A procedure for ranking efficient units in data envelopment analysis
Management Science
A closer look at the use of data envelopment analysis for technology selection
Computers and Industrial Engineering
A note on simulating weights restrictions in DEA: an improvement of Thanassoulis and Allen's method
Computers and Operations Research
Computers and Operations Research
A new method based on the dispersion of weights in data envelopment analysis
Computers and Industrial Engineering
Ranking efficient decision-making units in data envelopment analysis using fuzzy concept
Computers and Industrial Engineering
Exploring the efficiency and effectiveness in global e-retailing companies
Computers and Operations Research
Computers and Industrial Engineering
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Data envelopment analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer decision making units (DMUs) with multiple input and outputs. Beside of its popularity, DEA has some drawbacks such as unrealistic input-output weights and lack of discrimination among efficient DMUs. In this study, two new models based on a multi-criteria data envelopment analysis (MCDEA) are developed to moderate the homogeneity of weights distribution by using goal programming (GP). These goal programming data envelopment analysis models, GPDEA-CCR and GPDEA-BCC, also improve the discrimination power of DEA.