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Prolific.ac—A subject pool for online experiments

Author

Listed:
  • Palan, Stefan
  • Schitter, Christian
Abstract
The number of online experiments conducted with subjects recruited via online platforms has grown considerably in the recent past. While one commercial crowdworking platform – Amazon’s Mechanical Turk – basically has established and since dominated this field, new alternatives offer services explicitly targeted at researchers. In this article, we present www.prolific.ac and lay out its suitability for recruiting subjects for social and economic science experiments. After briefly discussing key advantages and challenges of online experiments relative to lab experiments, we trace the platform’s historical development, present its features, and contrast them with requirements for different types of social and economic experiments.

Suggested Citation

  • Palan, Stefan & Schitter, Christian, 2018. "Prolific.ac—A subject pool for online experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 22-27.
    • Handle: RePEc:eee:beexfi:v:17:y:2018:i:c:p:22-27
    DOI: 10.1016/j.jbef.2017.12.004
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    References listed on IDEAS

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    1. Benndorf, Volker & Moellers, Claudia & Normann, Hans-Theo, 2017. "Experienced vs. inexperienced participants in the lab: Do they behave differently?," DICE Discussion Papers 251, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    2. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    3. Landers, Richard N. & Behrend, Tara S., 2015. "An Inconvenient Truth: Arbitrary Distinctions Between Organizational, Mechanical Turk, and Other Convenience Samples," Industrial and Organizational Psychology, Cambridge University Press, vol. 8(2), pages 142-164, June.
    4. Antonio A. Arechar & Simon Gächter & Lucas Molleman, 2018. "Conducting interactive experiments online," Experimental Economics, Springer;Economic Science Association, vol. 21(1), pages 99-131, March.
    5. Urs Fischbacher & Franziska Föllmi-Heusi, 2013. "Lies In Disguise—An Experimental Study On Cheating," Journal of the European Economic Association, European Economic Association, vol. 11(3), pages 525-547, June.
    6. Johannes Abeler & Armin Falk & Lorenz Goette & David Huffman, 2011. "Reference Points and Effort Provision," American Economic Review, American Economic Association, vol. 101(2), pages 470-492, April.
    7. Ofra Amir & David G Rand & Ya'akov Kobi Gal, 2012. "Economic Games on the Internet: The Effect of $1 Stakes," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-4, February.
    8. Neil Stewart & Christoph Ungemach & Adam J. L. Harris & Daniel M. Bartels & Ben R. Newell & Gabriele Paolacci & Jesse Chandler, "undated". "The Average Laboratory Samples a Population of 7,300 Amazon Mechanical Turk Workers," Mathematica Policy Research Reports f97b669c7b3e4c2ab95c9f805, Mathematica Policy Research.
    9. Ben Greiner, 2015. "Subject pool recruitment procedures: organizing experiments with ORSEE," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 114-125, July.
    10. Matthew J C Crump & John V McDonnell & Todd M Gureckis, 2013. "Evaluating Amazon's Mechanical Turk as a Tool for Experimental Behavioral Research," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-18, March.
    11. Volker Benndorf & Claudia Moellers & Hans-Theo Normann, 2017. "Experienced vs. inexperienced participants in the lab: do they behave differently?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 3(1), pages 12-25, July.
    12. Marreiros, Helia & Tonin, Mirco & Vlassopoulos, Michael & Schraefel, M.C., 2017. "“Now that you mention it”: A survey experiment on information, inattention and online privacy," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 1-17.
    13. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    14. Siddharth Suri & Duncan J Watts, 2011. "Cooperation and Contagion in Web-Based, Networked Public Goods Experiments," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-18, March.
    15. Cooper, David J., 2014. "A Note on Deception in Economic Experiments," Journal of Wine Economics, Cambridge University Press, vol. 9(02), pages 111-114, August.
    16. repec:cup:judgdm:v:10:y:2015:i:5:p:479-491 is not listed on IDEAS
    17. Chen, Daniel L. & Schonger, Martin & Wickens, Chris, 2016. "oTree—An open-source platform for laboratory, online, and field experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 88-97.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Prolific; Online experiment; Subject pool;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology

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