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The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers.

This paper uses a conceptual approach that is rooted in the service, robotics and AI literature.

The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level.

This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots.

This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

Extant research mainly focused on potentially negative customer responses to service robots. In contrast, this study is one of the first to explore a service context where service robots are likely to be the preferred service delivery mechanism over human frontline employees. Specifically, the authors examine how customers respond to service robots in the context of embarrassing service encounters.

This study employs a mixed-method approach, whereby an in-depth qualitative study (study 1) is followed by two lab experiments (studies 2 and 3).

Results show that interactions with service robots attenuated customers' anticipated embarrassment. Study 1 identifies a number of factors that can reduce embarrassment. These include the perception that service robots have reduced agency (e.g. are not able to make moral or social judgements) and emotions (e.g. are not able to have feelings). Study 2 tests the base model and shows that people feel less embarrassed during a potentially embarrassing encounter when interacting with service robots compared to frontline employees. Finally, Study 3 confirms that perceived agency, but not emotion, fully mediates frontline counterparty (employee vs robot) effects on anticipated embarrassment.

Service robots can add value by reducing potential customer embarrassment because they are perceived to have less agency than service employees. This makes service robots the preferred service delivery mechanism for at least some customers in potentially embarrassing service encounters (e.g. in certain medical contexts).

This study is one of the first to examine a context where service robots are the preferred service delivery mechanism over human employees.

The COVID-19 pandemic has brought about a contingent shift to remote working and learning worldwide. However, little is known regarding the impact of this shift on internships. Moreover, much of the available literature studies on internships are focused largely on perceptions by students, less so by supervisors. This paper describes the impact of COVID-19 on public health (PH) internships and examines interns' and supervisors' perspectives on their experiences in internships before and during the pandemic.

A cross-sectional study design was conducted on two cohorts of undergraduate students and their supervisors in Singapore. Participants were surveyed using questionnaires with both close-ended and open-ended questions about various aspects of the internship experience. Data were triangulated from these surveys and module evaluation reports, and analyzed quantitatively and qualitatively.

COVID-19 disrupted internships significantly, with a reduction in the number of placements offered and necessary changes to the internship scope. Overall, the internship experience has been positive. Supervisors and e-interns reported high levels of satisfaction and documented learning gains such as the development of technical skills and soft skills unique to remote work.

The study findings fill current gaps in the literature on supervisor perceptions and internship experiences during COVID-19. Recommendations are proposed to optimize e-internships, a potentially authentic workplace in the post-COVID era.