Impact of network density on the efficiency of innovation networks: An agent-based simulation study

被引:16
作者
Hua, Lei [1 ,2 ]
Yang, Zhong [2 ]
Shao, Jiyou [2 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Management Sci & Engn, Nanjing, Jiangsu, Peoples R China
[2] Nanjing Univ, Sch Business, Nanjing, Jiangsu, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
INTERORGANIZATIONAL COLLABORATION; KNOWLEDGE; PERFORMANCE; EXPLORATION; EVOLUTION; DYNAMICS; EXPLOITATION; DIFFUSION; TECHNOLOGIES; EMBEDDEDNESS;
D O I
10.1371/journal.pone.0270087
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Network density is an important attribute that affects the efficiency of innovation networks. However, the understanding of how network density affects the innovation efficiency of innovation networks is still unclear and even controversial. This paper uses a multiagent simulation method to study this problem. First, an innovation simulation model is established to describe the generation process of innovations in the context of network innovation, and a classical random network model is used to generate a test set of structures with different network densities. Then, the innovation model is run on the test set of networks to obtain the innovation efficiency of the structures with different network densities. The result shows that for explorative innovation, high network density is more conducive to improving innovation efficiency, and for exploitative innovation, low network density is more conducive to improving innovation efficiency. However, when network density is small enough to destroy network connectivity, it will lead to a large risk of innovation failure. Finally, the reasons for the results are further analyzed, and the theoretical and practical significance of the conclusions are discussed.
引用
收藏
页数:22
相关论文
共 57 条
[1]   Managerial foresight and attempted rent appropriation: Insider trading on knowledge of imminent breakthroughs [J].
Ahuja, G ;
Coff, RW ;
Lee, PM .
STRATEGIC MANAGEMENT JOURNAL, 2005, 26 (09) :791-808
[2]   Collaboration networks, structural holes, and innovation: A longitudinal study [J].
Ahuja, G .
ADMINISTRATIVE SCIENCE QUARTERLY, 2000, 45 (03) :425-455
[3]   Emergence of scaling in random networks [J].
Barabási, AL ;
Albert, R .
SCIENCE, 1999, 286 (5439) :509-512
[4]  
Baum JAC, 2000, STRATEGIC MANAGE J, V21, P267, DOI 10.1002/(SICI)1097-0266(200003)21:3<267::AID-SMJ89>3.0.CO
[5]  
2-8
[6]   Network-Independent Partner Selection and the Evolution of Innovation Networks [J].
Baum, Joel A. C. ;
Cowan, Robin ;
Jonard, Nicolas .
MANAGEMENT SCIENCE, 2010, 56 (11) :2094-2110
[7]   Exploitation, exploration, and process management: The productivity dilemma revisited [J].
Benner, MJ ;
Tushman, ML .
ACADEMY OF MANAGEMENT REVIEW, 2003, 28 (02) :238-256
[8]   Agent-based modeling: Methods and techniques for simulating human systems [J].
Bonabeau, E .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2002, 99 :7280-7287
[9]  
Borgatti SP, 1999, SOC NETWORKS, V21, P375
[10]  
Burt R.S., 2003, Networks in the knowledge economy, P13