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A Non-Parametric Approach to Assess the Performance of Egyptian Universities

机译:评估埃及大学绩效的非参数方法

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This paper aims to assess the performance of Egyptian universities with data reported to 2010/2011. This study applied the Data Envelopment Analysis (DEA) methodology. DEA based on non-parametric mathematical models. It evaluates the performance of each observation with a multidimensional perspective. The study used a data of 12 universities for which were obtained the scores of technical and scale efficiency. The technical efficiency scores indicated the benchmark universities, demonstrating the potential of DEA. For purposes of analysis, this research used DEA with Charnes, Cooper and Rhodes (CCR) or Constant Returns to Scale (CRS) and Banker, Charnes, Cooper (BCC) or Variable Returns to Scale (VRS) for both Input-Oriented model and Output-Oriented model. The results of CRS model suggested that; five universities are technically efficient,while the results of VRS showed that ten universities are pure technically efficient and of these ten, only five are scale efficient which indicates that these universities are operating at their ideal scale of operations. The overall inefficiency for two universities in the CCR is caused by inefficient operations rather than the scale inefficiency, while for five universities is attributed to disadvantageous conditions.
机译:本文旨在利用截至2010/2011年的数据评估埃及大学的表现。这项研究应用了数据包络分析(DEA)方法。基于非参数数学模型的DEA。它从多维角度评估每个观察的性能。该研究使用了12所大学的数据,这些大学获得了技术和规模效率的分数。技术效率得分表明了基准大学,证明了DEA的潜力。为了便于分析,本研究针对面向输入的模型和模型分别使用了具有Charnes,Cooper和Rhodes(CCR)或规模比例固定收益率(CRS)和Banker,Charnes,Cooper(BCC)或规模可变收益率(VRS)的DEA。面向输出的模型。 CRS模型的结果表明:五所大学在技术上是有效的,而VRS的结果显示十所大学在技术上是纯效率的,在这十所大学中,只有五所是规模效率的,这表明这些大学在其理想的运营规模上运作。 CCR中两所大学的整体效率低下是由于运营效率低下,而不是规模效率低下,而五所大学则是由于不利条件。

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