Circular Economy and Sustainability Integration in Emerging Markets: A Machine Learning-Based Content Analysis of Borsa Istanbul Companies
Abstract
Emerging global environmental challenges make the shift toward circular economy (CE) strategies imperative; nevertheless, there has been limited evidence about the relationships between multidimensional sustainability and CE in emerging markets. In the current research, the disclosure mechanisms of CE and sustainability in Turkish manufacturing sectors in the Borsa Istanbul Sustainability Index are explored. By employing a two-stage methodology, we first carry out bibliometrics based on 4,839 published papers to introduce analytical frameworks. Subsequently, through TF-IDF weighting and K-means analysis of corporate sustainability reports in four manufacturing sectors from 2021 to 2023 in Türkiye, we carry out network analysis as part of our methodology. The findings reveal asymmetric three-pillar integration patterns and distinct sectoral differences, where sectors consuming greater resources target waste management and energy utilization, contrariwise to sectors interacting with consumers who target product reuse and lifecycle extension. Additionally, networks mapping sustainability-CE relationships denote close linkages between both environmental and emerging relationships in both economic and governance aspects. The current research significantly contributes to theory by explaining the sustainability-CE interrelationship in emerging markets, validating forthcoming methodologies quantitatively in the analysis process, and providing practical insights for adopting circular transitions in these markets.
Keywords
References
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Details
Primary Language
English
Subjects
Machine Learning (Other)
Journal Section
Research Article
Authors
Hunaıda Avvad
0000-0002-6006-5944
Türkiye
Publication Date
September 15, 2026
Submission Date
February 10, 2026
Acceptance Date
June 3, 2026
Published in Issue
Year 2026 Volume: 9 Number: 2026