Keywords: Data envelopment analysis (DEA) Common weights analysis (CWA) Ranking The ideal line The special line a b s t r a c t Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decision making units (DMUs) in a homogeneous group. However, DEA does not provide more information about the efficient DMUs. In this research, the ...

Abstract Conventional models of data envelopment analysis (DEA) are based on the constant and variable returns-to-scale production technologies. Any optimal input output weights multiplier DEA these technologies interpreted as being most favorable for decision making unit (DMU) under assessment when latter is benchmarked against set all observed DMUs. In this paper we consider a very large clas...

Efficiency is the main issue in any data envelopment analysis. Realizing output by a minimum of input or reaching maximum given credo, scale effects often are only sort accessory. In modern economics play prominent role, however. What right size decision making unit (DMU) and how to proceed there. Returns inform DMU about its hitherto disregard show way towards ideal activity size. Combining ef...

A fundamental weakness of the Data Envelopment Analysis (DEA) is its weak discrimination in cases when a small number of decision making units are compared. Therefore, in such cases the basic DEA model (optimistic and pessimistic) is used in combination with other methods or additional constraints are added to the model. In this paper, the cross-efficiency method was combined with a self-rankin...

This paper clarifies the connection between multiple criteria decision-making and decision under uncertainty in a qualitative setting relying on a finite value scale. While their mathematical formulations are very similar, the underlying assumptions differ and the latter problem turns out to be a special case of the former. Sugeno integrals are very general aggregation operations that can repre...

This paper examines inability of CCR and BCC models in improving DMU’s scale efficiency when a production possibility frontier is assumed as variable returns to scale. This paper also finds that DEA result can be more efficient than the Pareto-efficiency when a DMU is feasibly projected to be both technically and scale efficient. This feasible projection can only be achieved by a VRS DEA model ...

In this paper, by introducing two virtual decision-making units (DMUs) called ideal DMU (IDMU) and anti-ideal DMU (ADMU) with fuzzy inputs-outputs, the efficiency evaluation of DMUs are done by fuzzy data envelopment analysis (FDEA). Therefore, we evaluate DMUs from the perspective of the best and worst possible relative efficiency. For each DMU two efficiencies are calculated while inputs and ...

Data envelopment analysis is a method for evaluating the relative efficiency of a collection of decision making units. The DEA classic models calculate each unit’s efficiency in the best condition, meaning that finds a weight that the DMU is at its maximum efficiency. In this paper, utilizing the directional distance function model in the presence of undesirable outputs, the efficiency of each ...