@article{4693,
  author = {Ezendu Ariwa},
  title = {A Digital Data-Driven Framework for Hierarchical Assessment of Students’ Innovation and Entrepreneurship Capabilities},
  journal = {Journal of Information Organization},
  year = {2026},
  volume = {16},
  number = {1},
  doi = {https://doi.org/10.6025/jio/2026/16/1/1-12},
  url = {https://www.dline.info/jio/fulltext/v16n1/jiov16n1_1.pdf},
  abstract = {This study addresses the critical gap in reliable, scalable assessment of college students’ innovation and
entrepreneurship capabilities by developing a digital, data driven evaluation system. Leveraging social
media analytics, data mining techniques, and the Analytic Hierarchy Process (AHP), the framework constructs
a three tier hierarchical indicator structure encompassing personal qualities (innovative awareness,
entrepreneurial motivation, psychological resilience), skill capabilities (professional knowledge, practical
innovation, teamwork), and learning experiences (self-directed learning, project participation,
entrepreneurial practice). Through crowdsourcing principles and frequency based indicator refinement,
the system transforms qualitative competencies into quantifiable metrics organized within a five level
classification (A–E). Experimental validation with 1,250 undergraduate students demonstrated that the
proposed system exhibited superior psychometric properties relative to conventional approaches, achieving
higher reliability (Cronbach’s  = 0.857), operational efficiency (0.853), and structural validity (average
factor loading = 0.275). The integrated platform deployed via cloud infrastructure with a WeChat miniprogram
interface enables objective benchmarking, precise talent identification, and evidence based
pedagogical interventions. By bridging digital youth engagement practices with rigorous multi criteria
decision making, this research contributes a scalable, empirically validated instrument for educators and
policymakers to systematically nurture innovation ready graduates. The framework’s robust performance
supports its application in curriculum design, mentorship allocation, and resource optimization within
entrepreneurship education ecosystems, ultimately advancing the development of future ready talent capable
of driving socioeconomic transformation.},
}