Abstract:

In the context of artificial intelligence (AI) adoption and digital transformation, organizations increasingly rely on supportive leadership and cultural mechanisms to sustain employee performance. This study examines how knowledge-oriented leadership (KOL) and knowledge sharing culture (KSC) influence job performance (JP) through employees’ learning goal orientation (LGO) and self-efficacy (SE). Drawing on Social Cognitive Theory, Achievement Goal Theory, and Self-Determination Theory, we propose a cross-level mediation model in which organizational support enhances performance by strengthening employees’ psychological resources.

Using survey data from 252 employees in Taiwan’s manufacturing and technology industries, the hypotheses were tested through covariance-based structural equation modeling (SEM). The results indicate that both KOL and KSC positively predict LGO and SE. In turn, LGO and SE are significantly associated with job performance. Mediation analyses reveal that the relationship between KOL and JP is fully mediated by LGO and SE, whereas KSC exerts both direct and indirect effects on JP, indicating partial mediation.

These findings suggest that leadership and culture contribute to performance in AI-driven environments primarily by fostering employees’ learning motivation and confidence in adapting to technological change. The study advances understanding of the psychological mechanisms underlying digital transformation and highlights the importance of aligning organizational support with employee adaptability to achieve sustainable performance outcomes.

Please choose your submission type: Full Paper

Primary Track: Human Resource Management

Keywords: Strategic HRM;Organizational behaviour and psychological state;Performance;Leadership

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Prof Jui-Yu Chen