The Relationship between Asset Size and Performance in Islamic Banks: An Application with SWARA-AHP-COPRAS Methods in the Covid-19 Era

1 Akçakanat, Ö., Eren, H., Aksoy, E., & Ömürbek, V. (2017). Bankacilik sektöründe ENTROPI ve WASPAS yöntemleri ile performans değerlendirmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(2), 285–300. https://dergipark.org.tr/en/pub/sduiibfd/issue/52993/703045 Search in Google Scholar

2 Akgül, Y. (2019). Çok kriterli karar verme yöntemleriyle Türk bankacilik sisteminin 2010-2018 yillari arasindaki performansinin analizi. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 4(4), 567–582. https://doi.org/10.29106/fesa.655722 Search in Google Scholar

3 Altınay Tarakçıoğlu, A., Doğan, M., & Kevser, M. (2022). Comparing the Financial Performance of Islamic Banks in 10 Countries: New Evidence using Entropy and WASPAS Methods. The Economics and Finance Letters, 9(2), 197–210. https://doi.org/10.18488/29.v9i2.3110 Search in Google Scholar

4 Babacan, A., & Tuncay, M. (2022). Türk Enerji Sektöründe Çalışma Sermayesi ve Finansal Performans Arasindaki Etkileşim: Swara, Ahp Ve Topsis Yöntemleriyle Karşılaştırmalı Bir Araştırma. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(3), 1976–2005. https://doi.org/10.30798/makuiibf.1097378 Search in Google Scholar

5 Beck, T., Demirguc-Kunt, A., & Merrouche, O. (2013). Islamic vs. conventional banking: Business model, efficiency and stability. Journal of Banking & Finance, 37(2), 433–447. https://doi.org/DOI10.1016/j.jbankfin.2012.09.016 Search in Google Scholar

6 Çakalı, K. R., & ÇAKALI, K. R. (2022). Performance evaluation of deposit banks with financial ratios: Combined use of objective and subjective criteria weighting methods (Combined entropy-SWARA …. Alanya Akademik Bakış, 6(2), 2351–2377. https://dergipark.org.tr/en/pub/alanyaakademik/issue/70088/1056754 Search in Google Scholar

7 Čereška, A., Zavadskas, E. K., Cavallaro, F., Podvezko, V., Tetsman, I., & Grinbergienė, I. (2016). Sustainable assessment of aerosol pollution decrease applying multiple attribute decision-making methods. Sustainability, 8(7), 586. Search in Google Scholar

8 Demir, G. (2022). Analysis of the financial performance of the deposit banking sector in the Covid-19 period with LMAW-DNMA methods. In International Journal of Insurance and Finance. scholar.archive.org. https://scholar.archive.org/work/li5gjtmbx5dupe7mneg3frtvda/access/wayback/https://www.ijif.net/public/admin/uploads/sayfalar/178/makale-2.pdf Search in Google Scholar

9 Demirgüç-Kunt, A., Pedraza, A., & Ruiz-Ortega, C. (2021). Banking sector performance during the COVID-19 crisis. Journal of Banking & Finance, 133, 106305. https://doi.org/10.1016/j.jbankfin.2021.106305 Search in Google Scholar

10 Doğan, M. (2013). Katılım ve Geleneksel Bankaların Finansal Performanslarının Karşılaştırılması: Türkiye Örneği. Turkish Association of Accounting & Finance Academicians, 58, 175–188. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=87114359&site=ehost-live Search in Google Scholar

11 Doumpos, M., & Zopounidis, C. (2010). A multicriteria decision support system for bank rating. In Decision support systems. Elsevier. https://www.sciencedirect.com/science/article/pii/S0167923610001089 Search in Google Scholar

12 El Tiby, A. M. (2011). Islamic banking: How to manage risk and improve profitability (Vol. 640). John Wiley & Sons. Search in Google Scholar

13 Elmas, B., & Yetim, A. (2021). Katılım bankalarının finansal performanslarının TOPSIS yöntemi ile uluslararası boyutta değerlendirilmesi. International Journal of Islamic Economics and Finance Studies, 7(3), 230–263. Search in Google Scholar

14 Erdas, M. L., & Ezanoglu, Z. (2022). How do bank-specific factors impact non-performing loans: Evidence from G20 countries. Journal of Central Banking Theory and Practice, 11(2), 97–122. Search in Google Scholar

15 Erdogan, H. H. (2023). Entropy-based Waspas approach for financial performance in the Covid-19 era: Evidence from Islamic countries. Financial Internet Quarterly, 19(3), 48–61. https://doi.org/10.2478/fiqf-2023-0018 Search in Google Scholar

16 Erdoğan, S., Gedikli, A., & Derindağ, M. R. (2020). An Investigation of Iran’s Banking System: Challenges and Remedies*. Bilimname XLI, 1(November 2018), 957–990. Search in Google Scholar

17 Eyceyurt Batır, T. (2019). Türkiye’de Kamu Katılım Bankalarının Bankacılık Sektörü Bazında Değerlendirilmesi: CAMELS Analizi İle 2015-2017 Yıllarına İlişkin Bir İnceleme. Muhasebe ve Finansman Dergisi, 83, 193–212. https://doi.org/10.25095/mufad.579969 Search in Google Scholar

18 Eyceyurt Batır, T. (2023). Covid-19 Pandemi Sürecinde Bankacilik Sektörü Performansinin Çok Kriterli Karar Verme Yöntemleri ile Karşılaştırmalı Analizi:“Critic-Edas Yaklaşımı Kapsaminda Bir İnceleme.” Uluslararası Muhasebe ve Finans Araştırmaları Dergisi, 4(2), 186–203. Search in Google Scholar

19 Eyceyurt Batır, T., & Güngör, B. (2016). Türkiye’de bankaların kârlılık belirleyicilerinin katılım bankaları ve mevduat bankaları bazında karşılaştırılması. Bankacılar Dergisi, 99(99), 74–98. Search in Google Scholar

20 Eyceyurt Batır, T., Volkman, D. A., & Gungor, B. (2017). Determinants of bank efficiency in Turkey: Participation banks versus conventional banks. Borsa Istanbul Review, 17(2), 86–96. https://doi.org/10.1016/j.bir.2017.02.003 Search in Google Scholar

21 Figueira, J., Greco, S., & Ehrgott, M. (2005). Multiple criteria decision analysis: state of the art surveys (J. Figueira, S. Greco, & M. Ehrgott (eds.)). Springer Science & Business Media. Search in Google Scholar

22 Gençtürk, M., Senal, S., & Aksoy, E. (2021). COVID-19 Pandemisinin Katılım Bankaları Üzerine Etkilerinin Bütünleşik CRITIC-MARCOS Yöntemi İle İncelenmesi. Muhasebe ve Finansman Dergisi, 92, 139–160. https://doi.org/10.25095/mufad.937185 Search in Google Scholar

23 Ghosh, R., & Saima, F. N. (2021). Resilience of commercial banks of Bangladesh to the shocks caused by COVID-19 pandemic: an application of MCDM-based approaches. In Asian Journal of Accounting Research. emerald.com. https://doi.org/10.1108/AJAR-10-2020-0102 Search in Google Scholar

24 Gülcemal Tuba, & Doğan Mesut. (2022). Covid 19 Pandemisinin Bankaların Finansal Performansı Üzerindeki Etkisi: Karşılaştırmalı Bir Analiz. Selçuk Üniversitesi Sosyal Bilimler MYO Dergisi, 25(2), 727–735. https://www.tbb.org.tr Search in Google Scholar

25 Hussain, S., Chen, J.-H., & Hussain, T. (2024). Decision-Making Framework for Improving Bank Performance in Emerging Markets: The Analysis of AHP-TOPSIS and AHP-GRA Models. Journal of Central Banking Theory and Practice, 3, 191–218. Search in Google Scholar

26 ICD. (2022). Refinitiv Islamic Finance Development Report 2022. https://icdps.org/uploads/files/ICDRefinitivifdi-report-20221669878247_1582.pdf Search in Google Scholar

27 Iddouch, K., El Badraoui, K., & Ouenniche, J. (2023). Landscape of Research on the Efficiency Profiles of Islamic Banks using DEA: Survey, Classification and Critical Analysis of the Literature. International Journal of Business, 28(3). Search in Google Scholar

28 Ikra, S. S., Rahman, M. A., Wanke, P., & Azad, M. A. K. (2021). Islamic banking efficiency literature (2000–2020): a bibliometric analysis and research front mapping. International Journal of Islamic and Middle Eastern Finance and Management, 14(5), 1043–1060. https://doi.org/10.1108/IMEFM-05-2020-0226 Search in Google Scholar

29 Iqbal, M., & Molyneux, P. (2005). Thirty Years of Islamic Banking: History, Performance, and Prospects. Palgrave Macmillan. Search in Google Scholar

30 Keršulienė, V., & Turskis, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and Economic Development of Economy, 17(4), 645–666. Search in Google Scholar

31 Kettell, B. (2011). Introduction to Islamic banking and finance (Vol. 1). John Wiley & Sons. Search in Google Scholar

32 Mastilo, Z., Štilić, A., Gligović, D., & Puška, A. (2024). Assessing the banking sector of Bosnia and Herzegovina: An analysis of financial indicators through the MEREC and MARCOS methods. Journal of Central Banking Theory and Practice, 13(1), 167–197. Search in Google Scholar

33 Myers, J. H., & Alpert, M. I. (1968). Determinant buying attitudes: meaning and measurement. Journal of Marketing, 32(4_part_1), 13-20. Search in Google Scholar

34 Rehman, A. U., Aslam, E., & Iqbal, A. (2022). Intellectual capital efficiency and bank performance: Evidence from islamic banks. Borsa Istanbul Review, 22(1), 113–121. Search in Google Scholar

35 Saaty, T. L. 1977. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology 15, 234–281. Search in Google Scholar

36 Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26. Search in Google Scholar

37 Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98. Search in Google Scholar

38 Sarı, T. (2020). Banka Performans Ölçümünde Topsis ve Promethee Yöntemlerinin Karşılaştırılması. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 34(1), 103–122. https://doi.org/10.16951/atauniiibd.480238 Search in Google Scholar

39 Teknomo, K. (2006). Analytic hierarchy process (AHP) tutorial. In Revoledu.com (Vol. 6, Issue 4). Search in Google Scholar

40 Thi My Phan, H., Daly, K., & Akhter, S. (2016). Bank efficiency in emerging Asian countries. Research in International Business and Finance, 38, 517–530. https://doi.org/http://dx.doi.org/10.1016/j.ribaf.2016.07.012 Search in Google Scholar

41 Wang, Z.-L., You, J.-X., Liu, H.-C., & Wu, S.-M. (2017). Failure mode and effect analysis using soft set theory and COPRAS method. International Journal of Computational Intelligence Systems, 10(1), 1002–1015. Search in Google Scholar

42 Wanke, P., Azad, M. A. K., Barros, C. P., & Hassan, M. K. (2016). Predicting efficiency in Islamic banks: An integrated multicriteria decision making (MCDM) approach. Journal of International Financial Markets Institutions & Money, 45, 126–141. https://doi.org/10.1016/j.intfin.2016.07.004 Search in Google Scholar

43 Warde, I. (2010). Islamic finance in the global economy. Edinburgh University Press. Search in Google Scholar

44 Wind, Y., & Saaty, T. L. (1980). Marketing applications of the analytic hierarchy process. Management science, 26(7), 641-658. Search in Google Scholar

45 Yalçın, N., & Ünlü, U. (2018). A multi-criteria performance analysis of initial public offering (IPO) firms using critic and vikor methods. Technological and Economic Development of Economy, 24(2), 534–560. https://doi.org/10.3846/20294913.2016.1213201 Search in Google Scholar

46 Yayar, R., & Baykara, H. V. (2012). TOPSIS Yöntemi ile Katilim Bankalarinin Etkinligi ve Verimliligi Üzerine Bir Uygulama/An Implementation upon Efficiency and Productivity of Participation Banks with TOPSIS Method. Business and Economics Research Journal, 3(4), 21. Search in Google Scholar

47 Yılmaz, N. (2023). Performance Analysis of Banking by Using the Multi Criteria Decision Making Method: SECA. In H. Altıntaş, M. Mete, & N. Bolat Bozaslan (Eds.), International Theory, Research And Reviews In Social, Human And Administrative Sciences (pp. 359–375). seruvenyayinevi. com. https://www.seruvenyayinevi.com/Webkontrol/uploads/Fck/socialekim2023.pdf#page=367 Search in Google Scholar

48 Zavadskas, E. K., Kaklauskas, A., & Šarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Vilnius Tech. https://etalpykla.vilniustech.lt/handle/123456789/111916 Search in Google Scholar

49 Zavadskas, E. K., & Turskis, Z. (2011). Multiple criteria decision making (MCDM) methods in economics: An overview. Technological and Economic Development of Economy, 17(2), 397–427. https://doi.org/10.3846/20294913.2011.593291 Search in Google Scholar