Foundations of Decision Analysis

Cover......Page 1
Title......Page 2
Copyright......Page 3
Brief Contents......Page 4
Contents......Page 6
 1.2 Normative Vs. Descriptive......Page 24
 1.3 Declaring a Decision......Page 27
 1.4 Thought Vs. Action......Page 30
 1.5 What is a Decision?......Page 31
 1.6 Decision Vs. Outcome......Page 33
 1.7 Clarity of Action......Page 36
 1.8 What is a Good Decision?......Page 37
 1.9 Summary......Page 41
  Key Terms......Page 42
  Problems......Page 43
 2.2 Analysis of a Decision: The Thumbtack and the Medallion Example......Page 45
 2.3 Lessons Learned from the Thumbtack and Medallion Example......Page 54
  Key Terms......Page 58
  Appendix A: Results of the Thumbtack Demonstration......Page 59
  Problems......Page 60
 3.2 Value in Use and Value in Exchange......Page 64
 3.3 Values Around a Cycle of Ownership......Page 68
 3.4 Summary......Page 73
  Key Terms......Page 74
  Problems......Page 75
 4.2 Lego-Like Precision......Page 78
 4.3 Precise Decision Language......Page 79
 4.4 Experts and Distinctions......Page 80
 4.5 Mastery......Page 82
  Key Terms......Page 83
  Problems......Page 84
 5.2 Creating Distinctions......Page 85
 5.3 The Possibility Tree......Page 88
 5.4 Measures......Page 95
 5.5 Sumary......Page 97
  Key Terms......Page 98
  Problems......Page 99
 6.2 Describing Degree of Belief by Probability......Page 101
 6.3 The Probability Tree......Page 105
 6.5 Multiple Degrees of Distinction......Page 114
 6.6 Probability Trees Using Multiple Distinctions......Page 117
 6.7 Adding Measures to the Probability Tree......Page 124
 6.8 Multiple Measures......Page 132
 6.9 Summary......Page 134
  Key Terms......Page 135
  Appendix A: The Chain Rule for Distinctions: Calculating Elemental Probabilities......Page 136
  Appendix B: Let’s Make a Deal Commentary......Page 138
  Appendix C: Further Discussion Related to the Example: At Least One Boy......Page 141
  Problems......Page 142
 7.2 Relevance with Simple Distinctions......Page 146
 7.3 Is Relevance Mutual?......Page 147
 7.4 Relevance Diagrams......Page 149
 7.5 Alternate Asessment Orders......Page 153
 7.6 Relevance Depends on Knowledge......Page 155
 7.7 Distinctive Vs. Asociative Logic......Page 160
 7.8 The Third Factor......Page 161
 7.10 Summary......Page 164
  Key Terms......Page 165
  Appendix A: More on Relevance Diagrams and Arrow Reversals......Page 166
  Problems......Page 169
 8.2 Using Rules for Decision Making......Page 179
 8.3 The Decision Situation......Page 181
 8.4 The Five Rules of Actional Thought......Page 182
 8.5 Summary......Page 188
  Key Terms......Page 189
  Problems......Page 190
 9.2 The Party Problem......Page 199
 9.3 Simplifying the Rules: E-Value......Page 205
 9.4 Understanding the Value of the Party Problem......Page 210
  Key Terms......Page 214
  Appendix A......Page 215
  Problems......Page 216
 10.2 Money as a Value Measure......Page 217
 10.3 u-curves......Page 220
 10.4 Valuing Clairvoyance......Page 224
 10.5 Jane’s Party Problem......Page 228
 10.6 Attitudes toward Risk......Page 231
 10.7 Mary’s Party Problem......Page 234
  Key Terms......Page 236
  Problems......Page 237
 11.2 Wealth Risk Attitude......Page 240
 11.3 Buying and Selling a Deal Around a Cycle of Ownership......Page 241
 11.4 The Delta Property......Page 244
 11.5 Risk Odds......Page 247
 11.6 Delta Property Simplifications......Page 252
 11.7 Other Forms of Exponential u-Curve......Page 254
 11.8 Direct Assessment of Risk Tolerance......Page 255
 11.9 Summary......Page 261
  Key Terms......Page 262
  Problems......Page 263
 12.2 Kim’s Sensitivity to Probability of Sunshine......Page 270
 12.3 Certain Equivalent Sensitivity......Page 272
 12.4 Value of Clairvoyance Sensitivity to Probability of Sunshine......Page 273
 12.5 Jane’s Sensitivity to Probability of Sunshine......Page 274
 12.6 Comparison of Kim’s and Jane’s Value of Clairvoyance Sensitivities......Page 275
 12.7 Risk Sensitivity Profile......Page 277
  Key Terms......Page 279
  Problems......Page 280
 13.2 The Value of Information......Page 288
 13.3 The Acme Rain Detector......Page 290
 13.4 General Observations on Experiments......Page 296
 13.5 Asymmetric Experiments......Page 300
 13.6 Information Gathering Equivalents......Page 303
 13.7 Summary......Page 306
  Problems......Page 308
 14.2 Nodes in the Decision Diagram......Page 315
 14.3 Arrows in Decision Diagrams......Page 316
 14.4 Value of Clairvoyance......Page 318
 14.6 Decision Tree Order......Page 319
 14.7 Detector Use Decision......Page 320
  Key Terms......Page 323
  Problems......Page 324
 15.1 Introduction......Page 331
 15.2 Probability Encoding......Page 333
 15.3 Fractiles of a Probability Distribution......Page 339
  Key Terms......Page 347
  Problems......Page 348
  Answers to Problem 2......Page 349
 16.2 Information Transmission......Page 350
 16.3 Perception......Page 351
 16.4 Cognition......Page 352
  Key Terms......Page 356
 17.2 Making a Decision......Page 357
 17.3 Selecting a Frame......Page 358
  Key Terms......Page 369
  Problems......Page 370
 18.2 The Beta Rain Detector......Page 371
 18.3 Clarifying the Value of Joint Clairvoyance on Two Distinctions......Page 378
 18.4 Value of Information for Multiple Uncertainties......Page 381
 18.5 Approaching Clairvoyance with Multiple Acme Detectors......Page 386
 18.6 Valuing Individually Immaterial Multiple Detectors......Page 395
 18.7 Summary......Page 398
  Key Terms......Page 399
  Problems......Page 400
 19.2 Contractual and Non-Contractual Options......Page 401
 19.3 Option Price, Exercise Price, and Option Value......Page 402
 19.4 Simple Option Analysis......Page 403
 19.5 Consequences of Failure to Recognize Options......Page 406
 19.6 Jane’s Party Revisited......Page 409
 19.7 Value of Clairvoyance as an Option......Page 411
 19.8 Sequential Information Options......Page 412
 19.10 Creating Options......Page 415
  Key Terms......Page 420
  Problems......Page 421
 20.1 Introduction......Page 422
 20.2 Detector with 100 Indications......Page 423
 20.3 The Continuous Beta Detector......Page 440
  Key Terms......Page 446
  Problems......Page 447
 21.2 Shirley’s Problem......Page 448
  Key Terms......Page 463
  Problems......Page 464
 22.1 Introduction......Page 465
 22.2 The Logarithmic u-Curve......Page 466
 22.3 Deals with Large Monetary Prospects for a DeltaPerson......Page 470
 22.4 Properties of the Logarithmic u-Curve......Page 474
 22.5 Certain Equivalent of Two Mutually Irrelevant Deal......Page 479
 22.6 The St. Petersburg Paradox......Page 482
 22.7 Summary......Page 485
  Key Terms......Page 486
  Appendix A: The Logarithmic Function and Its Properties......Page 487
  Appendix B: The Risk-Aversion Function......Page 488
  Appendix C: A Student’s Question Following an Economist Article......Page 489
  Problems......Page 494
 23.2 Linear Risk Tolerance......Page 496
  Key Terms......Page 504
  Appendix A: Derivation of Linear Risk Tolerance u-Curve......Page 505
  Appendix B: Student’s Problem Using Linear Risk Tolerance u-Curve......Page 506
  Problems......Page 508
 24.2 Moments of a Measure......Page 509
 24.3 Central Moments of a Measure......Page 513
 24.4 Approximating the Certain Equivalent Using First and Second Central Moments......Page 514
 24.5 Approximating the Certain Equivalent Using Higher Order Moments......Page 516
 24.7 Summary......Page 519
  Key Terms......Page 520
  Problems......Page 521
 25.2 Deterministic Dominance......Page 522
 25.3 First-Order Probabilistic Dominance......Page 527
 25.4 Second-Order Probabilistic Dominance......Page 531
 25.5 Dominance for Alternatives in the Party Problem......Page 535
  Key Terms......Page 538
  Problems......Page 539
 26.1 Introduction......Page 540
 26.2 Step 1: Direct Vs. Indirect Values......Page 541
 26.3 Step 2: Ordering Prospects Characterized by Multiple “Direct Value” Attributes......Page 545
 26.4 Summary......Page 552
  Key Terms......Page 553
  Appendix A: Deriving the Relation Between Increments in x and y as a Function of η in the Preference Function......Page 554
  Problems......Page 555
 27.1 Introduction......Page 556
 27.2 Rules for Evaluating Investment Cash Flows......Page 557
 27.3 Methods Not Equivalent to the Present Equivalent......Page 568
  Key Terms......Page 571
  Problems......Page 572
 28.1 Introduction......Page 573
 28.2 Stating Preference Probabilities with Two Attributes......Page 574
 28.4 Stating a u-Curve Over the Value Function......Page 575
 28.5 The Value Certain Equivalent......Page 577
 28.6 Other u-Function Approaches......Page 579
 28.7 Stating a u-Curve Over an Individual Attribute within the Value Function......Page 580
 28.8 Valuing Uncertain Cash Flows......Page 583
 28.9 Discussion......Page 587
  Key Terms......Page 588
  Problems......Page 589
 29.2 Betting on Disparate Probabilities......Page 590
 29.3 Practical Use......Page 594
  Key Terms......Page 595
  Problems......Page 596
 30.1 Introduction......Page 597
 30.2 Assigning Probability of Head and Tail for the Thumbtack......Page 598
 30.3 Probability of Heads on Next Two Tosses......Page 599
 30.4 Probability of Any Number of Heads and Tails......Page 600
 30.5 Learning from Observation......Page 601
 30.6 Conjugate Distributions......Page 604
 30.7 Does Observing a Head Make the Probability of a Head on the Next Toss More Likely?......Page 605
 30.8 Another Thumbtack Demonstration......Page 606
  Key Terms......Page 609
  Problems......Page 610
 31.2 Another Thumbtack Demonstration......Page 611
 31.3 Auctions 1 and 3 for a Deltaperson......Page 616
 31.4 Non-Deltaperson Analysis......Page 622
 31.5 The Value of the Bidding Opportunity for Auction 2......Page 624
 31.6 The Winner’s Curse......Page 628
 31.7 Summary......Page 640
  Key Terms......Page 641
  Problems......Page 642
 32.2 Scaling and Sharing Risk......Page 644
 32.3 Scaling an Uncertain Deal......Page 645
 32.4 Risk Sharing of Uncertain Deals......Page 648
 32.5 Optimal Investment in a Portfolio......Page 650
 32.6 Summary......Page 659
  Key Terms......Page 660
  Appendix A: Covariance and Correlation......Page 661
  Appendix B: Scalar (Dot) Product of Vectors......Page 666
  Appendix C: 2 × 2 and 3 × 3 Matrix Multiplications and Matrix Inversion......Page 667
  Problems......Page 670
 33.2 A Painful Dilemma......Page 671
 33.4 Using Micromort Values......Page 674
 33.5 Applications......Page 676
 33.6 Facing Larger Probabilities of Death......Page 678
  Key Terms......Page 681
  Problems......Page 682
 34.2 Value Function for Remaining Life Years and Consumption......Page 684
 34.3 Assigning a u-Curve Over the Value Function......Page 687
 34.4 Determining Micromort Values......Page 690
 34.5 Equivalent Perfect Life Probability (EPlP)......Page 696
  Key Terms......Page 698
  Appendix A: Mortality Table for 30-Year-Old Male......Page 699
  Appendix B: Example of a Black Pill Calculation, x = 10,000......Page 702
  Appendix C: Example of a White Pill Calculation, x = 10,000......Page 705
  Problems......Page 708
 35.1 Introduction......Page 709
 35.2 Equal Areas Method......Page 710
 35.3 Caution with Discretization......Page 714
 35.4 Accuracy of 10–50–90 Approximate Method for Equal Areas......Page 716
 35.6 Moment Matching Method......Page 719
  Key Terms......Page 721
  Appendix A: Rationale for Equal Areas Method......Page 722
  Problems......Page 725
 36.2 Using Simulation for Solving Problems......Page 726
 36.3 Simulating Decisions Having a Single Discrete Distinction......Page 727
 36.4 Decisions with Multiple Discrete Distinctions......Page 730
 36.5 Simulating a Measure with a Continuous Distribution......Page 733
 36.6 Simulating Mutually Irrelevant Distinctions......Page 737
 36.7 Value of Information with Simulation......Page 739
 36.8 Simulating Multiple Distinctions with Relevance......Page 743
  Key Terms......Page 745
  Problems......Page 746
 37.2 The Decision Analysis Cycle......Page 747
 37.3 The Model Sequence......Page 757
  Key Terms......Page 768
  Appendix A: Open Loop and Closed Loop Sensitivity for the Bidding Decision......Page 769
 38.1 Introduction......Page 776
 38.2 Operating to Maximize Value......Page 777
 38.3 Issues When Operating with Budgets......Page 779
 38.4 Issues with Incentive Structures......Page 780
 38.5 A Common Issue: Multiple Specifications Vs. Tradeoffs......Page 781
 38.6 Need for a Corporate Risk Tolerance......Page 782
 38.7 Common Motivational Biases in Organizations......Page 786
  Key Terms......Page 788
  Problems......Page 789
 39.2 Issues Contributing to Poor Group Decision Making......Page 790
 39.3 Classifying Decision Problems......Page 792
 39.4 Structuring Decision Problems within Organizations......Page 795
 39.5 Example: The Fifth Generation Corvette......Page 800
  Key Terms......Page 803
 40.1 Introduction......Page 804
 40.2 The Role of Ethics in Decision Making......Page 805
 40.3 Ethical Distinctions......Page 806
 40.4 Harming, Stealing, and Truth Telling......Page 809
 40.5 Ethical Codes......Page 812
 40.6 Ethical Situations......Page 813
 40.7 Summary......Page 815
  Key Terms......Page 816
  Problems......Page 817
 A......Page 818
 C......Page 819
 D......Page 820
 E......Page 821
 G......Page 822
 L......Page 823
 O......Page 824
 P......Page 825
 Q......Page 826
 S......Page 827
 U......Page 828
 V......Page 829
 Z......Page 830