Motivational Theory of Human Robot Teamwork

This paper presents a theory that allows us to better understand motivation in human‒robot teamwork. Teamwork with robots often involves both physical and mental activities. This implies that motivation might be particularly important to the success of human robot teams. Unfortunately, there is much we do not know with regards to the role of motivation in effective teamwork with robots. In this paper we propose the “Motivational Theory of Human‒Robot Teamwork” to better understand teamwork in human‒robot teams. In doing so, we leverage the research on robot personality.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145157/1/Motivation and Personality (2 cols) July 19 2018.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145157/4/Robert 2018.pdfDescription of Motivation and Personality (2 cols) July 19 2018.pdf : Preprint ArticleDescription of Robert 2018.pdf : Published Versio

Far but Near or Near but Far?: The Effects of Perceived Distance on the Relationship between Geographic Dispersion and Perceived Diversity

Geographic dispersion has been proposed as one means to promote cooperation and coordination in teams high in perceived diversity. However, research has found mixed support for this assertion. This study proposes that the inclusion of perceived distance helps to explain these mixed results. To test this assertion, we examined 121 teams—62 collocated and 59 geographically dispersed. Results demonstrate that perceived distance explains when geographic dispersion benefits teams high in perceived diversity. Results also indicate that the type of perceived diversity matters (surface-level vs. deep-level diversity). This study contributes to our understanding of distance and diversity in teams.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116792/1/paper2483 (Final Submission).pdfDescription of paper2483 (Final Submission).pdf : Main Articl

Trusting Robots in Teams: Examining the Impacts of Trusting Robots on Team Performance and Satisfaction

Despite the widespread use of robots in teams, there is still much to learn about what facilitates better performance in these teams working with robots. Although trust has been shown to be a strong predictor of performance in all-human teams, we do not fully know if trust plays the same critical role in teams working with robots. This study examines how to facilitate trust and its importance on the performance of teams working with robots. A 2 (robot identification vs. no robot identification) × 2 (team identification vs. no team identification) between-subjects experiment with 54 teams working with robots was conducted. Results indicate that robot identification increased trust in robots and team identification increased trust in one’s teammates. Trust in robots increased team performance while trust in teammates increased satisfaction.http://doi.org/10.24251/hicss.2019.031Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145619/1/You and Robert 2019 (Preprint).pd

Personality in Healthcare Human Robot Interaction (H-HRI): A Literature Review and Brief Critique

Robots are becoming an important way to deliver health care, and personality is vital to understanding their effectiveness. Despite this, there is a lack of a systematic overarching understanding of personality in health care human robot interaction (H-HRI). To address this, the authors conducted a review that identified 18 studies on personality in H-HRI. This paper presents the results of that systematic literature review. Insights are derived from this review regarding the methodologies, outcomes, and samples utilized. The authors of this review discuss findings across this literature while identifying several gaps worthy of attention. Overall, this paper is an important starting point in understanding personality in H-HRI.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156252/1/Esterwood and Robert 2020.pdfDescription of Esterwood and Robert 2020.pdf : ArticleSEL

Curiosity vs. Control: Impacts of Training on Performance of Teams Working with Robots

Training robot operators is one approach to promoting better performance in teams working with robots. Yet, training does not always result in better performance. This study conducts a preliminary analysis of why by examining two psychological states of use: control and curiosity. An experimental study involving 30 teams two humans and two robots employing robots was conducted. Results showed that training minimized the negative impacts of curiosity and heightened the positive impacts of control on task involving the use of a robot.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116395/1/You and Robert 2016.pd

Emotional Attachment, Performance, and Viability in Teams Collaborating with Embodied Physical Action (EPA) Robots

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

Technology Affordances and IT Identity

The study attempts to understand the impact of technology affordances on identifying the self with technology (IT identity). Furthermore, it seeks to understand the role of experiences in mediating the relationship between technology affordances and IT identity. To answer our research questions, we will conduct a cross-sectional survey

Facilitating Employee Intention to Work with Robots

Organizations are adopting and integrating robots to work with and alongside their human employees. However, their human employees are not necessarily happy about this new work arrangement. This may be in part due to the increasing fears that robots will eventually take their jobs. Organizations are now facing the challenge of integrating robots into their workforce by encouraging humans to work with their robotic teammates. To address this issue, this study employs similarity and attraction theory to encourage humans to work with and alongside their robotic co-worker. Our research model asserts that surface and deep level similarity with the robot will impact a human’s willingness to work with a robot. We also seek to examine whether risk moderates the importance of both surface and deep level similarity. To empirically examine this model, this proposal presents an experimental design. Results of the study should provide new insights into the benefits and limitations of similarity to encourage humans to work with and alongside their robot co-worker

Alternative Group Technologies and Their Influence on Group Technology Acceptance

There is a long history of study to understand why work groups do or do not adopt new collaboration technologies. However, research has focused on only one technology. The underlying assumption is that work groups can adopt or not adopt that one technology based on that technology alone. In making this assumption, many researchers have failed to realize the importance of alternative technologies in the adoption process or the fact that groups can adopt more than one technology. To address this issue, we examined an attempt by a scientific research organization to have its work groups adopt a particular group-collaboration technology. Although the target technology was more than appropriate for the task and the organization provided all the resources needed for work groups to adopt the technology, i largely failed. This was in large part because of two alternative collaboration technologies that acted as substitutes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144537/1/AJIS_7000100087_20180619_1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144537/4/Ammari et al. 2018.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144537/6/Ammari et al. 2018 (Published).pdfDescription of Ammari et al. 2018.pdf : Forthcoming versionDescription of Ammari et al. 2018 (Published).pdf : Final Versio

Herding a Deluge of Good Samaritans: How GitHub Projects Respond to Increased Attention

Collaborative crowdsourcing is a well-established model of work, especially in the case of open source software development. The structure and operation of these virtual and loosely-knit teams differ from traditional organizations. As such, little is known about how their behavior may change in response to an increase in external attention. To understand these dynamics, we analyze millions of actions of thousands of contributors in over 1100 open source software projects that topped the GitHub Trending Projects page and thus experienced a large increase in attention, in comparison to a control group of projects identified through propensity score matching. In carrying out our research, we use the lens of organizational change, which considers the challenges teams face during rapid growth and how they adapt their work routines, organizational structure, and management style. We show that trending results in an explosive growth in the effective team size. However, most newcomers make only shallow and transient contributions. In response, the original team transitions towards administrative roles, responding to requests and reviewing work done by newcomers. Projects evolve towards a more distributed coordination model with newcomers becoming more central, albeit in limited ways. Additionally, teams become more modular with subgroups specializing in different aspects of the project. We discuss broader implications for collaborative crowdsourcing teams that face attention shocks.National Science Foundation Grant No. IIS-1617820.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153786/1/Maldeniya et al. 2020.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153786/4/Maldeniya et al. 2020 Published Version.pdfDescription of Maldeniya et al. 2020.pdf : Main ArticleDescription of Maldeniya et al. 2020 Published Version.pdf : Published Versio