Multiteam systems (MTSs) are comprised of two or more teams with shared superordinate goals but unique subgoals. Membership can span diverse specialisms, both within and between organizations, creating a diverse pool of knowledge and resources to draw on. MTSs can also be scaled up or down depending on the task and situation, making them ideal for operating in risky and uncertain environments (for example, responding to terrorist attacks or calculating the response to COVID-19). Indeed, MTSs are widely adopted in a variety of extreme environments, including disasters, military operations, and medical emergencies. However, the complexity of these contexts and the large MTSs that form ad hoc to respond can make it difficult to develop facilitators traditionally associated with effective information sharing, such as familiarity, trust and shared understanding of who knows what. Poor information sharing can lead to decision delays and errors, increased workload, and distractions, in addition to hampering team performance.
The growth in MTS research over the past two decades has generated valuable insights into inter-team processes such as information sharing and coordination. However, much of this research is based on experimental methods used to study small MTSs comprised of two or three component teams with narrow goals and specializations responding to tasks of a short duration. MTSs operating in risky and uncertain environments tend to be larger, more complex and varied in shape, size and dynamism. The complex contexts in which they operate also tend to be faster paced and more dynamic than experimental settings and require MTSs to function over prolonged time periods. Whilst public inquiries often highlight problems with information sharing in large MTSs operating in extreme environments, limited research has focused on studying these processes in large MTSs within the contexts they operate, nor how processes change over time. The goal of the special issue is to present research that bridges the methodological gap between the laboratory and the real world. Paying greater attention to examining MTSs operating in risky and uncertain contexts provides opportunities for understanding how information sharing processes emerge and change over time, which is important for developing temporal theories of inter-team information sharing and improving. practice.
We are interested in original research or methods articles that focus on addressing one or more of the following issues:
• Using new methodologies to study information sharing in large multiteam systems operating in risky and uncertain environments.
• How the shape of the multiteam system (compatibility and separation of goals, knowledge, working practices, or capabilities between component teams) impacts information sharing processes within and between component teams.
• How level of variability and instability in the system (dynamism) impacts information sharing processes.
• Temporal aspects of information sharing (e.g., how do information sharing processes change over time, for example in response to feedback or changes in context, shape, instability or familiarity?).
• How the individual personality of team members impacts information sharing processes.
• What practices improve the relevance and timeliness of information sharing in ad hoc teams?
Multiteam systems (MTSs) are comprised of two or more teams with shared superordinate goals but unique subgoals. Membership can span diverse specialisms, both within and between organizations, creating a diverse pool of knowledge and resources to draw on. MTSs can also be scaled up or down depending on the task and situation, making them ideal for operating in risky and uncertain environments (for example, responding to terrorist attacks or calculating the response to COVID-19). Indeed, MTSs are widely adopted in a variety of extreme environments, including disasters, military operations, and medical emergencies. However, the complexity of these contexts and the large MTSs that form ad hoc to respond can make it difficult to develop facilitators traditionally associated with effective information sharing, such as familiarity, trust and shared understanding of who knows what. Poor information sharing can lead to decision delays and errors, increased workload, and distractions, in addition to hampering team performance.
The growth in MTS research over the past two decades has generated valuable insights into inter-team processes such as information sharing and coordination. However, much of this research is based on experimental methods used to study small MTSs comprised of two or three component teams with narrow goals and specializations responding to tasks of a short duration. MTSs operating in risky and uncertain environments tend to be larger, more complex and varied in shape, size and dynamism. The complex contexts in which they operate also tend to be faster paced and more dynamic than experimental settings and require MTSs to function over prolonged time periods. Whilst public inquiries often highlight problems with information sharing in large MTSs operating in extreme environments, limited research has focused on studying these processes in large MTSs within the contexts they operate, nor how processes change over time. The goal of the special issue is to present research that bridges the methodological gap between the laboratory and the real world. Paying greater attention to examining MTSs operating in risky and uncertain contexts provides opportunities for understanding how information sharing processes emerge and change over time, which is important for developing temporal theories of inter-team information sharing and improving. practice.
We are interested in original research or methods articles that focus on addressing one or more of the following issues:
• Using new methodologies to study information sharing in large multiteam systems operating in risky and uncertain environments.
• How the shape of the multiteam system (compatibility and separation of goals, knowledge, working practices, or capabilities between component teams) impacts information sharing processes within and between component teams.
• How level of variability and instability in the system (dynamism) impacts information sharing processes.
• Temporal aspects of information sharing (e.g., how do information sharing processes change over time, for example in response to feedback or changes in context, shape, instability or familiarity?).
• How the individual personality of team members impacts information sharing processes.
• What practices improve the relevance and timeliness of information sharing in ad hoc teams?
