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

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 di...

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Bibliographic Details
Published inCogent business & management Vol. 11; no. 1
Main Authors Haitham Al Qahtani, Jayendira P. Sankar
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 31.12.2024
Subjects
assessment of linkages
Bahrain aluminium industry
gap analysis
K-means cluster analysis
positioning
road map
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Summary: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.
ISSN:2331-1975
DOI:10.1080/23311975.2024.2361475