SEM MODEL VALIDATION BASED ON DMAIC IN VOCATIONAL TRAINING MANAGEMENT IN HANOI

In the context of digital transformation and rising demand for high-quality human resources, vocational training management needs to shift toward a data-driven, continuous improvement approach. This study aims to analyze the theoretical foundation, assess the current situation, and propose a system of management measures for vocational training to meet labor-market demands at intermediate vocational schools in Hanoi, following the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle. The research used a mixed methods design, combining a quantitative survey of 150 administrators, lecturers, final-year students, and enterprise representatives from five intermediate schools with in-depth interviews. Data was processed using SPSS and AMOS through reliability testing, exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. The results indicate that the components of the DMAIC cycle positively influence labor market responsiveness, with Define showing the strongest effect. Based on these findings, the study proposes a set of management measures aligned with each phase of the improvement cycle. The results of expert appraisal and pedagogical experimentation initially confirm the model’s suitability and feasibility. The study contributes a scientific basis for vocational training management grounded in a data-driven quality management approach.