Objective
Successful teamwork is crucial to solve many of today’s key problems, but to effectively perform the tasks, team members have to build a shared mental model (i.e. a shared understanding about who does what, when, and with whom) successfully and in a timely manner. I aim to tackle the (implicit) view in the literature that one level of convergence is appropriate for all teams, by analysing the shared mental model changing patterns (i.e. trajectories) of different teams via interdependence theory. This project aims to uncover the range of possible shared mental model trajectories, and understand whether and why different trajectories occur in different types of teams and what the implications for team performance are. I will conduct two longitudinal empirical studies. Study A will analyse the individual team members’ perception of shared mental models. I will use Academic Prolific to target 400 respondents. This study allows me to determine the best timing and interval length to capture shared mental models. Study B will build upon the insights I will gain from Study A to understand which trajectories fit with each type of team and what the implications for performance are. For Study B, I will collect data in 80 teams (team members and leaders) from different industries and sectors. As teamwork is essential to create a competitive European Union, my project will contribute to the development of the European Union labour market for the 21st century. I will accomplish this project by combining my expertise with the expertise in time research and interdependence theory at Maastricht University. Overall, this project and the foreseen two top publications will increase my research-related (e.g. methodological) and transferable (e.g. valorisation of knowledge) skills, which will bring me a significant leap in my career and increase my employability and career prospects in academia.
Programme(s)
Call for proposal
H2020-MSCA-IF-2018
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Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
6200 MD Maastricht
Netherlands