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A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem

机译:基于数据包络分析的R&D项目选择问题多准则排序方法

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In this paper, multiple criteria sorting methods based on data envelopment analysis (DEA) are developed to evaluate research and development (R&D) projects. The weight intervals of the criteria are obtained from Interval Analytic Hierarchy Process and employed as the assurance region constraints of models. Based on data envelopment analysis, two threshold estimation models, and five assignment models are developed for sorting. In addition to sorting, these models also provide ranking of the projects. The developed approach and the well-known sorting method UTADIS are applied to a real case study to analyze the R&D projects proposed to a grant program executed by a government funding agency in 2009. A five level R&D project selection criteria hierarchy and an assisting point allocation guide are defined to measure and quantify the performance of the projects. In the case study, the developed methods are observed to be more stable than UTADIS. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在本文中,开发了基于数据包络分析(DEA)的多种标准排序方法来评估研发(R&D)项目。准则的权重区间是从区间分析层次过程获得的,并用作模型的保证区域约束。基于数据包络分析,开发了两个阈值估计模型和五个分配模型进行排序。除了排序之外,这些模型还提供了项目的排名。将开发的方法和著名的UTADIS排序方法应用于实际案例研究,以分析政府资助机构于2009年执行的一项赠款计划中提出的R&D项目。五级R&D项目选择标准层次结构和辅助点分配定义指南以衡量和量化项目的绩效。在案例研究中,发现开发的方法比UTADIS更稳定。 (C)2016 Elsevier Ltd.保留所有权利。

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