Dominance Measuring Approach using Stochastic Weights

In this paper we propose an approach to obtain a ranking of alternatives in multicriteria decision-making problems when there is imprecision concerning the alternative performances, component utility functions and weights. We assume decision maker's preferences are represented by an additive multi-attribute utility function, in which weights are modeled by independent normal variables, the performance in each attribute for each alternative is an interval value and classes of utility functions are available for each attribute. The approach we propose is based on dominance measures, which are computed in a similar way that when the imprecision concerning weights is modeled by uniform distributions or by an ordinal relation. In this paper we will show how the approach can be applied when the imprecision concerning weights are represented by normal distributions. Extensions to other distributions, such as truncated normal or beta, can be feasible using Monte Carlo simulation techniques

Risk Preferences, Perceptions and Systematic Biases

Replaced with revised version of paper 07/21/06.Risk and Uncertainty,

Management decision making by the analytic hierarchy process: A proposed modification for large-scale problems

Frequently, management decision making problems involve multiple criteria/objectives/attributes. Over the years, many quantitative methods have been developed to facilitate making rational decisions involving multiple criteria. The Analytic Hierarchy Process (AHP) is, in general, regarded as one of the most successful techniques to solve decision making problems involving multiple criteria. In AHP, the decision maker starts by constructing the overall hierarchy of the decision problem. The hierarchy consists of criteria, subcriteria and alternatives of the decision making problem. A number of pairwise comparison matrices are formed in order to derive weights of the criteria and the local weights of the alternatives. Subsequently, the principle of hierarchical composition is used to determine the global weights of the alternatives. The alternative with the highest global weight is selected as the best alternative. The drawback of the traditional AHP is that it requires a large number of pairwaise comparisons, especially in the presence of a large number of criteria. The present empirical study attempts to investigate the possibility of eliminating insignificant criteria in order to reduce AHP computational time. Using the Expert Choice software, findings confirm that criteria that carry comparatively lesser weights can be excluded from the hierarchy and thereby the total time required for making the pairwise comparisons can be reduced drastically. To solve large-scale enterprise multi-criteria decision making problems (that involve large number of criteria) by AHP, it is proposed that at the very outset, decision makers can apply nominal group technique to identify the insignificant criteria. These criteria can be dropped from subsequent analysis and this exclusion will not affect the final decision significantly. This proposed methodology is expected to enhance the applicability of AHP in solving various kinds of larger sized multi-criteria decision making problems in any enterprise.Multiple criteria decision making, Analytic hierarchy process, Nominal group technique, Large-scale problems, International business

On the beliefs off the path: equilibrium refinement due to quantal response and level-k

This paper studies the relevance of equilibrium and nonequilibrium explanations of behavior, with respects to equilibrium refinement, as players gain experience. We investigate this experimentally using an incomplete information sequential move game with heterogeneous preferences and multiple perfect equilibria. Only the limit point of quantal response (the limiting logit equilibrium), and alternatively that of level-k reasoning (extensive form rationalizability), restricts beliefs off the equilibrium path. Both concepts converge to the same unique equilibrium, but the predictions differ prior to convergence. We show that with experience of repeated play in relatively constant environments, subjects approach equilibrium via the quantal response learning path. With experience spanning also across relatively novel environments, though, level-k reasoning tends to dominate

Governmental Positions on European Treaty Reforms: Towards a Dynamic Approach.

Governmental positions are a powerful predictor of European treaty reforms. Yet, few empirical studies analyze the conditionalies between positions over different issues or conflict dimensions. If governmental positions are conditional upon the real or expected outcome on other issues, the sequence of decisions becomes increasingly important for our understanding of European treaty reforms. So far, not many studies analyze the sequence of intergovernmental decisions. In the present paper, I argue that governmental preferences over the reform of the EU decision rule dependent on the delegation of competences to the EU and vice versa. Moreover, I present a statistical model which allows for estimating this conditionality. Subsequently, I apply this model to an extensive data set of reform positions revealed by national governments at the Intergovernmental Conferences (IGC) 2003/4. Next, I analyze the sequence of decision taken by this particular IGC in chronological order. For this purpose, I predict the change of governmental position in response to the decisions over subsets of issues and I compare these predictions to public statements issued by governmental leaders at the time. Finally, I discuss the implications for our understanding of the intergovernmental bargaining outcome

A prescriptive approach to qualify and quantify customer value for value-based requirements engineering

Recently, customer-based product development is becoming a popular paradigm. Customer expectations and needs can be identified and transformed into requirements for product design with the help of various methods and tools. However, in many cases, these models fail to focus on the perceived value that is crucial when customers make the decision of purchasing a product. In this paper, a prescriptive approach to support value-based requirements engineering (RE) is proposed, describing the foundations, procedures and initial applications in the context of RE for commercial aircraft. An integrated set of techniques, such as means-ends analysis, part-whole analysis and multi-attribute utility theory is introduced in order to understand customer values in depth and width. Technically, this enables identifying the implicit value, structuring logically collected statements of customer expectations and performing value modelling and simulation. Additionally, it helps to put in place a system to measure customer satisfaction that is derived from the proposed approach. The approach offers significant potential to develop effective value creation strategies for the development of new product