A robustness study of state-of-the-art surrogate weights for MCDM

A vast number of methods for solving multi-criteria decision problems have been suggested for assessing criteria weights requiring more exact input data than users normally are able to provide. In particular, the selection of adequate criteria weights is difficult and in order to be realistic, other methods must be introduced. One class of such methods is to introduce so called surrogate weights, where numerical weights are assigned to each criterion based on a cardinal or ordinal rank ordering, assumed to represent the information extracted from the user. One essential problem is the robustness of such methods. In this article, we compare state-of-the-art methods based on surrogate weights from the literature and, utilizing a simulation approach, discuss underlying assumptions and robustness properties. This results in a quantitative measurement of these weighting methods and a methodology applicable also to forthcoming methods

Utilizing Surrogate Numbers for Probability Elicitation

Comparatively few of the vast number of suggested decision-analytical methods have been widely spread in actual practice. The majority of those methods call for exact and accurate numbers as input, which could be one of several reasons for this lack of actual use; people frequently seem to be unfamiliar with, or reluctant to express those, in a sense, “true” values required. Many alternative methods to resolve this complication have been suggested over the years, including procedures for dealing with incomplete information. One way, which has proliferated for a while, is to introduce so-called surrogate numbers in the form of ordinal ranking methods for multi-criteria weights. In this chapter, we show how those can be adapted for use in probability elicitation. Furthermore, when decision-makers possess more information regarding the relative strengths of probabilities, that is, some form of cardinality, the input information to ordinal methods is sometimes too restricted. Therefore, we suggest a testing methodology and analyze the relevance of a set of cardinal ordering methods in addition to the ordinal ones

Imprecise swing weighting for multi-attribute utility elicitation based on partial preferences.

We describe a novel approach to multi-attribute utility elicitation which is both general enough to cover a wide range of problems, whilst at the same time simple enough to admit reasonably straightforward calculations. We allow both utilities and probabilities to be only partially specified, through bounding. We still assume marginal utilities to be precise. We derive necessary and sufficient conditions under which our elicitation procedure is consistent. As a special case, we obtain an imprecise generalization of the well known swing weighting method for eliciting multi-attribute utility functions. An example from ecological risk assessment demonstrates our method

The CAR Method for Using Preference Strength in Multi-criteria Decision Making

Multi-criteria decision aid (MCDA) methods have been around for quite some time. However, the elicitation of preference information in MCDA processes, and in particular the lack of practical means supporting it, is still a significant problem in real-life applications of MCDA. There is obviously a need for methods that neither require formal decision analysis knowledge, nor are too cognitively demanding by forcing people to express unrealistic precision or to state more than they are able to. We suggest a method, the CAR method, which is more accessible than our earlier approaches in the field while trying to balance between the need for simplicity and the requirement of accuracy. CAR takes primarily ordinal knowledge into account, but, still recognizing that there is sometimes a quite substantial information loss involved in ordinality, we have conservatively extended a pure ordinal scale approach with the possibility to supply more information. Thus, the main idea here is not to suggest a method or tool with a very large or complex expressibility, but rather to investigate one that should be sufficient in most situations, and in particular better, at least in some respects, than some hitherto popular ones from the SMART family as well as AHP, which we demonstrate in a set of simulation studies as well as a large end-user study

Imprecise swing weighting for multi-attribute utility elicitation based on partial preferences

We describe a novel approach to multi-attribute utility elicitation which is both general enough to cover a wide range of problems, whilst at the same time simple enough to admit reasonably straightforward calculations. We allow both utilities and probabilities to be only partially specified, through bounding. We still assume marginal utilities to be precise. We derive necessary and sufficient conditions under which our elicitation procedure is consistent. As a special case, we obtain an imprecise generalization of the well known swing weighting method for eliciting multi-attribute utility functions. An example from ecological risk assessment demonstrates our method

Deliberation, Representation, Equity

"What can we learn about the development of public interaction in e-democracy from a drama delivered by mobile headphones to an audience standing around a shopping center in a Stockholm suburb? In democratic societies there is widespread acknowledgment of the need to incorporate citizens’ input in decision-making processes in more or less structured ways. But participatory decision making is balancing on the borders of inclusion, structure, precision and accuracy. To simply enable more participation will not yield enhanced democracy, and there is a clear need for more elaborated elicitation and decision analytical tools. This rigorous and thought-provoking volume draws on a stimulating variety of international case studies, from flood risk management in the Red River Delta of Vietnam, to the consideration of alternatives to gold mining in Roșia Montană in Transylvania, to the application of multi-criteria decision analysis in evaluating the impact of e-learning opportunities at Uganda's Makerere University. Editors Love Ekenberg (senior research scholar, International Institute for Applied Systems Analysis [IIASA], Laxenburg, professor of Computer and Systems Sciences, Stockholm University), Karin Hansson (artist and research fellow, Department of Computer and Systems Sciences, Stockholm University), Mats Danielson (vice president and professor of Computer and Systems Sciences, Stockholm University, affiliate researcher, IIASA) and Göran Cars (professor of Societal Planning and Environment, Royal Institute of Technology, Stockholm) draw innovative collaborations between mathematics, social science, and the arts. They develop new problem formulations and solutions, with the aim of carrying decisions from agenda setting and problem awareness through to feasible courses of action by setting objectives, alternative generation, consequence assessments, and trade-off clarifications. As a result, this book is important new reading for decision makers in government, public administration and urban planning, as well as students and researchers in the fields of participatory democracy, urban planning, social policy, communication design, participatory art, decision theory, risk analysis and computer and systems sciences.

Deliberation, Representation, Equity: Research Approaches, Tools and Algorithms for Participatory Processes

In democratic societies there is widespread acknowledgment of the need to incorporate citizens’ input in decision-making processes in more or less structured ways. But participatory decision making is balancing on the borders of inclusion, structure, precision and accuracy. To simply enable more participation will not yield enhanced democracy, and there is a clear need for more elaborated elicitation and decision analytical tools. This rigorous and thought-provoking volume draws on a stimulating variety of international case studies, from flood risk management in the Red River Delta of Vietnam, to the consideration of alternatives to gold mining in Roșia Montană in Transylvania, to the application of multi-criteria decision analysis in evaluating the impact of e-learning opportunities at Uganda's Makerere University. This book is important new reading for decision makers in government, public administration and urban planning, as well as students and researchers in the fields of participatory democracy, urban planning, social policy, communication design, participatory art, decision theory, risk analysis and computer and systems sciences

The Explanatory and Predictive Power of Non Two-Stage-Probability Theories of Decision Making Under Ambiguity

Representing ambiguity in the laboratory using a Bingo Blower (which is transparent and not manipulable) and asking the subjects a series of allocation questions (which are more efficient than pairwise choice questions), we obtain data from which we can estimate by maximum likelihood methods (with explicit assumptions about the errors made by the subjects) a significant subset of the empirically relevant models of behaviour under ambiguity, and compare their relative explanatory and predictive abilities. Our results suggest that not all recent models of behaviour represent a major improvement in explanatory and predictive power, particularly the more theoretically sophisticated ones.Alpha Model, Ambiguity, Bingo Blower, Choquet Expected Utility, Contraction Model, Rank Dependent Expected Utility, Subjective Expected Utility,Vector Expected Utility.

Deliberation, Representation, Equity

"What can we learn about the development of public interaction in e-democracy from a drama delivered by mobile headphones to an audience standing around a shopping center in a Stockholm suburb? In democratic societies there is widespread acknowledgment of the need to incorporate citizens’ input in decision-making processes in more or less structured ways. But participatory decision making is balancing on the borders of inclusion, structure, precision and accuracy. To simply enable more participation will not yield enhanced democracy, and there is a clear need for more elaborated elicitation and decision analytical tools. This rigorous and thought-provoking volume draws on a stimulating variety of international case studies, from flood risk management in the Red River Delta of Vietnam, to the consideration of alternatives to gold mining in Roșia Montană in Transylvania, to the application of multi-criteria decision analysis in evaluating the impact of e-learning opportunities at Uganda's Makerere University. Editors Love Ekenberg (senior research scholar, International Institute for Applied Systems Analysis [IIASA], Laxenburg, professor of Computer and Systems Sciences, Stockholm University), Karin Hansson (artist and research fellow, Department of Computer and Systems Sciences, Stockholm University), Mats Danielson (vice president and professor of Computer and Systems Sciences, Stockholm University, affiliate researcher, IIASA) and Göran Cars (professor of Societal Planning and Environment, Royal Institute of Technology, Stockholm) draw innovative collaborations between mathematics, social science, and the arts. They develop new problem formulations and solutions, with the aim of carrying decisions from agenda setting and problem awareness through to feasible courses of action by setting objectives, alternative generation, consequence assessments, and trade-off clarifications. As a result, this book is important new reading for decision makers in government, public administration and urban planning, as well as students and researchers in the fields of participatory democracy, urban planning, social policy, communication design, participatory art, decision theory, risk analysis and computer and systems sciences.