Credit cards constitute one of the most common forms of consumer loans. The main purpose of this paper is to apply fuzzy data analysis to the credit scoring problem. A neuro-fuzzy classification technique is compared to the logis- tic regression approach and novel machine learning algorithms that are currently being…

There is a great amount of models in the operation research theory. The models describe various problems of production control, reserves control, aggregation planning and production scheduling. The languages of formal problems description in the operation research and the styles of the enterprise economics are differed from each other essentially.…

This paper postulates two poverty indices based on a fuzzyfication of the poverty line approach and shows that they satisfy some of the usual axioms in the poverty line literature. It also shows that the headcount ratio is a particular case of a poverty measure based on fuzzy sets. Finally…

In the paper it is shown how fuzzy set theory can be used for modeling imprecision and subjectiveness of the problems with a finite number of decision alternatives evaluated with respect to multiple criteria or attributes. The imprecision and subjectiveness appear especially when the decision maker has to assess the…

Transaction costs analysis is concerned with ways of aligning appropriate governance modes with the attributes of economic transactions. Nowadays transaction costs are universally accep-ted, despite the difficulty in measuring and quantifying them. Starting from the customary definition of transaction costs, this paper proposes a model for the buyer/seller relationship, focusing…

Relevant Component Analysis has been introduced recently as a way to incorporate a priori information, such as class or preference information, that may exist for a given data set. The method uses this information to define a new Mahalanobis distance metric on the data space. The purpose of the present…