Multi-criteria analysis of the Baltic banks from client attraction and profit generation perspectives
DOI: https://doi.org/10.3846/jbem.2025.24754Abstract
The economic and regulatory environment banks operate in poses challenges in regard to different facets of sustainability and requires proper managerial and technological innovations. Bank performance can be analysed from various viewpoints. Therefore, it is important to develop comprehensive frameworks for assessment of banking performance. The paper develops a twostage approach for measuring banking performance from the client attraction and profit generation perspectives. The multi-criteria framework involving three multi-criteria decision-making methods is developed to ensure robustness of the results. The empirical research deals with the 17 commercial banks operating in the three Baltic States. This case is interesting as it covers a low-interest-rate environment. While Lithuanian banks excelled in the client attraction perspective, the results for 2017–2021 suggest that they should focus on the improvement of performance in this regard and profit generation if compared to banks operating in Latvia and Estonia.
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bank performance, profitability, client attraction, multi-criteria analysis, composite indicator, hybrid approachHow to Cite
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References
Abbas, F., Rubbaniy, G., Ali, S., & Khan, W. (2021). Income and balance sheet diversification effects on banks’ cost and profit efficiency: Evidence from the US. SSRN. https://doi.org/10.2139/ssrn.3808379
Abueid, R., Rehman, S. U., & Nguyen, N. T. (2023). The impact of balanced scorecard in estimating the performance of banks in Palestine. EuroMed Journal of Business, 18(1), 34–45. https://doi.org/10.1108/EMJB-03-2021-0047
Bakashbayev, A., Nurgaliyeva, A., Gumar, N., Khamidullina, Z., & Saduakassova, M. (2020). Examining the trends in bank deposits through internal and external factors based on the supply chain strategies: A primary and secondary data survey. International Journal of Supply Chain Management, 9(2), 526–536.
Balci, E., & Ayvaz, B. (2020). Efficiency and productivity analysis in Turkish banking sector with data envelopment analysis and Malmquist Index. Southeast Europe Journal of Soft Computing, 9(1). https://doi.org/10.21533/scjournal.v9i1.185
Barth, J. R., Nolle, D. E., Phumiwasana, T., & Yago, G. (2003). A cross‐country analysis of the bank supervisory framework and bank performance. Financial Markets, Institutions & Instruments, 12(2), 67–120. https://doi.org/10.1111/1468-0416.t01-2-00001
Baselga-Pascual, L., Orden-Olasagasti, D., & Trujillo-Ponce, A. (2018). Toward a more resilient financial system: Should banks be diversified?. Sustainability, 10(6), Article 1903. https://doi.org/10.3390/su10061903
Beheshtinia, M. A., & Omidi, S. (2017). A hybrid MCDM approach for performance evaluation in the banking industry. Kybernetes, 46(8), 1386–1407. https://doi.org/10.1108/K-03-2017-0105
Belton, V., & Stewart, T. J. (2002). Multiple criteria decision analysis: An integrated approach. Springer. https://doi.org/10.1007/978-1-4615-1495-4
Bhaskaran, R. K., Sujit, K. S., & Mongia, S. (2023). Linkage between performance and sustainability initiatives in banking sector – An empirical examination. International Journal of Productivity and Performance Management, 72(1), 200–225. https://doi.org/10.1108/IJPPM-07-2020-0385
Buallay, A. (2019). Is sustainability reporting (ESG) associated with performance? Evidence from the European banking sector. Management of Environmental Quality: An International Journal, 30(1), 98–115. https://doi.org/10.1108/MEQ-12-2017-0149
Buallay, A., Fadel, S. M., Alajmi, J., & Saudagaran, S. (2021). Sustainability reporting and bank performance after financial crisis. Competitiveness Review, 31(4), 747–770. https://doi.org/10.1108/CR-04-2019-0040
Chakraborty, S., & Zavadskas, E. K. (2014). Applications of WASPAS method in manufacturing decision making. Informatica, 25(1), 1–20. https://doi.org/10.15388/Informatica.2014.01
Claeys, G. (2021). What are the effects of the ECB’s negative interest rate policy (Monetary Dialogue Papers). https://www.europarl.europa.eu/cmsdata/236768/02.%20BRUEGEL_final.pdf
Da Silva Inácio, L., & Delai, I. (2022). Sustainable banking: A systematic review of concepts and measurements. Environment, Development and Sustainability, 24, 1–39. https://doi.org/10.1007/s10668-021-01371-7
Dinçer, H., & Yüksel, S. (2018). Comparative evaluation of BSC-based new service development competencies in Turkish banking sector with the integrated fuzzy hybrid MCDM using content analysis. International Journal of Fuzzy Systems, 20, 2497–2516. https://doi.org/10.1007/s40815-018-0519-y
Drigă, I., & Dura, C. (2014, October 10–11). The financial sector and the role of banks in economic development. In 6th International Multidisciplinary Symposium “Universitaria SIMPRO” (pp. 10–11).
Ecer, F., Gunes, E., & Zavadskas, E. K. (2024). Focusing on identifying the digital transformation performance of banks in the technology age through a multi-criteria methodology. Transformations in Business & Economics, 23(1(61)), 127–153.
Forcadell, F. J., Aracil, E., & Úbeda, F. (2019). The influence of innovation on corporate sustainability in the international banking industry. Sustainability, 11(11), Article 3210. https://doi.org/10.3390/su11113210
Gambetta, N., García-Benau, M. A., & Zorio-Grima, A. (2019). Stress test impact and bank risk profile: Evidence from macro stress testing in Europe. International Review of Economics & Finance, 61, 347–354. https://doi.org/10.1016/j.iref.2018.04.001
Gemar, P., Gemar, G., & Guzman-Parra, V. (2019). Modeling the sustainability of bank profitability using partial least squares. Sustainability, 11(18), Article 4950. https://doi.org/10.3390/su11184950
Gupta, S., Mathew, M., Gupta, S., & Dawar, V. K. (2020). Benchmarking the private sector banks in India using MCDM approach. Journal of Public Affairs, 21(2), Article e2409. https://doi.org/10.1002/pa.2409
Gutiérrez-López, C., & Abad-González, J. (2020). Sustainability in the banking sector: A predictive model for the European banking union in the aftermath of the financial crisis. Sustainability, 12(6), Article 2566. https://doi.org/10.3390/su12062566
Henriques, I. C., Sobreiro, V. A., Kimura, H., & Mariano, E. B. (2020). Two-stage DEA in banks: Terminological controversies and future directions. Expert Systems with Applications, 161, Article 113632. https://doi.org/10.1016/j.eswa.2020.113632
Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Lecture notes in economics and mathematical systems: Vol. 186. Multiple attribute decision making (pp. 58–191). Springer. https://doi.org/10.1007/978-3-642-48318-9_3
Izzeldin, M., Mamatzakis, E., Murphy, A., & Tsionas, M. (2020). A novel MIMIC-style model of European bank technical efficiency and productivity growth (Working Paper No. 2012). https://doi.org/10.24149/wp2012
Karkowska, R. (2020). Business model as a concept of sustainability in the banking sector. Sustainability, 12(1), Article 111. https://doi.org/10.3390/su12010111
Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435–451. https://doi.org/10.15388/Informatica.2015.57
Khan, M. A., Siddique, A., & Sarwar, Z. (2020). Determinants of non-performing loans in the banking sector in developing state. Asian Journal of Accounting Research, 5(1), 135–145. https://doi.org/10.1108/AJAR-10-2019-0080
Kolari, J. W., López-Iturriaga, F. J., & Pastor Sanz, I. (2019). Predicting European bank stress tests: Survival of the fittest. Global Finance Journal, 39, 44–57. https://doi.org/10.1016/j.gfj.2018.01.015
Korzeb, Z., & Samaniego-Medina, R. (2019). Sustainability performance. A comparative analysis in the Polish banking sector. Sustainability, 11(3), Article 653. https://doi.org/10.3390/su11030653
Mansour, R., & El Moussawi, C. (2020). Efficiency, technical progress and productivity of Arab banks: A non-parametric approach. The Quarterly Review of Economics and Finance, 75, 191–208. https://doi.org/10.1016/j.qref.2019.02.002
Manta, F., Tarulli, A., Morrone, D., & Toma, P. (2020). Toward a quadruple bottom line: Social disclosure and financial performance in the banking sector. Sustainability, 12(10), Article 4038. https://doi.org/10.3390/su12104038
Mateev, M., Sahyouni, A., Moudud-Ul-Huq, S., & Nair, K. (2024). Bank performance and financial stability during the COVID-19 pandemic: Lessons from the MENA region. EuroMed Journal of Business. https://doi.org/10.1108/EMJB-07-2023-0182
Niţescu, D. C., & Cristea, M. A. (2020). Environmental, social and governance risks – New challenges for the banking business sustainability. Amfiteatru Economic, 22(55), 692–706. https://doi.org/10.24818/EA/2020/55/692
Özçalıcı, M., Kaya, A., & Gürler, H. E. (2022). Long-term performance evaluation of deposit banks with multi-criteria decision making tools: The case of Turkey. Pamukkale University Journal of Social Sciences Institute, (50), 87–114. https://doi.org/10.30794/pausbed.975901
Paule-Vianez, J., Gutiérrez-Fernández, M., & Coca-Pérez, J. L. (2019). Prediction of financial distress in the Spanish banking system. Applied Economic Analysis. https://doi.org/10.1108/AEA-10-2019-0039
Platonova, E., Asutay, M., Dixon, R., & Mohammad, S. (2018). The impact of corporate social responsibility disclosure on financial performance: Evidence from the GCC Islamic banking sector. Journal of Business Ethics, 151, 451–471. https://doi.org/10.1007/s10551-016-3229-0
Raut, R., Cheikhrouhou, N., & 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
Roy, P., & Shaw, K. (2023). A fuzzy MCDM decision-making model for m-banking evaluations: Comparing several m-banking applications. Journal of Ambient Intelligence and Humanized Computing, 14(9), 11873–11895. https://doi.org/10.1007/s12652-022-03743-x
Saadaoui, A., & Ben Salah, O. (2023). The moderating effect of financial stability on the CSR and bank performance. EuroMed Journal of Business, 18(4), 621–642. https://doi.org/10.1108/EMJB-10-2021-0163
Sama, H. R., Kosuri, S. V. K., & Kalvakolanu, S. (2022). Evaluating and ranking the Indian private sector banks – A multi‐criteria decision‐making approach. Journal of Public Affairs, 22(2), Article e2419. https://doi.org/10.1002/pa.2419
San-Jose, L., Retolaza, J. L., & Lamarque, E. (2018). The social efficiency for sustainability: European cooperative banking analysis. Sustainability, 10(9), Article 3271. https://doi.org/10.3390/su10093271
Scholtens, B., & van’t Klooster, S. (2019). Sustainability and bank risk. Palgrave Communications, 5(1), Article 105. https://doi.org/10.1057/s41599-019-0315-9
Sharif, O., Hasan, M. Z., Kurniasari, F., Hermawan, A., & Gunardi, A. (2019). Efficiency analysis using DEA: Evidence from financial companies listed in Bursa Malaysia. Management Science Letters, 9(2), 301–312. https://doi.org/10.5267/j.msl.2018.11.010
Shaverdi, M., Akbari, M., & Fallah Tafti, S. (2011). Combining fuzzy MCDM with BSC approach in performance evaluation of Iranian private banking sector. Advances in Fuzzy Systems, 2011, Article 148712. https://doi.org/10.1155/2011/148712
Shen, C.-H., Wu, M.-W., Chen, T.-H., & Fang, H. (2016). To engage or not to engage in corporate social responsibility: Empirical evidence from global banking sector. Economic Modelling, 55, 207–225. https://doi.org/10.1016/j.econmod.2016.02.007
Stauropoulou, A., & Sardianou, E. (2019). Understanding and measuring sustainability performance in the banking sector. IOP Conference Series: Earth and Environmental Science, 362, Article 012128. https://doi.org/10.1088/1755-1315/362/1/012128
Stoica, O., Oprea, O. R., Bostan, I., Sandu Toderașcu, C., & Lazăr, C. M. (2020). European banking integration and sustainable economic growth. Sustainability, 12(3), Article 1164. https://doi.org/10.3390/su12031164
Streimikis, J. (2025). Comparative assessment of circular economy performance in the Baltic States using MCDM methods. Transformations and Sustainability, 1(1), 30–42. https://doi.org/10.63775/pcxj8p61
Tan, Y., & Tsionas, M. G. (2020). Modelling sustainability efficiency in banking. International Journal of Finance & Economics, 27(3), 3754–3772. https://doi.org/10.1002/ijfe.2349
Tunowski, R. (2020). Sustainability of commercial banks supported by business intelligence system. Sustainability, 12(11), Article 4754. https://doi.org/10.3390/su12114754
Ünlü, U., Yalçın, N., & Avşarlıgil, N. (2022). Analysis of efficiency and productivity of commercial banks in turkey pre-and during COVID-19 with an integrated MCDM approach. Mathematics, 10(13), Article 2300. https://doi.org/10.3390/math10132300
Vafaei, N., Ribeiro, R. A., & Camarinha-Matos, L. M. (2016). Normalization techniques for multi-criteria decision-making: Analytical hierarchy process case study. In L. M. Camarinha-Matos, A. J. Falcão, N. Vafaei, & S. Najdi (Eds.), IFIP advances in information and communication technology: Vol. 470. Technological innovation for cyber-physical systems. DoCEIS 2016 (pp. 261–269). Springer. https://doi.org/10.1007/978-3-319-31165-4_26
Vo, D. H. (2018). Should bankers be concerned with intellectual capital? A study of the Thai banking sector. Journal of Intellectual Capital, 19(5), 897–914. https://doi.org/10.1108/JIC-12-2017-0185
Vunjak, N., Dragosavac, M., Vitomir, J., & Stojanović, P. (2020). Central and South – Eastern Europe banking sectors in the sustainable development function. Economics, 8(1), 51–60. https://doi.org/10.2478/eoik-2020-0009
Wanke, P., Azad, M. A. K., Barros, C. P., & Hadi‐Vencheh, A. (2016a). Predicting performance in ASEAN banks: An integrated fuzzy MCDM–neural network approach. Expert Systems, 33(3), 213–229. https://doi.org/10.1111/exsy.12144
Wanke, P., Azad, M. A. K., Barros, C. P., & Hassan, M. K. (2016b). Predicting efficiency in Islamic banks: An integrated multicriteria decision making (MCDM) approach. Journal of International Financial Markets, Institutions and Money, 45, 126–141. https://doi.org/10.1016/j.intfin.2016.07.004
Wanke, P., Azad, M. A. K., Antunes, J., Tan, Y., & Pimenta, R. (2023). Endogenous and exogenous performance sources in Asian Banking: A hybrid stochastic multi-criteria decision-making approach based on sign decomposition and transfer entropy. Expert Systems with Applications, 225, Article 120180. https://doi.org/10.1016/j.eswa.2023.120180
Wu, H., Tzeng, G., & Chen, Y. (2009). A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard. Expert Systems with Applications, 36(6), 10135–10147. https://doi.org/10.1016/j.eswa.2009.01.005
Yılmaz, G., & Nuri İne, M. (2018). Assessment of sustainability performances of banks by TOPSIS method and balanced scorecard approach. International Journal of Business and Applied Social Science, 4(1), 62–75.
Zhao, Q., Tsai, P. H., & Wang, J. L. (2019). Improving financial service innovation strategies for enhancing China’s banking industry competitive advantage during the fintech revolution: A Hybrid MCDM model. Sustainability, 11(5), Article 1419. https://doi.org/10.3390/su11051419
Zhu, K., & Guo, L. (2024). Financial technology, inclusive finance and bank performance. Finance Research Letters, 60, Article 104872. https://doi.org/10.1016/j.frl.2023.104872
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