Articles in which nonparametric data envelopment analysis (DEA) is applied to estimate the efficiency based on a network structure usually consider desirable intermediary parts that are first stage’s outputs be used as second inputs. In many real-life situations, parameters include and undesirable outputs. This issue has drawn much attention from DEA researchers recent years. The main motivatio...

Two-stage network data envelopment analysis (DEA) is widely used to evaluate efficiency of different organizations with multiple operations processes or hierarchical structures. Although existing two-stage DEA assumes systems resolve the inherent conflicts between two stages, coordination effect stages usually ignored. Recently, relation traditional “black box” has been studied from perspective...

Data envelopment analysis (DEA) is a method used for measuring the efficiency of decision-making units‎. Unlike the standard models‎, ‎which assume decision-making units to be a black box‎, ‎network data envelopment analysis focuses on the internal structure of these units‎. ‎Some researchers have developed a two-stage method where all the inputs are entirely used in the first stage‎, ‎producin...

data envelopment analysis (dea) and balanced scorecard (bsc) are two well-known approaches for measuring performance of decision making units (dmus). bsc is especially applied with quality measures, whereas, when the quantity measures are used to evaluate, dea is more appropriate. in the real-world, dmus usually have complex structures such as network structures. one of the well-known network s...

Data envelopment analysis (DEA) and balanced scorecard (BSC) are two well-known approaches for measuring performance of decision making units (DMUs). BSC is especially applied with quality measures, whereas, when the quantity measures are used to evaluate, DEA is more appropriate. In the real-world, DMUs usually have complex structures such as network structures. One of the well-known network s...