| Title: | Big data usage in European Countries : cluster analysis approach |
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| Authors: | ID Pejić Bach, Mirjana (Author)
ID Bertoncel, Tine (Author)
ID Meško, Maja (Author)
ID Suša-Vugec, Daila (Author)
ID Ivančić, Lucija (Author) |
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| Files: |  Bach-2020-Big_Data_Usage_in_European_Countries.pdf (3,39 MB)
MD5: 434652B82163523115E638D3CB32AEFC
 https://doi.org/10.3390/data5010025
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FOV - Faculty of Organizational Sciences in Kranj
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| Abstract: | 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. |
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| Keywords: | big data, cluster analysis, digital divide, k-means, enterprise, industry, Europe, quality |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 03.02.2020 |
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| Article acceptance date: | 10.03.2020 |
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| Publication date: | 12.03.2020 |
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| Publisher: | MDPI |
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| Year of publishing: | 2020 |
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| Number of pages: | Str. 1-16 |
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| Numbering: | Letn. 5, št. 1, št. članka 25 |
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| PID: | 20.500.12556/DKUM-91543  |
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| UDC: | 004 |
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| ISSN on article: | 2306-5729 |
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| COBISS.SI-ID: | 1542023364 |
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| DOI: | 10.3390/data5010025 |
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| Publication date in DKUM: | 14.01.2025 |
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| Views: | 100 |
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| Downloads: | 12 |
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| Metadata: |    |
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| Categories: | Misc.
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