in recent years, the existing competitions between investment companies have been increased largely by entering private investors in capital market. large and powerful companies try to achieve the goals predicted to increase the competition capacity. to analyze the efficiency of investment companies, parametric and non-parametric methods are used. in this research, based on the dissociation pow...

data envelopment analysis (dea) is a method for measuring the efficiency of peer decision making units (dmus) which uses a set of inputs to produce a set of outputs. in some cases, dmus have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. one important issue in two-stage dea is the sensitivity of...

The explanation of productivity differentials is very important to identify the economic conditions that create inefficiency and to improve managerial performance. In literature two main approaches have been developed: one-stage approaches and twostage approaches. Daraio and Simar (2003) propose a full nonparametric methodology based on conditional FDH and conditional order-m frontiers without ...

introduction: the quality of the information provided in the public sector is of a high importance due to the specific purpose of reporting. presenting reliable, complete, and timeliness information of the activities in the governmental sector by using desirable public sector accounting system provides a better opportunity for people's monitoring on the offering of governmental services, transp...

It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘best’ model. This paper proposes a novel Data Envelopment Analysis (DEA) based approach to combine models. We prove that for the 2-class classification problems, DEA models identify the same convex hull as the popular RO...