Research On Knowledge Transfer And The Structure Of Network Based On Instant Messenger

During knowledge era, knowledge has been replacing thetraditional scarce resources to be the most important resource toimprove the development of enterprise and individual. Butknowledge is restore in human’s Mental Model, it’s hard to makepeople to share their knowledge for considering it may hurt one’sown interests, so knowledge management brought to the forefront.The main content of knowledge management include knowledgeacquire, spread, innovation, especially knowledge transfer is theprecondition to other segment. Most researchers indicate How toimprove the speed of knowledge dissemination and stimulateknowledge innovation. During the early study period time, scholarsfocus on the interaction between knowledge mediator and receiver.With the introduction of SNA, researchers uncovering the mainfactors that influence the knowledge transfer. Along with the development of Internet and Mobile Terminal, instant massage toolbecome more and more important for knowledge transfer, whichbreak through the restriction of space and geographical position,provides individual the technical supports to expand social ties andcooperation.Nevertheless, there has limited literatures research on thetopology structure of knowledge transferring of IM that lead peoplehave difficult to handle the features of knowledge spreading inInternet. For this reason, the study is carried out from the practiceand emulation aspects. In respect of practice, through datacollection formed a knowledge transfer network based on IM, whichinclude 568 nodes. Grounded on complex network theory, proclaimthe network structure, analyze the transfer path of differentknowledge and the sensitive degree of different individuals as wellas network centrality、degree distribution、clustering coefficient、block、APL et. al.In respect of emulation, according to thecharacteristic of real world individual’s interaction is neitherrandom nor static, furthermore during the unit time radio of contactis heterogeneous. So the relationship of people is dynamic. Thestudy is combined the evolutionary game theory, use software toemulate knowledge transfer in dynamic condition. After these two steps, the study draws some conclusions:individual ability and self monitoring can influence networkcentrality, self monitoring and the same taste lead trust betweenboth sides.Finally, these factors impact the willingness and effect ofknowledge spread. By means of calculate the nodes and edges of IMknowledge transfer network, proved it is a sparse network withsmall-world character and exists the subgroups.After classifyknowledge found that the health care knowledge (HEAL-K in short)has a higher sensitive degree than other knowledge categories. Soresearch HEAL-K in detail. By symmetrize the structure of actors,the study analysis clusters、build block model and deliberate nodesposition. Although distinguish the centrality node can keep thenetwork stable and connectivity, the recognition of status of nodestransfer can improve the effective of knowledge spreading. Withemulation of knowledge transfer process in dynamic network foundalter ties can promote diffusion and strong those relationshipbetween nodes. The study confirms the evolutional game theoreticmodels and illustrates the important role of fluid condition that canencourage large-scare group knowledge collaboration.In short, the study try to know well of the law of knowledgetransfer based on IM, push forward knowledge generation、diffusion、 innovation. By means of recognize centrality nodes and individualstatus of knowledge transfer to enhance the effect，so as to supportmembers of society interchange knowledge online.