Volume 18, Issue 3 (9-2021)
jor 2021, 18(3): 49-71 |
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Ettehadi V, Hosseini-Nasab H, Fakhrzad M B, Khademi Zare H. A New Robust Open Network DEA Model. jor 2021; 18 (3) :49-71
URL: http://jamlu.liau.ac.ir/article-1-2011-en.html
URL: http://jamlu.liau.ac.ir/article-1-2011-en.html
Department of Industrial Engineering, Yazd University, Iran , hhn@yazd.ac.ir
Abstract: (1860 Views)
Efficiency evaluation is an important and key issue in competitive conditions. Organizations and companies face various uncertainties which make their efficiency evaluation extremely difficult and complicated. In this research, open-network data envelopment analysis models have been developed for three uncertain states, including uncertain outputs, uncertain inputs, and uncertain concurrent inputs and outputs. The proposed models are used to evaluate the efficiency of 10 two-stage processes for sellers and buyers in a supply chain, and the effect of data uncertainty is investigated. The results obtained from the developed models have been compared with the results of traditional DEA network models. The validity and accuracy of the developed models have also been examined. The results show that the proposed models are more reliable than the traditional DEA network models. Also, by examining the efficiency of decision-making units in different conditions of data uncertainty and deviations, it was determined that with increasing uncertainty and deviation, the efficiency score of different units decreases, which is consistent with reality.
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