Bankacılık Sektörü Sürdürülebilirlik Performans Değerlendirme Modeli: Homojen Olmayan Veri Seti ile Sezgisel Bulanık Çok Kriterli Yaklaşım

Year 2025, Volume: 10 Issue: Özel Sayı, 30 - 58, 31.10.2025

Burcu Şimşek Yağlı , Nuri Özgür Doğan

https://doi.org/10.30784/epfad.1813034

Abstract

Bu çalışma, bankacılık sektöründe sürdürülebilirlik performansını değerlendirmek için kapsamlı ve çok boyutlu bir çerçeve geliştirmeyi amaçlamaktadır. Çalışmada, sosyal, inovasyon, yönetişim, çevresel, ekonomik ve finansal kriterler olmak üzere altı boyutu birleştiren Bankacılık Sektörü Sürdürülebilirlik Modeli (BSSM) önerilmektedir. Bu boyutların göreli önemini belirlemek için Aralık Değerli Sezgisel Bulanık Best Worst Metodu (IVIF-BWM) kullanmaktadır. Ardından, bankalar heterojen verilere dayalı karşılaştırmaya olanak tanıyan Sezgisel Bulanık Ağırlıklı Korelasyon Katsayısı (IF-WCC) yöntemi kullanılarak sıralanmaktadır. Sonuçlar, uzman grupları arasında önceliklerde farklılıklar olduğunu göstermektedir; bazıları çevresel kaygıları vurgularken diğerleri ekonomik faktörleri önceliklendirmektedir ve bu da çerçevenin farklı paydaş bakış açılarını yakalama yeteneğini göstermektedir. Duyarlılık analizleri, önerilen yaklaşımın istikrarını ve güvenilirliğini doğrulamaktadır. Özetle çalışma, bankacılık sektöründe sürdürülebilirliği değerlendirmek için yeni ve pratik bir araç sağlamaktadır. Çerçevenin karar vericileri, finans kuruluşlarını ve araştırmacıları sürdürülebilir bankacılığa teşvik etmede ve sektörde şeffaflık ve hesap verebilirliği artırmada etkili olacağına inanılmaktadır.

Keywords

Bankacılık Sektörü Sürdürülebilirlik Modeli , Sezgisel Bulanık Kümeler , BWM , WCC , Heterojen Veri

Sustainability Performance Evaluation Model of Banking Sector: An Intuitionistic Fuzzy Multi-Criteria Approach with a Non-Homogeneous Data Set

Abstract

This study aims to develop a comprehensive and multidimensional framework to assess sustainability performance in the banking sector. We propose the Banking Sector Sustainability Model (BSSM), which integrates six dimensions: social, innovation, governance, environmental, economic, and financial criteria. To determine the relative importance of these dimensions, the study employs the Interval-Valued Intuitionistic Fuzzy Best-Worst Method (IVIF-BWM). Then, banks are ranked using the Intuitionistic Fuzzy Weighted Correlation Coefficient (IF-WCC) method, allowing for comparison based on diverse and heterogeneous data. The results reveal that expert groups have different priorities, with some highlighting environmental concerns and others prioritizing economic factors, indicating the framework's potential to capture diverse stakeholder perspectives. Sensitivity analyses confirm the stability and reliability of the proposed approach. Overall, the study proposes novel and practical tool for evaluating sustainability in the banking sector. The framework can support decision-makers, financial institutions, and researchers in promoting sustainable banking and enhancing transparency and accountability in the sector.

Keywords

Banking Sector Sustainability Model , Intuitionistic Fuzzy Sets , BWM , WCC , Heterogeneous Data

References

• Abdel-Basset, M., Ding, W., Mohamed, R. and Metawa, N. (2020). An integrated plithogenic MCDM approach for financial performance evaluation of manufacturing industries. Risk Management, 22(3), 192–218. https://doi.org/10.1057/s41283-020-00061-4
• Ahmed, S.U., Islam, Z.M. and Hasan, I. (2012). Corporate social responsibility and financial performance linkage: Evidence from the banking sector of Bangladesh. Journal of Organizational Management, 1(1), 14–21. Retrieved from http://www.hgpub.com/jorm.html
• Amor, S.B., de Almeida, A.T., de Miranda, J.L. and Aktas, E. (Eds.). (2020). Advanced studies in multi-criteria decision making. USA: CRC Press.
• Aracil, E., Nájera-Sánchez, J.J. and Forcadell, F.J. (2021). Sustainable banking: A literature review and integrative framework. Finance Research Letters, 42, 101932. https://doi.org/10.1016/j.frl.2021.101932
• Aras, G., Tezcan, N. and Furtuna, O.K. (2018). Multidimensional comprehensive corporate sustainability performance evaluation model: Evidence from an emerging market banking sector. Journal of Cleaner Production, 185, 600–609. https://doi.org/10.1016/j.jclepro.2018.01.175
• Aras, G., Tezcan, N., Furtuna, O.K. and Kazak, E.H. (2017). Corporate sustainability measurement based on entropy weight and TOPSIS: A Turkish banking case study. Meditari Accountancy Research, 25(3), 391–413. https://doi.org/10.1108/MEDAR-11-2016-0100
• Ashraf, M., Khan, B. and Tariq, R. (2017). Corporate social responsibility impact on financial performance of banks: Evidence from Asian countries. International Journal of Academic Research in Business and Social Sciences, 7(4), 618–632. Retrieved from http://hrmars.com/hrmars_papers/
• Barbosa, M.W. and de Oliveira, V.M. (2021). The corporate social responsibility professional: A content analysis of job advertisements. Journal of Cleaner Production, 279, 123665. https://doi.org/10.1016/j.jclepro.2020.123665
• Belton, V. and Stewart, T. (2002). Multiple criteria decision analysis: An integrated approach. Berlin: Springer Science and Business Media.
• Bouma, J.J., Jeucken, M. and Klinkers, L. (2017). Sustainable banking: The greening of finance. London: Routledge.
• Büyüközkan, G., Havle, C.A. and Feyzioğlu, O. (2020). A new digital service quality model and its strategic analysis in aviation industry using interval-valued intuitionistic fuzzy AHP. Journal of Air Transport Management, 86, 101817. https://doi.org/10.1016/j.jairtraman.2020.101817
• Carayannis, E.G., Ferreira, J.J., Jalali, S. and Ferreira, F.A. (2018). MCDA in knowledge-based economies: Methodological developments and real-world applications. Technological Forecasting and Social Change, 131, 1–3. https://doi.org/10.1016/j.techfore.2018.01.028
• Cavallaro, F., Zavadskas, E.K. and Streimikiene, D. (2018). Concentrated solar power (CSP) hybridized systems: Ranking based on an intuitionistic fuzzy multi-criteria algorithm. Journal of Cleaner Production, 179, 407–416. https://doi.org/10.1016/j.jclepro.2017.12.269
• Chejarla, K.C., Vaidya, O.S. and Kumar, S. (2022). MCDM applications in logistics performance evaluation: A literature review. Journal of Multi-Criteria Decision Analysis, 29(3–4), 274–297. https://doi.org/10.1002/mcda.1774
• Chowdhury, M.M.H. and Paul, S.K. (2020). Applications of MCDM methods in sustainable supply chain management: A systematic review. Sustainable Production and Consumption, 23, 122–144. https://doi.org/10.1108/MEQ-12-2019-0284
• Çelik, S., Peker, İ., Gök-Kısa, A.C. and Büyüközkan, G. (2022). Multi-criteria evaluation of medical waste management process under intuitionistic fuzzy environment: A case study on hospitals in Turkey. Socio-Economic Planning Sciences, 101499. https://doi.org/10.1016/j.seps.2022.101499
• Çelikbilek, Y. and Tüysüz, F. (2020). An in-depth review of the theory of the TOPSIS method: An experimental analysis. Journal of Management Analytics, 7(2), 281–300. https://doi.org/10.1080/23270012.2020.1748528
• DiMaggio, P.J. and Powell, W.W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147-160. Retrieved from https://www.jstor.org/
• Ecer, F. and Pamucar, D. (2022). A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, 102690. https://doi.org/10.1016/j.omega.2022.102690
• El Amine, M., Pailhes, J. and Perry, N. (2014). Critical review of multi-criteria decision aid methods in conceptual design phases: Application to the development of a solar collector structure. Procedia CIRP, 21, 497–502. https://doi.org/10.1016/j.procir.2014.03.134
• Elkington, J. (1997). The triple bottom line. In M. V. Russo (Eds.), Environmental management: Readings and cases (pp. 49-66). USA: SAGE Publications.
• Esangbedo, M.O., Bai, S., Mirjalili, S. and Wang, Z. (2021). Evaluation of human resource information systems using grey ordinal pairwise comparison MCDM methods. Expert Systems with Applications, 182, 115151. https://doi.org/10.1016/j.eswa.2021.115151
• Freeman, R.E. and McVea, J. (2005) A stakeholder approach to strategic management. In M.A. Hitt, R. E. Freeman and J.S. Harrison (Eds.), The Blackwell handbook of strategic management (pp. 183-201). Oxford: Blackwell Publishers.
• Gangi, F., Mustilli, M. and Varrone, N. (2018). The impact of corporate social responsibility (CSR) knowledge on corporate financial performance: Evidence from the European banking industry. Journal of Knowledge Management, 23(1), 110–134. https://doi.org/10.1108/JKM-04-2018-0267
• Gerstenkorn, T. and Mańko, J. (1991). Correlation of intuitionistic fuzzy sets. Fuzzy Sets and Systems, 44(1), 39–43. https://doi.org/10.1016/0165-0114(91)90031-K
• Hassan, A. and Harahap, S.S. (2010). Exploring corporate social responsibility disclosure: The case of Islamic banks. International Journal of Islamic and Middle Eastern Finance and Management, 3(3), 203–227. https://doi.org/10.1108/17538391011072417
• Islam, M.A., Makripoulias, K. and Tedford, D. (2012). The relationship between corporate social responsibility and financial performance: Evidence from the banking industry. International Journal of Business and Management Tomorrow, 2(5), 1–8. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1999140
• Karagiorgos, T. (2010). Corporate social responsibility and financial performance: An empirical analysis on Greek companies. European Research Studies, 13(4), 85–106. Retrieved from https://www.um.edu.mt/
• Karande, P., Zavadskas, E. and Chakraborty, S. (2016). A study on the ranking performance of some MCDM methods for industrial robot selection problems. International Journal of Industrial Engineering Computations, 7(3), 399–422. https://doi.org/10.5267/j.ijiec.2016.1.001
• Karaşan, A., Kaya, İ. and Erdoğan, M. (2020). Location selection of electric vehicle charging stations by using a fuzzy MCDM method: A case study in Turkey. Neural Computing and Applications, 32(9), 4553–4574. https://doi.org/10.1007/s00521-018-3752-2
• Kaya, İ., Çolak, M. and Terzi, F. (2018). Use of MCDM techniques for energy policy and decision-making problems: A review. International Journal of Energy Research, 42(7), 2344–2372. https://doi.org/10.1002/er.4016
• Khattak, M.A. (2021). Corporate sustainability and financial performance of banks in Muslim economies: The role of institutions. Journal of Public Affairs, 21(1), e2156. https://doi.org/10.1002/pa.2156
• Kiliç, M., Kuzey, C. and Uyar, A. (2015). The impact of ownership and board structure on corporate social responsibility (CSR) reporting in the Turkish banking industry. Corporate Governance, 15(3), 357–374. https://doi.org/10.1108/CG-02-2014-0022
• Korzeb, Z. and Samaniego-Medina, R. (2019). Sustainability performance: A comparative analysis in the Polish banking sector. Sustainability, 11(3), 653. https://doi.org/10.3390/su11030653 Kumar, G., Subramanian, N. and Arputham, R.M. (2018). Missing link between sustainability collaborative strategy and supply chain performance: Role of dynamic capability. International Journal of Production Economics, 203, 96–109. https://doi.org/10.1016/j.ijpe.2018.05.031
• Mi, X., Tang, M., Liao, H., Shen, W. and Lev, B. (2019). The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why. what. what for and what's next? Omega, 87, 205–225. https://doi.org/10.1016/j.omega.2019.01.009
• Michailidou, A.V., Vlachokostas, C. and Moussiopoulos, N. (2016). Interactions between climate change and the tourism sector: Multiple-criteria decision analysis to assess mitigation and adaptation options in tourism areas. Tourism Management, 55, 1–12. https://doi.org/10.1016/j.tourman.2016.01.010
• Mishra, A.R., Mardani, A., Rani, P., Kamyab, H. and Alrasheedi, M. (2021). A new intuitionistic fuzzy combinative distance-based assessment framework to assess low-carbon sustainable suppliers in the maritime sector. Energy, 237, 121500. https://doi.org/10.1016/j.energy.2021.121500
• Mohammadi, S.S., Azar, A., Ghatari, A.R. and Alimohammadlou, M. (2022). A model for selecting green suppliers through interval-valued intuitionistic fuzzy multi-criteria decision making models. Journal of Management Analytics, 9(1), 60–85. https://doi.org/10.1080/23270012.2021.1881926
• Morioka, S.N. and de Carvalho, M.M. (2016). A systematic literature review towards a conceptual framework for integrating sustainability performance into business. Journal of Cleaner Production, 136, 134–146. https://doi.org/10.1016/j.jclepro.2016.01.104
• Nájera-Sánchez, J.J. (2019). A systematic review of sustainable banking through a co-word analysis. Sustainability, 12(1), 278. https://doi.org/10.3390/su12010278
• Nepomuceno, T.C.C., de Carvalho, V.D.H., Poleto, T. and Figueiredo, C.J.J. (2024). A knowledge-based directional multicriteria framework with defuzzified subset of preferences for sustainable banking strategy analysis. International Journal of Bank Marketing, 42(7), 1888–1919. https://doi.org/10.1108/IJBM-12-2023-0653
• Nizam, E., Ng, A., Dewandaru, G., Nagayev, R. and Nkoba, M.A. (2019). The impact of social and environmental sustainability on financial performance: A global analysis of the banking sector. Journal of Multinational Financial Management, 49, 35–53. https://doi.org/10.1016/j.mulfin.2019.01.002
• Ohene-Asare, K. and Asmild, M. (2012). Banking efficiency analysis under corporate social responsibilities. International Journal of Banking. Accounting and Finance, 4(2), 146–171. https://doi.org/10.1504/IJBAAF.2012.048331
• Onar, S.C., Oztaysi, B., Otay, İ. and Kahraman, C. (2015). Multi-expert wind energy technology selection using interval-valued intuitionistic fuzzy sets. Energy, 90, 274–285. https://doi.org/10.1016/j.energy.2015.06.086
• Özçelik, F. and Avcı Öztürk, B. (2014). Evaluation of banks' sustainability performance in Turkey with grey relational analysis. Journal of Accounting and Finance, 63, 189–210. Retrieved from https://dergipark.org.tr/tr/pub/mufad
• Pala, F. (2022). Bankacılık sektöründe kurumsal sosyal sorumluluk ile finansal performans arasındaki ilişki: Türkiye örneği. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 23(1), 49–78. https://doi.org/10.37880/cumuiibf.989475
• Pamuc̦ar, D., Ecer, F., Cirovic, G. and Arlasheedi, M.A. (2020). Application of improved best worst method (BWM) in real-world problems. Mathematics, 8(8), 1342. https://doi.org/10.3390/math8081342
• Pour, B.S., Nazari, K. and Emami, M. (2014). Corporate social responsibility: A literature review. African Journal of Business Management, 8(7), 228–234. Retrieved from http://www.academicjournals.org/AJBM
• Rabea’Hadi, M. Hasan, M.F., Flayyih, H.H. and Hussein, M.K. (2023). Green banking: A literature review on profitability and sustainability implications. Ishtar Journal of Economics and Business Studies, 4(2), 1–6. https://doi.org/10.55270/ijebs.v4i2.27
• Raut, R., Cheikhrouhou, N. and Kharat, M. (2017). Sustainability in the banking industry: A strategic multi‐criterion analysis. Business Strategy and the Environment, 26(4), 550–568. https://doi.org/10.1002/bse.1946
• Refinitiv. (2022). Environmental. social and governance scores from Refinitiv. Retrieved from https://www.refinitiv.com/content/dam/marketing/en_us/documents/methodology/refinitiv-esg-scores-methodology.pdf
• Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009
• Rezaei, J., Nispeling, T., Sarkis, J. and Tavasszy, L. (2016). A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. Journal of Cleaner Production, 135, 577–588. https://doi.org/10.1016/j.jclepro.2016.06.125
• Shao, M., Han, Z., Sun, J., Xiao, C., Zhang, S. and Zhao, Y. (2020). A review of multi-criteria decision making applications for renewable energy site selection. Renewable Energy, 157, 377–403. https://doi.org/10.1016/j.renene.2020.04.137
• Sharma, D. and Kumar, P. (2024). Prioritizing the attributes of sustainable banking performance. International Journal of Productivity and Performance Management, 73(6), 1797–1825. https://doi.org/10.1108/IJPPM-11-2022-0600
• Stauropoulou, A. and Sardianou, E. (2019). Understanding and measuring sustainability performance in the banking sector. IOP Conference Series: Earth and Environmental Science, 362(1), 012128. doi:10.1088/1755-1315/362/1/012128
• Stefanova, M. (2019). The CSR professional – Undiscovered agent of change. Economic Alternatives, 2, 313–323. Retrieved from https://www.unwe.bg/
• Şimşek Yağlı, B. and Zengin Taşdemir, S. (2023). Bütünleşik BWM ve TOPSIS yöntemleri kullanılarak OPEC üyesi ülkeler için kurumsal gelişmişlik analizi. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(1), 119–135. https://doi.org/10.25287/ohuiibf.1103498
• Simsek Yagli, B., Dogan, N.O. and Yagli, I. (2022). Weighting ESG criteria of banks by using interval valued intuitionistic fuzzy best worst method. In C. Kahraman, A.C. Tolga, S. Cevik Onar, S. Cebi, B. Oztaysi and U. Ucar Sari (Eds.), International conference on intelligent and fuzzy systems (pp. 598–605). Berlin: Springer.
• Teece, D.J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40-49. https://doi.org/10.1016/j.lrp.2017.06.007
• TBB. (2023). Sustainability in banking: Sectoral outlook report. Retrieved from https://www.tbb.org.tr/en/pdf/faaliyetler/116/5314
• UNEP FI. (2024). Principles for responsible banking: Annual report 2023. Retrieved from https://www.unepfi.org/industries/banking/prb-2nd-progress-report/
• Vatankhah, S., Darvishmotevali, M., Rahimi, R., Jamali, S.M. and Ale Ebrahim, N. (2023). Assessing the application of multi-criteria decision making techniques in hospitality and tourism research: A bibliometric study. International Journal of Contemporary Hospitality Management, 35(7), 2590–2623. https://doi.org/10.1108/IJCHM-05-2022-0643
• Wang, J., Ma, Q. and Liu, H.C. (2021). A meta-evaluation model on science and technology project review experts using IVIF-BWM and MULTIMOORA. Expert Systems with Applications, 168, 114236. https://doi.org/10.1016/j.eswa.2020.114236
• Wang, P., Zhu, Z., and Huang, S. (2017). The use of improved TOPSIS method based on experimental design and Chebyshev regression in solving MCDM problems. Journal of Intelligent Manufacturing, 28(1), 229–243. https://doi.org/10.1007/s10845-014-0973-9
• Wang, Z., Reimsbach, D. and Braam, G. (2018). Political embeddedness and the diffusion of corporate social responsibility practices in China: A trade-off between financial and CSR performance? Journal of Cleaner Production, 198, 1185–1197. https://doi.org/10.1016/j.jclepro.2018.07.116
• Weber, O. (2017). Corporate sustainability and financial performance of Chinese banks. Sustainability Accounting. Management and Policy Journal, 8(3), 358–385. https://doi.org/10.1108/SAMPJ-09-2016-0066
• World Economic Forum. (2024). Global risks report 2024. Retrieved from https://www.weforum.org/reports/global-risks-report-2024
• Ye, J. (2010). Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment. European Journal of Operational Research, 205(1), 202–204. https://doi.org/10.1016/j.ejor.2010.01.019
• Zhou, H., Yang, Y., Chen, Y., and Zhu, J. (2018). Data envelopment analysis application in sustainability: The origins. development and future directions. European Journal of Operational Research, 264(1), 1–16. https://doi.org/10.1016/j.ejor.2017.06.023