Based on the real-world knowledge innovation management characteristics of enterprises, in this paper a novel bilateral matching (BM) decision-making method for knowledge innovation management considering the matching willingness of bilateral enterprises is proposed. The method uses interval-valued intuitionistic fuzzy sets (IvIFSs) as its basis. First, using the IvIFS preferences of the bilateral enterprises, their matching willingness is calculated according to the TOPSIS method. Then, the BM model is constructed according to the IvIFS preference, the matching willingness and the BM matrix of the bilateral enterprises. According to the normalized interval-valued score function (NIvSF) and score function (SF), the BM model is transformed into a BM model with SFs. Considering the fairness of each agent of each side, the BM model with SFs is transformed into a two-objective BM model. Furthermore, a novel optimization algorithm is introduced to solve the two-objective model, and then the optimal BM scheme is obtained. Finally, the effectiveness and feasibility of the proposed method are verified by a knowledge innovation management case study. The key findings of the proposed work are as follows: (1) The proposed method establishes the BM model with IvIFSs and matching willingness; (2) a new algorithm for the BM model is developed; and (3) the obtained BM scheme using the proposed method reflects the matching willingness of the agents. The proposed method can be extended to other BM problems in knowledge innovation management operating under other intuitionistic fuzzy environments and can be applied to other decision-making problems in enterprise knowledge innovation management.

基于企业现实世界知识创新管理特点，提出一种考虑双边企业匹配意愿的知识创新管理双边匹配（BM）决策方法。该方法使用区间值直觉模糊集（IvIFSs）作为其基础。首先，利用双边企业的IvIFS偏好，按照TOPSIS方法计算其匹配意愿。然后，根据IvIFS偏好、匹配意愿和双边企业的BM矩阵构建BM模型。根据归一化区间值评分函数（NIvSF）和评分函数（SF），将BM模型转化为具有SFs的BM模型。考虑到每一方的每个代理的公平性，将带有SFs的BM模型转换为两目标BM模型。此外，还引入了一种新的优化算法来求解两目标模型，进而得到最优的BM方案。最后，通过知识创新管理案例研究验证了所提方法的有效性和可行性。所提出工作的主要发现如下：（1）所提出的方法建立了具有 IvIFS 和匹配意愿的 BM 模型；(2) 开发了一种新的BM模型算法；(3) 使用该方法得到的BM方案反映了智能体的匹配意愿。