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离散型产业内知识流动影响因素研究——以中药上市企业为例
引用本文:冯冲,董新月,袁红梅.离散型产业内知识流动影响因素研究——以中药上市企业为例[J].中草药,2018,49(6):1481-1488.
作者姓名:冯冲  董新月  袁红梅
作者单位:沈阳药科大学工商管理学院, 辽宁 沈阳 110016,沈阳药科大学工商管理学院, 辽宁 沈阳 110016,沈阳药科大学工商管理学院, 辽宁 沈阳 110016
基金项目:辽宁省教育厅人文社会科学研究项目:新常态下中国企业无形资产投资社会价值评估体系初探——以中国制药产业专利数据为研究样本(W2015369)
摘    要:离散型产业不同于复杂型产业,企业间的专利引用是其显性知识流动的主要渠道。为了帮助处于离散型产业的企业寻找模仿创新的对象及投资人评估离散型产业中上市企业的价值,以中药上市企业作为研究样本,首先运用社会网络分析法构建可视化的知识流动网络图,然后利用网络图的度数中心度和中间中心度进行K均值聚类,对发生知识流动的主体进行类型划分与归纳。最后基于对主体的分类,采用二元logistic回归,从知识流出和流入2个维度探究专利因素和企业因素对知识流动的影响。结果表明,对于企业的知识流出,企业年龄、技术宽度、企业规模、研发投入与其呈显著正相关;对于企业的知识流入,研发投入、权利要求数量与其呈显著正相关,而企业年龄、技术宽度、科学关联度、技术集中度则与其呈显著负相关。

关 键 词:离散型产业  知识流动  中药上市企业  专利  二元logistic回归
收稿时间:2017/11/12 0:00:00

Research on influencing factors of knowledge flow in discrete industry: A case study of Chinese materia medica listed companies
FENG Chong,DONG Xin-yue and YUAN Hong-mei.Research on influencing factors of knowledge flow in discrete industry: A case study of Chinese materia medica listed companies[J].Chinese Traditional and Herbal Drugs,2018,49(6):1481-1488.
Authors:FENG Chong  DONG Xin-yue and YUAN Hong-mei
Institution:College of Business Administration, Shenyang Pharmaceutical University, Shenyang 110016, China,College of Business Administration, Shenyang Pharmaceutical University, Shenyang 110016, China and College of Business Administration, Shenyang Pharmaceutical University, Shenyang 110016, China
Abstract:Discrete industry is different from the complex industry, the patent citation between enterprises is the main channel of its dominant knowledge flow. In order to help the enterprises to find the imitative innovation objects and the investors to evaluate the value of the listed companies in the discrete industries, this study took the Chinese materia medica listed companies as the research samples, first used the social network analysis method to construct the visual flow chart of knowledge flow, then the K-means clustering was carried out by using the degree centrality and the betweenness centrality of the network graph, and the type of knowledge flow was divided and summarized. Finally, based on the previous classification of the main body, the binary logistic regression was adopted to explore the influence of patent factors and business factors on the knowledge flow from two dimensions of knowledge outflow and inflow. The results showed that enterprise age, technology width, enterprise scale and R & D investment had a significantly positive correlation with the knowledge outflow; The knowledge inflow was positively relative with R & D investment and the number of claims, while with significantly negative correlation with the enterprise age, technology width, scientific relevance and technical concentration.
Keywords:discrete industry  knowledge flow  Chinese materia medica listed companies  patent  binary logistic regression
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