Performance measurement in the presence of fixed-sum outputs in data envelopment analysis (DEA) is an interesting and most frequently studied subject in the field of operations research. Different definitions of relative efficiency in the presence of fixed-sum outputs have been proposed in the literature of data envelopment analysis and in all of the existing definitions a common equilibrium ef...

This paper examines the Data Envelopment Analysis (DEA) methodology from a cognitive perspective. Specifically, it analyzes (a) the role of DEA scores as an overall efficiency measure and (b) to what extent the presence of DEA scores for a non-financial performance appraisal influences a posterior financial performance assessment. The study confirms that the efficiency score acts as a strong pe...

supplier evaluation and selection is important in supply chain management. this is a typical multiple criteria decision making that consists of both quantitative and qualitative factors. ahp is a proper approach to aid this decision making problem, because of its inherent capacity to handle qualitative and quantitative criteria, but when criteria are dependent this method is not so good. also t...

Data envelopment analysis (DEA) is one of the most efficient tools for efficiency measurement which can be employed as a benchmarking method with multiple inputs and outputs. However, DEA does not provide any suggestions for improving efficient units, nor does it provide any benchmark or reference point for these efficient units. Impracticability of these benchmarks under environmental conditio...

Data envelopment analysis (DEA) measures relative efficiency among the decision making units (DMU) without considering noise in data. The least efficient DMU indicates that it is in the worst situation. In this paper, we measure efficiency of individual DMU whenever it losses the maximum output, and the efficiency of other DMUs is measured in the observed situation. This efficiency is the minim...

This study examines the efficiency of 12 Taiwanese laptop manufacturers in 2002. This work demonstrates the feasibility of adopting Data Envelopment Analysis (DEA) to identify individual manufacturing firms that are less efficient than other ones. Efficiency is measured in terms of output variables relative to input variables. For those efficient laptop manufacturers lacking of productivity, th...

Within the data envelopment analysis context, problems of discrimination between efficient and inefficient decision-making units often arise, particularly if there are a relatively large number of variables with respect to observations. This paper applies Monte-Carlo simulation to generalize and compare two discrimination-improving methods; principal component analysis applied to data envelopme...

data envelopment analysis (dea) has been proven as an efficient technique to evaluate the performance of homogeneous decision making units (dmus) where multiple inputs and outputs exist. in the conventional applications of dea, the data are considered as specific numerical values with explicit designation of being an input or output. however, the observed values of the data are sometimes imprec...

Chiou et al. (2010) (A joint measurement of efficiency and effectiveness for non-storable commodities: integrated data envelopment analysis approache s. European Journal of Operationa l Research 201, 477– 489) propose an integrated data envelopment analysis model in measuring decision making units (DMUs) that have a two-stage internal netwo rk structure with multiple inputs, outputs, and consum...