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Developments of Tech-Innovation Network for Patent Cooperation: Case Study of Speech Recognition in China |
Guan Peng1,2,Wang Yuefen2(),Jin Jialin2,Fu Zhu3 |
1School of Economics and Law, Chaohu University, Hefei 238000, China 2School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094, China; 3School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
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Abstract [Objective] This paper examines the evolution of tech-innovation network from the perspective of patent cooperation. [Methods] First, we proposed a dynamic framework to analyze the patent cooperation network. Then, we conducted evolutionary analysis of the network’s topological structure based on network size, clustering, component analysis, degree distribution, and small-world theory. Third, we analyzed the centrality and structure holes of core network members. [Results] We evaluated the performance of our framework with an empirical study on speech recognition, which also investigated the impacts of network evolution on innovations. [Limitations] More research is needed to investigate the proposed model’s performance in other fields, as well as the influence of network structure on individual company’s innovations. [Conclusions] The domestic cooperative network for speech recognition patents, which has evolved from a fragmented network to the multi-center small-world one, plays an important role in innovation. The three core members of this network are companies, universities and research institutes, following the rule of “rich get richer”. This paper also discusses technology innovation management issues from the perspectives of cooperation and regional development.
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Received: 19 April 2020
Published: 05 February 2021
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Fund:The work is supported by the National Social Science Fund of China Grant No(16DZA224);the National Natural Science Foundation of China Grant No(71904043);the Key Project of Humanities and Social Sciences Research in Colleges and Universities in Anhui Province Grant No(SK2019A0550) |
Corresponding Authors:
Wang Yuefen
E-mail: yuefen163@163.com
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