Multi-Agent Based Simulation of Knowledge Propagation in Organizations

Abstract

In this study, we propose an agent model based on SECI model by Nonaka for simulating knowledge propagation in organizations. In this model, complexity of knowledge is expressed as bit-tag, and worker-agent and knowledge manager agent are introduced. Some parametric studies is performed for bit-tag length, internalization rates and communication pattern of worker-agent, and evaluate acquirement of knowledge to verify the present simulation model. Furthermore, scenario simulation is implemented with respect to employment periods of worker-agent and the effectiveness of multi-agent model is shown from qualitative evaluation of knowledge variation corresponding to joining and leaving organization.