研发支出、溢出池与专利申请——基于中国工业上市企业的经验研究
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  • 英文篇名:R&D Expenditure, Spillover Pool and Corporate Patenting——An Empirical Study on Chinese Industrial Listed Companies
  • 作者:周敏 ; 马书尧 ; 寇宗来
  • 英文作者:ZHOU Min;MA Shu-yao;KOU Zong-lai;School of Management ,University of Shanghai for Science and Technology;China Center for Economic Studies, Fudan University;
  • 关键词:研发支出 ; 溢出池 ; 专利申请
  • 英文关键词:R&D expenditure;;spillover pool;;patent application
  • 中文刊名:YJYF
  • 英文刊名:R&D Management
  • 机构:上海理工大学管理学院;复旦大学中国社会主义市场经济研究中心;
  • 出版日期:2019-04-15
  • 出版单位:研究与发展管理
  • 年:2019
  • 期:v.31
  • 基金:教育部人文社会科学研究青年基金项目“中国工业企业间技术溢出效应研究及其政策含义”(15YJC790158);教育部人文社会科学重点研究基地项目“知识产权、企业融资与技术进步”(18JJD79003);教育部在线教育基金重点项目“基于SCP范式的慕课战略研究”(2017ZD104)
  • 语种:中文;
  • 页:YJYF201902012
  • 页数:12
  • CN:02
  • ISSN:31-1599/G3
  • 分类号:125-136
摘要
本文匹配了2006—2015年中国上市企业数据库和中国专利数据库,以A股上市工业企业为研究对象,考察企业发明专利申请行为的决定因素及其影响机制。分析表明:由于外部激励对内部激励的挤出效应,企业专利申请与其研发支出呈U形关系,而非简单的线性关系;由其他企业研发支出按各种权重加总形成的溢出池对企业专利的影响为负,即"技术机会"效应占优于"知识溢出"效应;企业自身研发支出与溢出池的交互效应为负,说明企业在专利申请方面是战略替代的。
        It aimed to study the determinants of patenting behavior by matching Chinese listed companies with SIPO patent database from 2006 to 2015. The results show that: extrinsic incentive crowding out intrinsic incentives,corporate patenting has a U relationship with its observable R&D expenditure; technology opportunity effect dominates knowledge spillover effect and the spillover pool which is constructed by other companies' R&D expenditure has a negative effect on the corporate patent application; companies are strategic substitutes in terms of patenting competition, since the interaction between corporate's own R&D expenditure and other companies' R&D spillover pool on corporate patenting is negative.
引文
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    (1)这里的“威慑效应”与前文的“技术机会”是不同的。挤占技术机会是假定所有企业都创新成功的情况下哪家企业能申请到专利的问题;而威慑效应是预期到其他企业研发成功之后会挤出自己获取专利的机会,企业i会因此减少自己的研发支出。
    (2)本文只保留A股上市企业控股比例大于等于50%的子公司。精确匹配和模糊匹配的细节参考寇宗来和刘学悦[38]的研究。相比该文献,本文还保留了从名称上来看专利申请人是上市公司子公司(或分支机构)的样本,例如,匹配了上市公司“中兴通讯股份有限公司”和专利申请人“深圳市中兴通讯股份有限公司上海第二研究所”。
    (3)在2012版证监会行业分类代码中,B06~D46的行业属于工业行业。
    (4)本文核心解释变量研发支出使用了滞后一期的数据,因此回归时2006年的样本会被删除,那些第一次在样本期内出现的样本也会被删除。
    (5)参考寇宗来和刘学悦[39]的做法,本文在计算企业的专利向量时,根据上市企业(包括其子公司和分支机构)发明专利的专利分类号将每个专利对应到35个技术领域,因此专利向量是一个35维的向量。
    (6)员工总数、营业收入、企业规模和市场集中度等指标都是使用上市企业年报的合并报表数据计算得出。
    (7)本文还计算了各解释变量之间的VIF值(方差膨胀因子),各模型中最大的VIF值均远小于10,因此不存在共线性问题。

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