Efficiency Analysis of Turkish Banking Sector by Provinces

Authors

DOI:

https://doi.org/10.63556/tisej.2026.1722

Keywords:

Efficiency analysis,, Banking performance by provinces, Efficiency, data envelopment analysis, cluster analysis

Abstract

The banking sector, as one of the primary drivers of economic development, plays a decisive role in the efficient allocation of resources. However, regional disparities often lead to varying levels of output in banking services. This study measures the efficiency of the Turkish banking sector at the provincial level using Data Envelopment Analysis (DEA). Furthermore, it aims to identify the factors contributing to regional efficiency differentials and their respective degrees of impact. To achieve this, Tobit regression and clustering analysis methods were employed. Factors affecting efficiency were identified both structurally and on a province-specific basis.

Using the Turkish Banks Association database, provincial-level data including the number of personnel, total assets, and deposits were utilized as inputs, while sales and total loans were selected as output variables for the efficiency analysis. Additionally, given the diverse development and commercial activity levels across Turkish provinces, Tobit regression and clustering analyses were conducted to determine the predictors of efficiency scores and to control for structural differences among provinces.

The empirical findings reveal significant performance disparities across provinces in the Turkish banking sector and identify the underlying factors driving these differences. The results indicate that provincial banking efficiency scores are largely independent of scale. Furthermore, the study demonstrates that efficiency levels vary based on a centralized management approach rather than local administrative practices at the provincial level. Factors influencing efficiency were found to differ primarily according to commercial variables. Another key finding suggests that the banking system is managed through a highly centralized framework, and the sector responds rapidly to market fluctuations at the provincial level.

References

Abdulahi, S. M., Yitayaw, M. K., Feyisa, H. L., & Mamo, W. B. (2023). Factor affecting technical efficiency of the banking sector: Evidence from Ethiopia. Cogent Economics & Finance, 11(1), 2186039.

Al‐Faraj, T. N., Alidi, A. S., & Bu‐Bshait, K. A. (1993). Evaluation of Bank Branches by Means of Data EnvelopmentAnalysis. International Journal of Operations & Production Management, 13(9), 45-52.

Athanassopoulos, A. D. (1997). Service quality and operating efficiency synergies for management control in the provision of financial services: Evidence from Greek bank branches. European journal of operational research, 98(2), 300-313.

Atukalp, M. E. (2018). Malmquist Toplam Faktör Verimliliği Endeksi ile Türk Bankacılık Sisteminde Bölgesel Performans Ölçümü. Finans Politik ve Ekonomik Yorumlar, (638), 17-34.

Banker, R.D., A. Charnes and W.W. Cooper (1984), “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis”, Management Science, 30, 1078-1092.

Benbachir, S. (2025). Determinants of banking efficiency in the MENA region: A two-stage DEA-Tobit approach. Banks and Bank Systems, 20(1), 83.

Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European journal of operational research, 98(2), 175-212.

Charnes, A., W.W. Cooper and E. Rhodes (1978), “Measuring the Efficiency of Decision-Making Units”, European Journal of Operational Research, 2, 429-444.

Drake, L., & Howcroft, B. (1994). Relative efficiency in the branch network of a UK bank: an empirical study. Omega, 22(1), 83-90.

Erden, B., & Aslan, Ö. F. (2022). The impact of the COVID-19 pandemic outbreak on the sustainable development of the Turkish banking sector. Frontiers in Environmental Science, 10, 989070.

Giokas, D. I. (1991). Bank branch operating efficiency: A comparative application of DEA and the loglinear model. Omega, 19(6), 549-557.

Isik, I., & Hassan, M. K. (2002). Technical, scale and allocative efficiencies of Turkish banking industry. Journal of Banking & Finance, 26(4), 719-766.

Istaiteyeh, R., Milhem, M. A. M., & Elsayed, A. (2024). Efficiency assessment and determinants of performance: A study of Jordan’s banks using DEA and tobit regression. Economies, 12(2), 37.

Nakip, M. (2003). Pazarlama araştırmaları teknikler ve (SPSS destekli) uygulamalar, Seçkin Yayıncılık, 1. Baskı, Ankara.

Öksüzkaya, M., Atan, M., & Atan, S. (2018). Türkiye Bankacilik Sektöründe İl Bazinda Mevduat ve Kredi Etkinliği. Turkish Journal of Social Research/Turkiye Sosyal Arastirmalar Dergisi, 22(2).

Oral, M., & Yolalan, R. (1990). An empirical study on measuring operating efficiency and profitability of bank branches. European journal of operational research, 46(3), 282-294.

Oral, M., Kettani, O., & Yolalan, R. (1992). An empirical study on analyzing the productivity of bank branches. Iie Transactions, 24(5), 166-176.

Paradi, J. C., Yang, Z., & Zhu, H. (2011). Assessing bank and bank branch performance: modeling considerations and approaches. Handbook on data envelopment analysis, 315-361.

Parkan, C. (1987). Measuring the efficiency of service operations: an application to bank branches. Engineering Costs and Production Economics, 12(1-4), 237-242.

Patra, B., Padhan, P. C., & Padhi, P. (2023). Efficiency of Indian Banks–private versus public sector banks: A two-stage analysis. Cogent Economics & Finance, 11(1), 2163081.

Ramanathan, R. (2003). An introduction to data envelopment analysis: a tool for performance measurement. Sage.

Šalić, R. (2021). The relationship between deposits with banks and banks’ loans depends on the size of the bank (case study of Serbia). Časopis za upravljanje organizacijama, finansije i reviziju, 24(95-96), 51-56.

Sherman, H. D., & Gold, F. (1985). Bank branch operating efficiency: Evaluation with data envelopment analysis. Journal of banking & finance, 9(2), 297-315.

Soteriou, A. C., & Stavrinides, Y. (1997). An internal customer service quality data envelopment analysis model for bank branches. International Journal of Operations & Production Management, 17(8), 780-789.

Soteriou, A. C., & Zenios, S. A. (1999). Using data envelopment analysis for costing bank products. European Journal of Operational Research, 114(2), 234-248.

T.C. Sanayi ve Teknoloji Bakanlığı, Sosyo-Ekonomik Gelişmişlik Sıralaması Araştırmaları (SEGE), https://www.sanayi.gov.tr/bolgesel-kalkinma-faaliyetleri/analitik-calismalar/01161b adresinden alınmıştır.

Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica: journal of the Econometric Society, 24-36.

Türkiye Bankalar Birliği, Banka ve Sektör Bilgileri, https://www.tbb.org.tr/banka-ve-sektor-bilgileri adresinden alınmıştır.

Türkiye İstatistik Kurumu (TÜİK), https://data.tuik.gov.tr/ adresinden alınmıştır.

Vassiloglou, M., & Giokas, D. (1990). A study of the relative efficiency of bank branches: an application of data envelopment analysis. Journal of the operational research society, 41(7), 591-597.

Yılmaz, N. (2023). Financial Performance Analysis of Multi-Branch Banks with Integrated MPSI-MARA Model: The Case of Türkiye. Ekonomi ve Finansal Araştırmalar Dergisi, 5(2), 168-188.

Yılmaz, Z., & Uzgören, E. (2014). Türkiye’de İllerin Temel Bankacılık Faaliyetleri Yönünden Kümeleme Analizi Yöntemiyle Sınıflandırılması. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, 535-554.

Published

20.03.2026

How to Cite

KAYA, T., & ÇINAR, Y. (2026). Efficiency Analysis of Turkish Banking Sector by Provinces. Third Sector Social Economic Review, 61(1), 938–953. https://doi.org/10.63556/tisej.2026.1722

Issue

Section

Research Article

Similar Articles

<< < 5 6 7 8 9 10 11 12 13 14 > >> 

You may also start an advanced similarity search for this article.