Exploring Homophily: How it Influences the Clustering and Segregation of Organizational Communities in Emergency Collaborative Networks

Abstract

While previous studies have primarily examined how homophily shapes dyadic collaboration in emergency response, its influence on macronetwork structures remains underexplored. Drawing on organizational homophily theory, this study investigates the emergency collaborative network (ECN) formed during the “7.20” extreme rainstorm event in Zhengzhou City. By employing exponential random graph models, community detection, and bias-corrected bootstrap analysis, we examine how attribute, location, and institutional homophily shape organizational clustering and network segregation within China’s centralized and hierarchical emergency management system. The findings reveal that (1) the ECN comprises 22 tightly connected organizational communities; (2) all three forms of homophily significantly promote interorganizational collaboration; and (3) institutional homophily exerts the strongest effect, with affiliation homophily reinforcing clustering and jurisdiction level homophily intensifying segregation. These results highlight the structural variations in homophily effects under institutional constraints and offer a refined lens for studying ECNs. This study suggests enhancing network resilience by leveraging affiliation cohesion and establishing flattened, cross-level collaboration mechanisms.

Keywords

Emergency collaborative network / Exponential random graph models / Homophily / Network segregation / Organizational clustering / Zhengzhou “7.20” extreme rainstorm

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