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Social robots increasingly adopt service roles in the marketplace. While service research is beginning to unravel the implications for theory and practice, other scientific disciplines have amassed a wealth of empirical data of robots assuming such service roles. The purpose of this paper is to synthesize these findings from a role theory perspective with the aim of advancing role theory for human–robot service interaction (HRSI).

A systematic review of more than 10,000 articles revealed 149 empirical HRSI-related papers across scientific disciplines. The respective articles are analyzed employing qualitative content analysis through the lens of role theory.

This review develops an organizing structure of the HRSI literature across disciplines, delineates implications for role theory development in the age of social robots, and advances robotic role theory by providing an overarching framework and corresponding propositions. Finally, this review introduces avenues for future research.

This study pioneers a comprehensive review of empirical HRSI literature across disciplines adopting the lens of role theory. The study structures the body of HRSI literature, adapts traditional and derives novel propositions for role theory (i.e. robotic role theory), and delineates promising future research opportunities.

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.

With the advent of increasingly sophisticated AI, the nature of work in the service frontline is changing. The next frontier is to go beyond replacing routine tasks and augmenting service employees with AI. The purpose of this paper is to investigate whether service employees augmented with AI-based emotion recognition software are more effective in interpersonal emotion regulation (IER) and whether and how IER impacts their own affective well-being.

For the underlying study, an AI-based emotion recognition software was developed in order to assist service employees in managing customer emotions. A field study based on 2,459 call center service interactions assessed the effectiveness of the AI in augmenting service employees for IER and the immediate downstream consequences for well-being relevant outcomes.

Augmenting service employees with AI significantly improved their IER activities. Employees in the AI (vs control) condition were significantly more effective in regulating customer emotions. IER goal attainment, in turn, mediated the effect on employee affective well-being. Perceived stress related to exposure to the AI augmentation acted as a competing mediator.

Service firms can benefit from state-of-the-art AI technology by focusing on its capacity to augment rather than merely replacing employees. Furthermore, signaling IER goal attainment with the help of technology may provide uplifting consequences for service employee affective well-being.

The present study is among the first to empirically test the introduction of an AI-fueled technology to augment service employees in handling customer emotions. This paper further complements the literature by investigating IER in a real-life setting and by uncovering goal attainment as a new mechanism underlying the effect of IER on the well-being of the sender.

Service research offering a view of both the dark and bright sides of smart technology remains scarce. This paper embraces a critical perspective and examines the conflicting outcomes of smart services on the customer experience (CX), with a specific focus on chatbots.

This study uses empirical research methods to examine a single case study where an online retail service provider implemented a chatbot for customer service. Using discourse analysis, we analysed 7,167 conversations between customers and the chatbot over a two-year period.

The analysis identifies seven general themes related to the effects of the chatbot on CX: interaction quality, information gathering, procedure literacy, task achievement, digital trust, shopping stress and shopping journey. We illuminate both positive (i.e. having a pleasant interaction, providing information, knowing procedures, improving tasks, increasing trust, reducing stress and completing the journey) and negative outcomes (i.e. having an unpleasant interaction, increasing confusion, ignoring procedures, worsening tasks, reducing trust, increasing stress and abandoning the journey).

The paper develops a comprehensive framework to offer a clearer view of chatbots as smart services in customer care. It delves into the conflicting effects of chatbots on CX by examining them through relational, cognitive, affective and behavioural dimensions.

Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their smartness profiles, composed of five distinct smartness facets. Additionally, the study investigates how these perceptions of product intelligence impact consumers' evaluation of factors that either promote or impede the adoption of smart products. These factors are examined as potential mediators in the adoption process. This paper aims to determine if the value-based adoption model can be applied to a broad range of smart service systems.

Consumers assessed one of 28 smart products in a scenario-based quantitative study. Multilevel structural equation modeling (SEM) is used to test the conceptual model, taking the nested data structure into account.

The findings show that product smartness essentially enhances usage intention via adoption drivers (enjoyment and usefulness) and reduces usage intention via adoption barriers (intrusiveness). In particular, the ability to interact in a humanlike manner increases the benefits consumers perceive, which in turn increases consumer acceptance. Only the smartness characteristic of awareness impairs usage intention, mediated by the perceived benefits of enjoyment and usefulness.

In contrast to previous research, which usually focuses on single smart products, this work examines a variety of different products, which allows for better transferability of the results to other smart offerings. Furthermore, prior research has mainly focused on single facets of product smartness or researched smartness on an aggregated level. By considering the consumer perception of each smartness facet, the authors gain deeper insights into the perceptual differences regarding product smartness and how this affects technology adoption via conflicting key acceptance drivers and barriers.

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 assess, clarify and consolidate the terminology around the co-creation of services, establish its forms and identify its outcomes, to resolve the conceptual pluralism in service co-creation literature.

A focused literature review screened the articles published in five major service research journals to determine relevant contributions on the concept of co-creation of services. Then, a thematic analysis identifies the forms, themes and outcomes of co-creating services in the set of 80 qualifying articles.

The study reduces conceptual pluralism by establishing different forms of co-creating services and developing an explicit definition of co-creation in services. The authors develop an integrative framework that recognizes involvement, engagement and participation as prerequisites for co-creation. Relating to the different phases of the service process, the specific co-creation forms of co-ideation, co-valuation, co-design, co-testing and co-launching are classified as regenerative co-creation, while the specific co-creation forms of co-production and co-consumption are recognized as operative co-creation. Both beneficial and counterproductive outcomes of co-creation are identified and arranged into a typology.

The integrative framework illustrates that service providers and customers are involved, engaged and participate in co-creating services, which manifests in specific forms of co-creation; they attain beneficial and counterproductive outcomes (personal, social, hedonic, cognitive, economic and pragmatic); and are influenced by a contextual multi-actor network.

Co-creation in services is actionable; the typology of outcomes suggests service managers ways to motivate customers and employees to participate in co-creating services.

This paper defines and establishes the conceptual forms of co-creating services and the identified outcomes, and develops an integrative framework of co-creation in services.

The study analyses the role that open social innovation (OSI) perspective played for Fondazione Banco Alimentare Onlus (FBAO), a food bank in Italy, in responding to the COVID-19 crisis. It answers the following research question: how does a crisis, such as the COVID-19 pandemic, stimulate the adoption of OSI practices to revamp the activities of FBAO and facilitate appropriate solutions to carry out its social mission?

This study employs a qualitative approach. It is based on a single case study.

The study shows how COVID-19 has stimulated the adoption of OSI practices to continue to meet the social mission, creating innovative projects or finding new ways to do the same things.

The study is based on a single case study.

The paper contributes insights into the literature on OSI, examining how inbound and outbound OSI mechanisms can modify business models and increase the adaptation capacity of food banks and their effectiveness. In addition, it provides a rich context in which the social value drivers provided by OSI are studied.

This paper applies the OSI to a food bank to evaluate what this action mode produces for the food bank during a health crisis. Specifically, this is the first paper that studies the COVID-19 crisis response of a food bank from the OSI perspective, focusing on the inbound and outbound OSI processes that characterized the entire network of relationships.

Professional associations mark an important step in the development of any profession. Research Management and Administration (RMA) as a profession is still emerging across Europe, thus the relevance of RMA associations is pertinent. These associations operate either specifically at the transnational or international levels or have certain activities linked to both levels. The theory of social constructivism from the field of international relations will be applied in this analysis with a goal to add additional insights on the topic. The results confirm that RMA associations have an outstanding role in enforcing the internationalised culture of their members, however, members in return can also exert influence on their association. Members are also aware that the association is providing a platform for collective actions in policymaking at national, transnational, and international levels. However, time plays a crucial role in social learning for identity and interest formation, as well as in recognizing the role of RMA associations in corporate agency.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.