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 Croatia, the European Union (EU) countries and the post-transition EU countries. Due to technological progress, the paper among other things,...
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Format: | Article |
Language: | English |
Published: |
Sciendo
2017-12-01
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Series: | Croatian Review of Economic, Business and Social Statistics |
Subjects: | |
Online Access: | https://doi.org/10.1515/crebss-2017-0009 |
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author | Kurnoga Nataša Slišković Ana |
author_facet | Kurnoga Nataša Slišković Ana |
author_sort | Kurnoga Nataša |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-08T07:38:54Z |
format | Article |
id | doaj.art-34f767bd488f4d9e93f2f840783cfbaa |
institution | Directory Open Access Journal |
issn | 2459-5616 |
language | English |
last_indexed | 2024-03-08T07:38:54Z |
publishDate | 2017-12-01 |
publisher | Sciendo |
record_format | Article |
series | Croatian Review of Economic, Business and Social Statistics |
spelling | doaj.art-34f767bd488f4d9e93f2f840783cfbaa2024-02-02T17:51:25ZengSciendoCroatian Review of Economic, Business and Social Statistics2459-56162017-12-0132627210.1515/crebss-2017-0009E-commerce Analysis in selected European Union Countries: Position of CroatiaKurnoga Nataša0Slišković Ana1Faculty of Economic and Business, University of Zagreb, CroatiaAstellas d.o.o.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.https://doi.org/10.1515/crebss-2017-0009cluster analysise-commerceinternet usemultivariate analysisonline purchasepost-transition countriesc38l81 |
spellingShingle | Kurnoga Nataša Slišković Ana E-commerce Analysis in selected European Union Countries: Position of Croatia Croatian Review of Economic, Business and Social Statistics cluster analysis e-commerce internet use multivariate analysis online purchase post-transition countries c38 l81 |
title | E-commerce Analysis in selected European Union Countries: Position of Croatia |
title_full | E-commerce Analysis in selected European Union Countries: Position of Croatia |
title_fullStr | E-commerce Analysis in selected European Union Countries: Position of Croatia |
title_full_unstemmed | E-commerce Analysis in selected European Union Countries: Position of Croatia |
title_short | E-commerce Analysis in selected European Union Countries: Position of Croatia |
title_sort | e commerce analysis in selected european union countries position of croatia |
topic | cluster analysis e-commerce internet use multivariate analysis online purchase post-transition countries c38 l81 |
url | https://doi.org/10.1515/crebss-2017-0009 |
work_keys_str_mv | AT kurnoganatasa ecommerceanalysisinselectedeuropeanunioncountriespositionofcroatia AT sliskovicana ecommerceanalysisinselectedeuropeanunioncountriespositionofcroatia |