The relationship between team size and productivity is a question of broad relevance across
\neconomics, psychology, and management science. For complex tasks, however, where
\nboth the potential benefits and costs of coordinated work increase with the number of workers,
\nneither theoretical arguments nor empirical evidence consistently favor larger vs.
\nsmaller teams. Experimental findings, meanwhile, have relied on small groups and highly
\nstylized tasks, hence are hard to generalize to realistic settings. Here we narrow the gap
\nbetween real-world task complexity and experimental control, reporting results from an
\nonline experiment in which 47 teams of size ranging from n = 1 to 32 collaborated on a realistic
\ncrisis mapping task. We find that individuals in teams exerted lower overall effort than
\nindependent workers, in part by allocating their effort to less demanding (and less productive)
\nsub-tasks; however, we also find that individuals in teams collaborated more with
\nincreasing team size. Directly comparing these competing effects, we find that the largest
\nteams outperformed an equivalent number of independent workers, suggesting that gains
\nto collaboration dominated losses to effort. Importantly, these teams also performed comparably
\nto a field deployment of crisis mappers, suggesting that experiments of the type
\ndescribed here can help solve practical problems as well as advancing the science of collective
\nintelligence.<\/p>\n","protected":false},"excerpt":{"rendered":"
The relationship between team size and productivity is a question of broad relevance across economics, psychology, and management science. For complex tasks, however, where both the potential benefits and costs of coordinated work increase with the number of workers, neither theoretical arguments nor empirical evidence consistently favor larger vs. smaller teams. Experimental findings, meanwhile, have 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