<![CDATA[Prioritizing post-disaster actions requires balancing multiple, often conflicting criteria. To consolidate scattered evidence, this study reviews decision prioritization using Multi-Criteria Decision-Making (MCDM) in post-disaster management through a PRISMA-guided systematic review and bibliometric mapping. Initial searches yielded 18,454 records from Scopus, 47,206 from Google Scholar, 650 from Emerald Insight, 30,975 from ProQuest, and 4,468 from IEEE Xplore. We included English-language articles published between 2014 and 2025 that apply MCDM to prioritizing projects, interventions, or sites. This timeframe was chosen to capture the rise of hybrid and fuzzy variants, as well as early integrations with GIS, AI, and big data. We excluded non-English items, duplicates, and incomplete records, following PRISMA guidelines for screening and eligibility. We combined SLR procedures with bibliometric analysis using VOSviewer and R-bibliometrix to map keyword co-occurrence. From the initial pool, 32 studies met the final criteria. The results show that distance-based methods (TOPSIS, VIKOR, EDAS) and AHP dominate the field, while hybrid and fuzzy variants are increasingly utilized. Objective and mixed weighting methods are common, whereas normalization choices and ranking rules vary by context. Validation practices remain inconsistent; while case applications and expert judgment are frequently used, sensitivity tests and cross-method comparisons are scarce. This study synthesizes objectives, weighting, normalization, ranking, and validation to identify method–context fit and highlight reporting gaps. We provide method-selection guidelines and a reporting checklist for practitioners, alongside a roadmap for researchers focusing on standardized validation, transparent parameterization, and integration with GIS, AI, and big data.]]>
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