The impact of ambidextrous learning on employee performance under digital transformation stress

Abstract

Against the backdrop of accelerating digital transformation, enterprises are facing unprecedented pressure for change, and how employees adapt to this transformation has become a critical factor influencing organizational performance. Based on the stress-performance theory, ambidextrous learning theory, and perceived competence theory, this study constructs a mechanism model to examine the relationships among digital transformation stress perception, ambidextrous learning (exploratory learning and exploitative learning), perceived competence, and employee work performance. The research aims to explore how digital transformation stress perception influences employee work performance through ambidextrous learning, while further analyzing the moderating role of perceived competence to reveal how employees effectively learn and enhance performance in a digital environment. This study adopts a questionnaire survey method, collecting self-assessment data from 405 corporate sales managers regarding their perceptions of digital transformation pressure, learning approaches, perceived competence, and work performance. A structural equation model (SEM) was constructed to test the research hypotheses, and hierarchical regression analysis was employed to examine the moderating effect of perceived competence. Through quantitative analysis, the study reveals the mechanism by which digital transformation stress perception influences employee work performance through ambidextrous learning (exploratory learning and exploitative learning).