Paper Title
DATA ENVELOPMENT ANALYSIS & ITS APPLICATIONS:AN OVERVIEW
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Registration ID: IJNRD_195197
Published ID: IJNRD2305327
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Keywords: Data Envelopment Analysis, Decision Making Units, Constant Return to Scale, Variable Return to Scale, Operational Inefficiencies
Abstract
Data Envelopment Analysis (DEA) is a non-parametric method of measuring the efficiency of a decision–making unit (DMU) such as a firm or a public-sector agency. In contrast to the statistical approach, DEA evaluates DMUs relative to an average DMU. It compares each unit with only the best performing one. In DEA, there are a number of DMUs. These make decisions based on the available set of inputs which produce a set of outputs. Each unit has a varying level of inputs and gives a varying level of outputs. This technique attempts to determine which of the units are most efficient, and to point out specific inefficiencies of the other units thus assisting them to make realistic improvement targets and allocate resources more efficiently and effectively. Farrel [1957] suggested the concept of Frontier Analysis, which forms the basis of DEA. Four basic DEA models can be used to calculate the DEA efficiency score for the decision making units. The optimal objective function values of models, when solved, represent the efficiency score of the DMU. DEA has been used to evaluate efficiency of financial institutions such as banks, manufacturing companies, service organizations, pharmaceutical industries. DEA has also been used to evaluate efficiency of mutual funds, impact of strategies and policies adopted by governments, and for evaluating value of brand names. In the following article we review some of the prominent literatures in the field of DEA. Recent researches in the given field entails the work carried out by Saranga (2009) and Ramanathan (2009). Saranga (2009) carried out the performance analysis of the Indian auto component industry from the perspectives of an original equipment manufacturer and a component supplier. Ramanathan (2009) proposed (DEA) to generate local weights of alternatives from pair-wise comparison judgment matrices used in the analytic hierarchy process (AHP).
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Vipul Sharma & Geetika Sharma (May-2023). DATA ENVELOPMENT ANALYSIS & ITS APPLICATIONS:AN OVERVIEW. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), d188-d200. https://ijnrd.org/papers/IJNRD2305327.pdf
Issue
Volume 8 Issue 5, May-2023
Pages : d188-d200
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Paper Reg. ID: IJNRD_195197
Published Paper Id: IJNRD2305327
Research Area: Management
Author Type: Indian Author
Country: Bhiwani, Haryana, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2305327.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305327
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