The partner selection modes for knowledge-based innovation networks: a multi-agent simulation

With the advent of the knowledge economy, technological innovation has become more and more complex. Firms in innovation system need to cooperate with others to upgrade their knowledge level and market competitiveness. Proper partner selection can increase the efficiency of the entire innovation system. Different partner selection mechanism has a significant impact on the efficiency of knowledge transfer for the enterprises and innovation system. In this study, a multiagent simulation is conducted to explore the effects of four different partner selection modes on knowledge transfer of innovation network: random selection mode, mode of selection based on space, mode of selection based on knowledge capital and mode of selection based on complementary knowledge. The results indicate that: in a period time, (1)the spatial selection mode limits the scope of partner selection and reduces the knowledge transfer path;(2)mode of selection based on the knowledge capital enables the large firms to have more cooperation opportunities;(3)complementary knowledge based selection mode improves the knowledge transfer efficiency of the system.