From Services to Offices: Investigating the Integration of Service Robots into Our Lives

Technologies based on Artificial Intelligence (AI), such as service robots, are increasingly penetrating multiple areas of our lives: From services to office areas, they are integrated in a variety of functions and forms. In the service area, service robots are an important interface to customers and work alongside human employees. In offices, robots provide assistant services to their human colleagues. These developments call for guidance on how to effectively integrate service robots for successful human-robot interaction in these contexts. This dissertation aims to provide nuanced insights into service robot implementation, depending on the level and perspective of interaction. It thus sheds light on individual and team-level interactions between humans and robots, covering the external, i.e., customer perspective, and internal employee perspective on these service robots. With this differentiation, this work advances knowledge and theoretical concepts for each area and also provides concrete managerial guidance. The dissertation contains three research studies dedicated to specific levels and perspectives of human-robot interaction. Additionally, service and office contexts are investigated. Research study 1 focusses on individual interactions between human and robotic employees from an external customer perspective in a frontline service environment. Relying on social identity theory and the black sheep effect, study 1 shows that customers upgrade norm-compliant behaviors by human employees more than similar behaviors by service robots. Additionally, they downgrade norm-violating service behaviors more when interacting with a human service employee compared to a service robot. This effect also occurs in service failures with greater anger and frustration towards human service employees. As an important mechanism to the black sheep effect, this work shows that customers assign human service employees to a social ingroup, while service robots represent the social outgroup. This study gives theory-based guidance for the deployment of service robots in customer-service situations and effective division of labor with human service employees. Research study 2 addresses service robot implementation into an office context from an internal employee perspective. Again, individual interactions are the focus of the study. Based on a typology approach, distinct robot user types are established through interviews. These types and related patterns are then investigated in an online study providing insights on performance-related and social relations for each type. By utilizing these types, firms can tailor service robot implementation to their employees’ needs with targeted but economical strategies. Going beyond individual level interactions with service robots, research study 3 sheds light on an emerging phenomenon in services and office contexts, human-robot teams (HRTs.). In these teams, robotic and human capabilities can be combined to achieve organizational goals. The study combines the internal employee perspective and the external customer perspective and examines both response types to service robots in teams with an empirics-first mixed-methods approach. A first online study establishes important effects of robot design and acceptance. Specifically, android robotic team assistants are preferred over humanoid ones by employees. Relying on the expectation-disconfirmation paradigm and robot role theory, the study shows that the acceptance of the service robot is highest with high robot role expectations and corresponding high levels of experiences. A longitudinal pre-study shows that proactively behaving service robots are not well received. Finally, longitudinal team performance patterns reveal a smaller drop in performance for later team performance stages for HRTs than for a human-only team. Customers further rate the HRTs’ project outcomes higher. Notably, this study creates a comprehensive picture of HRTs and goes beyond single touch-points by providing a longitudinal perspective to these teams of the future. In summary, this work advances scientific research on human-robot interaction by shedding light on different levels of interaction and by covering multiple perspectives and areas. Besides providing new insights for each area, this dissertation transfers and extends important theories, approaches and models to robotics research with a variety of methods and instruments to create a holistic understanding. The goal is to pave the way for a successful introduction of service robots into our lives.