(2011) used DEA to develop an intellectual benchmarking knowledge-based system for benchmarking, performance evaluation and process improvement. On the other hand, Sun and Li (2008) and Wu and Hsu (2019) used decision tree techniques to introduce a multiple criteria decision-making method to determine suitable warning mechanisms of corporate financial failure or distress. (2011) used the artificial neural networks (ANNs). (2007) used decision trees, whereas Azadeh et al. (2017) used boosted generalized linear model, and Seol et al. Other researchers used different regression models to explain bank performance Anouze (2010) Emrouznejad and Anouze (2010) and Bou-Hamad et al. (2011) used Tobit regression in particular to explain bank performance. Casu and Molyneux (2003) Ariff and Can (2008) and San et al. Therefore, several studies, like that of Fethi and Pasiouras (2010), proposed a combination of measuring and explaining bank performance using DEA or SFA in the first stage to measure performance and regression models as a second stage to explain it. Although using these methods could help researchers determine performance level, they are not sufficient to explain inefficiency or predict performance. The most popular parametric method is known as the stochastic frontier approach (SFA), whereas the most popular nonparametric method is data envelopment analysis (DEA). There is substantial body of published academic research that discusses different methods of evaluating bank performance Berger and Humphrey (1997) grouped them into two main approaches, namely, parametric and nonparametric. Furthermore, it allows one to learn how to make better financial decisions that allocate financial resources in a more efficient manner. Additionally, studying bank performance greatly facilitates measuring the success of decisions made by a bank as compared to those of its counterpart during the same period. Sustainability is one of the concepts which has been associated with bank performance therefore, assessing and predicting bank performance have become vital for managers when examining the suitability of their managerial decisions. The full terms of this licence may be seen at Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors.

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