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Crowd Labor Markets as Platform for Group Decision and Negotiation Research: A Comparison to Laboratory Experiments

Author

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  • Florian Teschner

    (Karlsruhe Institute of Technology (KIT))

  • Henner Gimpel

    (University of Augsburg)

Abstract

Crowd labor markets such as Amazon Mechanical Turk (MTurk) have emerged as popular platforms where researchers can relatively inexpensively and easily run web-based experiments. Some work even suggests that MTurk can be used to run large-scale field experiments in which groups of participants interact synchronously in real-time such as electronic markets. Besides technical issues, several methodological questions arise and lead to the question of how results from MTurk and laboratory experiments compare. Our data shows comparable results between MTurk and a standard lab setting with student subjects in a controlled environment when running rather simple individual decision tasks. However, our data shows stark differences in results between the experimental settings for a rather complex market experiment. Each experimental setting—lab and MTurk—has its own benefits and drawbacks; which of the two settings is better suited for a specific experiment depends on the theory or artifact to be tested. We discuss potential causes for differences (language understanding, education, cognition and context) that we cannot control for and provide guidance for the selection of the appropriate setting for an experiment. In any case, researchers studying complex artifacts like group decisions or markets should not prematurely adopt MTurk based on extant literature regarding comparable results across experimental settings for rather simple tasks.

Suggested Citation

  • Florian Teschner & Henner Gimpel, 2018. "Crowd Labor Markets as Platform for Group Decision and Negotiation Research: A Comparison to Laboratory Experiments," Group Decision and Negotiation, Springer, vol. 27(2), pages 197-214, April.
    • Handle: RePEc:spr:grdene:v:27:y:2018:i:2:d:10.1007_s10726-018-9565-y
    DOI: 10.1007/s10726-018-9565-y
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    1. 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.
    2. Martin Spann & Bernd Skiera, 2003. "Internet-Based Virtual Stock Markets for Business Forecasting," Management Science, INFORMS, vol. 49(10), pages 1310-1326, October.
    3. Chandler, Dana & Kapelner, Adam, 2013. "Breaking monotony with meaning: Motivation in crowdsourcing markets," Journal of Economic Behavior & Organization, Elsevier, vol. 90(C), pages 123-133.
    4. Antonio Ferreira & Pedro Antunes & Valeria Herskovic, 2011. "Improving Group Attention: An Experiment with Synchronous Brainstorming," Group Decision and Negotiation, Springer, vol. 20(5), pages 643-666, September.
    5. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    6. Joyce E. Berg & Thomas A. Rietz, 2003. "Prediction Markets as Decision Support Systems," Information Systems Frontiers, Springer, vol. 5(1), pages 79-93, January.
    7. Gregory Kersten & Sunil Noronha, 1999. "Negotiation via the World Wide Web: A Cross-cultural Study of Decision Making," Group Decision and Negotiation, Springer, vol. 8(3), pages 251-279, May.
    8. Bennouri, Moez & Gimpel, Henner & Robert, Jacques, 2011. "Measuring the impact of information aggregation mechanisms: An experimental investigation," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 302-318, May.
    9. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    10. Fair, Ray C & Shiller, Robert J, 1989. "The Informational Context of Ex Ante Forecasts," The Review of Economics and Statistics, MIT Press, vol. 71(2), pages 325-331, May.
    11. Paul J. Healy & Sera Linardi & J. Richard Lowery & John O. Ledyard, 2010. "Prediction Markets: Alternative Mechanisms for Complex Environments with Few Traders," Management Science, INFORMS, vol. 56(11), pages 1977-1996, November.
    12. 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.
    13. Chen, Daniel L. & Horton, John J., 2016. "Are Online Labor Markets Spot Markets for Tasks?: A Field Experiment on the Behavioral Response to Wage Cuts," IAST Working Papers 16-37, Institute for Advanced Study in Toulouse (IAST).
    14. Ledyard, John & Hanson, Robin & Ishikida, Takashi, 2009. "An experimental test of combinatorial information markets," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 182-189, February.
    15. Florian Teschner & David Rothschild & Henner Gimpel, 2017. "Manipulation in Conditional Decision Markets," Group Decision and Negotiation, Springer, vol. 26(5), pages 953-971, September.
    16. Logan S. Casey & Jesse Chandler & Adam Seth Levine & Andrew Proctor & Dara Z. Strolovitch, 2017. "Intertemporal Differences Among MTurk Workers: Time-Based Sample Variations and Implications for Online Data Collection," SAGE Open, , vol. 7(2), pages 21582440177, June.
    17. Mullinix, Kevin J. & Leeper, Thomas J. & Druckman, James N. & Freese, Jeremy, 2015. "The Generalizability of Survey Experiments," Journal of Experimental Political Science, Cambridge University Press, vol. 2(2), pages 109-138, January.
    18. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, vol. 56(5), pages 1085-1118, September.
    19. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    20. Alain Pinsonneault & Henri Barki & R. Brent Gallupe & Norberto Hoppen, 1999. "Electronic Brainstorming: The Illusion of Productivity," Information Systems Research, INFORMS, vol. 10(2), pages 110-133, June.
    21. Robin Hanson, 2003. "Combinatorial Information Market Design," Information Systems Frontiers, Springer, vol. 5(1), pages 107-119, January.
    22. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    23. Shane Frederick, 2005. "Cognitive Reflection and Decision Making," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 25-42, Fall.
    24. Jim Lavoie, 2009. "The Innovation Engine at Rite-Solutions: Lessons from the CEO," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 1-11, April.
    25. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
    26. Tim Straub & Henner Gimpel & Florian Teschner & Christof Weinhardt, 2015. "How (not) to Incent Crowd Workers," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(3), pages 167-179, June.
    27. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    28. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
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    More about this item

    Keywords

    Experiments; Mechanical turk; Electronic markets; Information aggregation;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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