An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making

The use of Choquet integral as an aggregation operator in multi-criteria decision-making problems requires the prior estimation of fuzzy measure values. λ0 -measure is one form of fuzzy measure which was introduced to reduce the usual computational complexity associated with the estimation of fuzzy measure values. However, the existing techniques to estimate λ0 -measure require some amount of initial data from the decision-makers. This paper, therefore, aimed at proposing a completely unsupervised estimation technique, where the λ0- measure values are directly derived based on the available decision matrix, without the need for any initial data from the decision-makers. The technique was developed by incorporating the CRITIC method into the original λ0 - measure estimation technique. The usage of the proposed technique was illustrated based on a university course evaluation problem. The same problem was also solved with a conventional additive operator for the comparison purpose

Stochastic multiattribute acceptability analysis:an application to the ranking of Italian regions

<p>We consider the issue of ranking regions with respect to a range of economic and social variables. Departing from the current practice of aggregating different dimensions via a composite index, usually based on an arithmetic mean, we instead use stochastic multi-attribute acceptability analysis (SMAA). SMAA considers the ‘whole space’ of weights for the considered dimensions. The methodology is applied to the ranking of Italian regions, showing that although the north–south divide is definitely wider than the one measured simply in terms of gross domestic product. There are southern regions that perform generally better than those belonging to their broad region: a kind of ‘northern regions within the southern broad region’. This result poses interesting questions about the uneven development of Italian regions.</p

Combining user preferences and expert opinions: a criteria synergy-based model for decision making on the Web

Customers strongly base their e-commerce decisions on the opinions of others by checking reviews and ratings provided by other users. These assessments are overall opinions about the product or service, and it is not possible to establish why they perceive it as good or bad. To understand this “why”, it is necessary an expert’s analysis concerning the relevant factors of the product or service. Frequently, these two visions are not coincident and the best product for experts may not be the best one for users. For this reason, trustworthy decision-making methods that integrate the mentioned views are highly desirable. This article proposes a multi-criteria decision analysis model based on the integration of users’ preferences and experts’ opinions. It combines the majority’s opinion and criteria synergy to provide a unified perspective in order to support consumers’ ranking-based decisions in social media environments. At the same time, the model supplies useful information for managers about strengths and weaknesses of their product or service according to users’ experience and experts’ judgment. The aggregation processes and synergy criteria are modeled in order to obtain an adequate consensus mechanism. Finally, in order to test the proposed model, several simulations using hotel valuations are performed.Project UTN4058 of National Technological University (Argentine) Fellowship for Short Term Postdoctoral Stays at University of Malaga – International Campus of Excellence Andalucía Tec

Stochastic Multiattribute Acceptability Analysis: an application to the ranking of Italian regions

We consider the issue of ranking regions with respect to a range of economic and social variables. Departing from the current practice of aggregating different dimensions via an arithmetic mean, we instead use Stochastic Multiattribute Acceptability Analysis (SMAA). SMAA takes account of the “whole space” of weights for the considered dimensions. Thus, rather than considering an average person giving equal or fixed weights to all dimensions, SMAA explores how potential differences in individual preferences affect the outcome. In this sense, in contrast to the purported objectivity of the many rankings supplied by economic institutions and mass media, this proposal enhances, simplifies and renders transparent the ranking exercise. The methodology is applied to the ranking of Italian regions, unveiling patterns of similarity and dissimilarity even within the same broad regional economy. Many of these findings are neglected within the extant literature addressing the “Mezzogiorno” problem