Knowledge Leakage Risk Management Of Supply Chain Enterprises Based On WSR Methodology

Because of the interest conflicts,the opportunism and the moral hazard under the context of knowledge sharing among enterprises in supply chain,the partner enterprise may disclose the knowledge shared by the leading enterprise to the competitors through methods of transferring or saling.Knowledge leakage behaviors and effects of supply chain enterprises not only affect the value of shared knowledge,increase the loss of knowledge sender,but also leading to the collapse of supply chain.How to scientifically identify,accurately evaluate and effectively manage the knowledge leakage risk of supply chain enterprises is a particularly important and urgent research topic.Based on the methodology of WSR,this dissertation applied supply chain management theory,knowledge management theory,information economics,and mathematical modeling and empirical research method to research the knowledge leakage risk management of supply chain enterprises.The main research contents of this paper are as follows:Firstly,based on the WSR methodology,this dissertation probed into the influence factors of supply chain enterprise knowledge leakage risk,analyzed the comprehensive structure of the risk factors through the formulation of supply chain knowledge leakage risk scale from manufacturing enterprises.With 361 survey data collected from a questionnaire as the foundation,this dissertation constructed the structural equation model(SEM)risk model direct and indirect paths of supply chain knowledge leakage with AMOS21.0 software,empirically analyzed the path and effect of different risk factors of supply chain knowledge leakage on risk consequences,and revealed the deep-seated mechanism.Secondly,evaluation models are built based on the knowledge leakage risk factor index system of supply chain enterprises identified above from the perspective of WSR methodology.The above survey data of 361 enterprises are divided into training data group(320)and the testing data group(41).Through the appropriate neural network learning algorithm,this dissertation build six sub-models and one total BP neural network model for supply chain knowledge leakage risk assessment.In addition,in consideration of the hierarchy of knowledge leakage risk influence factors and the importance of expert opinions,four typical supply chain enterprises were selected from testing data group,and an expert scoring method was adopted to construct a knowledge leakage risk measurement model based on "triangular fuzzy number-entropy weight-TOPSIS-AHP" methodology,making up for the one-sidedness defect of the single evaluation method.Thirdly,from the view of WSR methodology,the principal-agent theory of information economics is used to establish a principal-agent risk contract governance model.This dissertation constructed a contract governance model of knowledge leakage risk in the vertical knowledge sharing activities between supply chain core enterprise and two suppliers,which are in three different relationships of competition,cooperation and independent.This dissertation also simulates the payment contract of knowledge leakage risk governance in the vertical knowledge sharing process of the leading enterprise of supply chain,and analyzes how the leading enterprise of supply chain establishes a reasonable incentive mechanism and contract arrangement under different risk preferences and information asymmetry.Finally,this dissertation proposes a governance model to knowledge leakage risk for supply chain enterprises.Through the identification of influencing factors,analysis of action path of risk factors,establishment of knowledge leakage risk assessment model and empirical analysis,the PDCA cycle model and specific measures of knowledge leakage risk of supply chain enterprises are proposed.This thesis is based on the practice of supply chain enterprise management,which can not only make up for the deficiency of theoretical research,but also improve the application value of research results,and help supply chain enterprises more accurately and effectively identify,evaluate and control knowledge leakage risks.