UNDERSTANDING EMPLOYEES\u27 PERCEPTIONS AND COLLABORATION BEHAVIOR INTENTIONS TOWARD SERVICE ROBOTS IN THE HOSPITALITY CONTEXT

Due to fast-paced developments in the technological sphere, we see that artificial intelligence (AI) and robotics are increasingly working and collaborating with human employees in the hospitality industry. As teaming humans and robots become commonplace in the hospitality context, it is crucial to understand the aspects facilitating and hindering successful human-robot collaboration. However, while research has focused on attributes affecting human-robot interaction from customers’ perspectives, employees’ perceptions and behavioral reactions toward working with service robots are less understood. By taking a Job Demands-Resources (JD-R) approach, this study examines how frontline hospitality employees’ perceptions and collaboration intentions with service robots can be affected by the design of robots’ appearance and job designs. The proposed research contains three experimental studies. Study 1 tests the association between robots’ human likeness and employees’ collaboration intention and the mediating mechanism of employees’ intrinsic motivation and job stress, guided by the JD-R theory. The results of Study 1 indicate that employees may perceive robots with low human likeness as job resources and, therefore, have a higher collaboration intention toward non-humanoid (vs. humanoid) service robots. Moreover, the results reveal a significant mediating effect of intrinsic work motivation and job stress on the relationship between service robots’ human likeness and employees’ collaboration intention. Building on the findings of Study1, Study 2 examines the interacting effects of robots’ human likeness and task interdependency on employees’ intrinsic work motivation, job stress, and collaboration intention. The results of Study 2 reveal that employees have a higher collaboration intention toward non-humanoid (vs. humanoid) service robots when task interdependence is low. However, such an effect is attenuated when task interdependence is high. Finally, Study 3 further tests the interacting effects of role clarification on the above-proposed model. The results of Study 3 suggest a significant interacting effect of robots’ human likeness and role clarification on employees’ collaboration. The adverse effect of robots’ human likeness on employees’ collaboration intention is mitigated when role clarification is provided. This finding supports the importance of clearly clarifying the role and responsibility of human and robot employees in improving employees’ intentions to interact and collaborate with service robots