The influence of training program quality, trainer quality, and training methods on overall training quality outcome provided by firms for the Japanese market

This study investigates the determinants of training quality outcomes in programs preparing workers for the Japanese labor market, with particular attention to training program quality, trainer quality, and training methods in the context of digital transformation and AI. Using survey data from 360 respondents, the study applies reliability testing, exploratory factor analysis, and multiple regression analysis to evaluate the relationships among key constructs. The results indicate that training program quality has the strongest positive impact on training outcomes, followed by trainer quality, while training methods show no statistically significant effect. These findings suggest that structural factors, such as curriculum design and instructor competence, remain critical, whereas methodological innovation has yet to fully translate into measurable outcomes. Importantly, the study highlights the role of governance and regulatory frameworks in shaping training effectiveness, particularly in ensuring alignment with Japanese labor standards and digital workplace requirements. The integration of AI and digital technologies presents both opportunities and challenges, requiring continuous adaptation of training systems. This study contributes to the literature by bridging vocational training theory with the sociology of economic action and digital transformation perspectives. Practical implications emphasize curriculum modernization, trainer upskilling, and policy support to enhance workforce readiness in global labor markets.