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There is growing interest in the use of human-like social robots, able to undertake complex tasks whilst building consumer engagement. However, further exploration is needed on the optimal level of humanoid appearance for service robots. In particular, the literature is limited with respect to mitigating disconfirmed expectations for robots high in human-likeness. This paper aims to address this gap by testing the effect of robot appearance, disconfirmed expectations and warmth (vs competence) on customers’ responses.

The study adopts a mixed-method design by presenting a focus group (Study 1) that guides two laboratory experiments (Studies 2 and 3). Studies 2 and 3 test for the moderating effect of warmth (vs competence) and the mediating roles of perceived eeriness and disconfirmed expectations.

The findings show that a robot high (vs low) in human-likeness leads to higher negative customers’ responses, which is explained by disconfirmed expectations rather than perceived eeriness. However, when customers interact with a warm (vs competent) robot high in human-likeness, this negative effect vanishes.

The paper investigates boundary conditions and underlying mechanisms that affect customers’ experiences. Although the study adopts high realistic experiments, a limitation lies in not measuring customers’ actual behaviours in the field.

This study provides new insights on how the appearance and characteristics of social robots influence the consumers’ experience. By doing so, this study offers managers actionable insights (i.e. enhancing warmth) to lessen the risk of disconfirmed expectations.

The paper offers new explanations as to why human-like robots can generate negative responses from customers. Moving beyond the “uncanny valley” hypothesis, this study shows the key role of disconfirmed expectations in explaining consumers’ negative responses towards humanoid robots. Moreover, it sheds light on the moderating role of warmth (vs competence), which can mitigate such negative effects.

Besides the direct physical health consequences, through social isolation COVID-19 affects a considerably larger share of consumers with deleterious effects for their psychological well-being. Two vulnerable consumer groups are particularly affected: older adults and children. The purpose of the underlying paper is to take a transformative research perspective on how social robots can be deployed for advancing the well-being of these vulnerable consumers and to spur robotic transformative service research (RTSR).

This paper follows a conceptual approach that integrates findings from various domains: service research, social robotics, social psychology and medicine.

Two key findings advanced in this paper are (1) a typology of robotic transformative service (i.e. entertainer, social enabler, mentor and friend) as a function of consumers' state of social isolation, well-being focus and robot capabilities and (2) a future research agenda for RTSR.

This paper guides service consumers and providers and robot developers in identifying and developing the most appropriate social robot type for advancing the well-being of vulnerable consumers in social isolation.

This study is the first to integrate social robotics and transformative service research by developing a typology of social robots as a guiding framework for assessing the status quo of transformative robotic service on the basis of which it advances a future research agenda for RTSR. It further complements the underdeveloped body of service research with a focus on eudaimonic consumer well-being.

In recent developments in Artificial Intelligence (AI) and especially in robotics we can observe a tendency towards building intelligent artefacts that are meant to be social, to have ‘human social’ characteristics like emotions, the ability to conduct dialogue, to learn, to develop personality, character traits, and social competencies. Care, entertainment, pet and educational robots are conceptualised as friendly, understanding partners and credible assistants which communicate ‘naturally’ with users, show emotions and support them in everyday life. Social robots are often designed to interact physically, affectively and socially with humans in order to learn from them. To achieve this goal, roboticists often model the human‐robot interaction on early caregiver‐infant interactions. In this paper I want to analyse prominent visions of these ‘socio‐emotional’ machines as well as early prototypes and commercial products with regard to the human‐machine interface. By means of this I will ask how feminist critiques of technology could be applied to the field of social robotics in which concepts like sociality or emotion are crucial elements while, at the same time, these concepts play an important role in feminist critiques of technology.

On the verge of what has been hailed as the next technological revolution, the purpose of this paper is to examine scientific and popular definitions of the social robot, reflecting on how expert and lay spheres of knowledge interact. Drawing on social representations theory, this paper aims to elucidate how social robots are named and classified, and to examine the dynamics contributing to their definition.

Scientific and popular definitions of the social robot were investigated by conducting: a systematic review of relevant articles published from 2009 to 2015 in the International Journal of Social Robotics; an analysis of the definitions retrievable from the scientific literature using Google Scholar; and an assessment of the interest in the public sphere, and of the popular definitions retrievable online (by inputting “social robot” in Google Trends, and in Google).

Scientific definitions of the social robot adopt two strategies, one drawing on and merging previous definitions, the other proposing new, visionary, forward-looking definitions. Popular online definitions of social robots attribute new emotional, linguistic and social capabilities to their physical body.

The findings need to be confirmed by further research, given the limited size of the data sets considered, and the distortions in the data due to filters and the opacity of the online tools employed.

Both scientific and non-scientific definitions see social robots as being capable of interacting with and working for humans, but attribute them a different degree of (functional or full) autonomy. In future, any controversy over the connotation of social robots is likely to concern their sociality and autonomy rather than their functionality.

The technological revolution in the service sector is radically changing the ways in which and with whom consumers co-create value. This conceptual paper considers social robots in elderly care services and outlines ways in which their human-like affect and cognition influence users’ social perceptions and anticipations of robots’ value co-creation or co-destruction potential. A future research agenda offers relevant, conceptually robust directions for stimulating the advancement of knowledge and understanding in this nascent field.

Drawing from service, robotics and social cognition research, this paper develops a conceptual understanding of the value co-creation/destruction potential of social robots in services.

Three theoretical propositions construct an iterative framework of users’ evaluations of social robots in services. First, social robots offer users value propositions leveraging affective and cognitive resources. Second, users’ personal values become salient through interactions with social robots’ affective and cognitive resources. Third, users evaluate social robots’ value co-creation/destruction potential according to social cognition dimensions.

Social robots in services are an emerging topic in service research and hold promising implications for organizations and users. This relevant, conceptually robust framework advances scholarly understanding of their opportunities and pitfalls for realizing value. This study also identifies guidelines for service managers for designing and introducing social robots into complex service environments.

The purpose of this study is to evaluate service robots as an alternative service provider that can reduce customers’ social discomfort in hospitality service encounters. Specifically, the authors discuss when and in what scenarios service robots can alleviate such social discomfort and explain this effect from the perspective of dehumanization.

Following a social constructivist paradigm, the authors adopt a qualitative research design, gathering data through 21 semistructured interviews to explore why the presence of service employees causes customers’ social discomfort in hospitality service encounters and how service robots alleviate such discomfort.

This study’s results suggest that both the active and passive engagement of service employees are sources of customers’ social discomfort in hospitality service encounters; thus, adopting service robots can help reduce such discomfort in some scenarios. Customers’ differentiating behaviors, a downstream effect of social discomfort, are also addressed.

Service robots can reduce customers’ social discomfort in certain scenarios and influence their consumption behaviors. This finding offers actionable insights regarding the adoption of service robots in hospitality service encounters.

This research enhances the understanding of social discomfort in hospitality service encounters and expands the research on service robots. To the best of the authors’ knowledge, it is the first attempt to reveal the bright side of robots in service encounters from a dehumanization perspective.

Social robot, a subtype of robots that is designed for the various interactive services for human, which must deliver superior user experience (UX) by expressing human-like social behavior or service and emotional sensitivity. This study develops a social robot app called the “Music Buddy” in ASUS Zenbo that provides a situational music based on the users' electroencephalogram (EEG) data. The research uses this app to explore its UX criteria and the prioritization of human robot interaction (HRI).

The research methodologies include the both system development and decision analysis for the social robot. The first part is to design and develop a social robot app. The second part is to investigate the criteria of HRI through the Analytic Hierarchy Process (AHP) from UX aspects.

In view of the results of the AHP, the first-layer criteria consist of personalized function, easy-to-use the system and intelligent process. In terms of prioritization of multi-criteria, the overall ranking discloses the nine criteria in order including autonomy for robot, easy-to-use EEG device, accurate music preference, simple operations for brainwave device and easy-to-use applications, active music recommendation, automatic updates of music and easy-to-use robot as well as fast detection for emotion.

This research includes a self-developed social robot app and its UX research using AHP. This paper contributes to the improvement and innovation of the social robot design according to the results of UX research on HRI of social robot.

Loneliness and isolation are on the rise, globally threatening the well-being across age groups; global social distancing measures during the COVID-19 crisis have intensified this so-called “loneliness virus”. The purpose of this paper is to develop an integrative framework and research agenda on the role of companion robots in mitigating feelings of loneliness.

A netnographic analysis of 595 online visual and textual descriptions offer empirical insights about the role of the companion robot Vector during the COVID-19 pandemic.

The contributions of this study are twofold. First, it postulates that companion robots have the potential of mitigating feelings of loneliness (i.e. indicator of well-being). Second, this study contributes to transformative service by developing an integrative framework introducing the roles (personal assistant, relational peer and intimate buddy) that companion robots can fulfill to mitigate feelings of loneliness through building different types of supportive relationships.

The proposed research agenda encourages future service scholars to investigate 1) the role of robots in addressing loneliness, 2) design features that drive adoption of robots, 3) social support for different groups, 4) the operationalization and the measurement of loneliness and 5) an impact analysis of companion robots.

Service providers and policy makers can leverage the insights about how companion robots can help reduce a sense of loneliness.

The integrative framework on loneliness reduction, based on 595 unprompted online contributions issued during the COVID-19 pandemic, offers initial evidence for the impact of companion robots in reducing people's feelings of loneliness.

The purpose of this paper is to address the role of social robots in the education industry, specifically within special developmental schools, as a part of an innovation technology portfolio. It identifies critical success factors (CSFs) arising from the development, adoption and implementation of social robots to educate students with special needs and assist their teachers.

The study engaged in longitudinal research over 12 months, tracking the role of the Matilda robot in providing educational services to students with special needs.

The results propose a three-faceted framework for social robot application in special education: development, adoption and implementation.

The study has shown the willingness of students and teachers to embrace social robot technology, and the CSF that arise from this adoption. It has also found that social robots achieve the greatest success within the development, adoption and implementation framework when championed by executive management, and peer teacher support.

This review scopes evidence on the use of social robots for older adults with depressive symptoms, in the scenario of smart cities, analyzing the age-related depression specificities, investigated contexts and intervention protocols' features.

Studies retrieved from two major databases were selected against inclusion and exclusion criteria. Studies were included if used social robots, included older adults over 60, and reported depressive symptoms measurements, with any type of research design. Papers not published in English, published as an abstract or study protocol, or not peer-reviewed were excluded.

28 relevant studies were included, in which PARO was the most used robot. Most studies included very older adults with neurocognitive disorders living in long-term care facilities. The intervention protocols were heterogeneous regarding the duration, session duration and frequency. Only 35.6% of the studies had a control group. Finally, only 32.1% of the studies showed a significant improvement in depression symptoms.

Despite the potential for using social robots in mental health interventions, in the scenario of smart cities, this review showed that their usefulness and effects in improving depressive symptoms in older adults have low internal and external validity. Future studies should consider factors as planning the intervention based on well-established supported therapies, characteristics and needs of the subjects, and the context in which the subjects are inserted.