企业机会主义行为对知识扩散最优网络结构的影响研究
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摘要
作为知识交互主体的企业,其不同行为必将对知识交互过程和扩散网络结构产生不同影响。据此,将企业机会主义行为嵌入到知识交互过程中来拓展现有模型。仿真结果表明,当企业无机会主义行为时,小世界网络最佳。当企业机会主义行为程度增加,最优结构趋向高随机度网络,且企业对不同类别知识表现出异质偏好时更为显著。联盟管理者可根据企业机会主义行为程度控制网络结构构建来提升知识扩散效率。
It is of great significance to explore the key factors that influence the network structure of knowledge diffusion and their effect mechanism. As the main actors involved in knowledge interaction,the different behaviors of firms are meant to exert some important influences on the process of knowledge interaction and the network structure of knowledge diffusion.Accordingly,in this paper,the firm's opportunistic behavior is embedded into the process of knowledge interaction to expand the existing model. The simulation results show that the small world network is optimal when firms have no opportunistic behavior. However,when the degree of opportunistic behavior increases,the optimal diffusion network structure tends to be highly random,especially when firms exhibit heterogeneous preferences for different types of knowledge,the evolution process will be more intense than that under homogeneous preferences. The policy-makers of firm alliance can enhance their knowledge diffusion efficiency by choosing different network structures according to the degree of firms' opportunistic behavior.
It is of great significance to explore the key factors that influence the network structure of knowledge diffusion and their effect mechanism. As the main actors involved in knowledge interaction,the different behaviors of firms are meant to exert some important influences on the process of knowledge interaction and the network structure of knowledge diffusion.Accordingly,in this paper,the firm's opportunistic behavior is embedded into the process of knowledge interaction to expand the existing model. The simulation results show that the small world network is optimal when firms have no opportunistic behavior. However,when the degree of opportunistic behavior increases,the optimal diffusion network structure tends to be highly random,especially when firms exhibit heterogeneous preferences for different types of knowledge,the evolution process will be more intense than that under homogeneous preferences. The policy-makers of firm alliance can enhance their knowledge diffusion efficiency by choosing different network structures according to the degree of firms' opportunistic behavior.
引文
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[19]GIRARD Y,HETT F,SCHUNK D. How individual characteristics shape the structure of social networks[J]. Journal of Economic Behavior&Organization,2015,115:197-216.
[20]WATTS D J,STROGATZ S H. Collective dynamics of ‘smallworld’networks[J]. Nature,1998,393(6684):440-442.
[2]NONAKA I. The knowledge creating company[J]. Harvard Business Review,1991,69(6):96-104.
[3]MUELLER M,BOGNER K,BUCHMANN T,et al. The effect of structural disparities on knowledge diffusion in networks:an agentbased simulation model[J]. Journal of Economic Interaction and Coordination,2017,12(3):613-634.
[4]BAUM J A,COWAN R,JONARD N. Network-independent partner selection and the evolution of innovation networks[J]. Management Science,2010,56(11):2094-2110.
[5]COWAN R,JONARD N. Structural holes,innovation and the distribution of ideas[J]. Journal of Economic Interaction and Coordination,2007,2(2):93-110.
[6]FILIERI R,MCNALLY R C,ODWYER M,et al. Structural social capital evolution and knowledge transfer:evidence from an Irish pharmaceutical network[J]. Industrial Marketing Management,2014,43(3):429-440.
[7]VAN-EGERAAT C,CURRAN D. Social networks and actual knowledge flow in the Irish biotech industry[J]. European Planning Studies,2014,22(6):1109-1126.
[8]HUNG C L. Social networks,technology ties,and gatekeeper functionality:implications for the performance management of R&D projects[J]. Research Policy,2017,46(1):305-315.
[9]唐厚兴.社会网络结构对企业间知识共享影响研究综述[J].情报科学,2017,35(6):164-170.
[10]MORONE P,TAYLOR R. Knowledge diffusion dynamics and network properties of face-to-face interactions[J]. Journal of Evolutionary Economics,2004,14(3):327-351.
[11]GRANOVETTER M S. The strength of weak ties[J]. American Journal of Sociology,1973,78(6):1360-1380.
[12]BURT R S. Structural holes:the social structure of competition[M].Cambridge:Harvard University Press,1992.
[13]ZHENG X,ZHAO Y. The impact of alliance network structure on firm innovation capability:an empirical study of ten high-tech industries in China[J]. Journal of Science and Technology Policy in China,2013,4(1):4-19.
[14]COWAN R,JONARD N. Network structure and the diffusion of knowledge[J]. Journal of Economics Dynamics and Control,2004,28(8):1557-1575.
[15]COWAN R,JONARD N. Network architecture,barter exchange and the diffusion of ideas[J]. International Journal of Agricultural Resources,Governance and Ecology,2007,6(2):165-178.
[16]MORONE A,MORONE P,TAYLOR R. A laboratory experiment of knowledge diffusion dynamics[M]//UWE C,FRANCO M. Innovation,industrial dynamics and structural transformation. Berlin:Springer-Verlag,2007:283-302.
[17]LIU B S,MADHAVAN R,SUDHARSHAN D. DiffuNET:the impact of network structure on diffusion of innovation[J]. European Journal of Innovation Management,2005,8(2):240-262.
[18]COINTET J P,ROTH C. How realistic should knowledge diffusion models be?[J]. Journal of Artificial Societies and Social Simulation,2007,10(3):Article_ID 5.
[19]GIRARD Y,HETT F,SCHUNK D. How individual characteristics shape the structure of social networks[J]. Journal of Economic Behavior&Organization,2015,115:197-216.
[20]WATTS D J,STROGATZ S H. Collective dynamics of ‘smallworld’networks[J]. Nature,1998,393(6684):440-442.