What factors contribute to the formation of interorganizational collaboration networks: A longitudinal study in response to COVID-19 emergency

Abstract

In the realm of addressing large-scale emergencies, interorganizational collaboration emerges as a crucial strategy for effectively mitigating crises. However, the existence of institutional and procedural disparities poses significant challenges in establishing collaborative networks among diverse organizations. Moreover, the determinants influencing cooperative formations exhibit heterogeneity across distinct network structures. This research employs proximity theory and the Exponential Random Graph Model (ERGM) to comprehensively examine the dynamic evolution of interorganizational collaboration networks. Our primary objective is to investigate the effects of institutional proximity, organizational proximity, geographical proximity and social proximity on the formation of interorganizational collaboration networks. Textual data was meticulously collected from the Wisers database and official websites. The findings underscore the pivotal roles of institutional and organizational proximity in fostering interorganizational collaboration networks, while the impact of geographical proximity is relatively insignificant. Additionally, we delve into the driving factors that influence the formation of diverse structural networks. Social proximity emerges as a significant catalyst for horizontal collaborative networks but impedes the establishment of vertical collaborative relationships. Furthermore, we partition the entire emergency response process into six stages to explore the dynamic evolution characteristics of these networks. The results reveal an overall decentralized structure with a tendency toward clustering in the collaborative network. These findings hold substantial significance as they elucidate the influential factors driving the formation of diverse collaborative networks in a dynamic context. Therefore, this research bears implications for policymakers and practitioners aiming to enhance their emergency response capabilities with optimal efficiency.