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Managing Innovation in a Crowd

Author

Listed:
  • Daron Acemoglu
  • Mohamed Mostagir
  • Asuman Ozdaglar

Abstract

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.

Suggested Citation

  • Daron Acemoglu & Mohamed Mostagir & Asuman Ozdaglar, 2014. "Managing Innovation in a Crowd," NBER Working Papers 19852, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19852
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    File URL: http://www.nber.org/papers/w19852.pdf
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    References listed on IDEAS

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    1. Amanda Pallais, 2013. "Inefficient Hiring in Entry-Level Labor Markets," NBER Working Papers 18917, National Bureau of Economic Research, Inc.
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    5. William Fuchs & Luis Garicano & Luis Rayo, 2015. "Optimal Contracting and the Organization of Knowledge," Review of Economic Studies, Oxford University Press, vol. 82(2), pages 632-658.
    6. Kevin J. Boudreau & Nicola Lacetera & Karim R. Lakhani, 2011. "Incentives and Problem Uncertainty in Innovation Contests: An Empirical Analysis," Management Science, INFORMS, vol. 57(5), pages 843-863, May.
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    Cited by:

    1. William Fuchs & Luis Garicano & Luis Rayo, 2015. "Optimal Contracting and the Organization of Knowledge," Review of Economic Studies, Oxford University Press, vol. 82(2), pages 632-658.

    More about this item

    JEL classification:

    • D20 - Microeconomics - - Production and Organizations - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure

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