A Review of Ranking Models in Data Envelopment Analysis
In the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/492421 |
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| author | F. Hosseinzadeh Lotfi G. R. Jahanshahloo M. Khodabakhshi M. Rostamy-Malkhlifeh Z. Moghaddas M. Vaez-Ghasemi |
| author_facet | F. Hosseinzadeh Lotfi G. R. Jahanshahloo M. Khodabakhshi M. Rostamy-Malkhlifeh Z. Moghaddas M. Vaez-Ghasemi |
| author_sort | F. Hosseinzadeh Lotfi |
| collection | DOAJ |
| description | In the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existing methods can be viewed from different aspects, it is possible that somewhat these groups have an overlapping with the others. The first group conducts the evaluation by a cross-efficiency matrix where the units are self- and peer-evaluated. In the second one, the ranking units are based on the optimal weights obtained from multiplier model of DEA technique. In the third group, super-efficiency methods are dealt with which are based on the idea of excluding the unit under evaluation and analyzing the changes of frontier. The fourth group involves methods based on benchmarking, which adopts the idea of being a useful target for the inefficient units. The fourth group uses the multivariate statistical techniques, usually applied after conducting the DEA classification. The fifth research area ranks inefficient units through proportional measures of inefficiency. The sixth approach involves multiple-criteria decision methodologies with the DEA technique. In the last group, some different methods of ranking units are mentioned. |
| format | Article |
| id | doaj-art-4945be8ac25346d3ae19430a5400d2d6 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-4945be8ac25346d3ae19430a5400d2d62025-02-03T06:11:10ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/492421492421A Review of Ranking Models in Data Envelopment AnalysisF. Hosseinzadeh Lotfi0G. R. Jahanshahloo1M. Khodabakhshi2M. Rostamy-Malkhlifeh3Z. Moghaddas4M. Vaez-Ghasemi5Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Mathematics, Faculty of Science, Lorestan University, Khorramabad, IranDepartment of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IranIn the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existing methods can be viewed from different aspects, it is possible that somewhat these groups have an overlapping with the others. The first group conducts the evaluation by a cross-efficiency matrix where the units are self- and peer-evaluated. In the second one, the ranking units are based on the optimal weights obtained from multiplier model of DEA technique. In the third group, super-efficiency methods are dealt with which are based on the idea of excluding the unit under evaluation and analyzing the changes of frontier. The fourth group involves methods based on benchmarking, which adopts the idea of being a useful target for the inefficient units. The fourth group uses the multivariate statistical techniques, usually applied after conducting the DEA classification. The fifth research area ranks inefficient units through proportional measures of inefficiency. The sixth approach involves multiple-criteria decision methodologies with the DEA technique. In the last group, some different methods of ranking units are mentioned.http://dx.doi.org/10.1155/2013/492421 |
| spellingShingle | F. Hosseinzadeh Lotfi G. R. Jahanshahloo M. Khodabakhshi M. Rostamy-Malkhlifeh Z. Moghaddas M. Vaez-Ghasemi A Review of Ranking Models in Data Envelopment Analysis Journal of Applied Mathematics |
| title | A Review of Ranking Models in Data Envelopment Analysis |
| title_full | A Review of Ranking Models in Data Envelopment Analysis |
| title_fullStr | A Review of Ranking Models in Data Envelopment Analysis |
| title_full_unstemmed | A Review of Ranking Models in Data Envelopment Analysis |
| title_short | A Review of Ranking Models in Data Envelopment Analysis |
| title_sort | review of ranking models in data envelopment analysis |
| url | http://dx.doi.org/10.1155/2013/492421 |
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