There is growing interest in the relationship between digital collaboration and organizational outcomes. Successful collaboration requires the development of shared meaning and representations, as well as trust among the team members (Bjørn & Ngwenyama, 2009; Kahai et al., 2007).
These elements can develop more naturally during in-person interactions, where nonverbal cues (Derks et al., 2008) and information about the interpersonal context (Van den Bossche et al., 2006) are widely available.
This can be more challenging in virtual collaboration, where non-verbal communication is limited. Because of this challenge, much attention has been given to the media capabilities that can help team members coordinate their behavior.
However, the focus has been mostly on cognitive and behavioral alignment. While cognitive alignment is central to team performance (DeChurch & Mesmer-Magnus, 2010), affective processes are also critical for work relationships and organizational outcomes (Kelly & Barsade, 2001).
Therefore, it is important that teams not only align cognitively but also affectively, as shared mood forms a ‘group affective tone’ (George, 1990). Considering how both technology and affective states mediate organizational processes and work relationships, and given the growing number of geographically dispersed teams, there is a need to understand how affective processes align when collaborative work is mediated by technology.
We are interested in working with Master students who would investigate this phenomenon of affective alignment in virtual teams. We will start running lab experiments soon, using eye tracking, galvanic skin response, heart rate variability, facial expression reading, speech analysis, etc.
We wish to work with student who would like to assist in running the experiments and subsequently conduct their own analysis on desired subsets of data. Alternatively, there is also a possibility to build up on their newly acquired experimental skills to run their own experiments in relation to emotional spread in online interaction/collaboration.
Students are most welcome to come up with suggestions related to the outlined topic. Prior experience in data analysis (SPSS, Stata, Python, R) is preferred but not mandatory. No prior experience in research or lab experiments is necessary, but it is important that students demonstrate interest in academic research and lab experiments, and the motivation to learn about those.
There might be opportunities to attend academic conferences related to the topic if that is of interest to the student. The project will start early November and therefore we invite students to manifest their interest as soon as possible.
This thesis will contribute to the ‘Mood synchronicity, collaboration media, and task outcomes’ project.
For further questions/suggestions and to discuss the collaboration, please contact: PhD Fellow Maylis Saigot, email@example.com. Please note that supervision in the Spring 2022 will be held online.