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Decision Analysis for Management Judgment Third Edition Paul Goodwin The Management School, <strong>University</strong> of Bath George Wright Durham Business School, <strong>University</strong> of Durham
Page 2 and 3: Decision Analysis for Management Ju
Page 6 and 7: Copyright © 2004 John Wiley & Sons
Page 9 and 10: Contents Foreword Lawrence D. Phill
Page 11 and 12: Foreword It is a curious fact that
Page 13 and 14: Preface In an increasingly complex
Page 15: Preface xiii Accompanying web site
Page 18 and 19: 2 Introduction However, when you me
Page 20 and 21: 4 Introduction has been dealt with
Page 22 and 23: 6 Introduction create and evaluate
Page 24 and 25: 8 Introduction (Chapter 3) to ident
Page 26 and 27: 10 Introduction Supporting top-leve
Page 28 and 29: 12 Introduction decision conferenci
Page 31 and 32: 2 How people make decisions involvi
Page 33 and 34: Heuristics used for decisions invol
Page 39 and 40: Summary 23 first brand. Apparently
Page 41 and 42: Discussion questions 25 Model Price
Page 43 and 44: 3 Decisions involving multiple obje
Page 45 and 46: An office location problem 29 we ma
Page 47 and 48: Constructing a value tree 31 office
Page 49 and 50: Constructing a value tree 33 evalua
Page 51 and 52: Measuring how well the options perf
Page 53 and 54: Measuring how well the options perf
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Measuring how well the options perf
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Determining the weights of the attr
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Aggregating the benefits using the
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Trading benefits against costs 45 V
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Sensitivity analysis 47 Sensitivity
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Theoretical considerations 49 shoul
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Conflicts between intuitive and ana
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Variants of SMART 53 then the model
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SMARTER 55 The second difference be
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Summary 57 we hope to obtain. Analy
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Exercises 59 Package Ease of use Fa
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Exercises 61 (b) For each form of t
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Exercises 63 apparent commitment to
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Exercises 65 all of the ‘benefit
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Exercises 67 (ii) ease of transport
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References 69 were respectively con
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4 Introduction Introduction to prob
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Approaches to probability 73 Approa
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Approaches to probability 75 The su
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The addition rule 77 If the events
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Marginal and conditional probabilit
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The multiplication rule 81 example,
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Probability distributions 83 Social
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Probability distributions 85 In con
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Expected values 87 easier to treat
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Summary 89 of the two monetary valu
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Exercises 91 What is the probabilit
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Exercises 93 probability that the m
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5 Decision making under uncertainty
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The maximin criterion 97 Given thes
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Limitations of the EMV criterion 99
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Limitations of the EMV criterion 10
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Single-attribute utility 103 Low at
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Single-attribute utility 105 (when
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Single-attribute utility 107 Choose
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Interpreting utility functions 109
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Utility functions for non-monetary
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The axioms of utility 113 Ronen et
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The axioms of utility 115 the highe
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More on utility elicitation 117 Dec
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How useful is utility in practice?
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How useful is utility in practice?
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Multi-attribute utility 123 linear
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Multi-attribute utility 125 Mutual
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Multi-attribute utility 127 Utility
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Multi-attribute utility 129 lottery
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Multi-attribute utility 131 0.5 0.5
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Exercises 133 maker does not have a
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Exercises 135 the offer and give th
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Exercises 137 Average weekly operat
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Exercises 139 been classified as ei
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References 141 11. Von Winterfeldt,
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144 Decision trees and influence di
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Car won't start All other problems
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180 Applying simulation to decision
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7 Appendix The standard deviation T
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8 Revising judgments in the light o
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Bayes’ theorem 217 1000 component
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Bayes’ theorem 219 probability th
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The effect of new information 221 E
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The effect of new information 223 P
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Assessing the value of new informat
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Practical considerations 235 inform
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Exercises 237 the reliability of th
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Exercises 239 (a) The company’s m
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Exercises 241 (8) The managers of R
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Exercises 243 bill of $6000 for any
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References 245 are favorable or unf
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248 Biases in probability assessmen
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278 Methods for eliciting probabili
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11 Risk and uncertainty management
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The Two Valleys Company 299 Fixed c
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The Two Valleys Company 301 annual
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The Two Valleys Company 303 Demand
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Summary 305 Table 11.3 - Ideas for
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Exercise 307 (a) The percentage of
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12 Decisions involving groups of in
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Aggregating judgments in general 31
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Aggregating judgments in general 31
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Aggregating preference judgments 31
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Structured group processes 321 said
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Decision conferencing 323 In contra
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Summary 325 virtually all real-worl
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References 327 Mean score Stay at B
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13 Resource allocation and negotiat
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The main stages of the analysis 331
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An illustrative problem 345 weekly
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An illustrative problem 347 Table 1
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Summary 349 Practical applications
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Discussion questions 351 Table 13.4
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References 353 References 1. Philli
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356 Decision framing and cognitive
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14 Appendix Figure 14.6 - Solution
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378 Scenario planning pressures. Th
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380 Scenario planning in, say, 10 y
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382 Scenario planning Positive Scen
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384 Scenario planning Provide high-
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386 Scenario planning ‘PLENTY FOR
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388 Scenario planning Is a Current
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390 Scenario planning But after a y
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392 Scenario planning low power hig
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394 Scenario planning Internet-faci
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396 Scenario planning collectivism
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398 Scenario planning government. E
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400 Scenario planning are determine
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402 Scenario planning against multi
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404 Scenario planning Scenario 1: (
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406 Scenario planning These scores
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408 Scenario planning Objective Wei
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410 Scenario planning process of an
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16 Introduction The analytic hierar
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Making pairwise comparisons of attr
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Obtaining weights and checking cons
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Sensitivity analysis 419 erroneous
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Strengths and criticisms of the AHP
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Exercises 423 Conclusion The AHP is
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References 425 8. Belton, V. and St
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428 Alternative decision-support sy
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464 Suggested answers to selected q
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Index @RISK 205 across-criteria wei
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Index 473 distinctive competencies
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Index 475 net present value (NPV) m
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Index 477 utility functions 7, 102
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