首页> 外文期刊>Research policy >Inventing by combining pre-existing technologies: Patent evidence on learning and fishing out
【24h】

Inventing by combining pre-existing technologies: Patent evidence on learning and fishing out

机译:结合现有技术进行发明:关于学习和挖掘的专利证据

获取原文
获取原文并翻译 | 示例
       

摘要

I develop a model of innovation where new technologies are combinations of pre-existing technological components. The model captures two opposing forces. The best ideas are used up (knowledge is exhaustible). However, as firms team which technologies can be combined, new ideas become feasible (knowledge accumulates). I test the model with more than 80 years of US patent data. Technological components are proxied by 13,517 patent office technology classifications. These are reused and recycled in 10,000 distinct three-component sets. Consistent with a learning/fishing-out dynamic, I show patenting in one set of components is correlated with a subsequent increase in similar patents (sharing two of three components), but a subsequent decrease in identical patents (sharing all three components). I use patent renewal data to show my results are not driven by changes in demand for various technology bundles. My results suggest the positive impact of learning on subsequent patenting is larger than the negative impact of fishing out.
机译:我开发了一个创新模型,其中新技术是现有技术组件的组合。该模型捕获两个相反的力。最好的想法用光了(知识是无穷的)。但是,随着公司团队将哪些技术可以组合起来,新的想法变得可行(知识不断积累)。我使用80多年的美国专利数据测试了该模型。技术成分由13,517个专利局技术分类来替代。这些可在10,000个不同的三组分组中重复使用和回收。与学习/退出动态一致,我显示一组组件的专利申请与随后的相似专利增加(共享三个组件中的两个)相关,但随后的相同专利减少(共享所有三个组件)相关。我使用专利续签数据显示我的结果不受各种技术束需求变化的驱动。我的研究结果表明,学习对后续专利的积极影响要大于淘汰钓鱼的负面影响。

著录项

  • 来源
    《Research policy》 |2018年第1期|252-265|共14页
  • 作者

    Matthew S. Clancy;

  • 作者单位

    USDA Economic Research Service, Washington DC, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Innovation; Patents; Combinatorial growth; Spillovers; RD;

    机译:革新;专利;组合增长;溢出;研发部;
  • 入库时间 2022-08-18 02:51:10

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号