Abstract：Exploring the factors that affect the tie dissolution of innovation cooperation in IC industry can realize the early warning of tie changes and improve the stability of innovation cooperation network.. Drawing on the embeddedness theory, this study constructs a model for analyzing the factors influencing the dissolution of ties within the innovation cooperation network of the integrated circuit industry, incorporating the dimensions of relational heterogeneity and relational embeddedness. Machine learning algorithms such as GBDT (Gradient Boosting Decision Tree) and RF (Random Forest) are employed to identify the key factors contributing to ties dissolution. The research findings indicate that as the scale of the integrated circuit industry's innovation cooperation network expands, ties dissolution becomes more apparent. The intensity of ties is identified as the fundamental factor influencing relationship dissolution. Regional heterogeneity and capability heterogeneity are identified as critical factors affecting tie dissolution. When assessing the risk of partnership dissolution, it is necessary to comprehensively consider tie intensity, regional heterogeneity, capability heterogeneity, and constraint coefficients.
刘晓燕, 赵曦雨, 单晓红, 谢桂生. 集成电路产业创新合作关系瓦解因素探析[J]. 复杂系统与复杂性科学, 2025, 22(4): 29-36.
LIU Xiaoyan, ZHAO Xiyu, SHAN Xiaohong, XIE Guisheng. Exploring the Factors of Tie Dissolution of Innovation Cooperation in Integrated Circuit Industry[J]. Complex Systems and Complexity Science, 2025, 22(4): 29-36.
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