Evaluation of the Impact of Uncertainty and Risk on the Operational Efficiency of the Credit Business of Branches in Different Areas of Tehran in the DEA Dynamic Network

Authors

  • Alireza Hamidieh * Department of Industrial Engineering, Payam Noor University, Tehran, Iran. https://orcid.org/0000-0001-7554-4641
  • Ali Ramezani Department of Industrial Engineering, Amir-Kabir University, Tehran, Iran.
  • Bahareh Akhgari Department of Industrial Engineering, Payam Noor University, Tehran, Iran.

https://doi.org/10.48314/apem.v2i3.46

Abstract

There are many uncertainties in the banking system due to economic and political crises. It makes it complicated to check their efficiency. However, banks control part of these crises. In this research, a Data Envelopment Analysis (DEA) network model faced with real conditions is presented. North's operational process has three stages: Cost and assets, deposit, and issuance of facilities. For these three stages, uncertainty and risk for operational efficiency have been investigated. The model presented to evaluate the efficiency of 5 branches of Tehran Bank in a DEA network has been used, and the impact of uncertainty and risk on operational efficiency has been investigated. The validity and accuracy of the model were investigated, and the results show that inefficiency and lack of investment are the causes of reducing operational efficiency to overcome uncertainty and maintain efficiency in the banking industry. Also, by increasing the efficiency of service and investment, it increases the productivity of branches.  

Keywords:

Uncertainty and risk, Data envelopment analysis network, Productivity, Bank credit business operations

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Published

2025-09-15

Issue

Vol. 2 No. 3 (2025): Annals of Process Engineering and Management

Section

Articles

How to Cite

Hamidieh, A. ., Ramezani, A. ., & Akhgari, B. . (2025). Evaluation of the Impact of Uncertainty and Risk on the Operational Efficiency of the Credit Business of Branches in Different Areas of Tehran in the DEA Dynamic Network. Annals of Process Engineering and Management, 2(3), 180-188. https://doi.org/10.48314/apem.v2i3.46

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