The double-edged sword effect of artificial intelligence awareness among hotel employees
Purpose With its continuous development and application in the hotel industry, artificial intelligence (AI) is gradually replacing many jobs traditionally performed by humans. This research aims to understand how this threat and opportunity of substitution affects hotel employees’ behavioral decision-making. Design/methodology/approach This study uses a structural equation model, ordinary least squares and bootstrapping method to analyze the data collected with a field study and a scenario experiment from star-hotels in Shanghai, Paris and Seoul. Findings The results discovered that employees’ AI awareness has a positive relationship with their work engagement and AI boycott through two paths. The promoting path involves recovery level, while the hindering path includes job insecurity. In addition, the estimates showed that AI awareness has a great indirect effect on work engagement or AI boycott when innovativeness as a job requirement is high. Practical implications The findings offer insights to help hotels optimize the relationship between AI and hotel human workers while providing valuable implications for addressing behavioral dilemmas faced by hotel employees in the era of AI. Originality/value By integrating the behavioral decision-making literature with the conservation of resources theory, the study focuses on the dual mechanisms – challenging and hindering – through which AI awareness influences hotel employees’ coping strategies.
Authors
- Shengmin Liu (ORCID: https://orcid.org/0000-0002-5763-0017)
- Pengfan Cheng (ORCID: https://orcid.org/0000-0002-8201-7265)
Institutions
- University of Shanghai for Science and Technology (CN)
- Shanghai University of International Business and Economics (CN)
Publication Details
- Journal
- International Journal of Contemporary Hospitality Management
- Published
- 2024-12-30
- DOI
- https://doi.org/10.1108/ijchm-01-2024-0051
- Citations
- 24
- Primary Topic
- Impact of AI and Big Data on Business and Society
- Type
- article
- Field-Weighted Citation Impact
- 11.77