Robotic Revolution: Exploring the impact of service robots in real life service settings

Driven by advancements in artificial intelligence (AI) and the increasing scarcity of labor, service robots have emerged in various industries, encompassing diverse roles in education and long-term care settings as well as serving meals in restaurants, assisting customers in supermarkets, or providing room service in hotels. The potential impact of these robots on user experiences has garnered significant attention from researchers. However, most of the existing studies evaluating robot-enabled services have been conducted in controlled laboratory settings or rely on hypothetical scenarios, limiting their applicability to real-world situations. As a result, few investigations rely on real-life human-robot interaction (HRI) at the frontline of service, considering the intricate social dynamics that occur in such contexts. In this project, we recognize that HRI during service encounters rarely occurs in isolated interactions between a single user and a robot. During many service encounters, users often partake in the experience with friends, family members, or colleagues, thereby creating what we refer to as collective frontline experiences.

What did we do?

Our research aims to explore the effects of introducing service robots and subsequent HRI on various users, including customers, employees, students, patients, and their immediate relatives. Specifically, we aim to investigate the impact of service robots in service settings that previously relied primarily on human-to-human interaction. Through three distinct studies, we will examine the influence of service robots on different types of collectives, namely:

1. Study 1: Groups of customers in hospitality settings
2. Study 2: Teams of students in higher education
3. Study 3: Constellations of patients and their formal and informal caregivers in long-term care settings

By conducting field studies, we seek to gain a comprehensive understanding of how the introduction of service robots is shaping real-life user experiences across several service settings.

What did we find out?

Study 1 (status: under review):  Service robot research recognizes that dyadic customer–service provider interactions do not occur in isolation, yet it has not comprehensively detailed HRI in collective frontline settings. In study 1, we gathered online hotel reviews referring to service robots, to identify how customers appraise and cope with HRI during collective frontline experiences. Based on these findings and relevant literature, we proposed a conceptual model of the impact of HRI on post-purchase service outcomes. Tests of the model with field data from customers who interacted with a service robot in a restaurant reveal that their challenge appraisals of HRI drive problem-focused, emotion-focused, and support-seeking coping strategies, whereas threat appraisals lead to emotion-focused coping. Such coping efforts during collective frontline experiences produce shared realities of the robot across customers, reducing switching intention and boosting relational well-being. Stressing the importance of perceived shared realities about the robot during collective frontline experiences, this study proposes the novel concept of plural humans–robot interaction (HsRI).

Study 2 (status: preparing submission): Learning and working from home by using information and communication technologies has become a new standard in higher education, in which following classes from home has advantages for students being sick, combining school and work, or living too far away. However, this poses a challenge to small-scale, collaborative learning settings. Collaborative learning settings, such as problem-based learning, have much been used because of their effectiveness for (team) learning and student performance. In such settings, group dynamics are essential for student engagement and successful collaboration, yet jeopardized when online students join their physically present team members via a laptop or smartboard. Namely, the asymmetry of presence – i.e., remote students are less present compared to their physically present counterparts – might lead to online students being less active and included in the group process. We posit that introducing a service robot, providing remote students with embodiment in the classroom, could mitigate this asynchrony of presence.

In this study, we investigate whether and how group dynamics are impacted by introducing a service robot in student teams collaborating in a blended classroom. We conducted an exploratory longitudinal field experiment and interviewed students in two Master of Science courses of an international business degree program. Analysis of our longitudinal data indicates that making use of a service robot that provides telepresence and embodiment to remote students has a strong positive effect on group dynamics in small-scale, collaborative teams, especially during the early stages of the course.

To get a deeper understanding of the results from our quantitative study and to further investigate how a service robot impacts group dynamics, we conducted in-depth qualitative interviews with students who experienced the robot in the classroom as well as students who used the robot remotely. Interview data suggest that embodiment by the service robot improves perceptions of physical and social presence, thereby reducing the asymmetry of presence in the blended classroom. With this mixed-method-approach, we make important contributions to the literature on service robots as well as group dynamics in the blended classroom in higher education.

Study 3 (status: data collection): In this study, we follow the implementation of service robots in six different long-term disability care providers. Leveraging the unique longitudinal opportunity of being able to follow such implementation project prior to real implementation, we first focus on investigating the expectations of employees, clients, and informal caregivers (such as close relatives or legal representatives) regarding the implementation of service robots. In a second interview round, we conduct in depth interviews with these stakeholders to gather insights about their experiences and reality two months after the implementation. Our study encompasses twenty distinct cases across these six different long-term care providers, each comprising a patient and their close care network consisting of both formal and informal caregivers.

The frontline of organizational care already involves complex interactions among patients, formal caregivers, and informal caregivers. The introduction of autonomous service robots is assumed to further amplify this complexity. Therefore, our study aims to comprehend the key factors that contribute to the successful implementation of service robots from the perspectives of the involved actors. It is worth noting that while patients and informal caregivers primarily interact with the service robot, employees also engage with the accompanying knowledge-based system for programming the robot. Furthermore, the goals and expectations of these actors may differ significantly. For instance, organisations may prioritize efficiency or timesaving, patients welcome help with day structure and loneliness prevention, formal caregivers may focus on stress reduction or depth of patient contact, while informal caregivers may seek to alleviate their burdens.