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328 Decisions involving groups of individuals 3. De Groot, M. H. (1974) Reaching a Consensus, Journal of the American Statistical Association, 69, 118–121. 4. Lock, A. (1987) Integrating Group Judgments in Subjective Forecasts, in G. Wright and P. Ayton (eds) Judgmental Forecasting, Wiley, Chichester. 5. Morris, P. A. (1983) An Axiomatic Approach to Expert Resolution, Management Science, 29,1,24–32. 6. Bordley, R. F. (1982) The Combination of Forecasts: A Bayesian Approach, Journal of the Operational Research Society, 33, 171–174. 7. Winkler, R. L. (1971) Probabilistic Prediction: Some Experimental Results, Journal of the American Statistical Association, 66, 675–685. 8. Seaver, D. A., Von Winterfeldt, D. and Edwards, W. (1978) Eliciting Subjective Probability Distributions on Continuous Variables, Organisational Behavior and Human Performance, 21, 379–391. 9. Von Winterfeldt, D. and Edwards, W. (1986) Decision Analysis and Behavioral Research, Cambridge <strong>University</strong> Press, New York. 10. Arrow, K. J. (1951) Social Choice and Individual Values, Wiley, New York. 11. French, S. (1988) Decision Theory: An Introduction to the Mathematics of Rationality, Ellis Horwood, Chichester. 12. Janis, I. R. (1982) Groupthink (2nd edn), Houghton Mifflin, Boston, MA. 13. Esser, J. K. and Lindoerfer, J. S. (1989) Groupthink and the Space Shuttle Challenger Accident: Towards a Quantitative Case Analysis, Journal of Behavioral Decision Making, 2, 167–177. See also: Park, W. W. (1990) A Review of Research on Groupthink, Journal of Behavioral Decision Making, 3, 229–245. 14. For reviews see: Parente, F. J. and Anderson-Parente, J. K. (1987) Delphi Inquiry Systems, in G. Wright and P. Ayton (eds) Judgmental Forecasting, Wiley, Chichester. See also: Rowe, G., Wright, G. and Bolger, F. (1991) Delphi: A Re-evaluation of Research and Theory, Technical Forecasting and Social Change, 39, 235–251; Rowe, G. and Wright, G. (1996) The Impact of Task Characteristics on the Performance of Structured Group Forecasting Techniques, International Journal of Forecasting, 12, 73–90;Rowe,G.and Wright, G. (1999) The Delphi Technique as a Forecasting Tool: Issues and Analysis, International Journal of Forecasting, 15, 353–375. 15. Linstone, H. and Turoff, M. (1975) The Delphi Method: Techniques and Applications, Addison-Wesley, Wokingham. 16. Ferrell, W. R. (1990) Aggregation of Judgments or Judgment of Aggregations? in N. Moray, W. Rouse and W. R. Ferrell (eds) Robotics, Control and Society: Essays in Honor of Thomas B. Sheridan, Taylor and Francis, New York. 17. Phillips, L. D. (1984) A Theory of Requisite Decision Models, Acta Psychologica, 56, 29–48. 18. McCartt, A. and Rohrbough, J. (1989) Evaluating Group Decision Support System Effectiveness: A Performance Study of Decision Conferencing, Decision Support Systems, 5, 243–253.
13 Resource allocation and negotiation problems Introduction In this chapter we will consider how decision analysis models can be applied to two types of problem which usually involve groups of decision makers. First, we will study problems where a limited resource has to be allocated between a number of alternative uses. For example, a group of product managers may have to decide on how next year’s advertising budget should be divided between the products for which they are responsible. Similarly, a local police force might have to determine how its available personnel should be allocated between tasks such as crime prevention, traffic policing and the investigation of serious and petty crimes. As Phillips 1,2 argues, the central purpose of resource allocation models in decision analysis is to resolve what is known as the commons dilemma. On the one hand, an organization can decentralize its decision making, allowing each manager to make the best use of the resources which he or she is allocated. While this delegation of responsibility will probably motivate the managers, it is unlikely that the resulting set of independent decisions will lead to an allocation of resources which is best for the organization as a whole. The alternative is to centralize decision making, but this may be demotivating and the resulting allocation will not take into account the local knowledge of the individual managers. The dilemma can be resolved by the managers meeting as a group, possibly in a decision conference, and examining the effect of trading off resources between their areas of responsibility. Of course, some managers may find that they lose resources as a result of this process, but these losses should be more than compensated by the increased benefits of reallocating the resources elsewhere. As we shall see, the number of combinations of options that are available in this sort of decision problem can be very large, therefore a computer is normally required
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Decision Analysis for Management Ju
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Decision Analysis for Management Ju
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To Mary and Josephine, Jamie, Jerom
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viii Contents Chapter 16 The analyt
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x Foreword real problems, and it is
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xii Preface accountancy, where rece
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1 Introduction Complex decisions Im
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The role of decision analysis 3 you
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Applications of decision analysis 5
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Overview of the book 11 and profit.
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References 13 8. Walls, M. R., Mora
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16 How people make decisions involv
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28 Decisions involving multiple obj
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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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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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