The Experts below are selected from a list of 228 Experts worldwide ranked by ideXlab platform
Detlof Von Winterfeldt - One of the best experts on this subject based on the ideXlab platform.
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Decision Analysis in Management Science
Management Science, 2020Co-Authors: James E. Smith, Detlof Von WinterfeldtAbstract:A part of the 50th anniversary of Management Science, the journal is publishing articles that reflect on the past, present, and future of the various subfields the journal represents. In this article, we consider Decision Analysis research as it has appeared in Management Science. After reviewing the foundations of Decision Analysis and the history of the journal’s Decision Analysis department, we review a number of key developments in Decision Analysis research that have appeared in Management Science and offer some comments on the current state of the field.
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Biases and Debiasing in Multi-criteria Decision Analysis
2015 48th Hawaii International Conference on System Sciences, 2015Co-Authors: Gilberto Montibeller, Detlof Von WinterfeldtAbstract:Developing models and estimating parameters for multi-criteria Decision Analysis requires judgments by experts and Decision makers. These judgments are subject to biases, which can reduce the quality of the Analysis. Some of these biases are due to faulty cognitive processes, some are due to motivations for preferred Analysis outcomes. We describe these biases, how they affect multi-criteria Decision Analysis and discuss some debiasing techniques.
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Pitfalls of Decision Analysis
Advances in psychology, 2008Co-Authors: Detlof Von WinterfeldtAbstract:Publisher Summary The purpose of this chapter is to systematically explore some typical traps and pitfalls of Decision Analysis, and increase the practitioner's awareness of these problems. Another purpose is to present examples and lessons of the ways pitfalls—once recognized—can best be avoided. Much of this discussion applies directly to Decision Analysis, for example, the pitfall of addressing the wrong problem. Other pitfalls appear to be handled well by Decision Analysis, for example, the neglect of intangibles. Still others seem unique to Decision Analysis, for example, the “gaming” of utilities or probabilities. To provide a rich set of pitfalls several practitioners of Decision Analysis contributed examples of their own applied experiences. This paper discusses their contributions, following the stages of Decision Analysis: developing an analyst–client relationship, defining the problem, organizing the Analysis, structuring and modeling, elicitation of utilities and probabilities, using and implementing the model. For each stage are described the general nature of the possible pitfalls. Hidden agendas sometimes occur in risk Analysis applications of Decision Analysis if the client's intention is to use the Analysis to prove that the product or technology is safe (or unsafe), rather than solving a Decision problem related to the safety of the product. In many such instances, the Analysis is in response to public or governmental concern about safety, and the client expects results that favor his or her position and, therefore, contribute to resolving the controversy in his or her favor. A common pitfall is to take the client's problem at face value. Another trap is to accept the client's restrictions of the part of the problem for which he or she wants an answer. The chapter stresses to understand the client, probe his or her motive, and carefully define the purpose of the Analysis.
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Anniversary Article: Decision Analysis in Management Science
Management Science, 2004Co-Authors: James E. Smith, Detlof Von WinterfeldtAbstract:As part of the 50th anniversary ofManagement Science, the journal is publishing articles that reflect on the past, present, and future of the various subfields the journal represents. In this article, we consider Decision Analysis research as it has appeared inManagement Science. After reviewing the foundations of Decision Analysis and the history of the journal's Decision Analysis department, we review a number of key developments in Decision Analysis research that have appeared inManagement Science and offer some comments on the current state of the field.
Salvatore Greco - One of the best experts on this subject based on the ideXlab platform.
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Trends in Multiple Criteria Decision Analysis - Trends in multiple criteria Decision Analysis
International Series in Operations Research & Management Science, 2020Co-Authors: Matthias Ehrgott, José Rui Figueira, Salvatore GrecoAbstract:Dynamic MCDM, Habitual Domains and Competence Set Analysis for Effective Decision Making in Changeable Spaces.- The Need for and Possible Methods of Objective Ranking.- Preference Function Modelling: The Mathematical Foundations of Decision Theory.- Robustness in Multi-criteria Decision Aiding.- Preference Modelling, a Matter of Degree.- Fuzzy Sets and Fuzzy Logic-Based Methods in Multicriteria Decision Analysis.- Argumentation Theory and Decision Aiding.- Problem Structuring and Multiple Criteria Decision Analysis.- Robust Ordinal Regression.- Stochastic Multicriteria Acceptability Analysis (SMAA).- Multiple Criteria Approaches to Group Decision and Negotiation.- Recent Developments in Evolutionary Multi-Objective Optimization.- Multiple Criteria Decision Analysis and Geographic Information Systems.
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trends in multiple criteria Decision Analysis
2010Co-Authors: Matthias Ehrgott, José Rui Figueira, Salvatore GrecoAbstract:Dynamic MCDM, Habitual Domains and Competence Set Analysis for Effective Decision Making in Changeable Spaces.- The Need for and Possible Methods of Objective Ranking.- Preference Function Modelling: The Mathematical Foundations of Decision Theory.- Robustness in Multi-criteria Decision Aiding.- Preference Modelling, a Matter of Degree.- Fuzzy Sets and Fuzzy Logic-Based Methods in Multicriteria Decision Analysis.- Argumentation Theory and Decision Aiding.- Problem Structuring and Multiple Criteria Decision Analysis.- Robust Ordinal Regression.- Stochastic Multicriteria Acceptability Analysis (SMAA).- Multiple Criteria Approaches to Group Decision and Negotiation.- Recent Developments in Evolutionary Multi-Objective Optimization.- Multiple Criteria Decision Analysis and Geographic Information Systems.
James E. Smith - One of the best experts on this subject based on the ideXlab platform.
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Decision Analysis in Management Science
Management Science, 2020Co-Authors: James E. Smith, Detlof Von WinterfeldtAbstract:A part of the 50th anniversary of Management Science, the journal is publishing articles that reflect on the past, present, and future of the various subfields the journal represents. In this article, we consider Decision Analysis research as it has appeared in Management Science. After reviewing the foundations of Decision Analysis and the history of the journal’s Decision Analysis department, we review a number of key developments in Decision Analysis research that have appeared in Management Science and offer some comments on the current state of the field.
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Anniversary Article: Decision Analysis in Management Science
Management Science, 2004Co-Authors: James E. Smith, Detlof Von WinterfeldtAbstract:As part of the 50th anniversary ofManagement Science, the journal is publishing articles that reflect on the past, present, and future of the various subfields the journal represents. In this article, we consider Decision Analysis research as it has appeared inManagement Science. After reviewing the foundations of Decision Analysis and the history of the journal's Decision Analysis department, we review a number of key developments in Decision Analysis research that have appeared inManagement Science and offer some comments on the current state of the field.
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valuing risky projects option pricing theory and Decision Analysis
Management Science, 1995Co-Authors: James E. SmithAbstract:In the academic literature and professional practice, there are a number of alternative and apparently competing methods for valuing risky projects. In this paper, we compare and contrast three different approaches: risk-adjusted discount-rate Analysis, option pricing Analysis, and Decision Analysis, focusing on the last two. We show that, in contrast to some of the claims made in the "real options" literature, when both option pricing and Decision Analysis methods are correctly applied, they must give consistent results. We also explore ways in which option pricing and Decision Analysis methods can be profitably integrated. In particular, we show how option pricing techniques can be used to simplify Decision Analysis when some risks can be hedged by trading and, conversely, how Decision Analysis techniques can be used to extend option pricing techniques to problems with incomplete securities markets.
Ralph L. Keeney - One of the best experts on this subject based on the ideXlab platform.
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GDN - Understanding and Using the Group Decision Analysis Model
Lecture Notes in Business Information Processing, 2015Co-Authors: Ralph L. KeeneyAbstract:Decision Analysis is usually thought of as a model for Decisions with a single Decision-maker. Many attempts to extend Decision Analysis to group Decisions have led to results indicating how it cannot be done. Other analyses, such as the well-known impossibility theorem of Arrow (1963) [1], have tried to combine rankings of alternatives by individual group members to produce a group ranking. As a result, there had been no logically consistent way to extend the principle of Decision Analysis to group Decisions. A different approach was used in Keeney (2013), where each member of a Decision-making group could have a different Decision frame for their common Decision. Using the assumptions of Decision Analysis for each member’s Analysis of their group Decision and using an analogous set of Decision Analysis assumptions for the group Decision to combine the member’s Decision analyses produced a group Decision Analysis model. This article discusses the concepts and intuitive logic for the model and practical aspects of applying it.
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Foundations for Group Decision Analysis
Decision Analysis, 2013Co-Authors: Ralph L. KeeneyAbstract:This paper derives a general prescriptive model for group Decision Analysis based on a set of logical and operational assumptions analogous to those for individual Decision Analysis. The approach accounts for each group member's potentially different frames of their common Decision, including different events and different consequences of concern. Assuming that each group member accepts the Decision Analysis assumptions to evaluate his or her Analysis of what the group should do and that the group accepts an analogous set of Decision Analysis assumptions for the group's Decision, it is proven that the group expected utility for an alternative should be a weighted sum of the individual member's expected utilities for the alternatives. After each group member does his or her Decision Analysis of the group's alternatives, the essence of the group Decision Analysis is to specify the weights based on the interpersonal comparison of utilities and on the relative importance or power of each individual in the group.
Matthias Ehrgott - One of the best experts on this subject based on the ideXlab platform.
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Trends in Multiple Criteria Decision Analysis - Trends in multiple criteria Decision Analysis
International Series in Operations Research & Management Science, 2020Co-Authors: Matthias Ehrgott, José Rui Figueira, Salvatore GrecoAbstract:Dynamic MCDM, Habitual Domains and Competence Set Analysis for Effective Decision Making in Changeable Spaces.- The Need for and Possible Methods of Objective Ranking.- Preference Function Modelling: The Mathematical Foundations of Decision Theory.- Robustness in Multi-criteria Decision Aiding.- Preference Modelling, a Matter of Degree.- Fuzzy Sets and Fuzzy Logic-Based Methods in Multicriteria Decision Analysis.- Argumentation Theory and Decision Aiding.- Problem Structuring and Multiple Criteria Decision Analysis.- Robust Ordinal Regression.- Stochastic Multicriteria Acceptability Analysis (SMAA).- Multiple Criteria Approaches to Group Decision and Negotiation.- Recent Developments in Evolutionary Multi-Objective Optimization.- Multiple Criteria Decision Analysis and Geographic Information Systems.
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trends in multiple criteria Decision Analysis
2010Co-Authors: Matthias Ehrgott, José Rui Figueira, Salvatore GrecoAbstract:Dynamic MCDM, Habitual Domains and Competence Set Analysis for Effective Decision Making in Changeable Spaces.- The Need for and Possible Methods of Objective Ranking.- Preference Function Modelling: The Mathematical Foundations of Decision Theory.- Robustness in Multi-criteria Decision Aiding.- Preference Modelling, a Matter of Degree.- Fuzzy Sets and Fuzzy Logic-Based Methods in Multicriteria Decision Analysis.- Argumentation Theory and Decision Aiding.- Problem Structuring and Multiple Criteria Decision Analysis.- Robust Ordinal Regression.- Stochastic Multicriteria Acceptability Analysis (SMAA).- Multiple Criteria Approaches to Group Decision and Negotiation.- Recent Developments in Evolutionary Multi-Objective Optimization.- Multiple Criteria Decision Analysis and Geographic Information Systems.
