| Naslov: | Big data usage in European Countries : cluster analysis approach |
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| Avtorji: | ID Pejić Bach, Mirjana (Avtor)
ID Bertoncel, Tine (Avtor)
ID Meško, Maja (Avtor)
ID Suša-Vugec, Daila (Avtor)
ID Ivančić, Lucija (Avtor) |
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| Datoteke: |  Bach-2020-Big_Data_Usage_in_European_Countries.pdf (3,39 MB)
MD5: 434652B82163523115E638D3CB32AEFC
 https://doi.org/10.3390/data5010025
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| Jezik: | Angleški jezik |
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| Vrsta gradiva: | Znanstveno delo |
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| Tipologija: | 1.01 - Izvirni znanstveni članek |
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| Organizacija: | FOV - Fakulteta za organizacijske vede
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| Opis: | 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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| Ključne besede: | big data, cluster analysis, digital divide, k-means, enterprise, industry, Europe, quality |
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| Status publikacije: | Objavljeno |
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| Verzija publikacije: | Objavljena publikacija |
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| Poslano v recenzijo: | 03.02.2020 |
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| Datum sprejetja članka: | 10.03.2020 |
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| Datum objave: | 12.03.2020 |
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| Založnik: | MDPI |
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| Leto izida: | 2020 |
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| Št. strani: | Str. 1-16 |
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| Številčenje: | Letn. 5, št. 1, št. članka 25 |
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| PID: | 20.500.12556/DKUM-91543  |
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| UDK: | 004 |
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| COBISS.SI-ID: | 1542023364 |
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| DOI: | 10.3390/data5010025 |
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| ISSN pri članku: | 2306-5729 |
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| Datum objave v DKUM: | 14.01.2025 |
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| Število ogledov: | 101 |
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| Število prenosov: | 12 |
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| Metapodatki: |    |
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| Področja: | Ostalo
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