A Moderated Mediation Analysis of Artificial Intelligence Awareness and Work Withdrawal
Unlock the Power of Responsible AI Integration
This study investigates the complex relationship between AI awareness, psychological detachment, segmentation preference, and work withdrawal among hotel employees. It reveals that AI awareness positively influences work withdrawal, mediated by psychological detachment. Crucially, segmentation preference moderates this indirect effect, weakening the negative impact of AI awareness on psychological detachment and subsequent work withdrawal when segmentation preference is high. These findings offer practical implications for managing AI integration in the hospitality sector.
Executive Impact at a Glance
Key metrics from the analysis, highlighting critical factors influencing AI adoption and workforce dynamics.
3.66
Mean Work Withdrawal
0.038
Indirect Effect (AI→PD→WW)
-0.25
Low Segmentation Impact (AI→PD)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
This study significantly contributes to enterprise management literature by extending the understanding of AI's impact on employee outcomes, corroborating the 'dark side' of AI awareness. It offers a resource conservation perspective, elucidating how AI awareness affects employee psychology and behavior via psychological detachment. Furthermore, it fills gaps by demonstrating that employees' segmentation preferences moderate the relationship between AI awareness and work outcomes, identifying conditions under which AI's impact is enhanced or diminished.
Our findings provide valuable insights for organizational management. Organizations adopting AI technologies should conduct systematic assessments of employee anxiety, offer training before AI introduction, and provide counseling. Employees should establish clear boundaries between professional and personal domains, with organizations facilitating this by prohibiting after-hours work-related communications. Integrating segmentation preference assessments into talent acquisition, prioritizing candidates with stronger segmentation preferences, can also mitigate negative impacts.
87.1%
Female Employees in Sample
Enterprise Process Flow
AI Awareness (Independent Variable)
→
Psychological Detachment (Mediator)
→
Work Withdrawal (Dependent Variable)
| Factor Model | X²/df | RMSEA |
|---|---|---|
| 1-factor | 7.865 | 0.135 |
| 4-factor | 1.962 | 0.050 |
Impact of AI Awareness on Work Withdrawal
The study found that AI awareness significantly impacts work withdrawal in hotel employees. Specifically, heightened AI awareness leads to greater job insecurity and psychological stress, driving employees to withdraw. This aligns with the Conservation of Resources (COR) theory, where individuals conserve depleted resources by reducing their engagement.
Impact: A positive direct effect of AI awareness on work withdrawal was observed, with a β = 0.088, indicating that higher AI awareness is linked to increased work withdrawal.
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Implementation Roadmap
A strategic phased approach to integrating AI, minimizing disruption and maximizing long-term benefits.
Phase 1: Awareness & Assessment
Conduct thorough assessments of employee AI anxiety, introduce AI technologies with comprehensive training, and provide counseling for stress management.
Phase 2: Boundary Establishment
Implement clear organizational policies prohibiting after-hours work-related communications to foster psychological detachment.
Phase 3: Talent Integration
Incorporate segmentation preference assessments into talent acquisition, prioritizing candidates who demonstrate stronger work-home segmentation preferences.
Phase 4: Continuous Monitoring & Adaptation
Regularly review AI implementation impact, gather employee feedback, and adapt strategies to optimize employee well-being and productivity.
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