An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA
It is well known that data envelopment analysis (DEA) models are sensitive to selection of input and output variables. As the number of variables increases, the ability to discriminate between the decision making units (DMUs) decreases. Thus, to preserve the discriminatory power of a DEA model, the...
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Wiley
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/658635 |
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| author | Farhad Hosseinzadeh-Lotfi Gholam-Reza Jahanshahloo Mansour Mohammadpour |
| author_facet | Farhad Hosseinzadeh-Lotfi Gholam-Reza Jahanshahloo Mansour Mohammadpour |
| author_sort | Farhad Hosseinzadeh-Lotfi |
| collection | DOAJ |
| description | It is well known that data envelopment analysis (DEA) models are sensitive to selection of input and output variables. As the number of variables increases, the ability to discriminate between the decision making units (DMUs) decreases. Thus, to preserve the discriminatory power of a DEA model, the number of inputs and outputs should be kept at a reasonable level. There are many cases in which an interval scale output in the sample is derived from the subtraction of nonnegative linear combination of ratio scale outputs and nonnegative linear combination of ratio scale inputs. There are also cases in which an interval scale input is derived from the subtraction of nonnegative linear combination of ratio scale inputs and nonnegative linear combination of ratio scale outputs. Lee and Choi (2010) called such interval scale output and input a cross redundancy. They proved that the addition or deletion of a cross-redundant output variable does not affect the efficiency estimates yielded by the CCR or BCC models. In this paper, we present an extension of cross redundancy of interval scale outputs and inputs in DEA models. We prove that the addition or deletion of a cross-redundant output and input variable does not affect the efficiency estimates yielded by the CCR or BCC models. |
| format | Article |
| id | doaj-art-df52cc3b9c3640f79267f6b85c02687d |
| 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-df52cc3b9c3640f79267f6b85c02687d2025-02-03T01:11:49ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/658635658635An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEAFarhad Hosseinzadeh-Lotfi0Gholam-Reza Jahanshahloo1Mansour Mohammadpour2Department of Mathematics, Science and Research Branch, Islamic Azad University, Hesarak, Poonak, Tehran, IranFaculty of Mathematical Science and Computer Engineering, University for Teacher Education, 599 Taleghani Avenue, Tehran 15618, IranDepartment of Mathematics, Science and Research Branch, Islamic Azad University, Hesarak, Poonak, Tehran, IranIt is well known that data envelopment analysis (DEA) models are sensitive to selection of input and output variables. As the number of variables increases, the ability to discriminate between the decision making units (DMUs) decreases. Thus, to preserve the discriminatory power of a DEA model, the number of inputs and outputs should be kept at a reasonable level. There are many cases in which an interval scale output in the sample is derived from the subtraction of nonnegative linear combination of ratio scale outputs and nonnegative linear combination of ratio scale inputs. There are also cases in which an interval scale input is derived from the subtraction of nonnegative linear combination of ratio scale inputs and nonnegative linear combination of ratio scale outputs. Lee and Choi (2010) called such interval scale output and input a cross redundancy. They proved that the addition or deletion of a cross-redundant output variable does not affect the efficiency estimates yielded by the CCR or BCC models. In this paper, we present an extension of cross redundancy of interval scale outputs and inputs in DEA models. We prove that the addition or deletion of a cross-redundant output and input variable does not affect the efficiency estimates yielded by the CCR or BCC models.http://dx.doi.org/10.1155/2013/658635 |
| spellingShingle | Farhad Hosseinzadeh-Lotfi Gholam-Reza Jahanshahloo Mansour Mohammadpour An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA Journal of Applied Mathematics |
| title | An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA |
| title_full | An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA |
| title_fullStr | An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA |
| title_full_unstemmed | An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA |
| title_short | An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA |
| title_sort | extension of cross redundancy of interval scale outputs and inputs in dea |
| url | http://dx.doi.org/10.1155/2013/658635 |
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