2011•Asia Pacific journal of research in business managementRequires access

Benchmarking through Data Envelopment Analysis: A Quantitative Approach of Relative Performance Evaluation

Sunil Kumar

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Abstract

The present study reviews the various methods of benchmarking for quantitative performance evaluation and describes how the technique of data envelopment analysis (DEA) can be used for benchmarking. DEA gained tremendous popularity as a non-parametric, deterministic and data-oriented benchmarking technique for measuring relative efficiency of the set of organizations using incommensurable multiple inputs and outputs. Using a hypothetical example, the study illustrates the way of computing efficiency scores, construction of the reference sets, and measuring the extent of potential input-saving and output-addition for inefficient organizations..

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The present study reviews the various methods of benchmarking for quantitative performance evaluation and describes how the technique of data envelopment analysis (DEA) can be used for benchmarking. DEA gained tremendous popularity as a non-parametric, deterministic and data-oriented benchmarking technique for measuring relative efficiency of the set of organizations using incommensurable multiple inputs and outputs. Using a hypothetical example, the study illustrates the way of computing efficiency scores, construction of the reference sets, and measuring the extent of potential input-saving and output-addition for inefficient organizations..

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Available abstract

The present study reviews the various methods of benchmarking for quantitative performance evaluation and describes how the technique of data envelopment analysis (DEA) can be used for benchmarking. DEA gained tremendous popularity as a non-parametric, deterministic and data-oriented benchmarking technique for measuring relative efficiency of the set of organizations using incommensurable multiple inputs and outputs. Using a hypothetical example, the study illustrates the way of computing efficiency scores, construction of the reference sets, and measuring the extent of potential input-saving and output-addition for inefficient organizations..

Key concepts: Benchmarking, Data envelopment analysis, Efficiency, Computer science, Set (abstract data type), Popularity, Parametric statistics, Data set

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