Modeling and simulation of the knowledge increase process in the technology innovation network

Abstract

Abstract: Based on the current studies at home and abroad in technology innovation networks, this paper examines the influence of technical innovation network density on network knowledge increase from the aspects of knowledge diffusion and knowledge innovation, and put forward a hypothesis that the network density has an inverted U-shaped relationship with knowledge increase. In order to test this hypothesis, a Multi-agent model was established, which demonstrates the process of knowledge increase in innovation network, and the NetLogo simulation platform was adopted to test the hypothesis. The results indicate that the effect of network density has the feature of duality. In other word, the network density will be disadvantageous to the knowledge increase of the innovation network when it is too high or too low. In the meantime, these results show that the inhibition of knowledge diffusion, which will then impede knowledge innovation, will appear when network density is too high and continue to increase.

Key words: network density, knowledge increase, knowledge diffusion, knowledge innovation, agent-based model and simulation

CLC Number:

Yu Xianyun, Zeng Deming, Chen Yanli, Wen Jinyan. Modeling and simulation of the knowledge increase process in the technology innovation network[J]. Science Research Management, 2013, 34(10): 35-41.

References

[1] Coleman J S. Foundations of social theory[M].Cambridge: The Belknap Press of Harvard University Press, 1990. [2] Portes A. Social Capital: its origins and applications in modern sociology[J]. Annual Review of Sociology, 1998, 24(1): 1-24. [3] Schilling M A, Phelps C C. Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation[J]. Management Science, 2007, 53(7): 1113-1126. [4] Burt R S.Structural holes: The social structure of comeptition[M].Cambridge MA: Harvard University Press, 1992. [5] Lin C H, Tseng S M. Bridging the implementation gaps in the knowledge management system for enhancing corporate performance[J]. Expert System with Applications, 2005, 22(1): 45-64. [6] Dyer J H, Nobeoka K. Creating and managing a high-Performance Knowledge-sharing network: The Toyota case[J]. Strategic Management Journal, 2000, 21(3): 345-367. [7] Kogut B. The network as knowledge: generative rules and the emergence of structure[J]. Strategic management Journal, 2000, 21(3): 405-425. [8] Gnyawali D R, Madhavan R. Cooperative networks and competitive dynamics: A structural embededness perspective[J].Academy of Management Review, 2001, 26(3): 431-445. [9] Phelps C C. A Longitudinal Study of the Influence ofAlliance Network Structure and Composition on Firm Exploratory Innovation[J]. Academy of Management Journal, 2010, 53(4): 890-913. [10] Mcevily Zaheer. Bridging ties: A source of firm heterogeneity in competitive capabilities[J]. Stragic Management Journal, 1999, 20(12): 1133-1156. [11] 钱锡红,徐万里,杨永福. 企业网络位置、间接联系与创新绩效[J]. 中国工业经济, 2010(2): 78-88. [12] Soda G, Usai A, Zaheer A. Network memory: the influence of past and current networks on performance[J].Academy of Management Journal, 2004, 47(6): 893-906. [13] Giovanna P. Enhancing the innovation performance of firm by balancing cohesiveness and bridging ties[J].Long Range Planning, 2008, 41(1): 395-419. [14] Burt R S.Bandwidth and echo: Trust information, and gossip in social networks[A]. A Casella, JE Rauch. Networks and Markets: Contributions from Economics and Sociology[C]. New York, 2001. [15] Chih-Hsing L. The effects of innovation alliance on network structure and density of cluster[J]. Expert Systems with Applications, 2011, 38(1): 299-305. [16] Gulati R., Sytch M. Does familiarity breed trust? Revisiting the antecedents of trust[J].Managerial and Decision Economics, 2008, 29(2): 165-190. [17] Dyer J H, Singh H. The relational view: Cooperative strategy and sources of inter- organizational competitive advantage[J]. Academy of Management Review, 1998, 3(4): 660-679. [18] Gulati R, Nohria N, Zaheer A.Strategic networks[J]. Strategic Management Joumal, 2000, 21(3): 203-215. [19] Kraatz M S. Learning by association? Interorganizational networks and adaptation to environmental change[J].Academy of Management Journal, 1998, 41(6): 621-643. [20] Hipkinand I, Naude P. Developing effective alliance partnerships: lessons from a case study[J].Long Range Planning, 2006, 39(1):51-69. [21] Gargiulo M, Benassi M. Trapped in your own net? Network cohesion, structural holes and the adaptation of social capital[J]. Organization Science, 2000, 11(2):183-196. [22] D. G. Green.Hierarchy, complexity and agent models, in Our Fragile World[C]. Paris, UNESCO, 2001. [23] 李宏亮.基于Agent的复杂系统分布仿真[D].长沙:国防科技大学,2001. [24] Rosanna Garcia. Uses of Agent Based Modeling in innovation—Newproduct Development Research[J].Journal of Product innovation management.2005, 22(5):380-398. [25] Kieron Meagher, Mark Rogerbs. Network density and R&D spillover[J].Journal of Economic Behavior & Organization, 2004, 53(2):237-260. [26] Sandra Phlippen. Come close and co-create: Proximities in pharmaceutical innovation networks[D].Erasmus Universiteit, 2008. [27] 李志刚,汤书昆,梁晓艳,等.基于网络结构的产业集群知识创新和扩散绩效[J].系统工程,2007,25(5):1-8. [28] Robin Cowan, Nicolas Jonard. Network structure and the diffusion of knowledge[J].Journal of Economic dynamics & Control, 2004, 28(8):1557-1575.