The cluster analysis in the aluminium industry with K-means method: an application for Bahrain

Haitham Al Qahtani and Jayendira P. Sankar

Cogent Business & Management, 2024, vol. 11, issue 1, 2361475

Abstract: This study examines the utilization of the K-means clustering method to analyze Bahrain’s aluminum industry. In addition, this study emphasizes the importance of clustering in understanding productivity, quality, and competitiveness within the sector. Data collection involved rigorous cleaning of diverse sources to ensure accuracy. By employing the K-means algorithm, this study successfully identified distinct clusters within the dataset, offering insights into industry dynamics. In addition, it proposes a roadmap for cluster development, providing actionable recommendations for stakeholders to enhance competitiveness and sustainability. Overall, this research advances knowledge of clustering techniques and informs strategic decision-making in Bahrain’s aluminum industry.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23311975.2024.2361475 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:oabmxx:v:11:y:2024:i:1:p:2361475

Ordering information: This journal article can be ordered from
http://cogentoa.tandfonline.com/journal/OABM20

DOI: 10.1080/23311975.2024.2361475

Access Statistics for this article

Cogent Business & Management is currently edited by Len Tiu Wright and Tahir Nisar

More articles in Cogent Business & Management from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().