Reconstructing the Data-Driven Talent Development Chain in New Business Education: Competency Identification, Collaborative Incubation, and Outcome Optimization_Vol. 3 No. 2 (JHET 2026)_Journal of Higher Education Teaching (ISSN: 3005-5776)

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Reconstructing the Data-Driven Talent Development Chain in New Business Education: Competency Identification, Collaborative Incubation, and Outcome Optimization

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DOI: https://doi.org/10.62517/jhet.202615219

Author(s)

Can Jiang, Xinyu Xu, Shuangjin Wang*

Affiliation(s)

School of Management, Tianjin University of Commerce, Tianjin, China *Corresponding Author

Abstract

This paper develops a conceptual framework for reconstructing the talent development chain in new business education through a data-driven approach. It treats talent training, project incubation, and venture development as one connected process rather than three separate activities. The framework centers on four linked tasks: competency identification, intelligent project recognition and targeted incubation, platform-based coordination, and multidimensional evaluation with iterative adjustment. The paper argues that effective reform depends on connecting capability development, resource matching, cross-actor collaboration, and long-term feedback within the same institutional system. It also stresses that educational data and AI should support human judgment rather than replace it. The study offers a practical framework for improving innovation and entrepreneurship talent development in new business education.

Keywords

New Business Education; Entrepreneurship Education; Data-Driven Governance; Business Incubation; Dynamic Capabilities; Learning Analytics; AI in Education

References

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