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A Novel Approach to Measuring Efficiency of Scientific Research Projects: Data Envelopment Analysis

机译:一种衡量科研项目效率的新方法:数据包络分析

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摘要

PurposeMeasuring the efficiency of resource allocation for the conduct of scientific projects in medical research is difficult due to, among other factors, the heterogeneity of resources supplied (e.g., dollars or FTEs) and outcomes expected (e.g., grants, publications). While this is an issue in medical science, it has been approached successfully in other fields by using data envelopment analysis (DEA). DEA has a number of advantages over other techniques as it simultaneously uses multiple heterogeneous inputs and outputs to determine which projects are performing most efficiently, referred to as being at the efficiency frontier, when compared to others in the data set.
机译:目的由于提供的资源(例如,美元或FTE)的异质性和预期的成果(例如,赠款,出版物)等原因,难以衡量医学科研项目的资源分配效率。尽管这是医学科学中的问题,但已通过使用数据包络分析(DEA)在其他领域成功解决了这一问题。 DEA与其他技术相比具有许多优势,因为与数据集中的其他项目相比,DEA同时使用多个异构输入和输出来确定哪些项目的执行效率最高(称为效率前沿)。

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