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Lens or prism? Patent citations as a measure of knowledge flows from public research

机译:镜头还是棱镜?专利引用是衡量公共研究知识流向的标准

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摘要

Patent citations are the most widely used measures of knowledge flows because they characterize the importance of public research to industrial innovation. They are also used as dependent variables in regression analyses examining knowledge outflows from public research to industry and as regressors in models explaining the influence of public science on invention and industrial R&D productivity. Since there are no other alternatives or comparable measures, patent citations limit the ability to assess whether they are sources of systematic measurement error. The research work based on 676 newly developed data set matches patent citations to Carnegie Mellon Survey (CMS) survey reports from research and development (R&D) lab managers. The patents from the NBER patent database applied for between 1991 and 1993 has tried to assess citations as a measure of one particular type of knowledge flows, those originating from public research institutions.
机译:专利引用是知识流使用最广泛的方法,因为它们体现了公共研究对产业创新的重要性。它们还用作回归分析的因变量,以检查从公共研究到产业的知识流出,并在解释公共科学对发明和工业研发生产力的影响的模型中用作回归。由于没有其他选择或可比较的度量标准,因此专利引用限制了评估它们是否为系统度量误差源的能力。基于676个新开发的数据集的研究工作将专利引文与研究与开发(R&D)实验室管理人员的卡内基梅隆调查(CMS)调查报告相匹配。 1991年至1993年之间申请的NBER专利数据库中的专利试图评估引文,以衡量一种特定类型的知识流,这些知识流来自公共研究机构。

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  • 来源
    《Operations Research》 |2014年第2期|27-29|共3页
  • 作者

    Michael Roach; Wesley M. Cohen;

  • 作者单位

    Fuqua School of Business, Duke University, Durham, NC 27708;

    Fuqua School of Business, Duke University, Durham, NC 27708, and National Bureau of Economic Research, Cambridge, MA 02138;

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  • 正文语种 eng
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