Research on influencing factors of knowledge flow in discrete industry: A case study of Chinese materia medica listed companies
10.7501/j.issn.0253-2670.2018.06.036
- Author:
Chong FENG
1
Author Information
1. College of Business Administration, Shenyang Pharmaceutical University
- Publication Type:Journal Article
- Keywords:
Binary logistic regression;
Chinese materia medica listed companies;
Discrete industry;
Knowledge flow;
Patent
- From:
Chinese Traditional and Herbal Drugs
2018;49(6):1481-1488
- CountryChina
- Language:Chinese
-
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.
