in this paper, non parametric data envelopment analysis (dea) was subjected to the energy data of wheat producers in punjab state, india, and technical, pure technical and scale efficiencies were calculated for farms both category wise and zone wise. the main objective was to determine the strength of the correlation between non-parametric efficiencies and indices such as energy ratio and speci...

sueyoshi and sekitani in 2007 presented a paper that explores the measurement of returns to scale under a possible occurrence of multiple solution in a reference set and a supporting hyperplane. the occurrence ofmultiple solutions is classified into type i and type ii. type i is an occurrence of multiple solutions in a reference set. type ii is an occurrence of multiple solutions on a supportin...

data envelopment analysis (dea) is a branch of management, concerned with evaluating the performances of homogeneous 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 increase in one or more inputs generate a reduction in one or more outputs. in ...

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...

The inverse Data Envelopment Analysis (InvDEA) is an exciting and significant topic in the DEA area. Also, uncertain data various real-life applications can degrade efficiency results. current work addresses InvDEA presence of stochastic data. Under maintaining score, inputs/outputs-estimation problem investigated when some or all its outputs/inputs increase. A novel optimality concept for mult...

Decision makers (DMs) face different levels of uncertainty throughout the decision making process. In particular, natural language is generally subjective or ambiguous when used to express perceptions and judgments. The aim of this paper is to extend the VIKOR method and develop a methodology for solving multi-criteria decision making (MCDM) problems with stochastic data. The weights of the sto...

Like model selection in statistics, the choice of appropriate Data Mining Algorithms (DM-Algorithms) is a very important task in the process of Knowledge Discovery. Due to this fact it is necessary to have sophisticated metrics that can be used as comparators to evaluate alternative DMalgorithms. It has been shown in literature, that Data Envelopment Analysis (DEA) is an appropriate platform to...

occupational accidents severely deteriorate human capital, and hence negatively affect the productivity andcompetitiveness. but despite these negative points, there are still deficiencies in safety managementperformance and indicators. therefore the safety issue needs an active management. for this reason, thewriter has proposed an approach to evaluate organizations based on safety management. ...

inthis article we offer a method of ranking contractors by using dea based onanalysis deficit and ahp. the process of hierarchical analysis (ahp) byproviding scales from paired comparison matrix, performs the contractor’sprioritizing choice. but ahp has some problems and to solve those problems,jahanshahloo and his colleagues presented a new model which uses dea andstandard deviation. in this a...