4. Conclusion, limitations and directions for future research
On the basis of complex network theory and knowledge management theory, the influence of network density on the knowledge increase. of supply chain network was analyzed. Agent-based model and simulation were used to simulate and analyze the process. Our results indicate that the increase of network density is beneficial to knowledge innovation and knowledge diffusion when the entire structure of a whole supply chain network is relatively sparse or dense. At that time, the growth of network density substantially promotes the knowledge increase of the supply chain network. Our findings also show that knowledge growth of the supply chain network will decreases when the network density is in a certain range . It means that the effect of network density on the knowledge increase of supply chain network is nonlinear. A network density that is high or low is conductive to knowledge increase but not the middle value. A cubic relationship between network density and knowledge increase of a supply chain network exists. Furthermore, the most appropriate network densities for knowledge innovation in a supply chain network are equal to those for knowledge increase.
The findings presented here have some suggestions for enterprises. First of all, in order to improve the performance of innovation, the density of supply chain network should continue to increase. Secondly, enterprises in the supply chain network have taken measures, including the harsh management system and technical structure arrangement to mitigate the risk of knowledge leakage. Our research suggests that these actions shouldn’t hinder the sharing and flow of knowledge in supply chain network. Finally, there are still some deficiencies in the process of internal innovation in supply chain network, so it is important for enterprises to strengthen cooperation with the external partners in the field of innovation.
