How does the hypernetwork model incorporate human agency to enhance urban resilience and QOUL?

The hypernetwork model embeds human agency by forming hyperedges that link built-environment assets, urban performance indicators, and citizen-generated human-need nodes, with public perceptions and feedback acting as inputs that shape infrastructure priorities. This feedback loop identifies and resolves postdisaster needs, which elevates QOUL, and improved QOUL in turn empowers residents to actively shape resilience strategies.

In the proposed hypernetwork model, human agency is incorporated through a multilayer structure of three subnetworks: Built Environment, Urban Performance/Public Perception, and Human Needs. Hyperedges connect heterogeneous nodes across these layers, such as a resident need node linked to drainage and transport assets, representing how citizen perceptions and needs are tied to objective infrastructure. Human agency appears in the closed-loop feedback from residents, who act as "human sensors" by generating service requests or complaints during disturbances. The model uses this citizen-generated data as continuous input, dynamically updating the network and capturing how resident perceptions shape infrastructure priorities through feedback loops. The results show that this embedded agency lets the model identify critical postdisaster needs and infrastructure weaknesses, enabling targeted interventions that reduce the mismatch between subjective needs and objective built conditions. Reducing that mismatch raises QOUL. A symbiotic relationship is described: human agency embedded in the network of nodes helps identify and resolve postdisaster needs and elevate QOUL, while enhanced QOUL empowers agency by fostering environments where residents actively shape resilience strategies. Thus the hypernetwork treats infrastructure as a dynamic enabler of human agency rather than a passive artifact, making resilience human-centric.