A four-factor model of knowledge agglomeration

This study develops a comprehensive four-factor model to analyze the factors that influence knowledge agglomeration. To test the model empirically, we use a dataset from firms in China’s digital industry and employ the structural equation model and RM-DEMATEL method to determine the relationship between these factors and their impact on knowledge agglomeration. We find that effectiveness, coupling, and talent synergy have significant positive impact on knowledge agglomeration. Instead, knowledge concentration has an inverted U-shaped relationship with knowledge agglomeration. In addition, knowledge concentration moderates the relationship between knowledge effectiveness, coupling, talent synergy, and knowledge agglomeration. Based on these findings, we construct a multi-dimensional indicator system that allows us to assess more extensively the roles of those factors, we find that knowledge concentration is a fundamental factor in this system. The density and speed of concentration and knowledge causality also play important roles. Our findings offer a theoretical framework for firms in developing their knowledge management strategies.