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Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn

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  • Tracy Xiao Liu

    (Department of Economics, School of Economics and Management, Tsinghua University, Beijing 100084, China)

  • Jiang Yang

    (IBM, Armonk, New York 10504)

  • Lada A. Adamic

    (School of Information, University of Michigan, Ann Arbor, Michigan 48109)

  • Yan Chen

    (School of Information, University of Michigan, Ann Arbor, Michigan 48109)

Abstract

To explore the effects of different incentives on crowdsourcing participation and submission quality, we conduct a randomized field experiment on Taskcn, a large Chinese crowdsourcing site using mechanisms with features of an all-pay auction. In our study, we systematically vary the size of the reward as well as the presence of a soft reserve, or early high-quality submission. We find that a higher reward induces significantly more submissions and submissions of higher quality. In comparison, we find that high-quality users are significantly less likely to enter tasks where a high-quality solution has already been submitted, resulting in lower overall quality in subsequent submissions in such soft reserve treatments.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1845 . This paper was accepted by Uri Gneezy, behavioral economics.

Suggested Citation

  • Tracy Xiao Liu & Jiang Yang & Lada A. Adamic & Yan Chen, 2014. "Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn," Management Science, INFORMS, vol. 60(8), pages 2020-2037, August.
  • Handle: RePEc:inm:ormnsc:v:60:y:2014:i:8:p:2020-2037
    DOI: 10.1287/mnsc.2013.1845
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