Research on the Efficiency Evaluation of Cross-Organizational Knowledge Synergy in Industry University Cooperation Based on BP Neural Network Algorithm

• Published in: Mathematical problems in engineering Vol. 2022; pp. 1 - 8
• Main Author: Jing, Li
• Format: Journal Article
• Language: English
• Published: New York Hindawi 08.06.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Back propagation networks; Collaboration; Collective action; Competitive advantage; Cooperation; Decision making; Efficiency; Employees; Evaluation; Field investigations; Intellectual property; Knowledge management; R&D; Regression models; Research & development
• ISSN: 1024-123X; 1026-7077; 1563-5147; 1563-5147
• DOI: 10.1155/2022/1873862

The difference of decision-making knowledge among members is conducive to the successful realization of group cooperative production. In the actual production, if the different knowledge environments between organizations can cooperate and penetrate each other, the common knowledge of groups can be formed, which is a key step to successfully solve the social and economic problems of public resources. The final efficiency of cross-organizational knowledge collaboration is the key to measure the success or failure of collaboration. Because the cross-organizational knowledge synergy efficiency of industry university cooperation is the result of the cross-influence of many factors, the general linear regression model is difficult to describe the relationship between these influencing factors and knowledge synergy efficiency. Based on the analysis of the importance of cross-organizational knowledge sharing efficiency evaluation of industry university cooperation, this study constructs the efficiency evaluation index system from different angles. At the same time, based on the field investigation of the index system, BP network model is established to effectively evaluate the collaborative efficiency.