The research focus on the analysis of interdependence of economic and ICT development results from the fact that, in recent decades, ICTs have become a dominant factor in generating socio-economic prosperity of countries. ICT expansion is a stimulus for economic growth, and vice versa. In order...

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

The paper examines over seventy episodes of current account adjustment in industrial and major emerging market economies. It argues that these episodes were characterised by strongly divergent economic developments. To reduce this divergence, the paper classifies episodes with similar...

The paper identifies the business models followed by banks in the euro area, utilising a proprietary dataset collected in the context of the supervisory reporting of the Single Supervisory Mechanism. The concept of a 'business model' has been neglected by economic theory and is defined here with...

The main objective of the paper is to evaluate ICT usage in enterprises in 31 European countries. For that purpose, ICT usage in enterprises index (ICTEI) was developed using the TOPSIS approach based on the entropy method. Subsequently, having used the cluster analysis, countries were...

The focus of the paper is on identification of hidden patterns in the opinion of accounting professionals, in order to identify the deficiencies in the legal accounting regulations and to examine their perspective on international and legal accounting regulations. The data collected through the...

The increasing turbulence of the economic environment leads to changes in the business style, and adapting to this new style requires a cluster approach. In this sense, the goal of the research relates to determining the impact of the cluster internal and external interaction on innovative...

We introduce a new dynamic clustering method for multivariate panel data char- acterized by time-variation in cluster locations and shapes, cluster compositions, and, possibly, the number of clusters. To avoid overly frequent cluster switching (flickering), we extend standard cross-sectional...