Abstract
The purpose of this study was to discover the relationships among 18 psychological features in a cooperative team in order to analyse work team performance. A Bayesian network (BN) has been built from a dataset of 403 soccer semi-professional players, taking into account prototypical sportive teams with respect to other workteams, regarding its psychological features, such as leadership, cohesion or group roles. The BN shows three conditionally independent features according to the local Markov property: two cohesion dimensions and the cooperative style of management/coaching; and features such as players satisfaction, experience, social integration in the team, and the workplace specificity, i.e., the players’ positions, which were located at the bottom in the BN show a clear dependence. The BN was used to make inferences achieving: (1) The social side of the cohesion has a low likelihood influence on the performance; (2) All psychological leadership styles (positive and/or negative) have some influence on the performance, the years remaining in the same team, and the player’s position; (3) The positive leadership style is not a required condition for the performance or for the player’s satisfaction, but a consequence of the other psychological variables.
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This research was funded by the Spanish Ministry of Science and Innovation (PI13/01477).
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Fuster-Parra, P., García-Mas, A., Cantallops, J., Ponseti, F.J. (2015). Cooperative Team Work Analysis and Modeling: A Bayesian Network Approach. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2015. Lecture Notes in Computer Science(), vol 9320. Springer, Cham. https://doi.org/10.1007/978-3-319-24132-6_1
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