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Decision Modeling in Policy Management : An Introduction to the Analytic Concepts - Giampiero Beroggi

Decision Modeling in Policy Management

An Introduction to the Analytic Concepts

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Published: 31st October 1998
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The effectiveness of policy decisions depends not only on the quality of the analysis but also on the communication between analyst and decision-maker. As a result, this book employs the following three-step decomposition of the decision modeling process throughout the book: (1) visual-structural modeling, (2) analytic-formal modeling, and (3) algorithmic resolution modeling. The 10 chapters address the most relevant issues in decision modeling in policy management: the problem-solving process, visual decision modeling, descriptive and normative preference elicitation and aggregation methods, dealing with uncertainty in dynamic problems, social choices, conflict resolution, and constraint-optimization problems. A problem-oriented engineering approach has been taken throughout the book because this approach covers the most popular decision modeling issues in: (1) decision analysis (decision trees, probabilistic influence diagrams, fuzzy decision-making, risk analysis), (2) operations research (facility location, scheduling, linear and non-linear programming, network optimization), and (3) economics (cost-benefit analysis, capital budgeting, shadow prices, marginal rate of substitution, net present value, game theory).
Decision Modeling in Policy Management:

  • Introduces a visual approach to decision modeling in policy management (over 100 figures and illustrations), integrating the European School (outranking relations, dimension reduction, ordinal preferences, rank correlation) and the American School (utility theory, analytic hierarchy process, game theory, constraint-optimization).
  • Presents analytic approaches in the context of structural, formal, and resolution modeling; references to further practical and theoretical readings; intuitive visual reasoning; detailed numerical examples replacing theorems and formal proofs.
  • Discusses new decision analytical features: visual interactive preference ordering; dynamic plots in virtual negotiation; hypermedia influence diagram modeling.
  • Integrates 100 problems with worked-out solutions; an Internet syllabus with assignments, students comments, and Internet multimedia software are available.

Prefacep. xv
Acknowledgmentsp. xvii
Introductionp. xix
The Problem Solving Process
The Context of Problem Solvingp. 1
What is a Problem?p. 1
The Problem Solving Process in Policy Managementp. 3
Problem Identification: The Elements of Decision Makingp. 6
Actors and Decision Makersp. 6
Attribute, Criterion, Objective, and Goalp. 8
Actions and Decision Variablesp. 14
Uncertainties, States, and Scenariosp. 16
Problem Definitionp. 17
Evaluation Measuresp. 17
Measurement Scalesp. 20
Preference Elicitationp. 22
Binary Preference Relationsp. 24
Problem Solutionp. 26
Preference Aggregationp. 26
Dominant and Efficient Alternativesp. 27
Preference Graphsp. 28
Search for Solutionsp. 30
Sensitivity Analysisp. 31
Summaryp. 32
Problemsp. 33
The Analytic Modeling Process
From Problem to Modelp. 36
The Model as Abstraction of Realityp. 36
The Analytic Modeling Processp. 37
Structural Modelsp. 38
Definitions and Elementsp. 38
Actionsp. 41
Criteriap. 43
Scenariosp. 44
Decision Makersp. 45
Formal Modelsp. 46
General Aspectsp. 46
Descriptive vs. Normative Preference Elicitationp. 47
Descriptive Preference Elicitationp. 48
Normative Preference Elicitationp. 49
Single versus Multiaction Decision Problemsp. 51
Resolution Modelsp. 53
General Resolution Approachp. 53
Resolution Complexityp. 55
Interactive Complete Strong Preference Orderingp. 56
Structural Modelp. 56
Formal Modelp. 57
Resolution Modelp. 58
Summaryp. 60
Problemsp. 61
Descriptive Assessment - Criteria and Weights
Relative Intensities and Weightsp. 64
Consistent Assessmentp. 64
Relative Importance and Ratio Scalep. 67
Resolution of Inconsistenciesp. 69
Hierarchical Decomposition of Criteriap. 74
Structural Modelp. 74
Formal Modelp. 75
Aggregation of Criteriap. 76
Differentiation Power of Criteriap. 76
Computational Aspectsp. 79
An Example of Dimension Reduction and Interpretationp. 82
Summary and Further Readingsp. 85
Problemsp. 85
Descriptive Assessment - Alternatives and Ranking
Structural Model of Descriptive Approachesp. 88
Basic Conceptsp. 88
Preference Aggregation: Basic Principlesp. 90
Formal and Resolution Modelsp. 92
Ordinal and Interval Scalesp. 92
Aggregation of Preference Valuesp. 94
Preference Aggregation with Type A Preference Functionp. 95
Preference Aggregation with Type B Preference Functionp. 96
Incomplete Preference Ranking of Alternativesp. 98
Ratio Scalep. 100
Relative Preference Assessmentp. 100
Absolute Preference Assessmentp. 101
Formalizing Structural and Content Goalsp. 103
Sensitivity Analysisp. 104
Structural Instabilityp. 105
Functional Instabilityp. 107
Numerical Instabilityp. 109
Summary and Further Readingsp. 110
Problemsp. 111
Values and Normative Choice
The Structural Modelp. 112
Conceptual Aspectsp. 112
The Structurep. 114
The Formal Model of Value Theoryp. 115
Motivation and Axioms of Value Theoryp. 115
Preferential Independencep. 118
Two Criteriap. 119
Three Criteriap. 120
More than three Criteriap. 121
Additive Value Functionsp. 121
Linear Value Functions and Perfect Complementsp. 123
Value Functions Over Time Streamsp. 125
Interpretation of 2-Dimensional Value Functionsp. 126
Interpretation of Component Value Functionsp. 128
The Resolution Modelp. 129
The General Approachp. 129
Assessment of Mutual Preferential Independencep. 130
Elicitation of 2-Dimensional Value Functionsp. 131
Elicitation of Component Value Functionp. 132
Assessment of Scaling Constantsp. 134
Solution Searchp. 136
Convex Set and Efficient Frontierp. 136
Evaluation of Explicit versus Search for Implicit Alternativesp. 138
Real-Valued Solutionsp. 139
Sensitivity Analysisp. 140
Summary and Further Readingsp. 141
Problemsp. 142
Choices Under Uncertainty
Decision Making Under Complete Uncertaintyp. 144
Structural Modelp. 144
Formal Modelp. 145
Wald's MaxMin Rulep. 146
Savage's MinMax Regret Rulep. 147
Hurwicz's Optimism-Pessimism Indexp. 148
Laplace's Principle of Insufficient Reasoningp. 148
Resolution Modelp. 149
Decision Making Under Riskp. 149
Structural Modelp. 149
Formal Model: Concept of Probability Theoryp. 151
Types of Probabilityp. 151
Probabilistic Independencep. 153
Arc Reversal (2-dimensional)p. 154
Arc Reversal (3-dimensional)p. 156
Decision Rulesp. 161
Individual Riskp. 161
Collective Riskp. 161
Group Riskp. 164
Aggregation of Linguistic Variablesp. 166
Resolution Modelp. 169
Summary and Further Readingsp. 171
Problemsp. 172
Uncertainty and Normative Choice
The Structural Model for Decision Making Under Uncertaintyp. 174
Conceptual Aspectsp. 174
The Structural Modelp. 177
The Formal Model of Utility Theoryp. 177
Motivation of Utility Theoryp. 177
The Axioms of Utility Theoryp. 179
Assessing Component Utility Functionsp. 181
Interpretation of the Utility Function and Risk Attitudesp. 185
Utility Independencep. 186
Multidimensional Utility Functionsp. 188
Multilinear Utility Functionsp. 188
Multiplicative Utility Functionsp. 189
Additive Utility Functionsp. 190
The Resolution Modelp. 191
The General Approachp. 191
Assessment of Mutual Utility Independencep. 193
Assessment of Scaling Constants and Selection of Modelp. 194
Assessment of Component Utility Functions and Evaluation of Alternativesp. 195
Comments about Utility Theoryp. 197
Summary and Further Readingsp. 198
Problemsp. 200
Sequential Decision Making
The Structure of Sequential Decisionsp. 202
Concept of Probabilistic Influence Diagramsp. 202
The Meaning of Influences in Probabilistic Influence Diagramsp. 204
The Formal Modelp. 209
Defining Probabilistic Relationsp. 209
Decision Treesp. 210
Probabilistic Influence Diagramsp. 211
The Resoltion Modelp. 213
Resolution Stepsp. 213
Barren Node Removalp. 215
Arc Reversalp. 215
Chance Node Removalp. 217
Decision Node Removalp. 220
Node Elimination Algorithmp. 221
Sensitivity Analysisp. 224
Probabilistic Sensitivityp. 224
Value of Informationp. 225
Summary and Further Readingsp. 226
Problemsp. 227
Multi-Actor Decision Making
Structural Models in Multi-Actor Settingsp. 232
Conceptual Aspectsp. 232
Finding the Best Alternative in Group Decision Makingp. 232
Finding the Best Alternative for each Individual Decision Makerp. 233
Formal and Resolution Models in Group Decision Makingp. 234
Aggregation of Ordinal Assessmentsp. 234
Voting Principlesp. 234
Statistical Approachesp. 236
Aggregation of Cardinal Assessmentsp. 240
Aggregation Processp. 240
Aggregation of Normative Evaluationsp. 241
Aggregation of Descriptive Evaluationsp. 243
Aggregation of Linguistic Assessmentsp. 246
Aggregation across Criteriap. 247
Aggregation across Decision Makersp. 248
Formal and Resolution Models in Conflict Settingsp. 249
Two-Actor Strictly Competitive Settingsp. 249
Pure Strategy Sequential Eliminationp. 250
Pure Strategy MinMax Testp. 251
Mixed (Randomized) Strategy Solutionsp. 252
Conflict Resolution and Negotiation Supportp. 254
Non-Pareto Optimal Equilibriump. 254
Pure and Mixed Strategy Equilibriump. 256
Cooperation in Conflict Situationsp. 256
Bargaining (Negotiation) Setsp. 258
Summary and Further Readingsp. 260
Problemsp. 261
Constraint-Based Policy Optimization
Structural Modelp. 264
Basic Concepts and Types of Decision Problemsp. 264
The Structural Modelp. 265
Formal Modelsp. 266
Content Goals: constraints and Aspiration Levelsp. 266
Single-Criterion Optimizationp. 266
Multi-Criteria Optimizationp. 272
Structural Goals: Actions and Content Goalsp. 274
Structural Goals referring to Actionsp. 274
Structural Goals referring to Content Goalsp. 276
Additional Examples of Formal Modelsp. 278
Transportation Planningp. 278
Two-Actor Zero-Sum Conflictsp. 279
Nurse Schedulingp. 281
Mixing Substancesp. 283
Resolution Modelsp. 284
Real-Valued Decision Variablesp. 284
Theoretical Considerationsp. 284
The Simplex Algorithmp. 285
Numerical Examplep. 291
Comments about the Simplex Algorithmp. 292
Duality and Sensitivity Analysisp. 293
General Conceptp. 293
Numerical Examplep. 294
Integer Decision Variablesp. 297
Binary Decision Variablesp. 298
Computer Implementationp. 299
Summary and Further Readingsp. 301
Problemsp. 302
Solutions to Problemsp. 304
Referencesp. 334
Symbol Indexp. 342
Subject Indexp. 344
Table of Contents provided by Syndetics. All Rights Reserved.

ISBN: 9780792383314
ISBN-10: 0792383311
Audience: General
Format: Paperback
Language: English
Number Of Pages: 349
Published: 31st October 1998
Publisher: Springer
Country of Publication: US
Dimensions (cm): 23.88 x 15.95  x 2.29
Weight (kg): 0.64