Simulation study on Tissue Knowledge Sharing based on Small-world Network Model

By means of small-world network theory and methods, knowledge sharing network model is proposed to study the network structure of the organization knowledge sharing. With consideration of knowledge sharing, knowledge learning and knowledge innovation, this paper puts forward a calculation method about knowledge level when they take knowledge sharing. The WS small world network model was used to Simulation Analysis which studies the impact to knowledge sharing trends from four indicators: the average shortest path network L (p), clustering coefficient C (p), a random re-connection probability P, and degree distribution K. With comparative analysis, we find that high clustering coefficients and short path can increase the exchange of knowledge associated with the node and enhance sharing efficiency when proper degree of freedom knowledge difference degree.