Financial Performance Analysis with the Fuzzy COPRAS and Entropy-COPRAS Approaches


ÜNVAN Y. A. , ERGENÇ C.

Computational Economics, 2021 (Journal Indexed in SCI Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2021
  • Doi Number: 10.1007/s10614-021-10143-4
  • Title of Journal : Computational Economics
  • Keywords: COPRAS, Entropy, Financial performance, Fuzzy COPRAS

Abstract

© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.The evaluation of financial performance and profitability for the banking sector has become more important with the recent economic developments, increasing competitive environment, technological developments, and globalization. Banks are one of the most important factors of the financial structures of the countries. Performance measurement and evaluation both determine the positions of banks in the sector and have strategic importance in process management for the country's economy. Banks can evaluate the situation required to create competitive advantage and interpret their potential to take risks with performance measurement. In this study, a financial performance analysis is examined by determining the criteria and weights that affect the financial performance of banks. Based on relevant criteria, the first seven banks are ranked in total assets according to reports received from The Banks Association of Turkey for 2014–2018 financial year and a performance evaluation is done by using the fuzzy COPRAS and Entropi-COPRAS (complex proportional assessment) methods. The criterion weights are determined by the entropy method and banks are ranked in terms of their financial performance by the COPRAS method. Fuzzy approaches are preferred as risk, uncertainty and competition continue to increase in the banking sector. This research adopts fuzzy COPRAS as a fuzzy multi-criteria decision-making technique to determine the weight of each criterion and the importance of alternatives, apart from the entropy and COPRAS approaches.