The Mediating Role of Big Data Analysis Applications in the Relationship between Knowledge Management Competence and Quality Performance in Vocational Education Institutions

This study investigates how Big Data Analysis Applications (BDAA) mediate the relationship between Knowledge Management Technical Competence (KMTC) and Quality Performance (QP) in vocational education institutions amid ongoing digital transformation. Grounded in the Knowledge-Based View (KBV) and the Information System Success Model (ISSM), a quantitative research design was employed using survey data from 412 educators and administrators across Chinese vocational universities and colleges, analyzed through Structural Equation Modeling (SEM). The results reveal that KMTC positively influences both BDAA and QP, while BDAA exerts a significant direct impact on QP and partially mediates the KMTC–QP relationship, confirming the knowledge–analytics–performance (KAP) mechanism. These findings demonstrate that knowledge management competence enhances institutional quality primarily through the effective application of data analytics. The study extends KBV and ISSM by integrating analytics as a mediating mechanism within the educational management context and provides practical insights for vocational institutions seeking to strengthen data governance, analytics capability, and quality assurance systems in pursuit of sustainable digital transformation.