Managing Innovation in a Crowd
Crowdsourcing is an emerging technology where innovation and production are sourced out to the public through an open call. At the center of crowdsourcing is a resource allocation problem: there is an abundance of workers but a scarcity of high skills, and an easy task assigned to a high-skill 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. 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. This hierarchy can be constructed and implemented in a decentralized manner even though neither the difficulties of the tasks nor the skills of the candidate workers are known. We provide a dynamic pricing mechanism that achieves this implementation by inducing workers to self select into different layers. The mechanism is simple: each time a task is attempted and not finished, its price (reward upon completion) goes up.
We thank Glenn Ellison, Luis Garicano, Karim Lakhani, Jonathan Levin, David Miller, and seminar participants at Duke, Johns Hopkins, Michigan, Microsoft Redmond, MIT, University of Texas-Austin, and University of Washington for useful comments and discussion. We gratefully acknowledge financial support from Draper Labs and the Toulouse Network for Information Technology (supported by Microsoft). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.