Customers’ evaluation of mechanical artificial intelligence in hospitality services: a study using online reviews analytics

Purpose This paper aims to analyze if and what extent mechanical artificial intelligence (AI)-embedded in hotel service robots-influences customers’ evaluation of AI-enabled interactions. study deploys online reviews (ORs) analytics understand the presence AI-related text ORs influences OR valence across 19 leading international hotels that have integrated AI – guise robots into their operations. Design/methodology/approach First, authors identified three continents pioneered adoption robots. Second, by deploying big data techniques, gathered entire population hosted on TripAdvisor (almost 50,000 ORs) generated analytics. Subsequently, used ordered logistic regressions analyses hospitality interactions are evaluated customers. Findings The (text related robots) positively electronic word-of-mouth (e-WOM) valence. Hotel guests writing explicitly mentioning with more prone associate high ratings ORs. robot’s proper name (e.g., Alina, Wally) moderates positive effect ratings. Research limitations/implications Hospitality practitioners should evaluate possibility introduce operations develop tailored strategies (such as using human-like short names). Moreover, managers communicate initiatives investments AI, monitor e-WOM invest educating non-tech-savvy customers appreciate technology. Platform developers might create a robotic tag be attached signal this specific element design an additional attribute tentatively named “service robots.” Originality/value current represents first attempt