An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise data
Recently, Park [1] proposed a mathematical Data Envelopment Analysis (DEA) model to estimate the lower bound of efficiency scores in the presence of imprecise data. The current paper shows that its model uses infeasible precise data instead of ordinal data. In addition, in some cases, we may be unab...
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REA Press
2024-12-01
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| Series: | Big Data and Computing Visions |
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| Online Access: | https://www.bidacv.com/article_208946_5a09b3e5403999736091e19addf5c61e.pdf |
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| author | Bohlool Ebrahimi Duško Tešić |
| author_facet | Bohlool Ebrahimi Duško Tešić |
| author_sort | Bohlool Ebrahimi |
| collection | DOAJ |
| description | Recently, Park [1] proposed a mathematical Data Envelopment Analysis (DEA) model to estimate the lower bound of efficiency scores in the presence of imprecise data. The current paper shows that its model uses infeasible precise data instead of ordinal data. In addition, in some cases, we may be unable to calculate the relative efficiencies with his model. To overcome the problems, we propose a simple, practical algorithm to estimate the expected value of efficiencies, which is inspired by considering the DEA axioms to the imprecise data. |
| format | Article |
| id | doaj-art-506e1805992b4a2da052025b0d4060aa |
| institution | Kabale University |
| issn | 2783-4956 2821-014X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | REA Press |
| record_format | Article |
| series | Big Data and Computing Visions |
| spelling | doaj-art-506e1805992b4a2da052025b0d4060aa2025-01-30T12:23:43ZengREA PressBig Data and Computing Visions2783-49562821-014X2024-12-014430731310.22105/bdcv.2024.486910.1216208946An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise dataBohlool Ebrahimi0Duško Tešić1Department of Industrial Engineering, ACECR, Sharif Unit, Tehran, Iran.Military Academy, University of Defence, Belgrade, Serbia.Recently, Park [1] proposed a mathematical Data Envelopment Analysis (DEA) model to estimate the lower bound of efficiency scores in the presence of imprecise data. The current paper shows that its model uses infeasible precise data instead of ordinal data. In addition, in some cases, we may be unable to calculate the relative efficiencies with his model. To overcome the problems, we propose a simple, practical algorithm to estimate the expected value of efficiencies, which is inspired by considering the DEA axioms to the imprecise data.https://www.bidacv.com/article_208946_5a09b3e5403999736091e19addf5c61e.pdfdata envelopment analysisefficiency measureimprecise dataranking |
| spellingShingle | Bohlool Ebrahimi Duško Tešić An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise data Big Data and Computing Visions data envelopment analysis efficiency measure imprecise data ranking |
| title | An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise data |
| title_full | An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise data |
| title_fullStr | An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise data |
| title_full_unstemmed | An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise data |
| title_short | An improvement on the efficiency bounds and efficiency classifications in DEA with imprecise data |
| title_sort | improvement on the efficiency bounds and efficiency classifications in dea with imprecise data |
| topic | data envelopment analysis efficiency measure imprecise data ranking |
| url | https://www.bidacv.com/article_208946_5a09b3e5403999736091e19addf5c61e.pdf |
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