Modeling Employee Adaptive Performance Through Digital Mindset, Learning Agility, and Technostress

Vollständiger Abstract

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This study examines how digital mindset, learning agility, and technostress shape employee adaptive performance within organizations undergoing digital transformation. Using a quantitative explanatory approach, data were gathered from 200 employees employed in technology-driven organizational environments. The proposed framework was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the relationships among the variables. The results indicate that both digital mindset and learning agility positively contribute to adaptive performance, while technostress demonstrates a significant negative influence. Among these predictors, learning agility emerged as the strongest determinant, emphasizing the critical role of continuous learning capacity in enhancing adaptability at work. These findings suggest that employees who are capable of embracing digital change and rapidly acquiring new competencies are more likely to perform effectively in uncertain and evolving work settings. Conversely, excessive technological demands may undermine employees’ capacity to adjust. This study contributes to the development of adaptive performance literature by integrating cognitive, behavioral, and psychological perspectives into a single analytical framework. From a practical perspective, organizations should prioritize strengthening employees’ digital orientation, fostering agile learning cultures, and minimizing technology-related stress to sustain workforce adaptability in an increasingly digitalized business environment.