Application-oriented undergraduate institutions' path innovation and practice exploration of e-commerce talent training based on big data mining and prediction

Abstract

The deepening development of the digital economy has propelled the e-commerce industry into a new phase characterized by "technology-driven innovation, cross-sector integration, and global competition,"with computer technologies such as big data analytics, artificial intelligence, and VR/AR emerging as core drivers. However, the existing training models in applied undergraduate institutions - key platforms for cultivating e-commerce professionals - have increasingly demonstrated mismatches with industry demands through big data mining and predictive analytics. This study analyzes the essential requirements for e-commerce talent's "digital technology application capabilities"in the digital economy era, utilizing survey data from 20 applied undergraduate universities across China's eastern, central, and western regions. The research reveals regional disparities in technical curriculum design, intelligent practice platform development, and faculty technical competencies. Proposing a cultivation pathway of "technology stratification and regional adaptation,"the study implements technical solutions including building a "digital tools-intelligent scenarios-practical projects"curriculum system, establishing VR/AR e-commerce training platforms, and developing AI-powered "position-skills"matching models. These measures ensure precise alignment between talent development and industry needs. This work provides actionable technical implementation plans for reforming e-commerce programs in applied universities and offers empirical support for theoretical research on "technology-empowered education"in applied undergraduate institutions through big data mining and predictive analytics.