Keywords: Data envelopment analysis Target unit Undesirable output Multiple objective linear programming Minimax method a b s t r a c t Data Envelopment Analysis (DEA) is a mathematical programming technique for identifying efficient Decision Making Units (DMUs) with multiple inputs and multiple outputs. DEA provides a technical efficiency score for each DMU, a technical efficiency reference se...

Selection of an appropriate set of Information System (IS) projects is a critical business activity which is very helpful to all organizations. In this paper, after describing real IS project selection problem of Iran Ministry of Commerce (MOC), we introduce two Data Envelopment Analysis (DEA) models. Then, we show applicability of introduced models for identifying most efficient IS project fro...

One of the existing DEAmethods’ limitations noted in the literature lies in the process of benchmarking of reference targets for inefficient DMUs. Difficulties arising in this process can be summarized to three aspects. First, the reference target might be a hypothetical DMU that does not actually exist (it is difficult and indeed unrealistic to learn from such a DMU). Second, the reference set...

Efficiency analysis is commonly used to assess and compare the productivity of similar decision-making units (DMUs). In this research, we broaden the applicability of efficiency analysis to situations where each DMU comprises interconnected sub-DMUs (e.g., departments). Extant research espouses that embracing the connectedness between subDMUs (e.g., marketing–sales interface, marketing–R&D inte...

Traditional super-efficiency data envelopment analysis (DEA) models rank efficient units under the assumption of constant returns to scale (CRS). However, infeasibility may occur in super-efficiency models under variable returns to scale (VRS). This paper proposes a modified VRS super-efficiency DEA model to deal with infeasibility by relaxing the convexity constraint 1, 0 1 n j j j λ = ≠ = ∑ t...

Data Envelopment Analysis (DEA) is actually to obtain the efficiency using inputs and outputs, which can determine efficient and inefficient units with the help of performance calculations such that the efficiency for efficient DMUs is one and less than one for inefficient DMUs [1]. In some cases, the ranking of the decision-making units are not important for decision-makers, and they are only ...

In this paper, we will propose a Slacks-Based measure (SBM) of efficiency in DEA. This scalar measure deals directly with the input surplus and the output shortage of the decision making unit (DMU) concerned. It is unit invariant and monotone decreasing with respect to input surplus and output shortage. Furthermore, this measure is decided only by consulting with the reference set of the DMU an...

The inefficient DMUs are usually arranged after the technical efficient ones by DEA methods, however, it is possible that a technical efficient DMU neither be efficient nor be more efficient than some inefficient ones. This study distinguishes between the terms ‘technical efficiency’ and ‘efficiency’ and demonstrates that the technical efficiency is a necessary condition for being efficient and...

This study addresses the problem of finding the range of efficiency for each Decision Making Unit (DMU) considering uncertain data. Uncertainty in the DMU coefficients in each factor (input or output) is captured through interval coefficients (i.e., these are uncertain but bounded). A twophase additive Data Envelopment Analysis (DEA) model for performance evaluation is used, which is adapted to...