Understanding team collapse via probabilistic graphical models

arXiv:2402.10243v1 Announce Type: cross
Abstract: In this work, we develop a graphical model to capture team dynamics. We analyze the model and show how to learn its parameters from data. Using our model we study the phenomenon of team collapse from a computational perspective. We use simulations and real-world experiments to find the main causes of team collapse. We also provide the principles of building resilient teams, i.e., teams that avoid collapsing. Finally, we use our model to analyze the …

abstract analyze arxiv computational cs.lg cs.si data dynamics how to learn learn parameters perspective physics.soc-ph show simulations study team type understanding via work world