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Storm Crowds: Evidence from Zooniverse on Crowd Contribution Design

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  • Sandra Barbosu
  • Joshua Gans

Abstract

Crowdsourcing - a collaborative form of content production based on the contributions of large groups of individuals - has proliferated in the past decade. Due to this growth, recent research has focused on understanding the factors that affect its sustainability. Prior studies have highlighted the importance of volunteers’ prosocial motivations, the sense of belonging to a community, and symbolic rewards within crowdsourcing websites. One factor that has received limited attention in the existing literature is how the design of crowdsourcing platforms affects their sustainability. We study whether the design element - particularly, the divisibility of contributions (i.e. whether contributing tasks are bundled together or can be carried out separately) - is a factor that affects the level and quality of crowdsourcing contributions. We investigate this in the context of Zooniverse, the world’s largest crowd-sourced science site, in which volunteers contribute to scientific research by performing data processing tasks. Our choice of empirical setting is motivated by the fact that one of the Zooniverse projects, Cyclone Center, underwent a format change that decreased the divisibility of contributions, by bundling together two tasks that were previously separate. We refer to contributions for which both tasks were done as complete, and contributions for which only one task was done as incomplete. In this context, we develop a theoretical model that predicts (i) a positive relationship between contribution divisibility and the total number of contributions (i.e. complete and incomplete) per volunteer, (ii) an ambiguous relationship between contribution divisibility and the number of complete contributions per volunteer, and (iii) an ambiguous relationship between contribution divisibility and the value of complete contributions. We test these predictions empirically by exploiting the format change in Cyclone Center. We find that after the format change, which decreased contribution divisibility, (i) the total number of contributions per volunteer decreased, (ii) the number of complete contributions made by anonymous volunteers increased, while that made by registered volunteers remained unchanged, and (iii) the value of complete contributions increased because anonymous volunteers, who increased their number of complete contributions, contributed high quality contributions. Our results have strategic implications for crowdsourcing platforms because they suggest that the design of crowdsourcing platforms, specifically the divisibility of contributions, is a factor that matters for their sustainability.

Suggested Citation

  • Sandra Barbosu & Joshua Gans, 2017. "Storm Crowds: Evidence from Zooniverse on Crowd Contribution Design," NBER Working Papers 23955, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:23955
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    References listed on IDEAS

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    1. Josh Lerner & Jean Tirole, 2002. "Some Simple Economics of Open Source," Journal of Industrial Economics, Wiley Blackwell, vol. 50(2), pages 197-234, June.
    2. Carliss Y. Baldwin & Kim B. Clark, 2006. "The Architecture of Participation: Does Code Architecture Mitigate Free Riding in the Open Source Development Model?," Management Science, INFORMS, vol. 52(7), pages 1116-1127, July.
    3. Yuxiang Zhao & Qinghua Zhu, 2014. "Evaluation on crowdsourcing research: Current status and future direction," Information Systems Frontiers, Springer, vol. 16(3), pages 417-434, July.
    4. Jiye Baek & Jesse Shore, 2020. "Forum Size and Content Contribution per Person: A Field Experiment," Management Science, INFORMS, vol. 66(12), pages 5906-5924, December.
    5. Franzoni, Chiara & Sauermann, Henry, 2014. "Crowd science: The organization of scientific research in open collaborative projects," Research Policy, Elsevier, vol. 43(1), pages 1-20.
    6. Barry L. Bayus, 2013. "Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community," Management Science, INFORMS, vol. 59(1), pages 226-244, June.
    7. Aleksi Aaltonen & Stephan Seiler, 2016. "Cumulative Growth in User-Generated Content Production: Evidence from Wikipedia," Management Science, INFORMS, vol. 62(7), pages 2054-2069, July.
    8. Yan Huang & Param Vir Singh & Kannan Srinivasan, 2014. "Crowdsourcing New Product Ideas Under Consumer Learning," Management Science, INFORMS, vol. 60(9), pages 2138-2159, September.
    9. Aisling Irwin, 2018. "No PhDs needed: how citizen science is transforming research," Nature, Nature, vol. 562(7728), pages 480-482, October.
    10. Linda See & Alexis Comber & Carl Salk & Steffen Fritz & Marijn van der Velde & Christoph Perger & Christian Schill & Ian McCallum & Florian Kraxner & Michael Obersteiner, 2013. "Comparing the Quality of Crowdsourced Data Contributed by Expert and Non-Experts," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-11, July.
    11. Eric Schenk & Claude Guittard, 2011. "Towards a characterization of crowdsourcing practices," Post-Print halshs-00439256, HAL.
    12. Jana Gallus, 2017. "Fostering Public Good Contributions with Symbolic Awards: A Large-Scale Natural Field Experiment at Wikipedia," Management Science, INFORMS, vol. 63(12), pages 3999-4015, December.
    13. Eric Schenk & Claude Guittard, 2011. "Towards a characterization of crowdsourcing practices," Journal of Innovation Economics, De Boeck Université, vol. 0(1), pages 93-107.
    14. Elizabeth Lyons & Laurina Zhang, 2019. "Trade-offs in motivating volunteer effort: Experimental evidence on voluntary contributions to science," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-12, November.
    15. Xiaoquan (Michael) Zhang & Feng Zhu, 2011. "Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia," American Economic Review, American Economic Association, vol. 101(4), pages 1601-1615, June.
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    More about this item

    JEL classification:

    • H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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