How Software Agents Can Help to Coordinate Emergency Response Teams: Adaptive Team Performance Comparing Manual and Automated Team Communication

Abstract

Abstract In interprofessional emergency response teams, firefighters, police, and paramedics must communicate efficiently (i.e., request the correct expert) to avoid life-threatening consequences. However, this communication is sometimes inefficient, for example, when a wrong expert is requested due to the lack of meta-knowledge. Team research has shown that meta-knowledge of “who knows what” improves team communication, so that members correctly request each other according to their expertise. Advances in technology, such as software agents holding meta-knowledge, can be used to improve team communication. In this paper, we analyze the effects of meta-knowledge on expert seeking, mistakes in requesting experts, and (adaptive) team performance by comparing manual and automated agent-based team communication. Using a control-center simulation, 360 students in 120 three-person teams had the interdependent task of handling emergencies in three phases. We manipulated meta-knowledge in advance, with 61 teams learning and 59 teams not learning other team members’ expertise. Furthermore, in phases 1 and 3, team members had to communicate manually. In phase 2, communication was automated by a software agent taking over expert requesting. In line with our hypotheses, results showed that software agents can compensate the lack of meta-knowledge, so that there were no performance differences between teams with and without meta-knowledge with automated team communication. Our findings provide implications for research and practice that established team constructs should also be considered in human-automation teams.