Ranking performance indicators related to banking by using hybrid multicriteria methods in an uncertain environment: a case study for Iran under COVID-19 conditions
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Author (Corporation)
Publication date
2022
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01A - Journal article
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Parent work
Systems Science & Control Engineering
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Volume
10
Issue / Number
1
Pages / Duration
166-180
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Taylor & Francis
Place of publication / Event location
London
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Abstract
This research aims to identify performance indicators and use them to prioritize banks in Iran. Today, the banking industry is severely challenged by decreasing revenues, especially during crisis such as the COVID-19 pandemic. Hence, evaluating banks to find their weaknesses is vital and shows how banks with flaws can be benchmarked from best practice banks. For this work, data is collected from Iranian banks and then evaluated based on the Delphi method. Since the importance of the considered factors is quite diverse, they should be ranked. We use Evaluation by an Area-Based Method of Ranking (EAMR) for this research study. As this method requires factor-specific weights, the Stepwise Weight Assessment Ratio Analysis (SWARA) method is used for determining these weights. This paper looks forward to introducing new hybrid MADM methods in an uncertain environment with high reliability in the results. This new model leads to ensure managers that they can make their decisions accurately. The results reveal the performance of Iranian banks and a respective ranking of them including a model for benchmarking. This empirical research study also provides useful guidance to a better understanding of performance measurement in the banking sector in Iran.
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ISBN
ISSN
2164-2583
Language
English
Created during FHNW affiliation
Yes
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Publication status
Published
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Peer review of the complete publication
Open access category
Gold
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Citation
Karbassi Yazdi, A., Spulbar, C., Hanne, T., & Birau, R. (2022). Ranking performance indicators related to banking by using hybrid multicriteria methods in an uncertain environment: a case study for Iran under COVID-19 conditions. Systems Science & Control Engineering, 10(1), 166–180. https://doi.org/10.1080/21642583.2022.2052996