Research On Customer Tacit Knowledge Acquisition And Refinement Under The Background Of Knowledge Economy

In the era of knowledge economy,knowledge has become the core source of corporate value creation,and knowledge management is gradually becoming the focus of corporate research.Compared with explicit knowledge,tacit knowledge can create core competitiveness for enterprises.In knowledge management,enterprises need to integrate,analyze,and apply a large amount of dynamic customer data collected to dig out the hidden customer tacit knowledge.Customers are the foundation for the existence and development of enterprises.How to achieve the acquisition and refinement of customer tacit knowledge has become the focus of industry research.In view of this,this article focuses on the acquisition and refinement of customer tacit knowledge so that companies can accurately grasp customer needs and their evolution trends,so as to provide customers with targeted products and services,and enhance customer satisfaction and cultivation Loyalty,and then maintain lasting competitiveness.First,the paper introduces the research background and significance of customer tacit knowledge acquisition and refinement,summarizes the research status of customer tacit knowledge and customer knowledge management,and finds the entry point of this article through analysis of existing problems,and proposes the technical route and ideas of this article.Furthermore,the definition,classification and characteristics of customer tacit knowledge,as well as the acquisition and refinement methods of customer tacit knowledge are summarized and analyzed,and the theories of rough set,BP neural network and genetic algorithm are explained.Then,the thesis analyzes and determines the knowledge source of customer tacit knowledge acquisition,and analyzes and defines customer knowledge value;meanwhile,the measurement method of customer knowledge value is discussed through the customer knowledge value matrix.The process dependence of customer tacit knowledge acquisition is analyzed,and three methods of customer tacitknowledge acquisition are proposed based on it,and the strategy and method of source data pre-processing are discussed using rough set ideas.Then,Based on the BP neural network,the paper constructs an initial model of customer tacit knowledge refinement,and analyzes the selection of model parameters and data normalization.On this basis,the deficiencies of the BP neural network and the ideas for improvement are discussed.Based on GA theory,the aforementioned initial model is supplemented and optimized,and technical details such as coding selection,population initialization,fitness function,number of iterations,and specific genetic operations are analyzed in detail.Finally,In the experimental analysis part,the paper will use MATLAB software to simulate and analyze the collected data,verify the model effect,and provide corresponding optimization suggestions for enterprises.At the end of the article,we summarize and research prospects for the acquisition and refinement of customer tacit knowledge,and put forward the research deficiencies in this article based on the actual situation,as well as the problems that need attention in future research and further research directions.