چکیده:
Since the optimal functioning of banks has a significant impact on the economic development of the country, creating the necessary infrastructure to improve the quality and quantity of bank performance in the shadow of healthy competition can play a remarkable role in achieving goals. Therefore, one of the methods that helps bank branches in identifying their competitive position and performance quality is to measure their performance from various dimensions and rank them. The method of this research, in terms of purpose, is applied-developmental and in terms of data, it is descriptive. In the present research, a decision support system based on the PROMETHEE II method has been designed to rank the branches of Tejarat Bank. The output of this system is the rank assigned to each branch in comparison with other branches, which ranks the branches according to a complete list of performance evaluation indicators, including quantitative and qualitative indicators, and ultimately provides useful sensitivity analysis for decision-makers.
خلاصه ماشینی:
Designing a Decision Support System for Ranking Bank Branches (Case Study: Bank Tejarat) Ameneh Khadivar1, Zahra Mohammadi 2 Since the optimal functioning of banks has a significant impact on the economic development of the country, creating the necessary infrastructure to improve the quality and quantity of bank performance in the shadow of healthy competition can play a notable role in achieving goals.
In the present study, a decision support system based on the PROMETHEE II method has been designed to rank the branches of Bank Tejarat.
Performance evaluation, ranking of bank branches, PROMETHEE method, multi-criteria decision-making methods, decision support system 1.
Various methods have been used to rank bank branches in different studies, and some examples of these methods include: statistical method, using financial ratios (Pourkazemi, 1386), principal component analysis (PCA), TAXONOMY method (Iranzadeh & Barghi, 1388), analytical network process model (Jabal Ameli & Rasouli Nejad, 1389), regression method (Islami Bidgoli & Kashani Pour, 1383), data envelopment analysis method and factor analysis method (Sarmi & Malayi, 1382), etc.
All quantitative information collected from the Studies and Planning and Risk Department of Tejarat Bank, along with information obtained from customer satisfaction and branch management quality questionnaires, are considered data and form the input of the decision support system.
Sensitivity Analysis of Criterion C1 Conclusion and Suggestions This research was conducted to design a decision support system for ranking branches of Bank Tejarat.
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