Managing Innovation in a Crowd

Abstract

Crowd innovation is an emerging technology where innovation is sourced out to the public through an open call. At the center of crowd innovation is a resource allocation problem: there is an abundance of workers but a scarcity of high skills, and an easy task assigned to a skilled worker is a waste of resources. This problem is complicated by the fact that the exact difficulties of innovation tasks may not be known in advance, so tasks that require high-skill labor cannot be identified and allocated ahead of time. More problematically, worker skills in a crowd environment are their own private information, and they may have an incentive to misrepresent that information. Taken together, these aspects imply that the firm has to solve the challenging problem of how to assign tasks to workers even though it knows neither the difficulties of the tasks nor the skills of the workers. We first relax the constraint that the firm does not know the skills of the workers (and that workers participate voluntarily) and examine the resulting assignment problem. We show that the solution to this problem takes the form of a skill hierarchy, where tasks are first attempted by low-skill labor, and high-skill workers only engage with a task if less skilled workers are unable to finish it. We derive this structure of the optimal matching by studying a dynamic programming formulation. The most distinctive property of the optimal matching is that it ensures that the heterogeneous skills of the available workers are efficiently utilized. We then show that this optimal matching can be implemented when worker skills are unknown and workers' participation (and in particular, their decision of \textit{when} to participate) is voluntary. This implementation relies on an ascending price scheme in which rewards for completing tasks increase the longer these tasks remain in the system. What makes this pricing scheme support the optimal matching is that, as we show, there is a natural comparative advantage property in this environment: if a worker of a given skill level prefers to participate later rather than earlier, then higher-skilled workers would also choose to do so. Thus, the increasing sequence of prices together with comparative advantage provide the correct incentives for workers to sort themselves into the optimal hierarchy that arises in the solution to the assignment problem.