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Decision Tree based on data envelopment analysis for effective technology commercialization

机译:基于数据包络分析的决策树,用于有效的技术商业化

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摘要

In recent years, much governmental investment has been committed to R&D in the area of information technology industry. However, its commercialization rate is reported to be lower than expected. In order to prevent such waste, feedback information obtained from the rigorous evaluation of the finished R&D project needs to be utilized for future selection of new projects. The main purpose of our study is to provide the roadmap of the effective technology commercialization projects using the Decision Tree (DT) of data envelopment analysis (DEA) results when a company tries to develop or transfer its new technology. The environmental variables representing the characteristics of technology provider, receiver and technology itself are used as input variables for DT where the DEA results are used as a target variable. It is expected that our proposed approach can be effectively used to obtain the efficient scenario among the alternatives of several technology projects.
机译:近年来,政府在信息技术行业的研发投入了大量资金。但是,据报道其商业化率低于预期。为了避免这种浪费,需要对从完成的R&D项目进行严格评估而获得的反馈信息,用于将来的新项目选择。我们研究的主要目的是在公司尝试开发或转让其新技术时,使用数据包络分析(DEA)结果的决策树(DT)提供有效的技术商业化项目的路线图。代表技术提供者,接收者和技术本身特征的环境变量用作DT的输入变量,而DEA结果用作目标变量。期望我们提出的方法可以有效地用于在几个技术项目的替代方案中获得有效的方案。

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