This study examines the relationships among big data analytics capabilities, inter-organizational coordination capabilities and humanitarian supply chain resilience. Drawing on Dynamic Capability Theory (DCT), the study explains how humanitarian organizations leverage data analytics and inter-organizational coordination to strengthen supply chain resilience in uncertain and disruption-prone environments. A quantitative cross-sectional survey was conducted among 88 humanitarian organizations operating in Uganda. Data were analyzed using partial least squares structural equation modeling (PLS-SEM) in SmartPLS to assess the hypothesized direct relationships and the mediating effect of IOCC. The findings reveal that BDAC has a significant positive effect on both IOCC and HSCR. IOCC also significantly enhances HSCR. Furthermore, IOCC partially mediates the relationship between BDAC and HSCR, indicating that the resilience benefits of big data analytics arise both directly and indirectly through strengthened inter-organizational coordination. The cross-sectional design limits the ability to capture how analytics capabilities, coordination mechanisms, and resilience evolve. Future research could employ longitudinal and qualitative designs to examine the dynamic processes through which humanitarian organizations develop and deploy these capabilities across different stages of disruptions. Humanitarian organizations should complement investments in big data analytics and digital infrastructure with mechanisms that strengthen information sharing, joint planning, resource coordination, and collaborative decision-making among supply chain partners. Integrating analytics with strong coordination capabilities can improve preparedness, responsiveness, and recovery from humanitarian supply chain disruptions. This study extends the application of DCT to humanitarian supply chains by demonstrating that IOCC constitutes an important mechanism through which BDAC translates into HSCR
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Aryatwijuka et al. (2026) studied this question.
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