Working with a robot assistant in the kitchen: restaurant chefs' perspectives
Purpose The purpose of this research is to investigate how the three different robot product levels influence restaurant chefs' perceived job demand-control and affect work engagement. Design/methodology/approach Consistent with the research framework grounded in three theories, a three-factor, two-level, between-subjects experimental design was employed. The proposed hypotheses were tested using data from 396 restaurant chefs. Findings The robot's core product significantly influences employees' perceived job control. Job demands and job control impact employees' work engagement. Moreover, a higher level of employees' service innovation behavior moderates the relationship between job control and work engagement. Research limitations/implications This research integrates the product level theory with the job demand-control model and presents the dynamics among robot product levels, job duality and work engagement. Practical implications This research has implications for various stakeholders involved in human-robot collaboration, covering robot design and selection, staff recruitment and training, policymaking, as well as employee self-awareness. Originality/value This study contributes not only to hospitality robot research but also to the emerging literature on human-AI collaboration and AI-enabled work design by demonstrating how the distinct technological characteristics of collaborative robots reshape employees' perceptions, thereby influencing work engagement.
Authors
- Emily Ma (ORCID: https://orcid.org/0000-0002-0161-7710)
- Aaron Hsiao (ORCID: https://orcid.org/0000-0003-0418-4356)
- Jingjing Xu (ORCID: https://orcid.org/0000-0002-0861-4328)
- Sacha Reid
Institutions
- Griffith University (AU)
- Surrey Memorial Hospital (CA)
- East Surrey Hospital (GB)
- University of Surrey (GB)
Publication Details
- Journal
- Journal of Hospitality and Tourism Horizons
- Published
- 2026-08-27
- DOI
- https://doi.org/10.1108/jhth-10-2025-0132
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00