Dynamics of post-disaster recovery in behavior-dependent business networks

The recovery of businesses after disasters is a critical component of community economic resilience; however, little is known about the network dynamics and spillover effects that shape recovery speed. This study investigates how post-disaster business recovery is influenced by the network diffusion process in pre-disaster business dependency networks formed by visitation behaviors among business points of interest (POIs). Using a network diffusion model, we simulated the recovery progression across businesses in the Louisiana Gulf Coast following Hurricane Ida in 2021 and validated the results with empirical data. The analysis explores four key components: (1) the presence of network diffusion underlying recovery; (2) variations in how recovery speed depends on inter-business relationships; (3) the identification of recovery multiplier business types whose recovery accelerates the overall network’s recovery; and (4) differences in recovery multipliers between high- and low- income areas. Results revealed that business recovery is governed by diffusion dynamics in behavior-based dependency networks, with recovery speeds closely linked to pre-disaster visitation patterns. Retail and service businesses were identified as recovery multipliers, significantly accelerating regional recovery and enhancing economic resilience. Additionally, the composition of recovery multipliers varies by income level, highlighting the need for tailored recovery strategies. These findings deepen our understanding of the complex network mechanisms shaping economic resilience and provide important insights for designing effective post-disaster recovery policies.