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| Identifying R&D Teams and Innovations with Patent Collaboration Networks |
Guan Peng1,2( ),Wang Yuefen2,Fu Zhu3,Jin Jialin2 |
1School of Economics and Law, Chaohu University, Hefei 238024, China
2School of Management, Tianjin Normal University, Tianjin 300387, China
3School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
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Abstract [Objective] This paper tries to ide.pngy technology R&D teams based on the patent holders’ collaboration networks, aiming to analyze factors influencing these teams’ innovations. [Methods] First, we ide.pngied the core R&D personnel and their team members. Then, we used the number of patents as the quantity index of innovation outputs, and the number of patent citations and claims as the quality index of innovation outputs. Finally, we used the negative binomial regression model to analyze the impacts of team characteristics on their innovations. [Results] We conducted an empirical study in the field of speech recognition technology and the proposed algorithm effectively ide.pngied 566 evolutionary sequences of R&D teams, including 1 827 R&D teams in each snapshot, with an average size of 16.670. These teams form a small world sub-network with an average clustering coefficient of 0.856 and an average shortest path length of 1.646. [Limitations] The proposed algorithm could not effectively find technology R&D teams from the fields with few well-known experts. The sample size also needs to be expanded. [Conclusions] The team size and average shortest path length of team network have significant positive impacts on the quantity and quality of innovations. The persistence, stability and network density of these teams have significant negative effects on the quantity and quality of innovations. The team clustering coefficient has significant negative effects on the quantity of innovations, but no significant impacts on the quality of innovations.
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Received: 30 July 2021
Published: 21 June 2022
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| Fund:National Social Science Fund of China(16DZA224);Social Science Fund of Anhui Province, China(AHSKQ2020D23);Foundation for Distinguished Young Talents in Higher Education of Anhui Province, China(gxyqZD2019066) |
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Corresponding Authors:
Guan Peng
E-mail: guanpeng1983@163.com
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