Abstract
In banking system the evaluation of productivity and performance is the key factor among the fundamental concepts in management. For identify the potential performance of a bank efficiency is the parameter to evaluate effective banking system. To measure the efficiency of a bank selection of appropriate input-output variables is one of the most vital issues. The suitable identification of input-output variables helps to create and identify model in order to evaluate the efficiency and analysis. The Data Envelopment Analysis (DEA) is a mathematical approach used to measure the efficiency of identified Decision Making Units (DMUs). The DEA is a methodology for evaluating the relative efficiency of peer decision making units of identified input/output variables for the financial year 2018-19. In this study the basic DEA CCR, BCC models used for measure the efficiency of DMUs. In addition to these models for minimize the input excess and output shortfall Slack Based Measure (SBM) efficiency used. The SBM is a scalar measure which directly deals with slacks of input, output variables which help in obtain improved efficiency score compare with previous model. The result from the analysis is
Highlights
The Data Envelopment Analysis is non-parametric linear programming problem used to measure the relative efficiency of Decision Making Units (DMUs) of identified multiple input, output variables[1] of Private Sector Banks (Pvt.SBs).The output performance metrics of DMUs are classified as DEA inputs and outputs (Charnes et al 1978)
The performance of inefficient DMUs always depends on the efficient DMUs, efficient DMUs are only characterized by a unity efficiency score
The Data Envelopment Analysis is the linear mathematical programming which deals with optimizing the optimum solution of Decision Making Units of identified input, output variables
Summary
The Data Envelopment Analysis is non-parametric linear programming problem used to measure the relative efficiency of Decision Making Units (DMUs) of identified multiple input, output variables[1] of Private Sector Banks (Pvt.SBs). In the Data Envelopment Analysis for measure the efficiency of DMUs the basic model is CCR (Charnes, Cooper, Rhode) given in the year 1978 This approach used to measure the efficiency from the ratio of multiple outputs to input of the DMUs for the analysis. The subsequent improvement in calculating efficiency scores by minimizing the slacks of input, output variables given by Kavoru Tone (1997, 2001) is Slack Based Measure (SBM). According to this approach the CCR, BCC approach fails to attain input excess and output shortfall which gives the result as non-zero slack and it is proceeded to follow the evaluation of radial (proportional) efficiency of the DMUθ∗[5]. Selection and Analysis of Input-Output Variables using Data Envelopment Analysis of Decision Making Units – Indian Private Sector Banks (1) In-variant with respect to the units of the data. (2) Monotone decreasing in the slacks of input and output
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