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24 How people make decisions involving multiple objectives If human decision making is not as bad as earlier researchers believed, does decision analysis still have a role as an aid to management decision making? We believe it does. The fast and frugal heuristics identified by Gigerenzer et al. enable us to make smart choices when ‘time is pressing and deep thought is unaffordable luxury’. Major decisions, such as a decisions on whether to launch a new product or where to site a new factory, do merit time and deep thought. Decision analysis allows managers to use this time effectively and enables them to structure and clarify their thinking. It encourages decision makers to explore trade-offs between attributes and both clarifies and challenges their perceptions of risk and uncertainty. As the previous chapter indicated it also delivers a documented and defensible rationale for a given decision and enhances communication within decision-making teams. The rest of this book is devoted to showing how decision analysis methods can provide these important benefits and hence overcome the limitations of unaided decision making. The next chapter introduces a method designed to support decision makers faced with decisions involving multiple objectives. As we shall see, in contrast to heuristics like the lexicographic strategy or elimination by aspects, this method is designed to allow decision makers to make compensatory choices. Discussion questions (1) In what circumstances is the recognition heuristic likely to work well? (2) A manager is ordering 40 inkjet printers for staff working in the company’s main office. Details of the available models are given below. The print quality score has been produced by an independent magazine. The score ranges from 1 = very poor to 5 = excellent. Model Price Mono printing speed (ppm) Print quality score Noise level (dBA) Solar $200 12.0 5 45 Symbol $159 7.8 4 46 Real $169 5.4 3 38 CCC $250 6.0 5 40 Tiger $80 4.1 4 48 Linwood $110 5.6 4 43 GA $185 5.4 4 40 Superb $210 7.2 4 45
Discussion questions 25 Model Price Mono printing speed (ppm) Print quality score Noise level (dBA) Multitask $170 6.1 5 36 AR52 $237 14.0 5 48 Zeta $105 7.0 2 45 Multitask 2 $118 9.1 3 43 Use the above information to demonstrate how the manager could apply each of the following strategies to choose the computer and discuss the advantages and disadvantages of using these strategies. (a) Lexicographic (b) Semi-lexicographic (c) Elimination by aspects (d) Satisficing. (3) After her examinations a student decides that she needs a holiday. A travel agent supplies the following list of last minute holidays that are available. The student works down the list, considering the holidays in the order that they appear until she comes across one that is satisfactory, which she books. Her minimal requirements are: (i) The holiday must last at least 10 days (ii) It must cost no more than $1500 (iii) It must not be self-catering (iv) It must be located in accommodation, which is no more than 5 minutes’ walk from the beach. Determine which holiday she will choose from the list below and discuss the limitations of the strategy that she has adopted. Location Duration Cost Self-catering? Walking time to beach Canada 7 days $750 No 2 minutes Barbados 10 days $1200 No 4 minutes Canary Isles 14 days $2000 No 10 minutes Greece 10 days $1100 Yes 2 minutes Spain 10 days $1000 Yes 5 minutes Turkey 14 days $1000 No 1 minute California 14 days $975 No 0 minutes Florida 10 days $1800 No 30 minutes Mexico 14 days $1500 No 8 minutes
Page 2 and 3: Decision Analysis for Management Ju
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Page 7: To Mary and Josephine, Jamie, Jerom
Page 10 and 11: viii Contents Chapter 16 The analyt
Page 12 and 13: x Foreword real problems, and it is
Page 14 and 15: xii Preface accountancy, where rece
Page 17 and 18: 1 Introduction Complex decisions Im
Page 19 and 20: The role of decision analysis 3 you
Page 21 and 22: Applications of decision analysis 5
Page 27 and 28: Overview of the book 11 and profit.
Page 29: References 13 8. Walls, M. R., Mora
Page 32 and 33: 16 How people make decisions involv
Page 44 and 45: 28 Decisions involving multiple obj
Page 88 and 89: 72 Introduction to probability Beca
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74 Introduction to probability prac
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76 Introduction to probability we w
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78 Introduction to probability whet
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80 Introduction to probability give
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82 Introduction to probability prob
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84 Introduction to probability deci
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86 Introduction to probability that
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88 Introduction to probability inte
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90 Introduction to probability subj
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92 Introduction to probability (5)
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94 Introduction to probability (a)
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96 Decision making under uncertaint
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98 Decision making under uncertaint
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100 Decision making under uncertain
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6 Decision trees and influence diag
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Constructing a decision tree 145 be
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Determining the optimal policy 147
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Decision trees and utility 149 succ
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Decision trees involving continuous
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Practical applications of decision
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Assessment of decision structure 15
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Assessment of decision structure 15
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Eliciting decision tree representat
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Eliciting decision tree representat
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Summary 163 where the resulting dec
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Exercises 165 other elements of the
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Exercises 167 (b) Assuming that Wes
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Exercises 169 is not hired, given t
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Exercises 171 failing to meet the p
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Exercises 173 why it was rational f
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Exercises 175 (11) In the Eagle Mou
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References 177 ABC Chemicals are pl
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7 Applying simulation to decision p
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Monte Carlo simulation 181 Of cours
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Monte Carlo simulation 183 Table 7.
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Applying simulation to a decision p
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Applying simulation to investment d
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Summary 205 Hull 10 ), some of them
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Exercises 207 (c) Use your simulati
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Exercises 209 For each factor the f
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Exercises 211 (b) Suppose that your
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References 213 6 million Therefore
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216 Revising judgments in the light
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9 Biases in probability assessment
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Introduction 249 of people watching
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The availability heuristic 251 make
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The representativeness heuristic 25
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The anchoring and adjustment heuris
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The anchoring and adjustment heuris
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Other judgmental biases 263 Other j
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Is human probability judgment reall
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Exercises 271 Did you receive timel
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References 273 have been taken from
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References 275 18. Hamilton, D. L.
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10 Methods for eliciting probabilit
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Preparing for probability assessmen
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Consistency and coherence checks 28
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Assessment of the validity of proba
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Assessment of the validity of proba
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Assessing probabilities for very ra
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Exercises 293 Odds in favor of even
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References 295 13. Wright, G. and W
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298 Risk and uncertainty management
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310 Decisions involving groups of i
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330 Resource allocation and negotia
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14 Decision framing and cognitive i
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How people frame decisions 357 Figu
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Imposing imaginary constraints and
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Inertia in strategic decision makin
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Studies in the psychological labora
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Overcoming inertia? 369 it is diffi
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Discussion questions 373 frame anal
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References 375 References 1. Luchin
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15 Scenario planning: an alternativ
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Introduction 379 documented in Chap
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Scenario construction: the extreme-
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Using scenarios in decision making
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Using scenarios in decision making
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Scenario construction: the driving
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Case study of a scenario interventi
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Table 15.1 - The components of the
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Illustrative case study 403 (b) Att
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Illustrative case study 405 Stage 4
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Illustrative case study 407 importa
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Conclusion 409 combinations. Often
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References 411 2. Van der Heijden,
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414 The analytic hierarchy process
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17 Alternative decision-support sys
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Expert systems 429 generally agreed
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Expert systems 431 that knowledge e
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Expert systems 433 (1) That the sub
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Expert systems 435 information syst
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Expert systems 437 to focus on ‘t
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Expert systems 439 On the basis of
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Is there any intention/expectation
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Expert systems 443 described above
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Expert systems 445 body of knowledg
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Statistical models of judgment 447
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Comparisons 453 ‘broken leg’ cu
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Some final words of advice 455 Ques
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Some final words of advice 457 of t
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References 459 Table 17.1 - Summary
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References 461 20. Eisenhart, J. (1
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Chapter 3 Suggested answers to sele
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Suggested answers to selected quest
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472 Index Brown, C.E. 446 Brown, S.
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474 Index HIVIEW 58 Hodgkinson, G.P
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476 Index scenario intervention cas
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