Abstract
Manufacturing supply chains face growing risks from events such as pandemics and climate-related disruptions, making supply chain resilience (SCR) increasingly essential for business continuity and competitiveness. This study adopts a quantitative research approach to examine the factors influencing SCR, drawing on a large dataset of manufacturing firms. Grounded in the dynamic capability view, the analysis focuses on key variables, such as supplier collaboration, lead time, transportation cost efficiency, supply chain complexity, and SCM practices. Using a combination of statistical techniques, including t-tests, ANOVA, correlation, and regression analysis, the study finds that stronger supplier collaboration and more efficient transportation significantly enhance resilience, while longer and more variable lead times reduce it. Notably, well-managed supply chain complexity also contributes positively to SCR. The findings advance theory by linking operational metrics to dynamic capabilities and offer practical guidance for improving resilience through logistics optimisation, collaboration, and data-driven planning. Overall, the research highlights SCR as a measurable and strategic capability essential for sustaining manufacturing performance in uncertain environments.

Keywords:
Supply chain resilience, Manufacturing, Data analytics, Dynamic capabilities, Supplier collaboration.

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