This paper examines inability of CCR and BCC models in improving DMU’s scale efficiency when a production possibility frontier is assumed as variable returns to scale. This paper also finds that DEA result can be more efficient than the Pareto-efficiency when a DMU is feasibly projected to be both technically and scale efficient. This feasible projection can only be achieved by a VRS DEA model ...

A significant theme in data envelopment analysis (DEA) is the stability of returns to scale (RTS) classification of specific decision making unit (DMU) which is under observed production possibility set. In this study the observed DMUs are public postal operators (PPOs) in European Union member states and Serbia as a candidate country. We demonstrated a sensitivity analysis of the inefficient P...

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...

this article will address the extension of super efficiency method to rank the non-extreme efficient decision making units. many methodologies have introduced methods that can rank efficient units, amongst which, the super efficiency method due to its ability to provide meaningful geometrical as well as economic analyses has a significant place. but the common problem with all the super efficie...

Data envelopment analysis (DEA) is widely used as a benchmarking tool for improving productive performance of decision making units (DMUs). The benchmarks produced by DEA are obtained as a sideproduct of computing efficiency scores. As a result, the benchmark units may differ from the evaluated DMU in terms of their input–output profiles and the scale size. Moreover, the DEA benchmarks may oper...

In this paper, we introduce a novel multi-period data envelopment analysis (MDEA) model that attempts to circumvent the limitations of existing MDEA models. The proposed global is essentially based on major modifications fundamental DEA axioms enable decision making unit (DMU), defined with inputs and outputs period t , be evaluated within production possibility set (PPS) another l ≠ l. Buildin...

Benchmarking cleaner production performance is an effective way of pollution control and emission reduction in coal-fired power industry. A benchmarking method using two-stage super-efficiency data envelopment analysis for coal-fired power plants is proposed – firstly, to improve the cleaner production performance of DEA-inefficient or weakly DEA-efficient plants, then to select the benchmark f...

in a recent paper in this journal, yang et al. [feng yang, dexiang wu,liang liang, gongbing bi & desheng dash wu (2009), supply chaindea:production possibility set and performance evaluation model] definedtwo types of supply chain production possibility set which were proved to beequivalent to each other. they also proposed a new model for evaluatingsupply chains. there are, however, some short...