Evaluation and Decision Models: A Critical Perspective(32 International Series in Operations Research & Management Science)

The purpose of this text is to provide a critical thinking framework for all individuals utilizing decision and evaluation models, whether it be for research or applications. It is axiomatic that all evaluation and decision models suffer some limitations. There are situations where a decision model will not perform to expectations. This book argues that there is no best decision or evaluation model, but that decision-makers must understand the principles of formal evaluation and decision models and apply them critically. Hence, the book seeks to deepen our understanding of evaluation and decision models and encourage users of these models to think more analytically about them. The authors work in six different European universities. Their backgrounds are varied: mathematics, economics, engineering, law, and geology, and they teach in engineering, business, mathematics, computer science, and psychology in their universities. As a group, the authors have particular expertise in a variety of decision models that include preference modelling, fuzzy logic, aggregation techniques, social choice theory, artificial intelligence, problem structuring, measurement theory, operations research, and multiple criteria decision support. In addition to their decision analysis research, all the authors have been involved in a variety of high-impact applications which include software evaluation, location of a nuclear repository, the rehabilitation of a sewer network, and the location of high-voltage lines. It is this variety within the authorship that unifies this book into a systematic examination of how best formal decision models can be used. The monograph should prove a useful tool for researchers of decision analysis and decision-makers.

Table of Contents:
1 Introduction.- 1.1 Motivations.- 1.2 Audience.- 1.3 Structure.- 1.4 Outline.- 1.5 Who are the authors?.- 1.6 Conventions.- 1.7 Acknowledgements.- 2 Choosing on the basis of several opinions.- 2.1 Analysis of some voting systems.- 2.2 Modelling the preferences of a voter.- 2.3 The voting process.- 2.4 Social choice and multiple criteria decision support.- 2.5 Conclusions.- 3 Building and aggregating evaluations.- 3.1 Introduction.- 3.2 Grading students in a given course.- 3.3 Aggregating grades.- 3.4 Conclusions.- 4 Constructing measures.- 4.1 The human development index.- 4.2 Air quality index.- 4.3 The decathlon score.- 4.4 Indicators and multiple criteria decision support.- 4.5 Conclusions.- 5 Assessing competing projects.- 5.1 Introduction.- 5.2 The principles of CBA.- 5.3 Some examples in transportation studies.- 5.4 Conclusions.- 6 Comparing on several attributes.- 6.1 Thierry’s choice.- 6.2 The weighted sum.- 6.3 The additive value model.- 6.4 Outranking methods.- 6.5 General conclusion.- 7 Deciding automatically.- 7.1 Introduction.- 7.2 A System with Explicit Decision Rules.- 7.3 A System with Implicit Decision Rules.- 7.4 An hybrid approach for automatic decision-making.- 7.5 Conclusion.- 8 Dealing with uncertainty.- 8.1 Introduction.- 8.2 The context.- 8.3 The model.- 8.4 A didactic example.- 8.5 Conclusions.- 9 Supporting decisions.- 9.1 Preliminaries.- 9.2 The Decision Process.- 9.3 Decision Support.- 9.4 Conclusions.- Appendix A.- Appendix B.- 10 Conclusion.- 10.1 Formal methods are all around us.- 10.2 What have we learned?.- 10.3 What can be expected?.