Curricular innovation for economic symbiosis: a neural network approach to aligning university supply chain programs with regional industry demands

Abstract

PurposeThe study aims to refine the local university’s supply chain management curriculum to meet regional industry demands, thus boosting the local economy.Design/methodology/approachMixed-methods action research combined with neural network modeling was employed to align educational offerings with the needs of the local supply chain management industry.FindingsThe 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/implicationsThe study is specific to one region and industry, suggesting a need for broader application to verify the findings.Practical implicationsAdopting the recommended curricular changes can yield a workforce better prepared for the SCM industry, enhancing local business performance and economic health.Social implicationsThe study supports a role for higher education in promoting economic vitality and social welfare through targeted, responsive curriculum development.Originality/valueThis study introduces an innovative approach, integrating neural network analysis with action research, to guide curriculum development in higher education based on industry requirements.