms -- References -- 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 -- 8.7.1 Roughneck North American Strategy (by Eric R. Johnson) -- 8.7.2 Geneptin Personalized Medicine (by Sean Xinghua Hu) -- 8.7.3 Data Center Location (by Gregory S. Parnell) -- 8.8 Summary -- Key Words -- References -- 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 -- 9.4.1 Keep Inputs Separated from Calculations -- 9.4.2 Parameterize Everything -- 9.4.3 Use Range Names for Readability -- 9.4.4 Use Uniform Indexing for Rows and Columns of a Sheet -- 9.4.5 Manage the Model Configurations -- 9.5 Organization of a Spreadsheet Decision Model -- 9.5.1 Value Components -- 9.5.2 Decisions -- 9.5.3 Uncertainties -- 9.5.4 Business Units -- 9.5.5 Time.

9.5.6 Representation of Business Units, Value Components, and Time: P&L Calculation Sheet(s) -- 9.5.7 Inputs Sheet(s) -- 9.6 Spreadsheet Model for the RNAS Illustrative Example -- 9.6.1 Selectors -- 9.6.2 Inputs and Strategy Table Sheets -- 9.6.3 Calculations Sheets -- 9.7 Debugging the Model -- 9.8 Deterministic Analysis -- 9.8.1 Sources of Value -- 9.8.2 Deterministic Sensitivity Analysis -- 9.8.3 Scenario Analysis -- 9.9 Deterministic Modeling Using Monetary Multidimensional Value Functions (Approach 1B) -- 9.10 Deterministic Modeling Using Nonmonetary Multidimensional Value Functions (Approach 1A) -- 9.10.1 The Additive Value Function -- 9.10.2 Single-Dimensional Value Functions -- 9.10.3 Swing Weights -- 9.10.4 Swing Weight Matrix -- 9.10.5 Scoring the Alternatives -- 9.10.6 Deterministic Analysis -- 9.11 Illustrative Examples -- 9.11.1 Geneptin -- 9.11.2 Data Center Location -- 9.12 Summary -- Key Terms -- References -- Chapter Ten: Quantify Uncertainty -- 10.1 Introduction -- 10.2 Structure the Problem in an Influence Diagram -- 10.3 Elicit and Document Assessments -- 10.3.1 Heuristics and Biases -- 10.3.2 Reference Events -- 10.3.3 Assessment Protocol -- 10.3.4 Assessing a Continuous Distribution -- 10.3.5 Conditioning Cases -- 10.3.6 The Reluctant Expert -- 10.4 Illustrative Examples -- 10.4.1 Geneptin -- 10.5 Summary -- Key Terms -- References -- Chapter Eleven: Perform Probabilistic Analysis and Identify Insights -- 11.1 Introduction -- 11.2 Exploration of Uncertainty: Decision Trees and Simulation -- 11.2.1 Decision Trees -- 11.2.2 Simulation -- 11.2.3 Choosing between Monte Carlo Simulation and Decision Trees -- 11.2.4 Software for Simulation and Decision Trees -- 11.3 The Value Dialogue -- 11.3.1 P&L Browsers -- 11.3.2 Total Value and Value Components -- 11.3.3 Cash Flow over Time -- 11.3.4 Direct EV Tornado Diagram.

11.3.5 Delta EV Tornado Diagram.

A ONE-OF-A-KIND GUIDE TO THE BEST PRACTICES IN DECISION ANALYSIS Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet most training materials on the subject overlook the soft skills that are essential for success in the field. This unique resource fills this gap in the decision analysis literature and features both soft personal/interpersonal skills and the hard technical skills involving mathematics and modeling. Readers will learn how to identify and overcome the numerous challenges of decision making, choose the appropriate decision process, lead and manage teams, and create value for their organization. Performing modeling analysis, assessing risk, and implementing decisions are also addressed throughout. Additional features include: Key insights gleaned from decision analysis applications and behavioral decision analysis research Integrated coverage of the techniques of single- and multiple-objective decision analysis Multiple qualitative and quantitative techniques presented for each key decision analysis task Three substantive real-world case studies illustrating diverse strategies for dealing with the challenges of decision making Extensive references for mathematical proofs and advanced topics The Handbook of Decision Analysis is an essential reference for academics and practitioners in various fields including business, operations research, engineering, and science. The book also serves as a supplement for courses at the upper-undergraduate and graduate levels.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2018. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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