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In a field study, the dissertation examined the influence of shared leadership on team performance for 51 military combat teams in a simulated dangerous environment. To simulate the dangerous context, the study employed amilitary tactical urban fighting complex, paintball weapons, role players, and a dynamic combat scenario. Using social network analysis techniques and after controlling for team diversity and combat experience, the study found the density measure of shared leadership to be positively and significantly related to team performance, accounting for 40% of the variance in team performance. This research also found both the centralization measure and density/centralization interaction effect to be insignificantly related to team performance. A stepwise multiple regression analysis found the density measure of shared leadership and the control variable of team combat experience as the best predictors of team performance, accounting for 49% of the variance in team performance.
The study also collected qualitative data during and following the field study. Analyzing written observations and definitions of leadership from the 208 participants during the field study, the results found the project’s measure of shared leadership appropriately reflected the perceived leadership of the participants. Additionally, post-study interviews of four shared leadership scholars and four dangerous environment practitioners found the quantitative results appropriately reflected the phenomenon of shared leadership in teams under extreme situations.
The results suggest a promising future for shared leadership in teams operating in dangerous or extreme contexts. The study found military teams relying on multiple individuals for influence in a combat scenario performed at higher levels than those functioning under a vertical model. These results do not imply an end of vertical leadership in dangerous or conventional contexts. Rather, the findings suggest shared leadership may be as viable of a leadership framework as traditional models of downward influence during extreme situations.
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