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Service robots are gradually becoming more anthropomorphic and intelligent. This research aims to investigate how anthropomorphic service robots with different levels of intelligence affect their human counterparts.

Two between-subject experimental studies were used to test whether different levels of service robot anthropomorphism with different levels of intelligence influence employees' morale and resistance to service robots.

Study 1 shows that the effect of service robot anthropomorphism (low vs. high) on employees' resistance and morale is mediated by perceived job-security threat. Study 2 validates this mediating effect and shows that it is moderated by the type of AI (mechanical vs. analytical). Specifically, when exposed to mechanical AI-powered service robots, employees exhibit a higher perceived job-security threat toward robots with a high (vs. low) degree of anthropomorphism. This moderating effect is not observed when employees are exposed to analytical AI-powered service robots. This moderated mediation effect is also found for the signing of a petition as the behavioral outcome.

Service firms considering the adoption of mechanical AI-powered service robots should choose a low (vs. high) anthropomorphic robot to reduce the sense of job-security threat felt by human employees, which subsequently increases their acceptance. However, if analytical AI-powered service robots with are to replace their human employees, the degree of anthropomorphism becomes irrelevant.

This is the first empirical study to explore how anthropomorphic service robots can influence human employees' evaluations and behaviors.

The purpose of this study is to explore customer-artificial intelligence (AI) service technology engagement and relationship development drivers, as well as potential negative consequences in the context of social chatbots.

A sequential mixed-method approach combined exploratory qualitative and confirmatory quantitative analyses. A conceptual model developed from Study 1 qualitative content analysis of in-depth interviews with active users of the AI social chatbot Replika was tested in Study 2 by analyzing survey data obtained from current Replika users.

Loneliness, trust and chatbot personification drive consumer engagement with social chatbots, which fosters relationship development and has the potential to cause chatbot psychological dependence. Attachment to a social chatbot intensifies the positive role of engagement in relationship development with the chatbot.

This study was the first to combine qualitative and quantitative approaches to explore drivers, boundary conditions and consequences of relationship and dependence formation with social chatbots. The authors proposed and empirically tested a novel theoretical model that revealed an engagement-based mechanism of relationship and dependence formation with social chatbots.

The human service triad (i.e. the relationship between the customer, frontline employee (FLE) and managerial employee) experiences a range of well-being challenges when faced with the introduction of service robots. Despite growth in service robot scholarship, understanding of the well-being challenges affecting the human service triad remains fragmented. Hence, the purpose of this paper is to synthesise the literature and offer a research agenda aligned with the proposed Robotic-Human Service Trilemma. By taking a job performance approach (which considers the actions, behaviours and outcomes linked to organisational goals), the Robotic-Human Service Trilemma conceptualises three well-being challenges (intrusion, sideline and interchange). These challenges are realised via the realistic capabilities and constraints of service robot implementation.

This research relies on a systematic review of all disciplines concerning service robots. In total, 82 articles were analysed using thematic coding and led to the development of the Robotic-Human Service Trilemma and research agenda.

The analyses reveal the Robotic-Human Service Trilemma consists of three challenges: intrusion, sideline and indifference. The findings demonstrate that FLEs are required to counterbalance the constraints of service robots, leading to an uneven well-being burden within the human service triad. This paper suggests a research agenda for investigation of the challenges that underpin the Robotic-Human Service Trilemma.

Through the conceptualisation of the Robotic-Human Service Trilemma, this study is the first to explore how states of well-being equilibrium exist within the human service triad and how these states are challenged by service robots. The authors present a balanced centricity perspective to well-being that contrasts previous trade-off approaches and that enhances the body of service robot literature with a well-being lens.