Scientific Collection «InterConf», (39): with the Proceedings of the 8th International Scientific and Practical Conference «Science and Practice: Implementation to Modern Society» (December 26-28, 2020) at Manchester, Great Britain

Elchin Suleymanov 
Vice Rector For Scientific Affairs. Assoc.Prof. 
Baku Engineering University, Republic of Azerbaijan 
Ulvi Yagubov Makhdut 
PhD Candidate at UNEC, Lecturer Department of Finance 
Baku Engineering University, Republic of Azerbaijan 
 
COMPARATIVE ANALYSIS OF THE AZERBAIJANI BANKING
SECTOR IN 2019 AND 2020
 
 
Abstract: In this paper, first of all, we discussed the Data Envelopment Analysis 
method. The analysis was carried out using the Data Envelopment Analysis method 
for the 2019 and 3
rd
 half of 2020 based on the data of the five largest banks for total 
assets in the Azerbaijan. In this analysis, we used the CCR (Charnes Cooper Rhodes) 
model of the Data Envelopment Analysis method with the DEA Solver application. As 
a result of the analysis, both years 2 banks were efficient 3 banks were found to be 
inefficient. 
Keywords: Efficiency, Efficiency Measurement Methods, Data Envelopment Analysis. 
 
THE METHODOLOGY 
The DEA (Data Envelopment Analysis) technique is a nonparametric, linear 
programming principle that makes it possible to compare the relative efficiency of 
events between organizations. It is a method of analysis that can measure relative 
efficiency and perform efficiency analysis by comparing the institutions and 
organizations that produce similar outputs by using the same inputs as Decision 
Making Units (DMU) in the literature. 
Another similar definition is that DEA is a linear programming-based technique 
aimed at measuring the relative performance of decision units in situations where 
inputs and outputs that are measured with multiple and different scales or have different 

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 SCIENCE AND PRACTICE: IMPLEMENTATION TO MODERN SOCIETY
409 
measurement units make comparison difficult. 
From these definitions, we can define the DEA concept as a linear programming-
based method, which is used to evaluate the relative efficiency of the decision points 
responsible for outputting using similar inputs. The main feature that distinguishes the 
DEA method from other methods for similar purposes is that it can be evaluated in 
cases where there are many inputs and outputs. Because of the analysis, information 
on the efficiency of each decision point, how to increase the efficiency of the 
ineffective decision points on the input/output ratios, and the decision points that can 
be used as a reference are obtained. 
Data envelopment analysis, which measures the relative efficiency of decision-
making units, allows comparative efficiency analysis when there are multiple inputs and 
multiple outputs. It is an advantage to determine the efficiency limit according to the 
performance of the decision-making units in comparing the decision units of the DEA. 
The CCR model developed by Charnes, Cooper, Rhodes, which is capitalized by 
initials of their names, calculates the efficiency limit in the case of constant returns to 
scale (CRS). The CCR relative efficiency model there is the total efficiency. Moreover, 
with the restriction of the upper efficiency limit at 1.0 in DEA, the efficiency scores of 
all decision make unit’s take a value between 1.0 and 0.0. 
In this article, we employ the Data Envelopment Analysis with the CCR model 
which adopts the assumption of a constant return on a scale. The input and output-
oriented approach of the CCR should be determined by examining the existing data 
structures of the decision make unit’s. Since the use of inputs is usually the primary 
factor in the decision-making process, an input-driven approach has been adopted in 
many of the DEA studies in the banking sector. For this reason, input focused CCR 
model will be applied in the thesis.