Although different types of teams increasingly employ embodied physical action (EPA) robots as a collaborative technology to accomplish their work, we know very little about what makes such teams successful. This paper has two objectives: the first is to examine whether a team's emotional attachment to its robots can lead to better team performance and viability; the second is to determine whether robot and team identification can promote a team's emotional attachment to its robots. To achieve these objectives, we conducted a between-subjects experiment with 57 teams working with robots. Teams performed better and were more viable when they were emotionally attached to their robots. Both robot and team identification increased a team's emotional attachment to its robots. Results of this study have implications for collaboration using EPA robots specifically and for collaboration technology in general.
Despite the benefits associated with virtual teams, many people on these teams are unsatisfied with their experience. The goal of this study was to determine how to better facilitate satisfaction through shared leadership, individual trust, and autonomy. Specifically, in this study we sought a better understanding of the effects of shared leadership, team members’ trust, and autonomy on satisfaction. We conducted a study with 163 individuals in 44 virtual teams. The results indicate that shared leadership facilitates satisfaction in virtual teams both directly and indirectly through the promotion of trust. Shared leadership moderated the relationships of individual trust and individual autonomy with satisfaction. Team‐level satisfaction was a strong predictor of virtual team performance. We discuss these findings and the implications for theory and design.
Organizations now face a new challenge of encouraging their employees to work alongside robots. In this paper, we address this problem by investigating the impacts of human-robot similarity, trust in a robot, and the risk of physical danger on individuals' willingness to work with a robot and their willingness to work with a robot over a human co-worker. We report the results from an online experimental study involving 200 participants. Results showed that human-robot similarity promoted trust in a robot, which led to willingness to work with robots and ultimately willingness to work with a robot over a human co-worker. However, the risk of danger moderated not only the positive link between the surface-level similarity and trust in a robot, but also the link between intention to work with the robot and willingness to work with a robot over a human coworker. We discuss several implications for the theory of human-robot interaction and design of robots.
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Advances in robotics now permit humans to work collaboratively with robots. However, humans often feel unsafe working alongside robots. Our knowledge of how to help humans overcome this issue is limited by two challenges. One, it is difficult, expensive and time-consuming to prototype robots and set up various work situations needed to conduct studies in this area. Two, we lack strong theoretical models to predict and explain perceived safety and its influence on human-robot work collaboration (HRWC). To address these issues, we introduce the Robot Acceptance Safety Model (RASM) and employ immersive virtual environments (IVEs) to examine perceived safety of working on tasks alongside a robot. Results from a between-subjects experiment done in an IVE show that separation of work areas between robots and humans increases perceived safety by promoting team identification and trust in the robot. In addition, the more participants felt it was safe to work with the robot, the more willing they were to work alongside the robot in the future.
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