Hierarchical team structure and multidimensional localization (or siloing) on networks

TL;DR

This paper introduces a layered model of organizational networks to understand how hierarchical and mesoscopic structures influence information localization and siloing, integrating complex contagion mechanisms.

Contribution

It develops a new hierarchical localization model that combines multiple known localization phenomena and explores their interactions within organizational networks.

Findings

Hierarchical localization can coexist with mesoscopic and core-periphery localization.

The model reveals how different structural features influence information spread and siloing.

It opens avenues for optimizing organizational structures to control information flow.

Abstract

Knowledge silos emerge when structural properties of organizational interaction networks limit the diffusion of information. These structural barriers are known to take many forms at different scales - hubs in otherwise sparse organisations, large dense teams, or global core-periphery structure - but we lack an understanding of how these different structures interact. Here we bridge the gap between the mathematical literature on localization of spreading dynamics and the more applied literature on knowledge silos in organizational interaction networks. To do so, we introduce a new model that considers a layered structure of teams to unveil a new form of hierarchical localization (i.e., the localization of information at the top or center of an organization) and study its interplay with known phenomena of mesoscopic localization (i.e., the localization of information in large groups), $k$-core localization (i.e., around denser $k$-cores) and hub localization (i.e., around high degree stars). We also include a complex contagion mechanism by considering a general infection kernel which can depend on hierarchical level (influence), degree (popularity), infectious neighbors (social reinforcement) or team size (importance). This general model allows us to study the multifaceted phenomenon of information siloing in complex organizational interaction networks and opens the door to new optimization problems to promote or hinder the emergence of different localization regimes.