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隐性知识作为影响企业核心竞争能力的关键要素之一,目前在各创新主体间传递效率较低,其主要原因在于隐性知识供需主体间供需信息不匹配。基于此,为了提高隐性知识利用效率,文章着眼于浅隐性知识视角,结合其易表达特征,利用可拓物元模型表达出浅隐性知识的同时,融合案例推理方法的基本原理,设计构造了浅隐性知识的供需匹配框架。并在此基础上,利用模糊案例推理算法和信息熵,计算出浅隐性知识在供需主体之间的匹配度。结果表明:该算法通过可以实现浅隐性知识供需主体知识源的快速对接,提高浅隐性知识供需匹配效率。
Tacit knowledge, as one of the key elements that affect the core competitiveness of enterprises, is currently less efficient among innovation entities. The main reason is that tacit knowledge does not match the supply and demand information. Based on this, in order to improve the utilization efficiency of tacit knowledge, the article focuses on the perspective of shallow tacit knowledge, combines its easy-to-express features, expresses the shallow tacit knowledge by using the extension matter-element model, at the same time, Constructed a shallow supply of tacit knowledge matching framework. Based on this, the fuzzy case reasoning algorithm and information entropy are used to calculate the matching degree of shallow tacit knowledge between supply and demand parties. The result shows that this algorithm can improve the efficiency of supply and demand of shallow tacit knowledge through the rapid docking which can realize the knowledge source of supply and demand of shallow tacit knowledge.