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 ...

data envelopment analysis (dea) is a method to measure relative efficiency of a set of decision-making units (dmus) which uses multiple inputs and produces multiple outputs. in the conventional dea, crisp inputs and outputs are fundamentally necessary. but the observed values of inputs and outputs in real-world problems are sometimes imprecise. thus, performance measurement often needs to be do...