Arrow Index of Fuzzy Choice Function

The Arrow index of a fuzzy choice function C is a measure of the degree to which C satisfies the Fuzzy Arrow Axiom, a fuzzy version of the classical Arrow Axiom. The main result of this paper shows that A(C) characterizes the degree to which C is full rational. We also obtain a method for computing A(C). The Arrow index allows to rank the fuzzy choice functions with respect to their rationality. Thus, if for solving a decision problem several fuzzy choice functions are proposed, by the Arrow index the most rational one will be chosen.Fuzzy choice function, revealed preference indicator, congruence indicator, similarity

A Possibilistic and Probabilistic Approach to Precautionary Saving

This paper proposes two mixed models to study a consumer's optimal saving in the presence of two types of risk.Comment: Panoeconomicus, 201

Possibilistic risk aversion with many parameters

AbstractThe study of risk aversion of an agent confronted by a risk situations with several parameters is an important topic of risk theory. It is tackled traditionally with probabilistic methods. When these do not offer an appropriate shaping we can use Zadeh's possibility theory. In this paper a possibilistic model of risk aversion with several parameters is proposed. The notion of possibilistic risk premium vector is introduced as a measure of an agent's risk aversion to a situation with several risk parameters. The main result of the paper is an approximate calculation formula of this indicator. The way we can apply this model in risk aversion evaluation in grid computing is sketched out

Public Administration Digitalization and Government Effectiveness in EU Countries

Purpose: This study continues the series of previous research carried out by the authors on the digital transformation in EU countries. It aims to identify and analyse the progress made by EU administrations in terms of digitization and effective governance in the period 2019–2021. Design/methodology/approach: Based on selected variables from Eurostat and the World Bank databases, the article provides insights into the dynamic changes that occurred in the EU in the period under consideration. The research employs Principal Component Analysis (PCA) and K-means clustering as the primary research methods to analyse the variations and correlations among 10 numerical variables selected from Eurostat and World Bank databases.  Findings and Practical Implications: The results obtained through PCA show the impact of digitalization on government effectiveness. A comprehensive analysis of government effectiveness has been conducted using PCA, which reveals that the first two principal components account for 77.05% of the initial variance. A K-means clustering with four clusters reveals that the most significant and noteworthy increase in digitalization and government effectiveness in the EU is achieved by the Nordic countries, which exhibit high levels of digitalization and government efficiency. Originality: In this ranking, clusters 2 and 3 comprise well-developed countries with a positive relation between governmental digitalization and efficiency, while cluster 4 consists of emerging countries where the correlation between digitization and governmental efficiency is low or very low, which is primarily attributed to the limited degree of digitization within government institutions