Measurement and prediction of the relationships among the patent cooperation network, knowledge network and transfer network of the energy storage industry in China

The commercialization process of energy storage patents affects the development of the energy storage industry. Clarifying the relationships between the characteristics of the applicants and patent transfer can facilitate technology transfer. In this study, China's energy storage patent data from 2009 to 2021 were divided by the rolling period. Based on this, the patent cooperation network, knowledge network, and transfer network were constructed via social network analysis. The analysis reveals the following. First, the number of industry -university-research institutions that jointly apply for patents is increasing, and the knowledge field is also expanding. Cooperation and transfer activities are more frequent in the eastern developed regions of China. Second, by using grey relational analysis theory, it was found that the degree centrality, closeness centrality, and clustering coefficient of the cooperation network are closely related to the transfer network. Compared with the cooperation network, the energy storage knowledge network has a more significant relationship with the transfer network. The knowledge elements stock of patent transferor and transferee is more relevant to patent transfer activity than the patent stock. This also proves that the knowledge and cooperation networks are decoupled. Additionally, patent applicants for energy storage patents should focus not only on their past average locations to maintain the competitive advantage, but also on future location trends to seize development opportunities. Finally, the proposed recommendations can help applicants facilitate patent transfer activities in the energy storage industry by adjusting the location of the network.