并购与创新:一种新的专利分类

Zhao-Hong Cheng, G. Jin, Mario Leccese, Dokyun Lee, Liad Wagman
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引用次数: 1

摘要

决策者越来越担心,对小公司或年轻公司的收购可能会减缓而不是加速创新,但很难确定哪些公司在快速变化的技术创新空间中是相关的。本文提出了一种新的数据驱动方法,利用专利受让人信息在概率基础上将专利数据划分为技术商业区域。在将标准普尔全球市场情报公司的并购数据与美国专利商标局的PatentsView数据相结合后,我们将讨论区域分类如何帮助合并审查和其他研究。
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M&A and Innovation: A New Classification of Patents
Policymakers are increasingly concerned that incumbent acquisitions of small or young firms may slow down rather than speed up innovation, but it is difficult to identify which firms are related in the fast-changing space of technological innovation. This paper proposes a new, data-driven method to classify patent data into tech-business zones on a probabilistic basis, using patent assignee information. After combining mergers and acquisitions data from S&P Global Market Intelligence with PatentsView data from the US Patent and Trademark Office, we discuss how the zone classification can aid merger reviews and other lines of research.
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