If actors want to reach a particular goal, they are in many situations better off by forming collaborative relations and invest together rather than investing separately. In this paper we study the coordination and cooperation problems that hinder successful collaboration in such situations (which we label the production of a „network good with complementarities‟). Using a game-theoretic model, we were able to predict the outcomes in a computerized experiment in continuous time remarkably well. First, groups of subjects nearly always create a pairwise stable network configuration, i.e., they end up either in the empty or the full network. As the costs of forming links increase groups succeed less often in coordinating on the full network, which can yield higher payoffs than the empty network. Second, given the created network structure, subjects invest mostly according to their Nash strategy. This implies a suboptimal amount of network good production, because if linked subjects cooperate by investing more than in their Nash strategy, everybody can be better off. If cooperation is successful, this is mostly in the experimental condition in which subjects can monitor how much their partners invest. Finally, we were able to gain some insight in the individual level mechanisms underlying these outcomes. We find that groups consisting of more foresighted subjects are better able to solve the coordination and cooperation problems. Moreover, subjects learn to deal with the problems better as they gain experience. These results provide stimulating leads for further research into the mechanisms at the individual level
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