Empirical Study On Knowledge Flow Model In Innovative Network Based On Rules

In the age of knowledge-based economy, continuing accessing to innovativeknowledge is an important foundation for enterprises to improve innovationcapability and core competitiveness. In order to improve innovation capability andcore competitiveness, the alliance between enterprises form knowledge alliance. Inrecent years, more and more scholars have began to study knowledge alliance, therules of knowledge flows and the influence to the network, which has achieved someresults. In this paper, the innovation network formed by enterprises in the knowledgealliance is chosen as study object, technique knowledge vector is utilized to representthe level of technique knowledge, angle from the physics technique knowledgepotential energy, the rules of knowledge flows between enterprises in the innovationnetwork is analyzed and studied, and a dynamic simulation model is established tosimulate the flow of technique knowledge in the innovation network.The contribution of this paper are as follows:(1)The innovation network and technique knowledge structure. Innovationnetwork is the carrier of researching for the rules of knowledge flows. In theinnovation network, the enterprises in the knowledge alliance are nodes, the alliancerelations are edges. In this paper, the generation rules are studied, at the same time,some sociological indicators are adopted to examine the characteristics of the entirenetwork, and give some relative conclusions. The level of enterprises knowledge isconsisted of two parts, which is represented by technique knowledge vector. Thelevel of enterprises knowledge is the foundation of quantitative knowledge flowstudy. At present, there is no standard in the partition of technique field, therefore,the partition method in technique field is proposed, which determines the patenttechnique field according to the international classification of patents, and thenbuilds the enterprise technique knowledge vector.(2) The knowledge flow model based on rules. In most of the traditional knowledge flow models, cellular automation is adopted as the simulation tools toexamine personal knowledge dissemination. Random grid or network constructed bysome certain probability according to sociological theory is selected in most of themodels, and the flowing scope is limited to a certain grid adjacent to nodes. In theprocess of knowledge, fixed coefficient function are usually adopted to update bothof the stocks of knowledge, or only two states (knowledge and un-knowledge) areused to express knowledge dissemination. For these deficiencies, a knowledge flowmodel of innovation network based on rules is proposed in this paper, in which, fromthe physics technical knowledge energy angle, complex network theory is added,.and the cellular automaton ideological rules and LBM flow theory integrated into it,the entire knowledge flow process is divided into two stage: migration and collision,in different stage, different formulas are adopted to update the enterprise technicalknowledge potential energy. According to experiments and results, the experimentalresults are significantly better than fixed coefficient function of knowledgeexchange.