Parallel Innovation Contests

We study multiple parallel contests in which 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 the solution for each contest the solver enters, but the quality of the solver’s solution in 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 participating 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 are eliciting innovative solutions rather than low-novelty solutions, they may benefit from solvers participating in multiple contests. We also show that organizers’ average profit increases when solvers participate 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 suggests running a larger number of contests when the majority of these organizations are seeking innovative solutions rather than low-novelty solutions.