Innovation contests have been a feature of the creative landscape for some time now, with a wide number of competitions and prizes offered for innovations of various types. There have been various attempts down the years to understand the optimal format of such contests. The standard approach taken by these models however regards the quality of innovation achieved by the contest as a random variable.
A new model proposes a new, asymmetric approach to innovation contests. The framework describes a scenario whereby the sponsor wishes to obtain an innovation that can be produced by two or more agents. The quality of this innovation is determined by the ability of the agent and the amount of effort they devote to the task. The framework suggests that the agent determines the effort they will devote to the task based upon their perceived ability.
So far, so good. The paper then seems to go down a bit of a wrong path. It suggests that there are circumstances whereby it is optimal for the sponsor of the contest to artificially boost the chances of a particular contestant. The paper suggests that such positive discrimination can be optimal because it leads to an increase in the aggregate effort of all contestants. The theory is that you’ll earn more in extra effort than you spend in incentivizing the chosen one.
I’m not sure I really understand the rationale here. In my eyes, the whole point of an open innovation contest is that you’re inviting participation from people that are largely unknown to you. It’s this open net that will hopefully see talent pulled towards you that you didn’t know existed. It seems hard therefore to picture a scenario whereby you can weight the dice and make one or more of those contestants more likely to win as that seems to go against the whole point of open innovation itself.
The model used as the fulcrum of the paper was tested only theoretically, and was not given the light of real world exposure. Maybe if it was that would have changed the outcome a little, or maybe I’ve missed the point myself. Let me know your thoughts in the comments.Original post