Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiencies of decision-making units (DMUs) by using set inputs and outputs. However, traditional DEA models always assume that or outputs are independent each other, which unrealistic in practical problems. To reflect interactions between outputs, Choquet integral employed models. The usually used to find some specif...

Recent research has shown that combination approaches, such as taking the maximum or mean over different methods of estimating efficiency scores, have practical merits and offer a useful alternative to adopting only one technique. This recent shows minimizes risk underestimation, improves precision estimation. In this paper, we propose implement formal criterion weighting based on maximizing pr...

Information technology (IT) is a tool crucial for enterprises to achieve a competitive advantage and organizational innovation. A critical aspect of IT management is the decision whereby the best set of IT projects is selected from many competing proposals. The optimal selection process is a significant strategic resource allocation decision that can engage an organization in substantial long-t...

The problem of determining an optimal benchmark to inefficient decision-making units (DMUs) is important issue in the field performance analysis. Previous methods for projection points DMUs have only focused on one objective and other features been ignored. This paper attempts determine best point each DMU when inputs outputs data are stochastic form presents alternative definition by consideri...

Electricity distribution network is a prime example of a natural local monopoly. In many countries, electricity distribution firms are regulated by the government. In Finland, the regulator estimates the efficient cost frontier using the data envelopment analysis (DEA) and stochastic frontier analysis (SFA) methods. This paper reports the main results of the research project commissioned by the...

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...

Literature of productive efficiency analysis is currently divided between two main paradigms: the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper develops a new encompassing framework that melds the SFA-style stochastic composite error term to the DEA-type nonparametric frontier that satisfies monotonicity and concav...