北京邮电大学学报(社科版) ›› 2018, Vol. 20 ›› Issue (5): 69-79.doi: 10.19722/j.cnki.1008-7729.2018.0113

• 经济与管理 • 上一篇    下一篇

基于PSM-DID模型的上市公司并购创新绩效研究

  

  1. 武汉理工大学 经济学院,湖北 武汉430070
  • 收稿日期:2018-05-21 出版日期:2018-10-31

Innovation Performance of Listed Company M&As: Empirical Research #br# Based on PSM-DID Model

  1. School of Economics, Wuhan University of Technology, Wuhan 430070, China
  • Received:2018-05-21 Online:2018-10-31

摘要: 将2006—2016年中国制造业1232家上市企业分为未发生并购的企业、非技术并购企业和技术并购企业,采用非经典PSM-DID(Propensity Score Matching-Difference in Differences)模型,交叉比较了三者并购前后技术创新绩效的变化。研究表明,非技术并购不能提升企业技术创新绩效,技术并购可以提升企业技术创新绩效的原假设也不成立;但企业可以通过加密加深与目标企业的经济联系,以及通过扩大自身的知识宽度来减弱这种负向效应。本研究区分了技术并购与非技术并购对企业技术创新绩效影响机理的差异,分析了主并方创新能力和属性特点对创新产出的作用效果,为企业可持续的利润最大化提供了有效途径。

关键词: 并购, 技术并购, 知识基础, 创新绩效

Abstract:  The effect of mergers and acquisitions (M&As) on technological innovation performance has not reached a conclusion. 1232 listed companies in China′s manufacturing industry from 2006 to 2016 were divided into three groups: never merged before, non-technological M&As and technological M&As. Then, the non-classical PSM-DID(Propensity Score Matching-Difference in Differences)  model is adopted to analyze the path and effect of three groups on the technological innovation performance. The result shows that non-technological M&As cannot improve enterprise′s technological innovation performance. The hypothesis that technological merger and acquisition can improve enterprise′s technological innovation performance is not tenable either. Despite of that, enterprises can weaken this negative effect by deepening economic ties with target companies and expanding their knowledge breadth. This study distinguishes the differences in the mechanism of technological innovation performance between technological and non-technological M&As and analyzes the main effects of innovation capabilities and acquirers′ characteristics on innovation output, providing effective ways to enterprises′ sustainable profit maximization.

Key words: acquisitions, technological acquisitions, knowledge base, innovation performance

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