Search results

The purpose of this study is to understand the perceptual differences toward smiling behaviors with head inclinations displaying by the human-like robot staff and human staff in a service setting.

This study adopted a 2 (staff: robot/human personal personnel) × 3 (head tilt: left/right/straight) full factorial design, while cross-examining participants’ cultural dimensions 2 (power distance: high/lower) × 2 (gender: male/female) during the service encounter.

Overall, it was found that male and female customers with different cultural background would perceive robot and human personnel with varying degrees of head tilt very differently, namely, regarding interpersonal warmth but not customer satisfaction.

Nonverbal cues serve as important elements in the interaction. This paper provides new directions on the design of anthropomorphic robot and gives insight to people’s perceptual differences. All in all, the present study is useful in facilitating human–robot interactions.

The purpose of this study is to analyze the robot trends of the next generation.

This paper is divided into two sections: the key modern technology on which Europe's robotics industry has built its foundation is described. Then, the next key megatrends were analyzed.

Artificial intelligence (AI) and robotics are technologies of major importance for the development of humanity. This time is mature for the evolution of industrial and service robots. The perception of robot use has changed from threading to aiding. The cost of mass production of technological devices is decreasing, while a rich set of enabling technologies is under development. Soft mechanisms, 5G and AI have enabled us to address a wide range of new problems. Ethics should guide human behavior in addressing this newly available powerful technology in the right direction.

The paper describes the impact of new technology, such as AI and soft robotics. The world of work must react quickly to these epochal changes to enjoy their full benefits.

This study aims to examine humans’ reactions to service robots’ display of warmth in robot-to-robot interactions – a setting in which humans’ impressions of a service robot will not only be based on what this robot does in relation to humans, but also on what it does to other robots.

Service robot display of warmth was manipulated in an experimental setting in such a way that a service robot A expressed low versus high levels of warmth in relation to another service robot B.

The results indicate that a high level of warmth expressed by robot A vis-à-vis robot B boosted humans’ overall evaluations of A, and that this influence was mediated by the perceived humanness and the perceived happiness of A.

Numerous studies have examined humans’ reactions when they interact with a service robot or other synthetic agents that provide service. Future service encounters, however, will comprise also multi-robot systems, which means that there will be many opportunities for humans to be exposed to robot-to-robot interactions. Yet, this setting has hitherto rarely been examined in the service literature.

Service robots are taking over the organizational frontline. Despite a recent surge in studies on this topic, extant works are predominantly conceptual in nature. The purpose of this paper is to provide valuable empirical insights by building on the attribution theory.

Two vignette-based experimental studies were employed. Data were collected from US respondents who were randomly assigned to scenarios focusing on a hotel’s reception service and restaurant’s waiter service.

Results indicate that respondents make stronger attributions of responsibility for the service performance toward humans than toward robots, especially when a service failure occurs. Customers thus attribute responsibility to the firm rather than the frontline robot. Interestingly, the perceived stability of the performance is greater when the service is conducted by a robot than by an employee. This implies that customers expect employees to shape up after a poor service encounter but expect little improvement in robots’ performance over time.

Robots are perceived to be more representative of a firm than employees. To avoid harmful customer attributions, service providers should clearly communicate to customers that frontline robots pack sophisticated analytical, rather than simple mechanical, artificial intelligence technology that explicitly learns from service failures.

Customer responses to frontline robots have remained largely unexplored. This paper is the first to explore the attributions that customers make when they experience robots in the frontline.

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.