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

Author:

Daigle Jamie L.ORCID,Stading Gary,Hall AshleyORCID

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.

Publisher

Emerald

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3