Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/326310 
Year of Publication: 
2024
Citation: 
[Journal:] Cogent Business & Management [ISSN:] 2331-1975 [Volume:] 11 [Issue:] 1 [Article No.:] 2361475 [Year:] 2024 [Pages:] 1-19
Publisher: 
Taylor & Francis, Abingdon
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.
Subjects: 
Bahrain aluminium industry
K-means cluster analysis
gap analysis
assessment of linkages
road map
positioning
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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