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Crowdsourcing contests

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  • Segev, Ella

Abstract

In a crowdsourcing contest a requester posts a task (e.g. logo design, programming task) on a platform and announces a monetary reward that he is willing to pay for a winning solution. Contestants (e.g. designers or programmers) submit solutions on the platform and the requester chooses the best solution (possibly more than one) and awards the prize. On-line platforms for crowdsourcing contests are already abundant and growing rapidly in market size. In this survey we present two streams of literature that study crowdsourcing contests. The first is theoretical research, which tries to capture the characteristics of these contests, describe them as a game and then analyze the equilibrium behavior of contestants. The second is the empirical research which collects crowdsourcing data and analyzes the behavior of the contestants in these platforms. The aim of this survey is to clarify the current status of the research of incentives and behavior of contestants, organizers and the platform in crowdsourcing contests and to highlight the many questions that are still open.

Suggested Citation

  • Segev, Ella, 2020. "Crowdsourcing contests," European Journal of Operational Research, Elsevier, vol. 281(2), pages 241-255.
    • Handle: RePEc:eee:ejores:v:281:y:2020:i:2:p:241-255
    DOI: 10.1016/j.ejor.2019.02.057
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    References listed on IDEAS

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    3. Palacios-Marqués, Daniel & Gallego-Nicholls, José Fernando & Guijarro-García, María, 2021. "A recipe for success: Crowdsourcing, online social networks, and their impact on organizational performance," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    4. Ma, Yujie & Du, Gang & Jiao, Roger J., 2020. "Optimal crowdsourcing contracting for reconfigurable process planning in open manufacturing: A bilevel coordinated optimization approach," International Journal of Production Economics, Elsevier, vol. 228(C).
    5. Lars Hornuf & Daniel Vrankar, 2022. "Hourly Wages in Crowdworking: A Meta-Analysis," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(5), pages 553-573, October.
    6. Wang, Haibo & Alidaee, Bahram, 2023. "White-glove service delivery: A quantitative analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    7. Naudé, Wim & Bray, Amy & Lee, Celina, 2021. "Crowdsourcing Artificial Intelligence in Africa: Findings from a Machine Learning Contest," IZA Discussion Papers 14545, Institute of Labor Economics (IZA).
    8. C. Gizem Korpeoglu & Ersin Körpeoğlu & Sıdıka Tunç, 2021. "Optimal Duration of Innovation Contests," Manufacturing & Service Operations Management, INFORMS, vol. 23(3), pages 657-675, May.
    9. Hou, Ting & Zhang, Wen, 2021. "Optimal two-stage elimination contests for crowdsourcing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    10. Ratul Lahkar & Rezina Sultana, 2023. "Rent dissipation in large population Tullock contests," Public Choice, Springer, vol. 197(1), pages 253-282, October.
    11. Dargahi, Rambod & Namin, Aidin & Ketron, Seth C. & Saint Clair, Julian K., 2021. "Is self-knowledge the ultimate prize? A quantitative analysis of participation choice in online ideation crowdsourcing contests," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    12. Bo Chen & Emilios Galariotis & Lijun Ma & Zijia Wang & Zhaobo Zhu, 2023. "On disclosure of participation in innovation contests: a dominance result," Annals of Operations Research, Springer, vol. 328(2), pages 1615-1629, September.

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