Identifying the Evolution of Patent Assignees Collaboration Networks: A Case of Chinese Academy of Sciences (CAS)

This paper is a fundamental work of a purpose to identify the correlation between patent assignees collaboration networks and technology innovation activities, which includes R&D collaboration and management, technology transfer and transform, etc. The principal task of this paper is to confirm a series of methods used for identifying the evolution pattern of the patent assignees collaboration networks and make a demonstration of the Chinese Academy of Sciences (CAS), P.R. China. The analysis was carried out at two levels: ego network, in which CAS was taken as one node, and global network, in which all the subinstitutes of CAS were taken as nodes. Analysis focused on applications numbers, growth of collaborators, densification and growth, network diameter and distribution patterns of final collaboration networks. The results shows that CAS patent applications grew rapidly and showed an exponential growth feature, the collaboration networks tended to densify, the diameters of global networks increased constantly with no signal of being stable, increase or decrease in future. The final global network from 1985-2009 had been mapped and the nodes had degrees k followed a power law distribution. the CAS patent assignees collaborations networks had the growth and preferential attachment features, was consistent to the hypothesis that there might be some factors deciding the evolution patterns of the patent assignees collaboration networks. It is a fundamental work to identify the correlation between patent assignees collaboration networks and technology innovation activities.

[1]  Luís M. A. Bettencourt,et al.  Scientific discovery and topological transitions in collaboration networks , 2009, J. Informetrics.

[2]  Ronald Rousseau,et al.  Social network analysis: a powerful strategy, also for the information sciences , 2002, J. Inf. Sci..

[3]  John Whitfield,et al.  Collaboration: Group theory , 2008, Nature.

[4]  Thomas Klose,et al.  Enhancing patent landscape analysis with visualization output , 2010 .

[5]  Yongtae Park,et al.  Patent network analysis of inter-industrial knowledge flows: The case of Korea between traditional and emerging industries , 2006 .

[6]  Ismael Rafols,et al.  A global map of science based on the ISI subject categories , 2009, J. Assoc. Inf. Sci. Technol..

[7]  Pei-Chun Lee,et al.  Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight , 2010, Scientometrics.

[8]  Weimao Ke,et al.  Mapping the Diffusion of Information Among Major U.S. Research Institutions , 2005 .

[9]  Ying Bai,et al.  A rapid analysis of Avian Influenza patents in the Esp@cenet® database – R&D strategies and country comparisons , 2007 .

[10]  Network Workbench Tool , 2014, Encyclopedia of Social Network Analysis and Mining.

[11]  Christos Faloutsos,et al.  Graphs over time: densification laws, shrinking diameters and possible explanations , 2005, KDD '05.

[12]  Holger Ernst,et al.  Patent information for strategic technology management , 2003 .

[13]  Thorsten Teichert,et al.  Inventive progress measured by multi-stage patent citation analysis , 2005 .

[14]  Kevin W. Boyack,et al.  Mapping the structure and evolution of chemistry research , 2009, Scientometrics.

[15]  Zhiping Yang,et al.  A Comparative Study on the Biotechnology Patents of CAS , 2009 .

[16]  Shiu-Wan Hung,et al.  Examining the small world phenomenon in the patent citation network: a case study of the radio frequency identification (RFID) network , 2009, Scientometrics.

[17]  Chaomei Chen,et al.  Visualizing knowledge domains , 2005, Annu. Rev. Inf. Sci. Technol..

[18]  Judit Bar-Ilan,et al.  Informetrics at the beginning of the 21st century - A review , 2008, J. Informetrics.

[19]  J. Müller,et al.  Group Theory , 2019, Computers, Rigidity, and Moduli.

[20]  Qinghua Zhu,et al.  Mapping library and information science in China: a coauthorship network analysis , 2009, Scientometrics.

[21]  Sungjoo Lee,et al.  Inter-technology networks to support innovation strategy: An analysis of Korea’s new growth engines , 2010 .

[22]  Tao Han,et al.  Mapping the Structure and Evolution of Science , 2013 .

[23]  Yang Zhiping,et al.  Profiles of Technological Capabilities of the Chinese Academy of Sciences(CAS)--A Comparison of Patenting Activities of the CAS with other National Level Institutions , 2009 .

[24]  Christian Sternitzke,et al.  Visualizing patent statistics by means of social network analysis tools , 2008 .

[25]  Bernard Gress,et al.  Properties of the USPTO patent citation network: 1963-2002 , 2010 .