45 Pages Posted: 28 Feb 2017 Last revised: 26 Jul 2017
Date Written: July 25, 2017
This paper studies innovation contests, a business process through which a firm (seeker) crowdsources innovation to a large pool of potential workers (solvers). In contrast to much of the existing literature, although there may be a large pool of potential solvers, only a fraction of this population ultimately chooses to enter the contest. Specifically, solvers who are heterogeneous in their ability must choose whether to enter the contest, and if so, how much effort they should exert. We use a game-theoretic model to study how a seeker should allocate her budget to rewards for the solvers so as to induce the best possible output from the participating solvers. In doing so, we establish boundary conditions for when it is reasonable to assume that the full population of solvers is equivalent to the number of solvers who compete for scarce rewards. For what we believe is the more realistic case, where only a fraction of an entire solver population chooses to enter, we characterize how the properties of an innovation problem, and the decisions of the seeker, affect the solvers’ participation and effort decisions. Most notably, we highlight the inherent tension the seeker faces between allocating her budget to induce higher participation and allocating it to induce the best performance. This tension is absent when the entire population of solvers chooses to enter the contest.
Keywords: open innovation, crowdsourcing, innovation contests, incentives for participation, innovation processes
Suggested Citation: Suggested Citation
Stouras, Konstantinos I. and Hutchison-Krupat, Jeremy and Chao, Raul O., Motivating Participation and Effort in Innovation Contests (July 25, 2017). Available at SSRN: https://ssrn.com/abstract=2924224