Multidimensional Sustainability Performance Measurement in the Banking Industry: A Data-Driven Grey Decision-Support Framework

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Özet

Given the critical role that banks play in sustainable development through their financial intermediation and capital allocation functions, assessing their sustainability performance has become an increasingly important research issue. In response, this research introduces a data-driven grey decision-support framework for assessing multidimensional sustainability performance in the banking industry. Sustainability indicators are systematically identified through text-mining-based content analysis of banks' sustainability reports and annual activity reports. The empirical analysis covers nine banks continuously included in the BIST Sustainability Index over the 2020–2024 period. To reflect temporal variability in sustainability disclosures, the assessment is formulated under grey interval numbers. Within this decision-support framework, Grey LODECI is employed to identify criterion importance, while Grey SWI is utilized to rank bank performance in terms of sustainability. This manuscript also offers useful implications for bank managers, regulators, investors, and sustainability rating agencies by supporting more comprehensive sustainability benchmarking and more informed strategic and regulatory decision-making. © 2026 The Author(s). Business Strategy and the Environment published by ERP Environment and John Wiley & Sons Ltd.

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RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/ebyu/10663Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1002/bse.71305Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorIşık, Özcan
dc.contributor.authorShabir, Mohsin
dc.contributor.authorOğuz, Alparslan
dc.contributor.authorAlkan, Okan
dc.date.accessioned2026-10-18T20:25:50.130284975Z
dc.date.available2026-10-18T20:25:50.130284975Z
dc.date.issued2026
dc.description.abstractGiven the critical role that banks play in sustainable development through their financial intermediation and capital allocation functions, assessing their sustainability performance has become an increasingly important research issue. In response, this research introduces a data-driven grey decision-support framework for assessing multidimensional sustainability performance in the banking industry. Sustainability indicators are systematically identified through text-mining-based content analysis of banks' sustainability reports and annual activity reports. The empirical analysis covers nine banks continuously included in the BIST Sustainability Index over the 2020–2024 period. To reflect temporal variability in sustainability disclosures, the assessment is formulated under grey interval numbers. Within this decision-support framework, Grey LODECI is employed to identify criterion importance, while Grey SWI is utilized to rank bank performance in terms of sustainability. This manuscript also offers useful implications for bank managers, regulators, investors, and sustainability rating agencies by supporting more comprehensive sustainability benchmarking and more informed strategic and regulatory decision-making. © 2026 The Author(s). Business Strategy and the Environment published by ERP Environment and John Wiley & Sons Ltd.
dc.identifier.doi10.1002/bse.71305
dc.identifier.eissn1099-0836
dc.identifier.issn0964-4733
dc.identifier.scopus2-s2.0-105044559463
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/10663
dc.identifier.wosWOS:001820153400001
dc.language.isoen
dc.publisherJohn Wiley and Sons Ltd
dc.relation.ispartofBusiness Strategy and the Environment
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectgrey systems theory
dc.subjectMCDM
dc.subjectsustainability performance
dc.subjectsustainable banking
dc.subjectsustainable development
dc.subjecttext mining
dc.titleMultidimensional Sustainability Performance Measurement in the Banking Industry: A Data-Driven Grey Decision-Support Framework
dc.typeArticle
dspace.entity.typePublication
rdl.citation.scopus0
rdl.citation.wos0
rdl.oa.statusgold
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexSocial Science Citation Index (SSCI)