Inertia mechanisms in networks and knowledge diffusion in team inertia networks

Knowledge diffusion is a critical driver of innovation, and team-based diffusion has increasingly become the dominant mode of knowledge diffusion. However, its efficiency is strongly shaped by inertia mechanisms embedded within teams. To capture this phenomenon, this paper first formalizes inertia mechanisms in networks, distinguishing between temporal inertia and spatial inertia. Building on this foundation, we propose a team inertia network model that integrates both forms of inertia and specify its evolutionary dynamics. Through extensive simulation experiments, we examine how temporal and spatial inertia jointly affect knowledge diffusion. The results indicate that moderate spatial inertia can enhance the average knowledge level of a team, whereas excessive or insufficient spatial inertia reduces diffusion efficiency. The impact of temporal inertia depends on communication density and knowledge dimensionality, where tighter connectivity enables members to gain more balanced benefits, reflected in a more stable Gini coefficient and more stable negative spatial autocorrelation. This work contributes a novel modeling framework for analyzing team knowledge evolution and provides practical insights for designing team structures and communication strategies that leverage inertia mechanisms to improve knowledge sharing, innovation capacity, and collaborative efficiency.