and Jordan. Three types of data envelopment analysis (DEA) models were used; i.e, CCR, BCC, SE. Four inputs were selected (number of bank branches, number of employees, net fixed assets, and customer deposits), and two outputs were selected (net loans and advances and net operating income). Bank sample consists of 81 banks, as follows: 23 Islamic banks, 31 conventional banks, and 27 mixed banks. Data were compiled through the published financial statements and annual reports of the banks for 2017. Results revealed that mixed banks were more efficient than Islamic and conventional banks in all types of DEA models. Islamic banks were more efficient than conventional banks in CCR and BCC models. However, conventional banks were more efficient than Islamic banks in SE model. There were statistically significant differences between efficiency of mixed and conventional banks according to the CCR model. There were statistically significant differences between efficiency of mixed and conventional banks, as well as between efficiency of conventional and Islamic banks, according to the BCC model. However, there were no statistically significant differences between efficiency of the three bank groups according to the SE model. At the level of each bank, results showed how to use the DEA method to improve the efficiency of inefficient banks in each of the three groups of banks by rationalizing the inputs assuming the stability of the outputs, or maximizing the outputs assuming the stability of the inputs.
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