Data envelopment analysis with imprecise data
By Dimitris K. Despotis, Y. G. Smirlis. European Journal of Operational Research, 2002
370 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/9347b766bfa5cb9a363b3f47bd2dbe5082f2b6cc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Gholam Reza Jahanshahloo
- Ali Emrouznejad
- Adel Hatami-Marbini
- Per J. Agrell
- Yingming Wang
- Madjid Tavana
- Shiang-Tai Liu
- Chiang Kao
In Management Science and Operations Research
- Gholam Reza Jahanshahloo
- Ali Emrouznejad
- Adel Hatami-Marbini
- Madjid Tavana
- Yingming Wang
- Shiang-Tai Liu
- Jianbo Yang
- Per J. Agrell
Citations in the corpus
- A new two-stage Stackelberg fuzzy data envelopment analysis model (2014, methodology): “In this study, the imprecise single-stage DEA model of Despotis and Smirlis [21], the two-stage DEA model of Kao and Hwang [36], and the two-stage fuzzy DEA model of Kao and Liu [37] are used to develop a comprehensive two-stage fuzzy DEA framework.”
- Predicting bank performance with financial forecasts: A case of Taiwan commercial banks (2004, background): “Recently, Despotis and Smirlis (2002) developed an approach for dealing with imprecise data in DEA.”
- Interval data without sign restrictions in DEA (2014, methodology): “Despotis and Smirlis [24] developed an interval approach for dealing with imprecise data in DEA by transforming a non-linear DEA model to an LP equivalent and they then defined the upper and lower bounds for the efficiency scores of the DMUs.”
- Ranking DMUs by ideal points with interval data in DEA (2011, background): “Despotis and Smirlis [14] also studied the problem of IDEA, but developed an alternative approach for dealing with imprecise data in DEA.”
- Interval efficiency assessment using data envelopment analysis (2005, methodology): “Despotis and Smirlis[5] also studied the problem of IDEA, but developed an alternative approach for dealing with imprecise data in DEA.”
- A new benchmarking approach in Cold Chain (2012, methodology): “In addition, compared with the interval DEA models developed by Despotis and Smirlis [53], their interval DEA models utilize a fixed and united production frontier as a target for measuring the efficiencies of all DMUs.”