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
[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.
Thamhain H J. Managing Innovative R&D Teams[J]. R&D Management, 2003, 33(3): 297-311.
[2]
Huang M H, Dong H R, Chen D Z. Globalization of Collaborative Creativity Through Cross-Border Patent Activities[J]. Journal of Informetrics, 2012, 6(2): 226-236.
doi: 10.1016/j.joi.2011.10.003
[3]
Funk R J. Making the Most of Where You Are: Geography, Networks, and Innovation in Organizations[J]. Academy of Management Journal, 2014, 57(1): 193-222.
doi: 10.5465/amj.2012.0585
( Xie Xuemei, Liu Siyu. Impact Mechanism of Collaborative Innovation Modes on Collaborative Effect and Innovation Performance[J]. Journal of Management Science, 2015, 28(2): 27-39.)
[5]
Fleming L, King C, Juda A I. Small Worlds and Regional Innovation[J]. Organization Science, 2007, 18(6): 938-954.
doi: 10.1287/orsc.1070.0289
( Gu Qinxuan, Wang Lihong. Influence Process of Social Capital on Innovative Performance in R&D Teams: Integration of the Team’s Psychological Safety and Learning Behaviors[J]. Journal of Management Sciences in China, 2015, 18(5): 68-78.)
( Xu Jianzhong, Du Xian. R&D Team Innovation Openness, Absorptive Capacity and Team Innovation Performance: An Empirical Analysis of Equipment Manufacturing Enterprises in Bohai Rim Region[J]. Modernization of Management, 2016, 36(5): 51-54.)
( He Xinwen, Kang Shanshan, Wang Yan. Research on R&D Team Heterogeneity’s Influence on Innovative Performance[J]. Scie.pngic Management Research, 2020, 38(3): 27-34.)
[9]
Chen M H, Chang Y C, Hung S C. Social Capital and Creativity in R&D Project Teams[J]. R&D Management, 2008, 38(1): 21-34.
( Li Gang, Liu Mingfei, Wu Qing, et al. A Research of Characters and Ide.pngications of Roles Among Research Groups Based on the Bow-Tie Model[J]. Library and Information Service, 2017, 61(5): 87-94.)
( Yu Houqiang, Bai Kuan, Zou Bentao, et al. Ide.pngication and Extraction of Research Team in the A.pngicial Intelligence Field[J]. Library and Information Service, 2020, 64(20): 4-13.)
( Zou Bentao, Wang Yuefen, Yu Houqiang. Study of the Evolution Pattern of Prolific Research Teams in the A.pngicial Intelligence Field[J]. Library and Information Service, 2020, 64(20): 23-33.)
( Wang Yuefen, Yang Xue, Yu Houqiang, et al. The Collaboration Pattern and Comparative Analysis of Research Teams in the A.pngicial Intelligence Field[J]. Library and Information Service, 2020, 64(20): 14-22.)
[18]
Berger-Wolf T Y, Saia J. A Framework for Analysis of Dynamic Social Networks[C]// Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2006: 523-528.
[19]
Takaffoli M, Sangi F, Fagnan J, et al. Community Evolution Mining in Dynamic Social Networks[J]. Procedia-Social and Behavioral Sciences, 2011, 22: 49-58.
doi: 10.1016/j.sbspro.2011.07.055
[20]
Žalik K R. Evolution Algorithm for Community Detection in Social Networks Using Node Centrality[A]//Intelligent Methods and Big Data in Industrial Applications[M]. Cham: Springer, 2019: 73-87.
[21]
Wuchty S, Jones B F, Uzzi B. The Increasing Dominance of Teams in Production of Knowledge[J]. Science, 2007, 316(5827):1036-1039.
doi: 10.1126/science.1136099
[22]
Milojević S. Modes of Collaboration in Modern Science-Beyond Power Laws and Preferential Attachment[J]. Journal of the American Society for Information Science and Technology, 2010, 61(7): 1410-1423.
doi: 10.1002/asi.21331
[23]
Milojević S. Principles of Scie.pngic Research Team Formation and Evolution[J]. PNAS, 2014, 111(11): 3984-3989.
doi: 10.1073/pnas.1309723111
pmid: 24591626
[24]
Levi D, Slem C. Team Work in Research and Development Organizations: The Characteristics of Successful Teams[J]. International Journal of Industrial Ergonomics, 1995, 16(1): 29-42.
doi: 10.1016/0169-8141(94)00076-F
[25]
Bain P G, Mann L, Pirola-Merlo A. The Innovation Imperative: The Relationships Between Team Climate, Innovation, and Performance in Research and Development Teams[J]. Small Group Research, 2001, 32(1): 55-73.
doi: 10.1177/104649640103200103
[26]
Reilly R R, Lynn G S, Aronson Z H. The Role of Personality in New Product Development Team Performance[J]. Journal of Engineering and Technology Management, 2002, 19(1):39-58.
doi: 10.1016/S0923-4748(01)00045-5
[27]
Takagi S, Toyama R. On Growth of Network and Centrality’s Change Analysis of Co-Inventors Network in Enterprise[C]// Proceedings of World Summit on Knowledge Society. 2008: 422-427.
[28]
Clauset A, Newman M E J, Moore C. Finding Community Structure in Very Large Networks[J]. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 2004, 70(6 Pt 2): 066111.
( Chen Zifeng, Guan Jiancheng. Impact of International Patent Collaboration and Citation on Innovation Performance[J]. Science Research Management, 2014, 35(3): 35-42.)
[30]
Shi Y, Guan J C. Small-World Network Effects on Innovation: Evidences from Nanotechnology Patenting[J]. Journal of Nanoparticle Research, 2016, 18(11): 329.
doi: 10.1007/s11051-016-3637-1
[31]
Tong X S, Frame J D. Measuring National Technological Performance with Patent Claims Data[J]. Research Policy, 1994, 23(2):133-141.
doi: 10.1016/0048-7333(94)90050-7
[32]
van Zeebroeck N, van Pottelsberghe de la Potterie B. Filing Strategies and Patent Value[J]. Economics of Innovation and New Technology, 2011, 20(6): 539-561.
doi: 10.1080/10438591003668646
[33]
Pritychenko B. Fractional Authorship in Nuclear Physics[J]. Scientometrics, 2016, 106(1): 461-468.
doi: 10.1007/s11192-015-1766-4
[34]
Guan J C, Zuo K R, Chen K H, et al. Does Country-Level R&D Efficiency Benefit from the Collaboration Network Structure?[J]. Research Policy, 2016, 45(4): 770-784.
doi: 10.1016/j.respol.2016.01.003
[35]
何晓群. 应用回归分析: R语言版[M]. 北京: 电子工业出版社, 2017: 156-158.
[35]
( He Xiaoqun. Applied Regression Analysis: R Language Edition[M]. Beijing: Publishing House of Electronics Industry, 2017: 156-158.)
[36]
Jackson S E. The Consequences of Diversity in Multi-Disciplinary Work Team[A]//Handbook of Work Psychology[M]. Chichester, UK: Wiley, 1996: 53-76.
[37]
Katz R, Allen T J. Investigating the not Invented Here (NIH) Syndrome: A Look at the Performance, Tenure, and Communication Patterns of 50 R&D Project Groups[J]. R&D Management, 1982, 12(1): 7-20.
[38]
Burt R S. The Network Structure of Social Capital[J]. Research in Organizational Behavior, 2000, 22: 345-423.
doi: 10.1016/S0191-3085(00)22009-1
[39]
Chen Y Y, Jaw Y L. How do Business Groups’ Small World Networks Effect Diversification, Innovation, and Internationalization?[J]. Asia Pacific Journal of Management, 2014, 31(4): 1019-1044.
doi: 10.1007/s10490-014-9385-9
( Guan Peng, Wang Yuefen, Huang Qin, et al. Research on the Impact of Regional Innovation Cooperation Network on Technological Innovation Performance: Based on the Yangtze River Delta[J]. Journal of Library and Information Science in Agriculture, 2021, 33(6): 40-53.)