I have read dozens of academic papers and practioner-oriented articles, and I work on contest design for quite some time. Yet, it seems that there is no commonly accepted definition of what we mean by an “innovation contest”. Here is my attempt:
An innovation contest is a paradigm in which a firm seeks to advance its technology by sourcing ideas from a crowd competing for prizes.Tweet
Implicit in this definition is that a crowd of ideators, or solvers, exist but must be incentivized to generate solutions, ideas or prototypes for the firm. To allure solvers to participate and exert high effort, a contest hosting firm offers prizes to a subset of participating solvers satisfying certain quality and ranking criteria. Such prizes can be in the form of extrinsic monetary rewards which depend on how challenging an time-consuming the task to solve is, the budget available or the budget that realistically can be raised (e.g. via crowdfunding) and on the subject area to innovate (e.g. art, app development, brand awareness, or technical/highly complex tasks).
Prizes do not always need to be monetary-based. A contest-organizing firm can offer a contract after the challenge to further develop the winner’s solution, fly them out to a conference to present their solution and gain networking opportunities, or meet with a top leader or influencer. Further, prizes can have intrinsic value related to the satisfaction of winning other experts, the joy of learning-by-doing and so on and so forth.
A first-order element of contest design is thus the way a firm should allocate a fixed budget into rewards to incentivize solvers to participate and exert solution effort. In recent game-theoretic research, joint with my co-authors we show that the right prize allocation can vary depending on the extent that solvers’ expertise/skills (“ability”) or market uncertainty (“noise”) are the key value-creation parameter of the innovation contest to the firm. Specifically, when contest outcomes are mainly driven by solver ability, multiple prizes are optimal (see Stouras, Hutchison-Krupat and Chao 2019). The optimal prize allocation in ability-driven innovation contests balances solver participation incentives (which increase with the number of prizes) with the value of each prize (which shrinks as the number of prizes grows). For instance, if the number of potential solvers is sufficiently large compared to firm budget, then even guaranteeing a prize to all solvers would make all solvers worse-off and reluctant to participate.
In contrast, when contest outcomes are mainly driven by market uncertainty or more generally by noise in determing the winning solution, then a single winner-takes-all prize is optimal (see Stouras, Erat and Lichtendahl 2020). In our model this is driven by solvers’ participation uncertainty. That is, when the firm announces its prizes, neither the firm nor each individual solver can know with certainty the number of solvers it will eventually attract. In the event the participants are fewer than the pre-announced number of prizes, the firm retains the remaining budget. That left-over budget could have been used to incentivize further entry if allocated to the top prize.