<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Computer and mobile technology, Internet use and e-commerce have grown enormously in recent years. The main aim of this paper was to analyse the e-commerce of Croatia, the European Union (EU) countries and the post-transition EU countries. Due to technological progress, the paper among other things, analyses the trend of online purchase at the Croatian and the EU level. The analysis revealed the presence of a linear trend. Furthermore, hierarchical and non-hierarchical cluster analyses were used to classify the countries, first at the EU level and then at the level of the post-transition EU countries. Two variables, the Internet use expressed as a percentage of individuals with the last Internet use in the last 12 months and the Internet purchases expressed as a percentage of individuals with the last online purchase in the last 12 months were used to classify those countries. According to Ward’s method with squared Euclidean distances and dendrogram, the countries were classified into three clusters, which were then used as the basis for the k-means method. Finally, the cluster analysis resulted in the following three clusters: most developed, developed and less developed. Croatia was classified in the less developed cluster at the level of the EU countries, while at the level of the post-transition EU countries it was classified in the developed cluster.</p></abstract>

Computer and mobile technology, Internet use and e-commerce have grown enormously in recent years. The main aim of this paper was to analyse the e-commerce of Croatia, the European Union (EU) countries and the post-transition EU countries. Due to technological progress, the paper among other things, analyses the trend of online purchase at the Croatian and the EU level. The analysis revealed the presence of a linear trend. Furthermore, hierarchical and non-hierarchical cluster analyses were used to classify the countries, first at the EU level and then at the level of the post-transition EU countries. Two variables, the Internet use expressed as a percentage of individuals with the last Internet use in the last 12 months and the Internet purchases expressed as a percentage of individuals with the last online purchase in the last 12 months were used to classify those countries. According to Ward’s method with squared Euclidean distances and dendrogram, the countries were classified into three clusters, which were then used as the basis for the k-means method. Finally, the cluster analysis resulted in the following three clusters: most developed, developed and less developed. Croatia was classified in the less developed cluster at the level of the EU countries, while at the level of the post-transition EU countries it was classified in the developed cluster.

E-commerce Analysis in selected European Union Countries: Position of Croatia

Croatian Review of Economic, Business and Social Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"E-commerce Analysis in selected European Union Countries: Position of Croatia"}

Computer and mobile technology, Internet use and e-commerce have grown enormously in recent years. The main aim of this paper was to analyse the e-commerce of...

E-commerce Analysis in selected European Union Countries: Position of Croatia

Published Online: Dec 29, 2017

Page range: 62 - 72

Received: Nov 22, 2017

Accepted: Dec 22, 2017

DOI: https://doi.org/10.1515/crebss-2017-0009

Keywords
cluster analysis, e-commerce, Internet use, multivariate analysis, online purchase, post-transition countries

© 2017 Nataša Kurnoga et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

E-commerce Analysis in selected European Union Countries: Position of Croatia

Published Online: Dec 29, 2017

Page range: 62 - 72

Received: Nov 22, 2017

Accepted: Dec 22, 2017

DOI: https://doi.org/10.1515/crebss-2017-0009

Keywordscluster analysis, e-commerce, Internet use, multivariate analysis, online purchase, post-transition countries

© 2017 Nataša Kurnoga et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
cluster analysis, e-commerce, Internet use, multivariate analysis, online purchase, post-transition countries