Objective Amid rapid urbanization and the increasing frequency of extreme climate events, urban systems are facing escalating systemic risks. As the fundamental unit of urban governance, community resilience — the capacity to withstand, adapt to, and recover from risks — has become a key concern in public administration. However, disparities in resource allocation, spatial power structures, and uneven risk exposure have made old and dilapidated communities — characterized by aging facilities, complex demographic structures, and weak infrastructure — concentrated zones of urban risk inequality. In China, there are over 200,000 such communities, home to more than 100 million residents, which are highly vulnerable to natural disasters, public safety incidents, and public health emergencies. These vulnerabilities generate a negative feedback loop of “vulnerable group concentration – declining resilience – cyclical risk accumulation” . Therefore, optimizing spatial resource allocation and addressing both external shocks and internal risks are essential to exploring resilience governance pathways that enhance the ability of diverse groups in old and dilapidated communities to resist, adapt, and recover rapidly, thereby strengthening grassroots governance and advancing resilient city construction.
Methods This research adopts a triangulated methodology integrating comparative analysis, inductive – deductive reasoning, and systematic literature review to clarify the conceptual foundations and mechanisms of risk inequality, identifying four core dimensions of community resilience governance, namely the spatial, social, institutional, and technological dimensions. Focusing on old and dilapidated communities, the research uses risk inequality as an analytical lens to systematically deconstruct structural barriers to resilience governance, revealing mechanisms of risk differentiation and institutional root causes. Drawing on social vulnerability theory, spatial justice theory, and resilience theory, the research develops an analytical framework centered on three pillars: stakeholder identification, resource allocation optimization, and adaptive governance responsiveness. Guided by spatial justice principles, the framework promotes multi-level, cross-dimensional interventions — including infrastructure renewal, governance structure reform, technological upgrading, and social capital rebuilding — to dismantle structural constraints of risk inequality, promote equitable risk distribution, and strengthen sustainable adaptive capacity.
Results The research reveals that risk inequality is neither accidental nor monocausal, but stems from the long-entangled interplay of multifaceted social, economic, and environmental factors, which collectively undermine the systemic resilience and sustainable development of old and dilapidated communities. Amid escalating uncertainties and increasingly frequent risk events, the diversification of risk sources and compounded community vulnerabilities synergistically amplify hazard impacts. Old and dilapidated communities — characterized by physical infrastructure decay, institutional inertia, eroded social capital, and technological marginalization — have become epicenters of risk inequality, where vulnerable groups face systemic disadvantages in disaster exposure levels, access to emergency resources, and adaptive response capacity. To address these challenges, resilience governance for old and dilapidated communities must focus on integrating internal/external resources, revitalizing institutional mechanisms, and holistically enhancing residents’ risk-coping capacities, thereby strengthening communities’ ability to withstand shocks while maintaining operational stability and sustainable trajectories. Centering on vulnerable subpopulations and spatial demands for disaster preparedness, the research embeds spatial justice principles into resilience governance frameworks. Key strategies include: precision identification of vulnerability profiles through data-driven diagnostics, optimized allocation of disaster-response spatial resources, dynamic simulation of emergency protocols, and construction of multi-stakeholder collaborative networks. These strategies disrupt the traditional “one-size-fits-all” governance paradigm, replacing rigid frameworks with adaptive, equity-driven interventions that reconcile structural risk disparities and foster inclusive resilience. To address the heterogeneous vulnerabilities of community subgroups, this research proposes differentiated governance strategies across four resilience dimensions: spatial, social, institutional, and technological dimensions. First, spatial integration of normal and emergency functions should be prioritized to establish a tiered public space system for risk management. Second, adaptive capacities must be strengthened by fostering endogenous community mutual-aid networks grounded in multi-stakeholder collaboration. Third, resource provision should be optimized through flexible risk prevention policies and dynamic compensation mechanisms. Fourth, technological compatibility requires enhancement via the development of inclusive smart governance tools for community resilience.
Conclusion The resilience governance of old and dilapidated communities should incorporate the concept of spatial justice, emphasizing the precise identification of vulnerability demands, optimization of disaster-response spatial configurations, dynamic simulation of operational workflows, and establishment of multi-stakeholder collaborative networks. This approach aims to dismantle the traditional “one-size-fits-all” governance mindset, advancing resilient community theory from a “system preservation” paradigm to one centered on “social equity”. Looking forward, resilience governance frameworks need refinement to address distinct challenges in traditional courtyard communities, state-owned unit housing, and modern residential complexes. This involves defining risk typologies, deciphering causal mechanisms, evaluating resilience components, and formulating tailored mitigation strategies. Besides, quantitative methodologies should be advanced to monitor risk fluctuations, measure vulnerability thresholds, conduct stress tests, and analyze spatiotemporal risk distribution patterns among vulnerable groups. Integration of cutting-edge tools — such as geographic information system (GIS), big data analytics, system dynamics, and social network analysis — can enable behavior-based simulations to innovate early warning systems and resilience governance models. This dual-track advancement of theory and technology will catalyze inclusive, adaptive, and sustainable transformations in old and dilapidated urban communities.
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