This paper proposes a non-radial DEA approach consisting of both a static and a dynamic environmental performance index (EPI) for measuring environmental performance. The static EPI is defined as the ratio of a non-radial efficiencymeasure for reducing undesirable outputs to that for increasing desirable outputs. The proposed non-radial DEA approach has been applied to model the environmental p...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. The standard DEA models assume that all inputs and outputs are crisp and can be changed at the discretion of management. While crisp input and output data are fundamentally indispensable in the standard DEA evalua...

This ‎paper presents a new multi-objective fuzzy stochastic data envelopment analysis model          (MOFS-DEA) under mean chance constraints and common weights to estimate the efficiency of decision making units for future financial periods of them. In the initial MOFS-DEA ‏model, the outputs and inputs are ‎characterized by random triangular fuzzy variables with normal distribution, in which ...

Data Envelopment Analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about efficiency and performance of firms, organizations, and all sorts of functionally similar, relatively autonomous operating units, known as Decision Making Units (DMU). Usually the investigated DMUs are characterized by a vector of multiple inputs and multiple outputs. Unfortu...

Most of ex-ante impact assessment policy models have been based on a parametric approach. We develop a novel non-parametric approach, called Inverse DEA. We use non parametric efficiency analysis for determining the farm’s technology and behaviour. Then, we compare the parametric approach and the Inverse DEA models to a known data generating process. We use a bio-economic model as a data genera...

Data envelopment analysis (DEA) is a widely used benchmarking technique. Its strength stems from the fact that it can include several inputs and outputs of not necessarily same type to evaluate efficiency scores. Indeed, aforesaid method based on mathematical optimization. This paper constructs second-order conic optimization problem unifying DEA models. Moreover, presents an algorithm solves f...

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...

This paper deals with the problem of fairly allocating a certain amount of divisible goods or burdens among individuals or organizations within the framework of data envelopment analysis (DEA). It is an extension work on our previous research of game theoretic approaches to weight assignments in DEA problems [6]. One of the main points in this previous work was that the core of the TU DEA game ...

Data Envelopment Analysis (DEA) is a relatively new “data oriented” non-parametric approach for evaluating the performance of complex entities called Decision Making Units (DMUs) which convert multiple inputs into multiple outputs. DEA as a linear programming procedure computes a comparative ratio of outputs to inputs for each DMU, which is reported as the relative efficiency score. In a relati...

In this paper we apply data envelopment analysis (DEA) to evaluate the performance of hedge fund classifications. The purpose of alternative investment strategies such as hedge funds is to offer absolute returns, so using passive benchmarks to measure their performance could be ineffective. With the increasing number of hedge funds available, institutional investors, pension funds, and high net...