The purpose of this paper is to examine how digital reskilling programs influence employee job performance by identifying the mechanisms through which training investments translate into performance outcomes.
Drawing on human capital theory and training transfer perspectives, this study uses a quantitative, cross-sectional research design. Data was collected through a structured online questionnaire administered to employees working in digitally transforming organizations. After data cleaning, 310 valid responses were analyzed using partial least squares structural equation modeling (PLS-SEM), which is particularly suited for predictive, theory-building research with complex mediation models.
The results indicate that digital reskilling programs have a significant direct effect on employee job performance. In addition, perceived learning agility and perceived skill utilization were found to act as parallel mediators in the relationship between digital reskilling and job performance. Specifically, reskilling initiatives enhance employees’ adaptive learning capabilities and strengthen perceptions of the practical application of skills, both of which contribute positively to performance outcomes.
The findings suggest that organizations should design reskilling initiatives that extend beyond technical skill development by fostering adaptive learning and creating opportunities for skill application in the workplace.
This study advances training and development research by unpacking the mechanisms linking digital reskilling programs to employee performance through a PLS-SEM mediation framework, offering a more nuanced understanding of reskilling effectiveness in digitally dynamic environments.
