知识创造行为对知识网络演化的影响——以知识贬值和知识活性为参数

Effect of Knowledge Creation Behavior on Knowledge Network Evolution:Using Knowledge Devaluation and Knowledge Emancipator as Parameters

根据网络的无标度特性建立了基于知识创造行为的组织知识网络演化模型,选用Matlab软件进行数理仿真。研究结果表明:不同的演化时间对网络结构能够产生影响;相比于随机网络和普通网络,小世界网络是个体进行自主研发和知识流动的最优选择;知识贬值率越高,网络知识创造的收益越小,越能激发个体的知识交流欲望,知识变化幅度越大;知识活性程度越高,网络的平均知识存量越少,个体对现有知识的保护意识越强,对自主研发能够起到促进作用,但不利于个体间的知识流动。

This paper uses the scale-free property of networks to construct an organizational network evolution model based on knowledge creation behavior, and carries out mathematical simulation with Matlab. The results show that, different length of evolution time could affect the network＇s structure; compared with random network and ordinary network, small-world network is an optimal choice for individuals to conduct independent research and development, as well as knowledge flow; if knowledge devaluation rate is much higher, then returns of knowledge creation in network will be less, and individual＇s desire for knowledge communicating will be inspired, knowledge＇s amplitude of variation will be larger; if knowledge emancipator is much higher, then the average knowledge stock will be less, individual＇s desire for knowledge protection will be stronger, this may encourage the independent research and development, but runs against individual＇s knowledge flows. This study enriches the research findings on combining knowledge management theory with complex network, provides beneficial reference for solving actual problems on knowledge devaluation and knowledge emancipator.