Behavior-based Organizational Knowledge Transfer Analysis Method

In recent years,knowledge has become a key resource for organizations to obtain economic advantages,and knowledge management has gradually become an essential core business in modern enterprise management.Knowledge transfer,as an important issue of knowledge management,is the basis for enterprises to obtain competitive advantages.The effect of knowledge transfer directly affects the organization's survival and sustainable development.As an organizational behavior,knowledge transfer is necessarily influenced by human psychology and behavior,and its purpose is to influence the effect of knowledge transfer by affecting or improving the behavior of knowledge subjects,and ultimately improve the performance level of the organization.This paper looks at the process of knowledge transfer from the perspective of behavior,focuses on the interaction of knowledge subjects in knowledge transfer,and the amount of knowledge transfer under interactive behavior.It proposes an analysis method to solve two measurement problems in knowledge transfer,one is knowledge transfer.Mining patterns in behavior,and second,behavioral patterns of knowledge measurement methods.This paper first excavates the characteristics of the organization's knowledge transfer behavior,collects the behavior data of the organization's interaction based on the characteristics of the behavior existing in the specific context,and uses the K-means algorithm to cluster the activity-associated individuals into different organizational groups.Principal Component Analysis(PCA)extracts the behavioral patterns of knowledge transfer.Secondly,due to the characteristics of continuous and changing behaviors,a real-time and meticulous knowledge measurement method is proposed for the knowledge subject under the behavior pattern,and information such as words and languages learned or expressed in interaction is collected as the knowledge text,and the key is selected using the TF-IDF algorithm.Knowledge points,and through the trained Word2 Vec algorithm,construct a vector representation of knowledge stock,and then use multidimensional scaling(MDS)to map the set of knowledge points to a twodimensional knowledge map.The semantic relations are preserved between vectors.And reduce complexity.After knowledge vectorization,the knowledge transfer amount and knowledge distance of the knowledge subject are further calculated,and the threshold of knowledge distance is corrected.Finally,this method is used to calculate the example of the passenger space,and the three interaction patterns of the workspace are obtained.They are the daily work mode,the summary report mode and the short-term project mode,and the knowledge stock of the individual under the behavior mode is constructed to calculate the knowledge distance.,And get the correspondence between behavioral patterns and knowledge transfer and management inspiration.This paper solves the problem of continuously,dynamically and objectively extracting behavior and knowledge features in the process of knowledge transfer.Behavior pattern mining helps to explore the law of knowledge transfer behavior in specific contexts.Individual knowledge measurement methods more precisely and dynamically measure the knowledge stock of the subject.This will facilitate the establishment of models of individual behavior patterns and knowledge transfer in the later period,and advances the research work of the Task Force on how “behavior affects the effect of knowledge transfer” and provides guidance for enterprises to enhance the efficiency of knowledge transfer.