The optimization decision-making analysis for partners in innovation based on SVM-TOPSIS

This study establishes a two-stage selection indexing system based on partners in innovation and a decision-making model on the basis of “primary selection, fine selection, and optimization,” in accordance with the features of different stages of collaborative innovation on the basis of support vector machine(SVM) theories and intuitionistic fuzzy sets. In the primary selection stage, SVM was used to reduce the selection range of partners in innovation as per the cooperation indexing system of the primary selection. In the stage of fine selection and optimization, the intuitionistic fuzzy set TOPSIS method was adopted to determine the final partners in collaborative innovation, and the characteristics of innovation partners in the process of collaborative innovation such as multi-attribute and group decision-making were completely considered. Finally, the feasibility of the decision-making model was depicted by the case analysis of selecting a partner for a pharmaceutical enterprise. This provided innovative decision-making insights and methods for the optimized selection of partners in a collaborative innovation.