Research On Tacit Knowledge Dissemination Model On Network View

Tacit knowledge is the core and spring of enterprises with unique characteristics which is difficult for competitors to imitate. Only the tacit knowledge in the enterprise well can make the enterprise sustain competitive advantage. Tacit knowledge is an important factor to promote the enterprise ability of knowledge appreciation and innovation, as well as a basic link to improve organization learning ability. With the development of technology, the transmission of tacit knowledge increasingly represents the complexity and dynamic. To get a better circulation and a greater economic value of tacit knowledge in the enterprise, therefore, the "Research on Tacit Knowledge Dissemination Model on Network View" is proposed in this dissertation, which can be shown as follows:1. The tacit knowledge dissemination between nodes. A model is presented for tacit knowledge transfer between the node and node based on the theory of system dynamics. The tacit knowledge dissemination is divided into four stages:preparation, spillover, absorption and conversion. Through simulation, the various factors of the transfer model are considered and their interaction relationships are studied and the results show how to improve the effectiveness of tacit knowledge transfer.2. The tacit knowledge dissemination in the network. A stochastic process model is presented for knowledge dissemination under the social networks environment. A Markov chain with four states is used to investigate the change of knowledge diffusion speed, the average level of knowledge, and the distribution of nodes with different state in the network. From the simulation experiments, we can see the factors of the social networks effect the speed of tacit knowledge disseminations. And proper selection of factors can improve the effectiveness of knowledge disseminations.3. Transmission optimization algorithm for externalization of tacit knowledge. The externalization of tacit knowledge is represented as matter-element with characteristics and value intervals based on extenics in the optimization algorithm which has advantages on calculation accuracy. A personalized recommendation according to the similarity of tacit knowledge can improve the efficiency of the tacit knowledge dissemination. 4. Risk assessment of tacit knowledge dissemination in the network. Take enterprise as the research subject, an HMM model of information entropy with multiple parameters is established to analyse and evaluate the probable risk in the process the knowledge dissemination. Evaluation results show that the state of risk in knowledge dissemination, which can be determined the most critical but the weakest parts of the enterprise and take the right measure.