Towards Resilient and Sustainable Post-Disaster Temporary Housing: A Multidimensional Review

Despite growing scholarly attention, post-disaster temporary housing continues to fail—not from technical deficiencies, but from fragmented decision-making that isolates technical, social, governance, and environmental dimensions. Central to this failure is a paradox: although socio-cultural factors remain the least-studied dimension in existing literature, case-based evidence indicates they are a decisive determinant of long-term effectiveness, as technically sound interventions repeatedly fail when local social dynamics are overlooked. This study addresses this gap by framing temporary housing as a socio-technical system and proposing a layered, context-sensitive decision framework.

Following PRISMA 2020 guidelines, a systematic review was conducted across Google Scholar, Scopus, and ScienceDirect (chosen for combined grey-literature and peer-reviewed coverage) using the string ("temporary housing" OR "post-disaster shelter" OR "emergency housing") AND ("design" OR "resilience" OR "sustainability"). From 180 records, duplicates and irrelevant results were screened out, yielding 40 peer-reviewed studies (2010–2025); coding reliability was confirmed via independent double-coding (80% agreement). Studies were analyzed across four dimensions: physical-temporal, socio-cultural, governance/institutional, and technological-environmental.

Findings indicate housing failures are primarily systemic, driven by misalignments between rapid delivery models, institutional frameworks, and community needs. Governance and institutional coordination was the most-studied dimension (16/40); socio-cultural factors were least-studied (4/40) despite their critical role in outcomes. Drawing on four cases in the reviewed literature—Kobe, Japan; Puerto Rico; China; and Fukushima, Japan—the six-layer framework was applied retrospectively, each case illustrating failure at a distinct layer, showing that technically sound interventions fail when local social contexts are insufficiently integrated.

In response, this study proposes a Context-Sensitive Layered Decision Framework organizing post-disaster housing decisions across six interdependent layers—initial assessment, emerging challenge identification, resource and capacity assessment, governance coordination, community needs extraction, and integrated decision-making—supported by a continuous feedback loop, and identifies data-driven and AI-assisted approaches as a promising direction for future research in sustainable temporary housing systems.