Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/340654 
Year of Publication: 
2025
Citation: 
[Journal:] Borsa İstanbul Review [ISSN:] 2214-8469 [Volume:] 25 [Issue:] 6 [Year:] 2025 [Pages:] 1558-1571
Publisher: 
Elsevier, Amsterdam
Abstract: 
This study examines the structural determinants of Environmental Pillar (EP) performance in the international banking system by integrating advanced machine learning techniques with model interpretability tools. Using a dataset of banks from 24 countries between 2019 and 2023, the analysis identifies key financial, institutional, and risk-related drivers of environmental sustainability and explores their interaction patterns across different regions. The results show that EP performance is not the outcome of isolated or linear dynamics but emerges from a multidimensional balance between ethical governance, social responsibility, financial soundness, and operational efficiency. Environmental sustainability is particularly reinforced when strong governance structures and high levels of social engagement act jointly as institutional anchors. The positive contribution of bank size to EP is conditional on a substantial social orientation, while excessive profitability or risk exposure is associated with lower environmental performance.
Subjects: 
Banking sustainability
Environmental pillar
Machine learning
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article
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