Increasing discrimination of network structure models by MCDEA at presence of undesirable output
Publish place: 9th National Conference on Data Envelopment Analysis
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
DEA09_058
تاریخ نمایه سازی: 8 آذر 1396
Abstract:
In many real world DMUs have a two – stage network scenarios, which have not only inputs and outputs, but also intermediate measures and undesirable factors that exist in-between the two-stage operations. However, we would argue that existing two-stage DEA models use an unrealistic weighting system. The multiple criteria DEA can be used to improve discriminating power of classical DEA method and overcomes weak discrimination between DMUs. In this paper we use a modified multiple criteria two-stage DEA model which yields more realistic weights for the inputs and outputs and thus has better discrimination power than traditional two-stage DEA models at presence of undesirable outputs.
Keywords:
Multiple criteria DEA , Two-stage DEA. Undesirable factor
Authors
Monir Zoriehhabib
Soofian Branch, Islamic Azad University, Iran
Mahnaz Maghbuli
Hadishahr Branch, Islamic Azad University, Iran
Mehdi Eyni
Payame Noor University, Iran