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...

The cross-efficiency method, as a Data Envelopment Analysis (DEA) extension, calculates the cross efficiency of each decision making unit (DMU) using the weights of all decision making units (DMUs). The major advantage of the cross-efficiency method is that it can provide a complete ranking for all DMUs. In addition, the cross-efficiency method could eliminate unrealistic weight results. Howeve...

In many applications, ranking of decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA), especially when there are extremely efficient DMUs. In such cases, many DEA models may usually get the same efficiency score for different DMUs. Hence, there is a growing interest in ranking techniques yet. The purpose of this paper is ra...

Basic models of Data Envelopment Analysis are intrinsically preference-free, in the sense that they consider all inputs and outputs and also all decision making units of the same importance. Although this property is beneficial in many ways, it has some drawbacks simultaneously, as the decision makers’ preferences are not taken into account in the process of evaluating units.  To overcome this ...

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 ...

Conventional DEA models tend to allocate the fixed resources multiple decision-making units (DMUs) and treat allocated resource as an extra input for every single DMU. However, existing allocation (DEA-RA) methods are applicable exclusively DMUs with exact values of inputs outputs. A lack precision or output data DMUs, such interval data, would cause a failure DMUs. In order resolve this proble...

In this paper, we introduce a novel multi-period data envelopment analysis (MDEA) model that attempts to circumvent the limitations of existing MDEA models. The proposed global is essentially based on major modifications fundamental DEA axioms enable decision making unit (DMU), defined with inputs and outputs period t , be evaluated within production possibility set (PPS) another l ≠ l. Buildin...

Data Envelopment Analysis (DEA) is an appropriate tool for estimating various types of efficiency including Cost Efficiency (CE). Identifying and identifying inefficiency resources plays an important role in analyzing unit performance in order to plan for improving the status of Decision Making Units (DMUs). Now , if information on the inputs and outputs and pricing information of the evaluated...

Here, we describe a novel spontaneous autosomal recessive mutation in the mouse that is characterized by skeletal and cardiac muscle degeneration. We have named this mutant degenerating muscle (dmu). At birth, mutant mice are indistinguishable from their normal littermates. Thereafter, the disease progresses rapidly and a phenotype is first observed at approximately 11 days after birth; the dmu...