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Open AccessArticle

Big Data Usage in European Countries: Cluster Analysis Approach

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Faculty of Economics and Business, University of Zagreb, 10000 Zagreb, Croatia
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Faculty of Organisation Studies, 8000 Novo Mesto, Slovenia
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Faculty of Management, University of Primorska, 6000 Koper, Slovenia
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Faculty of Organizational Sciences, University of Maribor, 4000 Kranj, Slovenia
*
Author to whom correspondence should be addressed.
Received: 3 February 2020 / Revised: 5 March 2020 / Accepted: 10 March 2020 / Published: 12 March 2020
(This article belongs to the Special Issue Challenges in Business Intelligence)
The goal of this research was to investigate the level of digital divide among selected European countries according to the big data usage among their enterprises. For that purpose, we apply the K-means clustering methodology on the Eurostat data about the big data usage in European enterprises. The results indicate that there is a significant difference between selected European countries according to the overall usage of big data in their enterprises. Moreover, the enterprises that use internal experts also used diverse big data sources. Since the usage of diverse big data sources allows enterprises to gather more relevant information about their customers and competitors, this indicates that enterprises with stronger internal big data expertise also have a better chance of building strong competitiveness based on big data utilization. Finally, the substantial differences among the industries were found according to the level of big data usage. View Full-Text
Keywords: big data; cluster analysis; digital divide; k-means; enterprise; industry; Europe; quality big data; cluster analysis; digital divide; k-means; enterprise; industry; Europe; quality
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Pejić Bach, M.; Bertoncel, T.; Meško, M.; Suša Vugec, D.; Ivančić, L. Big Data Usage in European Countries: Cluster Analysis Approach. Data 2020, 5, 25.

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