This paper takes the widest possible lens on service robot research in hospitality: it analyzes 284 published studies to map the state of the field, identify the most active research themes, and project where the field is heading. The result is a useful orientation for operators who want to understand the evidence base behind robot deployment decisions — and for technology buyers who need to separate hype from substance.
Using bibliometric analysis — a technique that maps citation networks, keyword clusters, and publication trends to identify intellectual structure in a field — the researchers identify four major research fronts that dominate the literature.
The first front focuses on the robot itself: performance characteristics, technology types (autonomous vs. remote-controlled, navigation capabilities, interaction modalities), and how different design decisions affect practical outcomes. This research cluster is largely the domain of engineering and computer science, but its practical implications for hospitality buyers are significant: the technical capabilities gap between entry-level robot products and premium systems is substantial, and the studies in this cluster provide useful frameworks for evaluating what you're actually getting when vendors make capability claims.
The second front centers on the consumer: how guests perceive, accept, and respond to robots in service environments. As discussed in other papers in this collection, emotional and psychological factors dominate. What this paper adds is scale — with 284 studies to draw from, it's possible to identify findings that replicate consistently across different markets, hotel types, and guest demographics versus findings that are context-specific. The most robust finding: guest satisfaction with robot service is strongly predicted by perceived competence and perceived warmth, both of which can be designed and tested before deployment.
The third front examines employees: how staff experience working alongside robots, how job roles change, and how robot deployment affects team dynamics and morale. This is the most underdeveloped research cluster — which itself is a finding. The field has studied guests far more intensively than workers, even though most robot deployment challenges in practice are HR and change management challenges rather than technical ones.
The fourth front addresses the service environment: how physical space, ambient conditions, and operational context affect robot performance and guest interaction. Hotels have a more controlled service environment than restaurants or outdoor tourism contexts, which is one reason hotel applications have been among the most successful.
The COVID-19 effect deserves specific mention: the paper documents a significant acceleration in both robot adoption and academic research during and after the pandemic. Contactless service became an operational priority rather than a guest preference differentiator, and robots were deployed in functions — guest temperature checking, sanitization, food delivery to quarantine rooms — that would not have been commercially justified before. This wave of real-world deployment generated a corresponding wave of research data, improving the quality of evidence available to operators considering deployment today.
For decision-makers, the key takeaway is that service robots in hospitality are now a well-researched technology area. There's enough evidence to make informed deployment decisions — you don't need to rely on vendor case studies or intuition. The researchers who know this field well can point you toward what works and what doesn't for your specific use case.