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The Impact of Job Anxiety Caused by Artificial Intelligence Substitution on Organizational Members’Turnover Intention: The Mediating Role of Job Insecurity and the Moderating Effect of Job Uncertainty

Authors
정자안JINXIU
Issue Date
Jun-2024
Publisher
한국생산성학회
Keywords
인공지능; 직무불안감; 직무불안정성; 직무불확실성; 이직의도; Artificial Intelligence; Job Anxiety; Job Insecurity; Job Uncertainty; Turnover Intention.
Citation
생산성연구: 국제융합학술지, v.38, no.3, pp 67 - 103
Pages
37
Journal Title
생산성연구: 국제융합학술지
Volume
38
Number
3
Start Page
67
End Page
103
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/92086
DOI
10.15843/kpapr.38.3.2024.6.67
ISSN
1225-3553
Abstract
Artificial intelligence (AI) represents a significant technological leap within the hotel industry, promising to revolutionize various aspects of operations. However, its full impact remains uncertain, particularly its effect on the workforce. One notable consequence is the potential erosion of employees' expertise, which often leads to heightened levels of anxiety. As AI takes over tasks traditionally performed by humans, employees may feel sidelined or redundant, uncertain about their future within the organization. This anxiety, in turn, can catalyze turnover intentions, as employees grapple with uncertainties about their roles and career prospects. Recognizing the importance of understanding these dynamics, this paper aims to delve into the intricate relationship between AI adoption, job anxiety, job insecurity, job uncertainty, and turnover intention in the context of hotel employment. By examining how AI implementation influences employee well-being, this study seeks to provide valuable insights for both industry practitioners and policymakers. Based on theories of anxiety and coping, this study constructs a comprehensive framework to assess the impact of AI implementation on employee well-being. Leveraging survey data from a diverse pool of 608 hotel employees, the research examines how organizational adoption of AI influences job anxiety levels and subsequent turnover intentions. The statistical analyses reveal compelling insights into the interplay between AI and employee turnover intentions. Key findings indicate that the introduction of artificial intelligence indeed shapes employees' intentions to leave their jobs. Notably, job anxiety induced by AI substitution emerges as a significant predictor of turnover intention, underscoring the psychological strain experienced by employees amidst technological advancements. Furthermore, the study unveils the mediating role of job insecurity, wherein heightened anxiety precipitates feelings of job instability, subsequently fueling turnover intentions. As AI continues to permeate the hotel industry, understanding and addressing these workforce dynamics will be crucial for maintaining employee morale and organizational stability in the face of technological change.
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