Comprehensive performance evaluation of Iranian banking groups: A group two-stages data envelopment analysis
Mohammad Sajjad Shahbazifar
1
(
Department of Mathematics, Qazvin Branch, Islamic Azad University, Qazvin, Iran
)
Reza Kazemi Matin
2
(
Department of Mathematics, Karaj Branch, Islamic Azad University, Karaj, Iran.
)
Mohsen Khounsiavash
3
(
Department of Mathematics, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
)
Fereshteh Koushki
4
(
Department of Mathematics, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
)
کلید واژه: Banking evaluation, Network data envelopment analysis, Group-Ranking,
چکیده مقاله :
This paper focuses on the application of Group Network efficiency evaluation (GNE) to conduct a comparative analysis of Iranian banking branches. The objective is to evaluate the efficiency of these branches and identify the factors contributing to their performance. The proposed method utilizes two-stages analysis to evaluate the banking branches, taking into account the relative efficiency scores of each unit within its respective group. The evaluation system provides insights into the strengths and weaknesses of individual branches and allows for comparison and benchmarking among the different banks. The results of this study contribute to enhancing the efficiency and performance of the banking sector by identifying areas for improvement and best practices. The findings can be utilized by banking institutions, policymakers, and regulators to make informed decisions and implement strategies for achieving higher levels of efficiency and competitiveness in the banking industry. In an empirical study, we compared 72 banking branches belonging to three different banking groups with each other.
چکیده انگلیسی :
This paper focuses on the application of Group Network efficiency evaluation (GNE) to conduct a comparative analysis of Iranian banking branches. The objective is to evaluate the efficiency of these branches and identify the factors contributing to their performance. The proposed method utilizes two-stages analysis to evaluate the banking branches, taking into account the relative efficiency scores of each unit within its respective group. The evaluation system provides insights into the strengths and weaknesses of individual branches and allows for comparison and benchmarking among the different banks. The results of this study contribute to enhancing the efficiency and performance of the banking sector by identifying areas for improvement and best practices. The findings can be utilized by banking institutions, policymakers, and regulators to make informed decisions and implement strategies for achieving higher levels of efficiency and competitiveness in the banking industry. In an empirical study, we compared 72 banking branches belonging to three different banking groups with each other.
Ang, Sheng, Menghan Chen, and Feng Yang. "Group Cross-Efficiency Evaluation in Data Envelopment Analysis: An Application to Taiwan Hotels." Computers & Industrial Engineering 125 (2018): 190-99.
2. Arora, Rakhi. "Banking Efficiency: A Systematic." International Journal of Management (IJM) 11, no. 6 (2020).
3. Berger, Allen N, and David B Humphrey. "Efficiency of Financial Institutions: International Survey and Directions for Future Research." European journal of operational research 98, no. 2 (1997): 175-212.
4. Charnes, Abraham, William W Cooper, and Edwardo Rhodes. "Measuring the Efficiency of Decision Making Units." European journal of operational research 2, no. 6 (1978): 429-44.
5. Cook, Wade D, and Joe Zhu. "Within-Group Common Weights in Dea: An Analysis of Power Plant Efficiency." European Journal of Operational Research 178, no. 1 (2007): 207-16.
6. Fukuyama, Hirofumi, Mike Tsionas, and Yong Tan. "Dynamic Network Data Envelopment Analysis with a Sequential Structure and Behavioural-Causal Analysis: Application to the Chinese Banking Industry." European Journal of Operational Research 307, no. 3 (2023): 1360-73.
7. Henriques, Iago Cotrim, Vinicius Amorim Sobreiro, Herbert Kimura, and Enzo Barberio Mariano. "Efficiency in the Brazilian Banking System Using Data Envelopment Analysis." Future Business Journal 4, no. 2 (2018): 157-78.
8. Ho, Chien-Ta Bruce, and Desheng Dash Wu. "Online Banking Performance Evaluation Using Data Envelopment Analysis and Principal Component Analysis." Computers & Operations Research 36, no. 6 (2009): 1835-42.
9. Izadikhah, Mohammad. "Improving the Banks Shareholder Long Term Values by Using Data Envelopment Analysis Model." Advances in mathematical finance and applications 3, no. 2 (2018): 27-41.
10. Kaffash, Sepideh, Reza Kazemi Matin, and Mohammad Tajik. "A Directional Semi-Oriented Radial Dea Measure: An Application on Financial Stability and the Efficiency of Banks." Annals of Operations Research 264 (2018): 213-34.
11. Kao, Chiang. "Efficiency Decomposition in Network Data Envelopment Analysis: A Relational Model." European journal of operational research 192, no. 3 (2009): 949-62.
12. Mahmoudabadi, Mohammad Zarei, and Ali Emrouznejad. "Comprehensive Performance Evaluation of Banking Branches: A Three-Stage Slacks-Based Measure (Sbm) Data Envelopment Analysis." International Review of Economics & Finance 64 (2019): 359-76.
13. Phung, Manh-Trung, Cheng-Ping Cheng, Chuanyin Guo, and Chen-Yu Kao. "Mixed Network Dea with Shared Resources: A Case of Measuring Performance for Banking Industry." Operations Research Perspectives 7 (2020): 100173.
14. Řepková, Iveta. "Efficiency of the Czech Banking Sector Employing the Dea Window Analysis Approach." Procedia Economics and Finance 12 (2014): 587-96.
15. Sahin, Guller, Levent Gokdemir, and Dogan Ozturk. "Global Crisis and Its Effect on Turkish Banking Sector: A Study with Data Envelopment Analysis." Procedia economics and finance 38 (2016): 38-48.
16. Shahbazifar, Mohammad Sajjad, Reza Kazemi Matin, Mohsen Khounsiavash, and Fereshteh Koushki. "Group Ranking of Two-Stage Production Units in Network Data Envelopment Analysis." RAIRO-Operations Research 55, no. 3 (2021): 1825-40.
17. Titko, Jelena, and Daiva Jureviciene. "Dea Application at Cross-Country Benchmarking: Latvian Vs Lithuanian Banking Sector." Procedia-Social and Behavioral Sciences 110 (2014): 1124-35.
18. Valami, H Bagherzadeh. "Group Performance Evaluation, an Application of Data Envelopment Analysis." Journal of computational and applied mathematics 230, no. 2 (2009): 485-90.
19. Wang, Ke, Wei Huang, Jie Wu, and Ying-Nan Liu. "Efficiency Measures of the Chinese Commercial Banking System Using an Additive Two-Stage Dea." Omega 44 (2014): 5-20.
20. Yannick, Gahé Zimy Samuel, Zhao Hongzhong, and Belinga Thierry. "Technical Efficiency Assessment Using Data Envelopment Analysis: An Application to the Banking Sector of Cote D’ivoire." Procedia-Social and Behavioral Sciences 235 (2016): 198-207.
21. Zhao, Linlin, Qingyuan Zhu, and Lin Zhang. "Regulation Adaptive Strategy and Bank Efficiency: A Network Slacks-Based Measure with Shared Resources." European Journal of Operational Research 295, no. 1 (2021): 348-62.
22. Zhou, Xiaoyang, Zhongwen Xu, Jian Chai, Liming Yao, Shouyang Wang, and Benjamin Lev. "Efficiency Evaluation for Banking Systems under Uncertainty: A Multi-Period Three-Stage Dea Model." Omega 85 (2019): 68-82.
