Parallel Innovation Contests

We study multiple parallel contests where contest organizers elicit solutions to innovation-related problems from a set of solvers. Each solver may participate in multiple contests and exert effort to improve her solution for each contest she enters, but the quality of her solution at each contest also depends on an output uncertainty. We first analyze whether an organizer's profit can be improved by discouraging solvers from participating in multiple contests. We show, interestingly, that organizers benefit from solvers' participation in multiple contests when the solver's output uncertainty in these contests is sufficiently large. A managerial insight from this result is that when all organizers elicit innovative solutions rather than low-novelty solutions, organizers may benefit from solvers' participation in multiple contests. We also show that organizers' average profit increases with solvers' participation in multiple contests even when some contests seek low-novelty solutions as long as other contests seek cutting-edge innovation. We further show that an organizer's profit is unimodal in the number of contests, and the optimal number of contests increases with the solver's output uncertainty. This finding may explain why many organizations run multiple contests in practice, and it prescribes running a larger number of contests when the majority of these organizations seek innovative solutions rather than low-novelty solutions.