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Decision Sciences Seminar

Monday January 28, 2013


10:00AM - 11:30AM



Mohamed Mostagir

Postdoctoral Associate at MIT


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 skilled worker is a waste of resources. This problem is complicated by the fact that the exact diculties of innovation tasks may not be known in advance, so tasks that require skilled 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-skilled labor and high-skilled workers only engage with a task if workers with lesser skills are unable to finish it. Organizing these hierarchies in crowdsourcing is dificult because firms have little or no information about the skills of the workers they can hire and the firm-worker relationship is fleeting and temporary, providing an incentive for workers to misrepresent their skills. This complicates the firm's problem: it now wants to find an optimal assignment of workers to tasks even though it knows neither the dificulties of the tasks nor the skills of the workers. We give a dynamic pricing mechanism for tasks that utilizes the concept of self-selection - the idea that workers know what they are capable of and optimize their decisions accordingly. Each time a task is attempted and not nished, its price (reward upon completion) goes up. By correctly setting the prices, the mechanism provides an incentive for workers to sort themselves into an optimal hierarchy, i.e. workers participate in the same level of the hierarchy that would be produced if the firm had knowledge of the workers' skills, ultimately leading to the desired optimal matching between workers and tasks.

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