In this study, I investigated the precursors and the outcomes of team resilience. In contrast to many resilience studies, which focus on low-probability, high-impact challenges, I investigated resilience in the face of high-frequency, low-impact challenges that teams can face in their operational environments. I conducted an extensive literature analysis of the field of resilience and on the basis of this constructed a model of team resilience by integrating insights from high reliability organizing, positive organizational scholarship, sensemaking and disaster resilience studies. I then tested and improved this model through an exploratory study of team behaviour in two 'Escape Game' settings in which teams of 5 people worked through a series of puzzles under time-constrained and somewhat stressful conditions. Following the exploratory study, I developed the resilience model into an operationalizable format and tested it using seven runs of a simulation study involving 547 individuals in 68 teams. In the simulation, teams had to work both quickly and accurately whilst adapting to the changing conditions of a turbulent, competitive environment. Quantitative and qualitative data were collected on various team attributes, team resilience and team performance. I have used quantitative data as the main source of analysis and qualitative data as a supporting tool. Self-completion questionnaires, objective performance indicators, direct observation and post-simulation team and individual reflections were among the data collection tools that were used to obtain data. Team resilience shows highly significant associations with a range of objective measures of team performance. In turn, resilience is supported by several team attributes, including collective mental models, effective channels of communication and systems of information gathering and team cohesion. When teams faced challenges outside of their existing action repertoires their ability to improvise also contributed to resilience. Finally, when teams overcame (novel) challenges, this fed back into their accumulated knowledge through collective learning, enriching action repertoires. Together, these features bestow teams with resilience, which, in turn, enables them to overcome disturbances that might otherwise impede operational performance. In its final form, my resilience model serves as an explanation of the mechanisms of resilience and identifies its antecedents and outcomes. It can inform teams operating in uncertain, ambiguous and volatile work conditions about the capacities and capabilities they need in order to create and sustain resilience in daily operations.

The Team Resilience Assessment Method for Simulation (TRAMS) is an instrument that consist of several measurements, such as team-member exchange, workload, the TRAMS observation protocol etc. This thesis researches the observation protocol. The TRAMS protocol is an assessment method for resilience in simulation games. The aim of this protocol is to support the identification of resilience strategies used and developed by the participants in a simulation game. It is a challenge to assess resilience in teams and that is why the TRAMS protocol has been developed. The scenario of the simulation games is a disruption for 10 days in the card payment system. During the simulation games, the participants work in teams and have to try to cope with the disruption in the card payment system. During the course of this study, 14 simulation games have been conducted with seven different teams. Each of the simulation games has been executed during one whole day, and the participating teams have in total played two games each. During every simulation game there were three observers equipped with the TRAMS protocol. To interpret the data collected with the TRAMS protocol, two methods have been used: transcription and thematic analysis. As a result, guidelines and design changes was formed. In addition, results showed that the distribution and frequency of observations of resilience strategies made were similar, that the observations noted by the observers were similar, and lastly eight themes from the data collection could be extracted: Coordinate and collaborate, Payment options, Cash circulation, Safety, Fuel and transportation, Inform, communicate and the media, Hoarding and rationing, Vulnerable groups. In conclusion, the TRAMS protocol is still under development and 15 more simulation games are planned to be conducted within the ongoing CCRAAAFFTING project. However, the protocol has been applied in this study´s 14 simulation games so far, and the similarities in how the observers filled in the protocol and how similar the observations were, indicate that it hopefully can develop into a recognized research tool in the future.

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