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Categories, attention, and the impact of inventions

机译:类别,关注和发明的影响

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Research Summary Whereas prior innovation and strategy literature studied how attentional and search dynamics influence the creation of inventions, we examine how these same processes affect the impact of inventions after their creation. We theorize that inventions classified in "high-contrast" technological categories garner more attention by potential users and, hence, accrue more citations than otherwise-equivalent inventions classified in "low-contrast" categories. We test this hypothesis via three studies. First, we estimate citation-count models among all USPTO patents granted between 1975 and 2010. Second, we conduct a twin patents test comparing inventions patented both at the USPTO and at the EPO. Third, we examine minute-by-minute search logs from a sample of USPTO examiners. These studies support our hypothesis and extend current understandings of attentional and search dynamics in the innovation process.Managerial Summary Patents that receive more citations tend to have greater economic value and greater impact on future technological developments. We show that the number of citations a patent receives does not only depend on its inherent technological value, but also on seemingly neutral classification decisions affecting the likelihood that it will be noticed by potential future users. We test our arguments via three related studies. Our results demonstrate that inventions classified in "high-contrast" technology classes garner considerably more attention-and hence citations-than twin-inventions classified in "low-contrast" classes. The key managerial implication is that, whenever feasible, nudging an invention towards higher-contrast classes will increase its future worth. The key policy implication is that maximizing categorical contrast across technology classes will help users identify relevant prior patents.
机译:研究总结,而先前的创新与战略文献研究了注意力和搜索动态如何影响发明的创造,我们研究了这些过程如何影响他们创造后的发明的影响。我们通过潜在的用户理解了归类于“高对比度”技术类别的发明,从而通过潜在用户获得更多的关注,而不是在“低对比度”类别中分类的其他发明。我们通过三项研究测试这一假设。首先,我们估算1975年至2010年间的所有USPTO专利中的引文计数模型。第二,我们进行双重专利测试比较在USPTO和EPO上专利的发明。第三,我们从USPTO审查员的样本检查分钟搜索日志。这些研究支持我们的假设,并在创新过程中延长了对注意力和搜索动态的当前谅解。获得更多引用的管理摘要专利往往具有更大的经济价值和对未来技术发展的影响更大。我们表明,专利收到的引文的数量不仅取决于其内在的技术价值,而且还依赖于看似中立的分类决策,影响其未来用户将注意到它的可能性。我们通过三项相关研究测试我们的论点。我们的结果表明,在“高对比度”技术课程中,归类于“高对比度”技术课程的发明更加关注,因此在“低对比度”课程中归类的双发明引用。关键管理暗示是,每当可行时,向更高对比度的发明揭示发明将增加其未来的价值。关键政策含义是,技术类别的最大化对比度将有助于用户识别相关的先前专利。

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