In original data envelopment analysis (DEA) models, the data for all inputs and outputs are known exactly. When some inputs and outputs are unknown decision variables, such as interval data, ordinal data, and ratio bounded data, the DEA model is called imprecise DEA (IDEA). In this paper, We develop an alternative approach based upon slacksbased measure of efficiency (SBM) for dealing with inte...

DEA is a non-parametric and linear programming based technique that attempts to maximize a decision making unit’s (DMUs) relative efficiency, expressed as a ratio of outputs to inputs, by comparing a particular unit’s efficiency with the performance of a group of similar DMUs that are delivering the same service. The traditional DEA models treat DMUs as black boxes whose internal structure is i...

In the history of DEA, there are two fundamental “Radial” and “Non-radial” approaches for the efficiency measurement. Each approach has its own advantageous and shortcomings. Avkiran et al. (2008) provided a unified framework, named Connected-SBM, for linking these approaches. In the present paper, first, based on the directional distance function we develop the Directional Slack-Based Measures...

in dea to obtain an efficient representation in ccr andbcc models for each dmu only one linear plan would be solved; however,it is possible in centralized resource allocation (cra) to solve allthe dmus by one linear planning. in this paper, models of centralizedresource allocation in input-oriented and in dynamic case will be offeredand by using dynamic sbm, the representation of dmus in each t...

We propose a dynamic DEA model involving network structure in each period within the framework of a slacks-based measure approach. We have previously published the network SBM (NSBM) and the dynamic SBM (DSBM) models separately. Hence, this article is a composite of these two models. Vertically, we deal with multiple divisions connected by links of network structure within each period and, hori...

Data envelopment analysis (DEA) mainly utilizes envelopment technology to replace production function in microeconomics. The input and output of decision making units (DMUs) are projected into the attributes to evaluate or measure their performance. However, if the inputs and outputs are linguistically termed or are fuzzy-numbered, conventional DEA can not easily measure the performance. Theref...

This paper is aimed to give an illustration on the application of Data Envelopment Analysis (DEA) as a tool to assess Quality Management (QM) efficiency. A variant of DEA, slack based measure (SBM) is used for this purpose. From this study, it is found that DEA is suitable to measure QM efficiency and give improvement suggestions to the inefficient QM. Keywords—Quality Management, Data Envelopm...

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them in DEA models, we propose a slacks-based network DEA model that can deal with intermediate products. Using this model we can ...

Efficiency reflects a scenario of higher quality product with fewer resource inputs and less pollution discharge. In terms of a manufacturing firm, it means a win-win strategy in both economic and environmental categories. The paper extends the Electric Arc Furnace (EAF) activity management by taking pollution discharge as undesirable outputs. After reviewing relative undesirable outputs DEA li...