Data analytics for business dynamism with extension to smart cities
Data analytics for business dynamism with extension to smart cities
- Author(s): E. A.H. Elamir 1 and G. A. Mousa 2
- DOI: 10.1049/icp.2021.0887
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- Author(s): E. A.H. Elamir 1 and G. A. Mousa 2
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View affiliations
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Affiliations:
1:
Department of Management & Marketing , College of Business administarion, University of Bahrain , Kingdom of Bahrain ;
2: Department of Accounting , College of Business administarion, University of Bahrain , Kingdom of Bahrain
Source:
3rd Smart Cities Symposium (SCS 2020),
2021
p.
421 – 426
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Affiliations:
1:
Department of Management & Marketing , College of Business administarion, University of Bahrain , Kingdom of Bahrain ;
- Conference: 3rd Smart Cities Symposium (SCS 2020)
- DOI: 10.1049/icp.2021.0887
- ISBN: 978-1-83953-522-2
- Location: Online Conference
- Conference date: 21-23 September 2020
- Format: PDF
The study uses the “Cluster Analysis” as a tool of big data analysis to cluster thirty-four emerging countries’ business dynamism to help in building smart cities. The future of big data application in smart cities offers many benefits in different areas of life, where computers with large storage capacity provide the opportunity to process a huge amount of data in a short time and low cost. The availability of such data helps decision makers in the fields of business and economy to make rational decisions. Consequently, cluster analysis has been chosen as an example for using data analytic technique in making economic decisions, namely, business dynamic segmentation that can bring economic savings and prosperity to countries where cluster analysis has unique advantages such as, it identifies similar groups among countries in the subject of interest which namely, in this study, is business dynamism. Our study does not seek to examine the relationship between business dynamics and other economic or technological factors. It is clusters 34 emerging countries into 6 similar groups according to dynamic business factors, which have a great effect on the way the decision-makers in these countries rationalize economic decisions and improve prospects for cooperation.
Inspec keywords: pattern clustering; Big Data; business data processing; decision making; microeconomics; town and country planning; data analysis; smart cities
Subjects: Data handling techniques; Public administration