Purpose: The study aims to refine the local university's supply chain management curriculum to meet regional industry demands, thus boosting the local economy. Design/methodology/approach: Mixed-methods action research combined with neural network modeling was employed to align educational offerings with the needs of the local supply chain management industry. Findings: The research indicates that curriculum revisions, informed by industry leaders and modeled through neural networks, can significantly improve the relevance of graduates' skills to the SCM sector. Research limitations/implications: The study is specific to one region and industry, suggesting a need for broader application to verify the findings. Practical implications: Adopting the recommended curricular changes can yield a workforce better prepared for the SCM industry, enhancing local business performance and economic health. Social implications: The study supports a role for higher education in promoting economic vitality and social welfare through targeted, responsive curriculum development. Originality/value: This study introduces an innovative approach, integrating neural network analysis with action research, to guide curriculum development in higher education based on industry requirements.