Foundations of decision analysis 9780132336246, 129207969X, 9781292079691, 0132336243

Table of contents :
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