Post-Disaster Resource Redistribution and Cooperation Evolution Based on Two-Layer Network Evolutionary Games

In the aftermath of large-scale disasters, the scarcity of resources and the paralysis of infrastructure raise severe challenges to effective post-disaster recovery. Efficient coordination between shelters and victims plays a crucial role in building community resilience, yet the evolution of two-layer behavioral feedback between these two groups through network coupling remains insufficiently understood. Here, this study develops a two-layer network to capture the cross-layer coupling between shelters and victims. The upper layer uses a post-disaster emergency resource redistribution model within the framework of the public goods game, while the lower layer adopts a cooperative evolutionary game to describe internal victim interactions. Monte Carlo simulations on scale-free networks reveal threshold effects of incentives: moderate public goods enhancement and subsidies promote cooperation, whereas excessive incentives induce free-riding. In contrast, credible and well-executed punishment effectively suppresses defection. Targeted punishment of highly connected shelters significantly enhances cooperation under resource constraints. A comparative analysis using a network generated from the actual coordinates of Beijing shelters confirms the model’s generality and practical applicability. The findings highlight the importance of calibrated incentives, enforceable sanctions, and structural targeting in fostering robust cooperation across organizational and individual levels in post-disaster environments.

💡 Research Summary

The paper addresses the critical challenge of coordinating scarce emergency resources and fostering cooperation among shelters and victims in the immediate aftermath of large‑scale disasters. Recognizing that existing studies either focus on resource allocation optimization or on abstract cooperation mechanisms, the authors develop a novel two‑layer network model that explicitly couples organizational (shelter) behavior with individual (victim) behavior through asymmetric cross‑layer feedback.

In the upper layer, shelters are represented as nodes in a scale‑free (Barabási–Albert) network (and, for validation, a spatial network derived from real Beijing shelter locations). Each shelter i possesses a limited amount of available resources y_i and decides on a contribution proportion θ_i∈