激励作用的SNS企业知识社区中知识转移网络模型

Effects of Incentive Mechanism to Knowledge Transfer Network Model in SNS Oriented Enterprise Knowledge Community

基于激励理论,结合仿真实验,研究激励水平作为环境主导因素对SNS企业知识社区中知识更新速率、知识转移能力以及对网络子图出现频率的影响,探讨有利于促进企业知识社区中知识转移的激励水平,为企业制定有效的激励机制以及知识社区管理提供决策依据。在相关文献综述的基础上,首先,深入分析了建模的理论基础,包括激励理论和网络理论;激励理论的实质是通过对变量值的调整,使得委托人与代理人各自的期望效用最大化。接着,在提出SNS(Social network services,SNS)企业知识社区中知识转移网络形成演化建模前提条件的基础上,建立激励作用的知识转移网络形成与演化模型。第三,应用Netlogo对模型进行实验仿真,研究激励水平对SNS企业知识社区中知识转移网络形成与演化的影响,并对仿真结果进行分析。最后对全文加以总结,并提出进一步研究方向。

The purpose of the paper is to explore the effects of incentive level to knowledge update rate,knowledge transfer ability and emergency frequency of sub-graph.Knowledge transfer network formulation and evolution model are constructed in knowledge community and simulation experiment is carried out.The decision making support for knowledge community management can be provided.On basis of review of relevant references,firstly,theory bases for modeling are analyzed,including incentive theory and network theory.The essence of incentive theory is to maximize expected benefits of both by variable adjustment.Secondly,based on assumptions knowledge transfer network formulation and evolution model is constructed.Thirdly,the algorithm of the model is put forward and simulated by Netlogo,the results of the simulation are analyzed.In the end,conclusions are made and further research directions are proposed.