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Decision-Making Framework for Improving Bank Performance in Emerging Markets: The Analysis of AHP-TOPSIS and AHP-GRA Models Cover

Decision-Making Framework for Improving Bank Performance in Emerging Markets: The Analysis of AHP-TOPSIS and AHP-GRA Models

Open Access
|Sep 2024

Abstract

This study utilizes the Analytic Hierarchy Process (AHP) in combination with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Grey Relational Analysis (GRA) models to thoroughly assess the performance of banks in China, India, Pakistan, and Thailand. The integrated results offer significant insights into the relative rankings of various banks in each country. In China, Bank of China Ltd (BOC) emerges as the top performer, setting a benchmark for others. Similarly, in India, the State Bank of India is consistently identified as the leading bank. The National Bank of Pakistan stands out as the top performer in Pakistan. In Thailand, despite minor deviations in results, Kasikornbank PCL (KBANK) consistently shows strong performance. The alignment of results between AHP-TOPSIS and AHP-GRA underscores the reliability of both models, providing stakeholders and decision-makers with a comprehensive understanding of bank performance. This enables them to identify benchmarks, leverage strengths, and address areas for improvement within each country’s banking sector.

Language: English
Page range: 191 - 218
Submitted on: Nov 10, 2023
Accepted on: Mar 25, 2024
Published on: Sep 19, 2024
Published by: Central Bank of Montenegro
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2024 Sabbor Hussain, Jo-Hui Chen, Talib Hussain, published by Central Bank of Montenegro
This work is licensed under the Creative Commons Attribution 4.0 License.