PREDICTING DIGITAL PERFORMANCE EFFICIENCY THROUGH QUALITY OF DIGITAL TRAINING AND SUSTAINABLE WORKPLACE PRACTICES

The continuing digitalization of higher education institutions has intensified expectations for employees to perform efficiently within technology-driven work environments. While digital tools are increasingly integrated into institutional operations, performance inefficiencies persist when digital initiatives are implemented without high-quality training and sustainable workplace support. This gap highlights the need to identify organizational factors that meaningfully enhance digital performance efficiency among higher education personnel. This study examined the predictive influence of digital training quality and sustainable digital workplace practices on employees’ digital performance efficiency in local colleges. Using a descriptive research design, data were collected from academic and administrative personnel through structured questionnaires. Descriptive statistics, validity and reliability testing, correlation analysis, and multiple regression analysis were employed to examine relationships among the variables. The results indicated that both digital training quality and sustainable digital workplace practices were positively and significantly associated with digital performance efficiency. Regression analysis further revealed that these variables significantly predicted employees’ digital efficiency, suggesting that structured training initiatives and sustainable digital systems jointly contribute to improved performance outcomes. The findings underscore the importance of aligning capacity-building efforts with sustainable digital workplace practices to optimize employee efficiency in higher education settings. The study contributes empirical evidence to the growing body of research on digital transformation in academia and offers practical insights for institutional leaders seeking to enhance digital performance. Future studies may explore additional organizational factors, such as digital leadership, institutional culture, and employee motivation, to further explain variations in digital performance efficiency.