기업 간 네트워크에서 배태성과 지식 자산과의 관계

The purpose of this study is to investigate the relationship between a firm’s embeddedness and knowledge base. In particular, it covers both the structural and relational dimensions of embeddedness and distinguishes a firm’s knowledge base with the breadth and depth of knowledge. In order to clarify the relationship among them, an agent-based model was established based on the organizational learning curve and simulations were conducted. The analysis of simulation data reveals that there is a positive relationship between a firm’s structural dimension of embeddedness and its breadth of knowledge, while a negative relationship with its depth of knowledge. The larger the degree centrality, the betweenness centrality, the number of structural holes, the number of balanced triads, the broader its knowledge and the less its depth of knowledge. Regarding the relational dimension of embeddedness, the larger the proportion of weak links and trust level, the broader its knowledge and the less its depth of knowledge base. The larger the proportion of strong links, the deeper its knowledge and the narrower its breadth. As for network type, a random network has the largest breadth and the lowest depth of knowledge base on average, while a small world network has the narrowest breadth and the largest depth of knowledge base on average. As the density of the network increases, the breadth of knowledge increases and the depth decreases on average. The greater the number of knowledge domains that a firm has, the wider and shallower the knowledge. The faster the industry is in depreciation of knowledge, the greater the breadth of knowledge and lessened the depth.