Service robots and COVID-19 : exploring perceptions of prevention efficacy at hotels in generation Z

Purpose: COVID-19 is expected to enhance hospitality robotization because frontline robots facilitate social distancing, lowering contagion risk. Investing in frontline robots emerges as a solution to recover customer trust and encourage demand. However, we ignore how customers perceive these initiatives and, therefore, their efficacy. Focusing on robot employment at hotels and on Generation Z customers, this study aims to analyze guests’ perceptions about robots’ COVID-19 prevention efficacy and their impact on booking intentions. Design/methodology/approach: This study tests its hypotheses combining an experimental design methodology with partial least squares. Survey data from 711 Generation Z individuals in Spain were collected in 2 periods of time. Findings: Generation Z customers consider that robots reduce contagion risk at hotels. Robot anthropomorphism increases perceived COVID-19 prevention efficacy, regardless of the context where the robots are used. Robots’ COVID-19 prevention efficacy provokes better attitudes and higher booking intentions. Research limitations/implications: The sampling method used in this research impedes this study’s results generalization. Further research could replicate this study using random sampling methods to ensure representativeness, even for other generational cohorts. Practical implications: Employing robots as a COVID-19 prevention measure can enhance demand, especially if robots are human-like. Hoteliers need to communicate that robots can reduce contagion risk, particularly in markets more affected by COVID-19. Robots must be employed in low social presence contexts. Governments could encourage robotization by financially supporting hotels and publicly acknowledging its benefits regarding COVID-19 prevention. Originality/value: This study combines preventive health, robotics and hospitality literature to study robot implementation during the COVID-19 pandemic, focusing on Generation Z guests – potential facilitators of robot diffusion.