Open AccessSelection and Analysis of Input-Output Variables using Data Envelopment Analysis of Decision Making Units - Indian Private Sector Banks
Author(s) -
B. Vittal,
Raju Nellutla,
M. Jaipal Reddy
Publication year - 2021
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e2674.0610521
Subject(s) - data envelopment analysis , measure (data warehouse) , computer science , efficiency , selection (genetic algorithm) , productivity , econometrics , identification (biology) , mathematical optimization , economics , mathematics , estimator , data mining , statistics , artificial intelligence , botany , macroeconomics , biology
In banking system the evaluation of productivityand performance is the key factor among the fundamentalconcepts in management. For identify the potential performanceof a bank efficiency is the parameter to evaluate effectivebanking system. To measure the efficiency of a bank selection ofappropriate input-output variables is one of the most vital issues.The suitable identification of input-output variables helps tocreate and identify model in order to evaluate the efficiency andanalysis. The Data Envelopment Analysis (DEA) is amathematical approach used to measure the efficiency ofidentified Decision Making Units (DMUs). The DEA is amethodology for evaluating the relative efficiency of peerdecision making units of identified input/output variables for thefinancial year 2018-19. In this study the basic DEA CCR, BCCmodels used for measure the efficiency of DMUs. In addition tothese models for minimize the input excess and output shortfallSlack Based Measure (SBM) efficiency used. The SBM is ascalar measure which directly deals with slacks of input, outputvariables which help in obtain improved efficiency scorecompare with previous model. The result from the analysis is