Stochastic frontier models along the lines of Aigner et al. are widely used to benchmark firms’ performances in terms efficiency. The typically fully parametric, with functional form specifications for as well both noise and inefficiency processes. Studies such Kumbhakar have attempted relax some restrictions parametric models, but so far all approaches limited a univariate response variable. S...

Data envelopment analysis (DEA) is a non-parametric approach for performance analysis of decision making units (DMUs) which uses a set of inputs to produce a set of outputs without the need to consider internal operations of each unit. In recent years, there have been various studies dealt with two-stage production systems, i.e. systems which consume some inputs in their first stage to produce ...

in this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (dmus) in stochastic data envelopment analysis (dea) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. it is shown that this deterministic model can be converted to a quadratic programming model. so fa...

in this article, non radial method of dynamic dea with the parallel network structure is presented and is used for calculation of relative efficiency measures when inputs and outputs do not change equally. in this model, dmu divisions under evaluation have been put together in parallel. but its dynamic structure is assumed in series. since in real applications there are undesirable inputs and o...

data envelopment analysis (dea) is an approach for evaluating performances of decision making units (dmus). the performances of dmus are affected by the amount of sources that dmus used. usually increases in inputs cause increases in outputs. however, there are situations where increases in one or more inputs generate a reduction in one or more outputs. in such situations there is congestion in...

Performance measurement with undesirable outputs is an important subject in production processes. There are papers in which works can be divided into two groups. First group develops production models which undesirable outputs are considered as inputs and in second one undesirable outputs are modeled as outputs. We provide a comparison between these two groups and we axiomatically show that pro...

Traditional data envelopment analysis (DEA) models evaluate two-stage decision making unit (DMU) as a black box and neglect the connectivity may exist among the stages. This paper looks inside the system by considering the intermediate activities between the stages where the first stage uses inputs to produce outputs which are the inputs to the second stage along with its own inputs. Additional...