Data-driven innovations in disaster risk management: Advancing resilience and sustainability through big data analytics

The integration of Big Data Analytics (BDA) into Disaster Risk Management (DRM) presents transformative opportunities to enhance decision-making and foster environmental sustainability across preparedness, response, recovery, and resilience. This study investigates the factors influencing BDA adoption in DRM using an integrated Technology-Organization-Environment and Diffusion of Innovation (TOE-DOI) framework. Survey data collected from academic participants with backgrounds in statistics, data analysis, and quantitative methods, along with technical, management, and disaster response professionals, were analyzed using ordinal logistic regression to assess the impact of technological, organizational, and environmental predictors. Key findings show that technological enablers drive BDA adoption by enhancing prediction and efficiency, while organizational readiness supports sustained integration. Stakeholder collaboration promotes adoption through improved coordination. In contrast, regulatory and competitive factors were not significant. The study provides actionable insights for advancing DRM through multidisciplinary strategies that align BDA integration with sustainability goals, emphasizing its potential to support resilient systems and informed decision-making in the face of complex environmental challenges.