Simulation of Knowledge Transfer Based on Complex Network

Hailian Liu, Shizhong Ai

Abstract: Knowledge rigidities in firms make them stick to existing knowledge and impede the inflow of new external knowledge. This paper explores knowledge transfer process among agents from a firms knowledge rigidity perspective, which helps investigate the factors inducing knowledge lock-in. To conduct a simulation of knowledge transfer process in network with scale-free characteristics, state variables, such as networks degree distribution, firms knowledge rigidity and so on, are defined. Knowledge transfer rule is also designed. The simulation data and analysis results show that the firms knowledge rigidities influence the knowledge transfer in networks significantly. Controlling firms knowledge rigidities and building diversified learning and cooperation relationships in different channels can expand the scope of the knowledge transfer and improve its effectiveness.

Keywords: absorptive ability, disseminative ability, knowledge rigidity, complex network, learning curve