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

Sabbor Hussain (), Jo-Hui Chen () and Talib Hussain ()
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Sabbor Hussain: College of Business, Chung Yuan Christian University, Chung-Li, Taiwand
Jo-Hui Chen: Department of Finance, Chung Yuan Christian University, Chung-Li, Taiwan
Talib Hussain: Department of Media Management, University of Religions and Denominations, Qom 37491-13357, Iran; Department of Management Sciences, Karakoram International University, Diamer Campus, Gilgit-Baltistan, Pakistan

Journal of Central Banking Theory and Practice, 2024, vol. 13, issue 3, 191-218

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.

Keywords: MCDM; AHP; TOPSIS; GRA; Emerging Market; Bank Performance. (search for similar items in EconPapers)
JEL-codes: E50 F16 F18 (search for similar items in EconPapers)
Date: 2024
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