This study examines the differences between hierarchical and network teams in emergency management. A controlled experimental environment was created in which we could study teams that differed in decision rights, availability of information, information sharing, and task division. Thirty-two teams of either two (network) or three (hierarchy) participants (N ¼ 80 in total) received messages about an incident in a tunnel with high-ranking politicians possibly being present. Based on experimentally induced knowledge, teams had to decide as quickly and as accurately as possible what the likely cause of the incident was: an attack by Al Qaeda, by anti-globalists, or an accident. The results showed that network teams were overall faster and more accurate in difficult scenarios than hierarchical teams. Network teams also shared more knowledge in the difficult scenarios, compared with the easier scenarios. The advantage of being able to share information that is inherent in network teams is thus contingent upon the type of situation encountered.
Computational models of attention can be used as a component of decision support systems. For accurate support, a computational model of attention has to be valid and robust. The effects of task performance and task complexity on the validity of three different computational models of attention were investigated in an experiment. The gaze-based model uses gaze behavior to determine where the subject's attention is, the task-based model uses information about the task and the combined model uses both gaze behavior and task information. While performing a tactical compilation task, participants had to indicate to what set of objects their attention was allocated. The indications of the participants were compared with the estimations of the three models. The results show that overall, the estimation of the combined model was better than that of the other two models. Contrary to what was expected, the performance of the models was not different for good and bad performers and was not different for a simple and complex scenario. The difference in complexity and performance might not have been strong enough. Further research is needed to determine if improvement of the combined model is possible with additional features and if computational models of attention can effectively be used in decision support systems. This can be done using a similar validation methodology as presented in this paper.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.