Dataset from Zenodo · Mayanta, Jason Obed
AI Usage and Quiet Quitting: Work Engagement and Well-Being as Pathways
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- License not specified
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- Formats
- XLSX
- Size
- 210 kB
- Updated
- Jul 22, 2026
Description
Abstract Quiet quitting, a global workforce phenomenon that affects 59% of the global workforce, defined as employees limiting contributions to the minimum required without resigning. Based with the Job Demands-Resources model, this research study how AI usage influence quiet quitting through work engagement and moderated by employee well-being with a proposed six hypotheses. A quantitative survey was conducted using purposive sampling on 195 employees across Indonesia. The findings confirmed AI usage positively enhances work engagement (H1), which mediated the AI usage to quiet quitting relationship (H4), and employee well-being moderates this link (H5). However, work engagement did not directly suppress quiet quitting (H2), AI usage had no direct effect on quiet quitting (H3), and employee well-being did not moderate the work engagement and quiet quitting relationship (H6). These findings extend the JD-R model by positioning AI as a technological job resource operating through psychological mediation rather than direct behavioral pathways, offering helpful implications for organizations. Keywords : AI Usage, Quiet Quitting, Employee Well-Being, Work Engagement, JD-R, Behavioral…
Description from Zenodo, shortened.
Files (1)
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