Verfügbarkeit: Making hard decisions with decision tools

Making hard decisions with decision tools:

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Bibliographische Detailangaben
Hauptverfasser:	Clemen, Robert T. (VerfasserIn), Reilly, Terence (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Mason, OH Cengage Learning 2014
Ausgabe:	3. ed.
Schlagworte:	Entscheidungsfindung Monte-Carlo-Simulation Sensitivitätsanalyse
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	XXVI, 816 S. graph. Darst.
ISBN:	9780538797573 0538797576

Internformat

MARC


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Datensatz im Suchindex

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adam_text	BRIEF CONTENTS PREFACE xxi 1 Introduction to Decision Analysis 1 SECTIONI Modeling Decisions 21 2 Elements of Decision Problems 23 3 Structuring Decisions 46 4 Making Choices 118 5 Sensitivity Analysis 177 6 Organizational Use of Decision Analysis 233 Section 1 Cases 261 SECTION 2 Modeling Uncertainty 269 7 Probability Basics 271 8 Subjective Probability 315 9 Theoretical Probability Models 367 10 Using Data 418 11 Simulation 481 12 Value of Information 531 13 Real Options 561 Section 2 Cases 603 SECTION 3 Modeling Preferences 635 14 Risk Attitudes 637 15 Utility Axioms, Paradoxes, and Implications 683 VII viii BRIEF CONTENTS 16 Conflicting Objectives I: Fundamental Objectives and the Additive Utility Function 713 17 Conflicting Objectives II: M u Iti attribute Utility Models with Interactions 760 Section 3 Cases 789 18 Conclusion and Further Reading 799 NAME INDEX 805 SUBJECT INDEX 807 CONTENTS PREFACE xxi Introduction to Decision Analysis 1 Why Are Decisions Hard? 3 Why Study Decision Analysis? 5 Subjective Judgments and Decision Making 7 The Decision Analysis Process 8 Requisite Decision Models 11 Where Is Decision Analysis Used? 11 Where Does the Software Fit In? 12 Where Are We Going from Here? 14 Summary 14 Questions and Problems 15 CASESTUDIES Commercial Space Travel 16 Dupont and Chlorofiuorocarbons 17 Choosing a Vice-Presidential Candidate 17 References 18 Epilogue 19 SECTION 1 Modeling Decisions 21 Elements of Decision Problems 23 Values and Objectives 23 Making Money. A Special Objective 24 Values and the Current Decision Context 25 Decisions to Make 27 Sequential Decisions 28 Uncertain Events 29 Consequences 31 The Time Value of Money: A Special Kind of Trade-Off 33 Summary 40 Questions and Problems 40 IX CONTENTS CASE STUDIES The Value of Patience 42 Early Bird, Inc. 43 References 44 Epilogue 45 3 Structuring Decisions 46 Structuring Values 47 Fundamental and Means Objectives 49 Getting the Decision Context Right 53 Structuring Decisions: Influence Diagrams 56 Influence Diagrams and the Fundamental Objectives Hierarchy 58 Using Arcs to Represent Relationships 60 Some Basic Influence Diagrams 61 The Basic Risky Decision 61 Imperfect Information 62 Sequential Decisions 65 Intermediate Calculations 67 Constructing an Influence Diagram 69 Some Common Mistakes 71 Multiple Representations and Requisite Models 72 Structuring Decisions: Decision Trees 73 Decision Trees and the Objectives Hierarchy 75 Basic Decision Trees 76 The Basic Risky Decision 76 Imperfect Information 77 Sequential Decisions 78 Decision Trees and Influence Diagrams Compared 79 Decision Details: Defining Elements of the Decision 80 More Decision Details: Cash Flows and Probabilities 82 Defining Measurement Scales for Fundamental Objectives 83 Using PrecisionTree for Structuring Decisions 89 Constructing a Decision Tree for the Research-and-Development Decision 89 Constructing an Influence Diagram for the Basic Risky Decision 97 Summary 104 Exercises 105 Questions and Problems 107 CASE STUDIES Prescribed Fire 114 VneSSKuniang 114 The Hillblom Estate, Part I 115 CONTENTS xi References 116 ь Epilogue 117 4 Making Choices us Decision Trees and Expected Monetary Value 122 Solving Influence Diagrams: Overview 127 Solving Influence Diagrams: The Details Online only at www.cengagebrain.com Risk Profiles 129 Cumulative Risk Profiles 133 Dominance: An Alternative to EMV 135 Making Decisions with Multiple Objectives 139 Analysis: One Objective at a Time 140 Subjective Ratings for Constructed Attribute Scales 142 Assessing Trade-Off Weights 143 Analysis: Expected Values and Risk Profiles for Two Objectives 145 Decision Analysis Using PrecisionTree 147 Decision Trees 148 Influence Diagrams 154 Multiple-Attribute Models 158 Summary 162 Exercises 162 Questions and Problems 164 CASE STUDIES Southern Electronics, Part I 170 Southern Electronics, Part II 170 Strenlar 171 Job Offers 172 SS Kuniang, Part It 173 Marketing Specialists, Ltd. 174 References 176 Epilogue 176 5 Sensitivity Analysis 177 Sensitivity Analysis: A Modeling Approach 180 Problem Identification and Structure 180 One-Way Sensitivity Analysis: Sensitivity Graphs 188 One-Way Sensitivity Analysis: Tornado Diagrams 191 Dominance Considerations 194 Two-Way Sensitivity Analysis 196 Sensitivity to Probabilities 200 xii CONTENTS Sensitivity to Probabilities — House-hunting 203 Sensitivity Analysis in Action 210 Sensitivity Analysis: A Built-in Irony 212 Sensitivity Analysis Using Excel® and PrecisionTree 212 Summary 223 Exercises 223 Questions and Problems 224 CASE STUDIES Dumond International, Part I 228 Strenlar, Part II 229 Job Offers, Part II 230 The Hülblom Estate, Part II 230 Manpads 230 References 232 6 Organizational Use of Decision Analysis 233 The Decision-Making Process 234 A Six-Step Decision Process: The Lacing Diagram 234 Organizational Issues in Enhancing Creativity and Enabling Choices 239 Developing Alternatives: Understanding the Creative Process 241 Value-Focused Thinking for Creating Alternatives 243 Fundamental Objectives 243 Means Objectives 244 Strategy Tables 246 Blocks to Creativity and Additional Creativity Techniques Online only at www.cengagebrain.com Managing and Monitoring the Six-Step Decision Process 254 Other Examples 255 Summary 256 Questions and Problems 257 CASE STUDY Eastman Kodak 258 References 259 Epilogue 260 Section 1 Cases 261 Athens Glass Works 261 Integrated Siting Systems, Inc. 263 International Guidance and Controls 266 George s T-shirts 267 CONTENTS xiii SECTION 2 Modeling Uncertainty 269 7 Probability Basics 271 A Little Probability Theory 271 Venn Diagrams 272 More Probability Formulas 273 PrecisionTree® and Bayes Theorem 279 Uncertain Quantities 279 Discrete Probability Distributions 280 Expected Value 282 Variance and Standard Deviation 285 Continuous Probability Distributions 288 Stochastic Dominance Revisited 290 Probability Density Functions 290 Expected Value, Variance, and Standard Deviation: The Continuous Case 291 Correlation and Covariance for Measuring Dependence Online only at www.cengagebrain.com Oil Wildcatting 293 John Hinckley s Trial 299 Summary 301 Exercises 301 Questions and Problems 305 CASE STUDIES Decision Analysis Monthly 308 Screening for Colorectat Cancer 309 AIDS 310 Discrimination and the Death Penalty 312 References 313 Epilogue 313 8 Subjective Probability 315 Uncertainty and Public Policy 315 Probability: A Subjective Interpretation 317 Assessing Discrete Probabilities 319 Assessing Continuous Probabilities 323 Heuristics and Biases in Probability Assessment 330 Memory Biases 332 Statistical Biases 334 Confidence Biases 336 Adjustment Heuristics and Biases 336 xiv CONTENTS Motivational Bias 338 Heuristics and Biases: Implications 338 Decomposition and Probability Assessment 339 Experts and Probability Assessment: Pulling It All Together 344 Constructing Distributions Using @RISK 350 Coherence and the Dutch Book Online only at www.cengagebrain.com Summary 354 Exercises 355 Questions and Problems 356 CASESTUDIES Assessing Cancer Risk—From Mouse to Man 361 Breast Implants 362 The Space Shuttle Challenger 363 References 365 Epilogue 366 9 Theoretical Probability Models 367 The Binomial Distribution 369 The Poisson Distribution 377 The Exponential Distribution 382 The Normal Distribution 385 The Triangular Distribution 390 The Beta Distribution 392 Summary 399 Exercises 400 Questions and Problems 401 CASESTUDIES Overbooking 41Î Earthquake Prediction 412 Municipal Solid Waste 414 References 416 Epilogue 417 10 Using Data 418 Using Data to Construct Probability Distributions 418 Empirical CDFs 422 Using Data to Fit Theoretical Probability Models 428 Using @RISK to Fit Distributions to Data 431 Using Data to Model Relationships 443 The Regression Approach 447 CONTENTS xv Assumption 1 447 - Assumption 2 450 Estimation: The Basics 452 Estimation: More than One Conditioning Variable 459 Regression Analysis and Modeling: Some Do s and Don ťs 465 Regression Analysis: Some Bells and Whistles 467 Regression Modeling: Decision Analysis versus Statistical Inference 470 An Admonition: Use with Care 471 Natural Conjugate Distributions Online only at www.cengagebrain.com Summary 471 Exercises 471 Questions and Problems 472 CASE STUDIES TACO Shells 479 References 480 Epilogue: Solar Trash Compactors 480 11 Simulation 481 Mechanics of Simulation 483 Sampling from Probability Distributions 486 Simulation Models 488 Simulating the Model 492 Simulation vs. Decision Trees 497 Examples of Simulation Models 501 Probability Models 501 A Capital Budgeting Model 504 Stock Price Model 506 Simulating Spreadsheet Models Using @RISK 511 Correlations Among Random Variables 516 Sequential Simulations 520 Simulation, Decision Trees, and Influence Diagrams 522 Summary 523 Exercises 523 Questions and Problems 524 CASE STUDIES Choosing a Manufacturing Process 526 La Hacienda Musa 527 Overbooking, Part III 529 References 529 Epilogue 530 xvi CONTENTS 12 Value of Information 531 Value of Information: Some Basic Ideas 532 Probability and Perfect Information 532 The Expected Value of Information 535 Expected Value of Perfect Information 536 Expected Value of Imperfect Information 538 Value of Information in Complex Problems 544 Value of Information, Sensitivity Analysis, and Structuring 545 Value of Information and Nonmonetary Objectives 547 Value of Information and Experts 548 Calculating EVPI and EVII with PrecisionTree 548 EVPI 548 Influence Diagrams 549 Decision Trees 550 EVII 552 Summary 553 Exercises 554 Questions and Problems 555 CASE STUDIES Texaco-Pennzoil Revisited 558 Medical Tests 558 Dumond International Part II 559 References 559 13 Real Options 561 Option Basics 563 Financial Options: A Brief Tutorial 564 Real Options 568 An Approach to Valuing Real Options 570 Discrete Uncertainties and Choices: Decision Trees 570 Continuous Uncertainties and Discrete Choices: Spreadsheet Simulation 573 Optionality and Proteiz 574 A Trigger Value for Deciding 577 Valuing the Abandon Option 578 Valuing the Scale-Up Option 581 Review of the Approach for Continuous Uncertainties 588 Comparison with Real Option Valuation from Financial Theory 588 What Discount Rate? 589 Finding Optimal Decision Values Using RISK Optimizer 590 CONTENTS xvii Summary 595 Exercises 595 Questions and Problems 597 References 602 Section 2 Cases 603 LAC Leman Festival De La Musique (A) 603 LAC Leman Festival De La Musique (В) 605 Sprigg Lane (A) 606 APPSHOP, Inc. 614 Calambra Olive Oil (A) 615 Calambra Olive Oil (B) 626 SCOR-eSTORE.COM SECTION 3 Modeling Preferences 635 14 Risk Attitudes 637 Risk 639 Risk Attitudes 641 Investing in the Stock Market, Revisited 643 Expected Utility, Certainty Equivalents, and Risk Premiums 645 Keeping Terms Straight 649 Utility Function Assessment 649 Assessment Using Certainty Equivalents 650 Assessment Using Probabilities 652 Assessment Using Tradeoffs 653 Gambles, Lotteries, and Investments 654 Risk Tolerance and the Exponential Utility Function 654 Pitfalls in Utility Assessment: Biases in the CE, PE, and TO Methods 657 The Endowment Effect 658 Preference Reversals 658 Implications for Assessing Utilities 659 Modeling Preferences Using PrecisionTree 660 Decreasing and Constant Risk Aversion 664 Decreasing Risk Aversion 665 An Entrepreneurial Example 665 Constant Risk Aversion 667 Some Caveats 669 Summary 670 Exercises 670 xviii CONTENTS Questions and Problems 672 CASESTUDIES Interplants, Inc. 680 Strenlar, Part III 681 References 681 Epilogue 682 15 Utility Axioms, Paradoxes, and Implications 683 Axioms for Expected Utility 684 Paradoxes 691 Hedonic Framing 696 Failure to Ignore Sunk Costs 697 Status Quo Bias 698 Implications 698 Implications for Utility Assessment 698 Managerial and Policy Implications 700 A Final Perspective 702 Summary 703 Exercises 703 Questions and Problems 704 CASE STUDIES The Life Insurance Game 708 Nuclear Power Paranoia 709 The Manager s Perspective 709 References 709 Epilogue 712 16 Conflicting Objectives I: Fundamental Objectives and the Additive Utility Function 713 Objectives and Attributes 716 Trading Off Conflicting Objectives: The Basics 718 Choosing an Automobile: An Example 718 The Additive Utility Function 720 Choosing an Automobile: Proportional Scores 721 Assessing Weights: Pricing Out the Objectives 722 Indifference Curves 724 Assessing Individual Utility Functions 725 Proportional Scores 726 Ratios 728 Standard Utility-Function Assessment 729 Assessing Weights 730 CONTENTS xix Pricing Out 730 Swing Weighting 731 Lottery Weights 734 Biases and Inconsistencies in Weight Assessment 736 Keeping Concepts Straight: Certainty versus Uncertainty 737 An Example: Library Choices 738 Using Software for Multiple-Objective Decisions 745 Summary 745 Exercises 746 Questions and Problems 747 CASE STUDIES The Satanic Verses 755 Dilemmas in Medicine 755 A Matter of Ethics 757 FDA and The Testing of Experimental Drugs 757 References 758 Epilogue 759 17 Conflicting Objectives II: Multiattribute Utility Models with Interactions 760 Multiattribute Utility Functions: Direct Assessment 761 Independence Conditions 763 Preferential Independence 763 Utility Independence 764 Determining Whether Independence Exists 765 Using independence 767 Additive Independence 768 Substitutes and Complements 770 Assessing a Two-Attribute Utility Function 771 Three or More Attributes Online only at www.cengagebrain.com When Independence Fails 776 Multiattribute Utility in Action: ВС Hydro 777 Summary 782 Exercises 782 Questions and Problems 783 CASE STUDY A Mining Investment Decision 786 References 788 Epilogue 788 xx CONTENTS Section 3 Cases 789 John Carter: Hedging J89 Sleepmore Mattress Manufacturing: Plant Consolidation 790 Susan Jones (A) 795 Susan Jones (B) 797 18 Conclusion and Further Reading 799 A Decision-Analysis Reading List 800 Decision Analysis 801 Behavioral Decision Making 802 AUTHOR INDEX 805 SUBJECT INDEX 807
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spelling	Clemen, Robert T. Verfasser aut Making hard decisions with decision tools Robert T. Clemen ; Terence Reilly 3. ed. Mason, OH Cengage Learning 2014 XXVI, 816 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Entscheidungsfindung (DE-588)4113446-1 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 gnd rswk-swf Sensitivitätsanalyse (DE-588)4129730-1 gnd rswk-swf Entscheidungsfindung (DE-588)4113446-1 s Sensitivitätsanalyse (DE-588)4129730-1 s Monte-Carlo-Simulation (DE-588)4240945-7 s DE-604 Reilly, Terence Verfasser aut Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026749260&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
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title	Making hard decisions with decision tools
title_auth	Making hard decisions with decision tools
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title_full	Making hard decisions with decision tools Robert T. Clemen ; Terence Reilly
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title_full_unstemmed	Making hard decisions with decision tools Robert T. Clemen ; Terence Reilly
title_short	Making hard decisions with decision tools
title_sort	making hard decisions with decision tools
topic	Entscheidungsfindung (DE-588)4113446-1 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd Sensitivitätsanalyse (DE-588)4129730-1 gnd
topic_facet	Entscheidungsfindung Monte-Carlo-Simulation Sensitivitätsanalyse
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