Research On Tacit Knowledge Representation And Reconstruction Among Innovation Team From The Perspective Of Knowledge Ecology

In the era of knowledge economy,innovation teams play a major role in knowledge innovation.As the core productivity of the innovation team,tacit knowledge has become the driving force and source of team innovation.Its effective representation and full utilization are the key to the team's competitive advantage and core competence.However,because tacit knowledge itself is highly personalized and ambiguous,it is difficult to achieve its representation and transmission under conventional means,which makes it more difficult for the knowledge subject to acquire and reuse it.Knowledge management requires innovative teams to make full use of knowledge resources and maximize their value.It depends on the coordinated development of team's knowledge subject,knowledge resources,knowledge creation environment and information technology.Knowledge ecology can provide new theoretical support for coordinating the complex relationships between the various elements of the innovation team.Based on this,in order to realize the effective representation and efficient reuse of the tacit knowledge of the innovation team,promote the "harmonious development" between the team knowledge,environment,technology and people,and improve the level of innovation ability of the team.From the perspective of knowledge ecology,this paper adopts the extenics method and case-based reasoning technology to study the tacit knowledge representation and reconstruction of the innovation team.This paper first reviews the theoretical basis of knowledge ecology,and then makes a comprehensive review of the research status of innovation teams and tacit knowledge research at home and abroad.Secondly,based on the knowledge ecology theory,the constituent elements of the innovation team knowledge ecosystem are analyzed in detail.Combined with the tacit knowledge transfer process,the process model of tacit knowledge representation and reconstruction of the innovation team is constructed and the influencing factors of tacit knowledge representation and reconstruction are analyzed,which provide a theoretical basis for the latent innovation team's tacit knowledge representation and reconstruction research.Thirdly,according to the characteristics of innovation team and the tacit knowledge connotation,the tacit knowledge of the innovation team is defined.Through the induction of the classification and representation of tacit knowledge of the innovation team,a questionnaire survey is adopted.According to the reliability and validity test,the characteristic attributes of the tacit knowledge of the innovation team are selected.And the extension matter-element model is used to structure the tacit knowledge of the innovation team.Then,the research framework of tacit knowledge reconstruction based on the basic idea of case-based reasoning is designed.The case database is constructed by using case representation.Combined with the ambiguity of tacit knowledge,based on the expert semantic variables,the weight of the case feature attributes is calculated by using the triangular fuzzy number solution fuzzy method.The similarity calculation method of different case attributes is given,and the relative order entropy is defined.The global similarity is designed by using the nearest neighbor method to solve the case retrieval algorithm.At the same time,a case self-correction method based on structural correction is proposed.The case library is clustered and re-searched again.The search results complete the case knowledge reconstruction.Finally,the application of case-based reasoning method in the tacit knowledge reconstruction of the innovation team is verified by a concrete example.The case-based reasoning method can effectively improve the reuse rate of tacit knowledge of innovative teams and is suitable for solving the problem of tacit knowledge reconstruction.