The widespread deployment of service robots in industries such as hospitality has significantly transformed service delivery, influencing not only customers but also employees. This study examines the multi-dimensional impact of service robots on hotel employees, focusing on their attitudes, emotional responses, and willingness to collaborate, as shaped by perceived benefits (service reliability, process efficiency, and job crafting) and risks (inefficiency, insufficient intelligence, and privacy concerns). Data were collected from 471 hotel employees in South Korea with experience working alongside service robots, and Hayes’ Process Macro Model 4 was employed for hypothesis testing. The findings reveal that perceived benefits positively influence employees’ attitudes, emotions, and willingness to collaborate, while perceived risks exert a negative impact. Furthermore, attitudes and emotional responses mediate these relationships. These findings provide theoretical and practical insights for managers, policymakers, and service robot manufacturers to address employee concerns, improve human–robot collaboration, and promote sustainable technological integration within the service industry.

As service robots become more prevalent in hospitality settings, understanding what shapes employees’ trust in these technologies is essential for fostering effective human–robot collaboration. Despite extensive research on customer trust and robot-related attributes, employee perspectives have received limited and fragmented attention. The aim of this study is to examine how human, robot, and organizational factors collectively influence employees’ trust in service robots, thereby offering a more comprehensive understanding of trust formation in hospitality contexts. To address this aim, this study adopts a three-dimensional trust framework (human, robot, and organizational factors) and provides the first comprehensive empirical test in the hospitality sector. Drawing on survey data from 301 frontline hospitality workers in the United States, we investigated how various human-, robot-, and organization-related factors influence employees’ trust in service robots using bootstrap multiple regression analysis. The results reveal that human factors, particularly employees’ attitudes toward and comfort with robots, emerged as dominant trust predictors. Surprisingly, organizational factors showed minimal direct impact, suggesting complex trust dynamics unique to hospitality contexts. These findings significantly expand existing human–robot interaction (HRI) theory and offer critical practical insights for hospitality managers integrating robots into frontline service.