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Research On Innovation Performance Evaluation Of Supply Chain Node Enterprises Based On Knowledge Sharing

Posted on:2023-10-18Degree:MasterType:Thesis
Country:ChinaCandidate:Q Q FanFull Text:PDF
GTID:2568307103479004Subject:Library and file management
Abstract/Summary:PDF Full Text Request
Innovation is the first driving force for development,and seeking innovation is seeking for the future.With the emergence of the knowledge economy,knowledge sharing is gradually emerging in the supply chain management process.How to promote the effective sharing of knowledge resources in the supply chain,enhance the core competitiveness of node enterprises,and enhance the innovation performance of node enterprises is a common concern of the competitive intelligence academic and business circles.This paper innovatively examines the innovation performance of nodal enterprises based on the perspective of supply chain knowledge sharing,which provides a new perspective for the measurement and evaluation of enterprise innovation performance and provides an extended study on supply chain knowledge sharing,which is of great relevance to the promotion of enterprise innovation abilities.By combing the relevant literature,we find that knowledge sharing has a positive impact on innovation performance.Based on this research,this paper evaluates the innovation performance of the node enterprises brought by the knowledge sharing activities among the supply chain enterprises.Firstly,integrating knowledge sharing principle and innovation theory and applying literature research method,the original assessment indicators system was established in five dimensions: knowledge management system,the willingness to share knowledge,the level of knowledge stock,the ability to share knowledge and the effect of knowledge sharing.The investigation questions were distributed and obtained 213 valid questionnaires.After the reliability and validity analysis,6 secondary indicators were eliminated and the evaluation index system was finally determined to consist of 5 primary indicators and18 secondary indicators.Secondly,based on the determined evaluation index system,the study hypotheses are proposed and the structuring equation model of innovation performance based on knowledge sharing is constructed.The weights of each index are calculated by using the standardized path coefficients of the higher-order structural equation model to determine the degree of influence of each evaluation index on the innovation performance of knowledge sharing among supply chain enterprises,and a fuzzy comprehensive evaluation model is constructed on this basis.Finally,the core node enterprises of the automobile supply chain are selected as samples for empirical analysis,and the evaluation index system and evaluation model are used to comprehensively evaluate the innovation performance of the node enterprises brought by the supply chain knowledge sharing.The results of the data-based analysis show that the knowledge management system,willingness to share knowledge,knowledge stock level,knowledge sharing capability and knowledge sharing effectiveness all have a positive relationship on innovation performance.The study concluded that all five factors were influential in innovation performance,with willingness to share knowledge having the strongest influence on innovation performance and the level of knowledge inventory having the weakest influence on innovation performance.The empirical analysis has validated the rationality and practicability of the constructed knowledge sharing-based innovation performance evaluation index system and evaluation model.According to the research findings,this paper makes recommendations to improve the innovation performance of nodal enterprises in four areas: strengthening the willingness of enterprises to share knowledge,strengthening the construction of knowledge management systems,fostering a culture of knowledge sharing and enhancing the amount of knowledge resources in enterprises.
Keywords/Search Tags:supply chain management, knowledge sharing, innovation performance, structural equation modeling, fuzzy synthetic evaluation
PDF Full Text Request
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