Big Data Usage in European Countries: Cluster Analysis Approach

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.

[1]  Jin Wang,et al.  Statistical process monitoring as a big data analytics tool for smart manufacturing , 2017, Journal of Process Control.

[2]  Union européenne,et al.  Handbook on Constructing Composite Indicators: Methodology and User Guide , 2008 .

[3]  Thomas J. Smith,et al.  Big Data Techniques in Auditing Research and Practice: Current Trends and Future Opportunities , 2017, Journal of Accounting Literature.

[4]  Adrian Gardiner,et al.  Skill Requirements in Big Data: A Content Analysis of Job Advertisements , 2018, J. Comput. Inf. Syst..

[5]  Alessandra Caggiano,et al.  Cloud-based manufacturing process monitoring for smart diagnosis services , 2018, Int. J. Comput. Integr. Manuf..

[6]  Tiago Oliveira,et al.  Assessing Industry 4.0 readiness in manufacturing: Evidence for the European Union , 2019, Comput. Ind..

[7]  T. Edgar,et al.  Smart Manufacturing. , 2015, Annual review of chemical and biomolecular engineering.

[8]  Tiago Oliveira,et al.  The Global Digital Divide: Evidence and Drivers , 2018, J. Glob. Inf. Manag..

[9]  Fernando Bação,et al.  The education-related digital divide: An analysis for the EU-28 , 2016, Comput. Hum. Behav..

[10]  Tiago Oliveira,et al.  Assessing the pattern between economic and digital development of countries , 2016, Information Systems Frontiers.

[11]  James F. Davis,et al.  A smart manufacturing methodology for real time chemical process diagnosis using causal link assessment , 2016 .

[12]  Ana Jesús López Menéndez,et al.  A multivariate framework for the analysis of the digital divide: Evidence for the European Union-15 , 2006, Inf. Manag..

[13]  Sunil Tiwari,et al.  Big data analytics in supply chain management between 2010 and 2016: Insights to industries , 2018, Comput. Ind. Eng..

[14]  Geert Gins,et al.  Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis , 2017 .

[15]  M. P. Bach,et al.  Review of corporate digital divide research: A decadal analysis (2003-2012) , 2022, International Journal of Information Systems and Project Management.

[16]  Ksenija Dumicic,et al.  Exploratory study of insurance companies in selected post-transition countries: non-hierarchical cluster analysis , 2018, Central Eur. J. Oper. Res..

[17]  R. Rohrbeck Harnessing a Network of Experts for Competitive Advantage: Technology Scouting in the ICT Industry , 2010 .

[18]  Ying Wang,et al.  Policy to cope with deadlocks and livelocks for flexible manufacturing systems using the max′-controlled new smart siphons , 2014 .

[19]  Lior Rokach,et al.  Data Mining And Knowledge Discovery Handbook , 2005 .

[20]  Nikola Vlahovic,et al.  Self-organizing maps for fraud profiling in leasing , 2018, 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[21]  K. Witkowski Internet of Things, Big Data, Industry 4.0 – Innovative Solutions in Logistics and Supply Chains Management ☆ , 2017 .

[22]  Yonggang Wen,et al.  Toward Scalable Systems for Big Data Analytics: A Technology Tutorial , 2014, IEEE Access.

[23]  Deborah Carr,et al.  The Global Digital Divide , 2007 .

[24]  GandomiAmir,et al.  Beyond the hype , 2015 .

[25]  Wanchun Zhu Analysis of the Application of Big Data in Intelligent Tourism Mode , 2016 .

[26]  Lior Rokach,et al.  Clustering Methods , 2005, The Data Mining and Knowledge Discovery Handbook.

[27]  T. Soni Madhulatha,et al.  An Overview on Clustering Methods , 2012, ArXiv.

[28]  I-Hsien Ting Developing Analytic Talent: Becoming a Data Scientist , 2015, Online Inf. Rev..

[29]  Erik Brynjolfsson,et al.  What it can — and cannot — do for your organization , 2017 .

[30]  J. Amankwah‐Amoah,et al.  A multidisciplinary perspective of big data in management research , 2017 .

[31]  Li Da Xu,et al.  Industry 4.0: state of the art and future trends , 2018, Int. J. Prod. Res..

[32]  Marko Sarstedt,et al.  A Concise Guide to Market Research: The Process, Data, and Methods Using IBM SPSS Statistics , 2011 .

[33]  The digital divide within the European Union , 2005 .

[34]  Erik Brynjolfsson,et al.  Big data: the management revolution. , 2012, Harvard business review.

[35]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[36]  B D Satoto,et al.  Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster , 2018, IOP Conference Series: Materials Science and Engineering.

[37]  James Moyne,et al.  Big Data Analytics for Smart Manufacturing: Case Studies in Semiconductor Manufacturing , 2017 .

[38]  Shu-Chun Ho,et al.  The impact of ICT development on the global digital divide , 2012, Electron. Commer. Res. Appl..

[39]  Seref Sagiroglu,et al.  Big data: A review , 2013, 2013 International Conference on Collaboration Technologies and Systems (CTS).

[40]  S. Dolnicar A Review of Unquestioned Standards in Using Cluster Analysis for Data-Driven Market Segmentation , 2002 .

[41]  Jacky Akoka,et al.  Research on Big Data - A systematic mapping study , 2017, Comput. Stand. Interfaces.

[42]  Spyros Makridakis,et al.  The Forthcoming Artificial Intelligence (AI) Revolution: Its Impact on Society and Firms , 2017 .

[43]  Cody Agnellutti Big data : an exploration of opportunities, values, and privacy issues , 2014 .

[44]  M. Nishijima,et al.  Evolution and determinants of digital divide in Brazil (2005–2013) , 2017 .

[45]  Trupti M. Kodinariya,et al.  Review on determining number of Cluster in K-Means Clustering , 2013 .

[46]  OliveiraTiago,et al.  The education-related digital divide , 2016 .

[47]  Murtaza Haider,et al.  Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..

[48]  Stefano Tarantola,et al.  Handbook on Constructing Composite Indicators: Methodology and User Guide , 2005 .