At the ATR Lab, we study dynamic teams operating in extreme and fluid contexts. This refers to teams collaborating across boundaries to address extreme events (e.g., firefighters and healthcare, military, and Antarctica research teams) or ad-hoc basis (e.g., management teams working on sustainability crises, social initiatives organized during the pandemic and war, etc.). To reach our goals, we conduct internationally recognized studies applying a multi-method approach. We observe teams in the field, as well as in experimental settings, using qualitative and quantitative research methods. Further, we create outreach by interacting closely with key players from various industries translating our findings into the workplace.
Effects of team reflexivity on individual and team outcomes
Our research examines the effectiveness of team reflexivity, which can be defined as a team learning process that involves evaluating past actions, the group's goals or procedures, forming intentions, and making decisions about future actions. This process can occur through brief "bursts" of reflection during a task (e.g., team time-out) or longer debriefings. We investigate the key elements of successful team reflexivity and its effects on individual and team performance.
Leadership in Extreme Contexts
Organizations face ongoing changes and high pressure to adapt quickly to stay competitive in the global market. Extreme teams operating in high-risk, high-stress environments (e.g. emergency services, military operations) are seen as potential sources for learning about how to adapt and perform in challenging environments. However, research on effective leadership in extreme teams is inconclusive. With our research, we aim to facilitate theory development and create evidence-based recommendations for organizations and leaders.
Dynamic Teams in Fluid Contexts
In modern working contexts, teamwork is becoming increasingly fluid. Fluidity refers to flexibility and a dynamization of interactions and virtual collaboration across boundaries of time, space, and structures (such as team participation). Fluidity can offer freedom in terms of collaboration; however, it may come with associated challenges that require further analysis. Despite the common agreement of academics on the fluid shifts in contemporary work, there is still little empirical research on the topic, which we address in our work.
Human-AI teaming refers to the collaboration between humans and artificial intelligence systems to solve complex problems. Human-AI teams can be found in various domains, from healthcare and finance to manufacturing and transportation. Trust is a critical factor in the success of human-AI interactions. Therefore we investigate influencing factors like transparency, explainability, and predictability of the AI systems to create a better understanding of how humans and AI can collaborate effectively and efficiently (This text has been generated 100% by AI).