The Research On Tacit Knowledge Measurement Method Based On Bayesian Network

In the context of big data explosion,the era of knowledge economy has arrived.At the same time,the knowledge and knowledge related management theory are more and more valuedable by the community,especially the core competitiveness of enterprises.The modern enterprise maintains the continuous learning ability and the innovation ability through the knowledge,thus maintains the competitive advantage in the intense market competition.Tacit knowledge is the source of innovation and competitiveness of enterprises,so the reasonable expression,transformation,sharing and measurement of it will bring intangible economic benefits to enterprises.Therefor,this paper introduced to the study of Bayesion Network measure to estimate tacit knowledge management problems of tacit knowledge,to form a new,more objective,scientific and feasible method to measure the tacit knowledge.The main work of this paper is as follows:Firstly,TKIM and cognitive map(CM)based on the tacit knowledge representation methods were analiezed,demonstrating advanced measure of tacit knowledge model based on Bayesianian network.TKIM information acquisition and the measure is too dependent on the questionnaire,and easily affected by the subjective intention of the test,the method represented by the questionnaire method failed to eliminate the subjective effects from testing and expert empowerment.The CM method is a more advanced qualitative and quantitative method proposed in recent years,but it still depends on the weight given by experts.For the weaknesses of the above methods,Based on Bayesian Network(BN)of the tacit knowledge measure model is proposed,combining prior knowledge to construct the network topology and parameter training algorithm by experts,weaken the system distortion,which showed a more scientific and objective advantages.Secondly,the process of using BN method to measure the individual tacit knowledge was describeed in detail.Construction of tacit knowledge measure model based on the method of BN include: set and analysis of specific situations,Bayes' s construction of network topology,network node parameter learning Bayes probability,probability inference,sorting and interpretation of the BN,the validity of the model test and the model of learning to update the six steps.In this paper,based on the original BN probability reasoning,the probability ranking and probability interpretation were add,and the probability value of probability inference is defined as the measure of tacit knowledge.Thirdly,the key problems of tacit knowledge measurement method based on Bayesian Network were studyed deeply.R & D personnel as an example,consider the impact of emotion and health status of the individual test results,exploring 69 direct accesses to the information of activity index results,and then construct the BN topology of objective facts.This paper explores the principles and steps of the task design of the tacit knowledge measurement model,and explains the design purpose of the test scenario,sub task,main task and task system in detail.This paper analyzes the relationship between tacit knowledge of the individual and the organization and the feasibility of using the model to measure tacit knowledge of the organization,and makes an exploration on the construction of the BN topological structure and task design of the tacit knowledge of the organization.Finally,taking L-company's R & D department as an example,using the MATLAB platform programming and operation,the paper makes an empirical analysis of tacit knowledge measurement model based on Bayesian Network.The results show that the validity of the model is 75%~80%,which provides reliable data support for management decision.The example shows that tacit knowledge measurement model based on Bayesian Network is feasible to measure tacit knowledge objectively.