William Widjaja

The retail industry has complex and demanding work dynamics. In this context, a deep understanding of the factors that influence employee performance is highly relevant to managing retail companies. This study examines the interrelationships among work intensification, high-performance work systems (HPWS), emotional exhaustion, employee creativity, and employee performance within the retail industry. This study used a survey approach with a quantitative methodology; data were gathered through questionnaire distribution to 235 retail employees across Jakarta, Indonesia, utilizing non-probability convenience sampling. Analysis was conducted using partial least squares-structural equation modeling (PLS-SEM) via the SmartPLS version 3.3.3 tool. Results revealed that work intensification significantly and positively influences HPWS and emotional exhaustion (p < 0.05). While HPWS exhibited no significant impact on employee creativity, emotional exhaustion had a significant and negative effect (p > 0.05). Furthermore, employee creativity demonstrated a significant positive effect on employee performance (p < 0.05). It was a significant mediator between emotional exhaustion and employee performance, though not between HPWS and employee performance (p < 0.05). The study underscores the intricate dynamics within the retail work environment, highlighting the intertwined roles of HPWS, emotional exhaustion, and employee creativity. Practical implications emphasize the necessity for effective management strategies to navigate work intensification and emotional exhaustion, ultimately enhancing employee performance. Notably, this paper offers a comprehensive analysis of factors shaping employee performance in the retail sector, emphasizing the pivotal significance of HPWS, emotional exhaustion, and employee creativity as interconnected components.

Type of the article: Research Article

This study examines the relationships among generative AI tool usage for Workplace Learning, Learning Agility, and Workplace Creativity among electronic retail employees in Indonesia. Learning Agility was modeled as a second-order construct comprising developing leadership or growth, seeking feedback, and developing systematically. Data were collected through a cross-sectional survey of 286 employees who actively used generative AI platforms for learning and work-related support. The hypotheses were tested using covariance-based structural equation modeling and bias-corrected bootstrap analysis. The results show that generative AI tool usage was positively associated with Learning Agility (β = 0.738, p < 0.001), while Learning Agility was positively associated with Workplace Creativity (β = 0.484, p < 0.001). Generative AI tool usage also maintained a positive direct relationship with Workplace Creativity (β = 0.408, p < 0.001). The indirect relationship through Learning Agility was statistically significant, with a bias-corrected 95% confidence interval ranging from 0.179 to 0.509. These findings indicate complementary partial mediation, suggesting that Generative AI Use is related to Workplace Creativity both directly and through employees’ adaptive learning capacity. The study applies Social Cognitive Theory to generative AI-supported workplace learning by distinguishing AI-enabled learning resources from employees’ behavioral engagement with those resources. The findings suggest that Generative AI Use is associated with Workplace Creativity both directly and indirectly through Learning Agility. Practically, electronic retail managers should combine AI adoption with employee development practices that encourage feedback seeking, reflection, experimentation, and systematic learning.