Using the large database of patent, the purpose of this paper is to structure a technology convergence network using various patent network analysis for integrating different results according to network characteristics.
The patent co-class analysis and the patent citation analysis are applied to discover core safety fields and technology, respectively. In specific, three types of network analysis, which are centrality analysis, association rule mining analysis and brokerage network analysis, are applied to measure the individual, synergy and group intensity.
The core safety fields derived from three types of network analysis used by different nature of data algorithms are compared with each other to understand distinctive meaning of cores of patent class such as medical safety, working safety and vehicle safety, differentiating network structure. Also, to be specific, the authors find the detailed technology contained in the core patent class using patent citation network analysis.
The results provide meaningful implications to various stakeholders in organization: safety management, safety engineering and safety policy. The multiple patent network enables safety manager to identify core safety convergence fields and safety engineers to develop new safety technology. Also, in the view of technology convergence, the strategy of safety policy can be expanded to collaboration and open innovation.
This is the initial study on applying various network analysis algorithms based on patent data (class and citation) for safety management. Through comparison among network analysis techniques, the different results are identified and the collective decision making on finding core of safety technology convergence is supported. The decision maker can obtain the various perspectives of tracing technology convergence.
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A5A8027985).
Jeon, J. and Suh, Y. (2019), "Multiple patent network analysis for identifying safety technology convergence", Data Technologies and Applications, Vol. 53 No. 3, pp. 269-285. https://doi.org/10.1108/DTA-09-2018-0077
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