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Fifty Days an MTurk Worker: The Social and Motivational Context for Amazon Mechanical Turk Workers

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  • Schmidt, Gordon B.

Abstract

The focal article of Landers and Behrend (2015) persuasively argues that universally condemning potential convenience data sources outside of traditional industrial–organizational (I-O) samples such as college students and organization samples is misguided. This author agrees that instead we need to consider the context, strengths, and weaknesses of more recently recognized potential data sources. This commentary will focus on understanding the context of one particular potential data source, Amazon's Mechanical Turk (MTurk; https://www.mturk.com/). While some existing research has looked at the demographic characteristics of Amazon MTurk workers and how those workers’ answers compared with more traditional samples (Casler, Bickel, & Hackett, 2013; Goodman, Cryder, & Cheema, 2013; Paolacci & Chandler, 2014), for this commentary I decided to take a primarily different tack. For the space of approximately 50 days, I acted as an MTurk worker on the site and participated in online communities at which MTurk workers congregate. The purposes of this were to experience the MTurk worker environment firsthand and observe how MTurk workers interact with each other and the site. This was done in the spirit of participant-observer research. Stanton and Rogelberg (2002) argue that online communities might be a particularly fruitful avenue for such participant-observer research within the field of I-O psychology. I am quick to note here that I don't see my efforts here as anywhere near as extensive as much of the participant-observer work of the past, and I did my time on MTurk in the spirit of such work rather than as a match for their methodological and analytical rigor. The observations I make in this commentary will be couched in my own experiences as well as the existing literature base on Amazon MTurk.

Suggested Citation

  • Schmidt, Gordon B., 2015. "Fifty Days an MTurk Worker: The Social and Motivational Context for Amazon Mechanical Turk Workers," Industrial and Organizational Psychology, Cambridge University Press, vol. 8(2), pages 165-171, June.
  • Handle: RePEc:cup:inorps:v:8:y:2015:i:02:p:165-171_00
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    Citations

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    Cited by:

    1. Cristiano Codagnone & Fabienne Abadie & Federico Biagi, 2016. "The Future of Work in the ‘Sharing Economy’. Market Efficiency and Equitable Opportunities or Unfair Precarisation?," JRC Research Reports JRC101280, Joint Research Centre (Seville site).
    2. Laurie A. Garrow & Ziran Chen & Mohammad Ilbeigi & Virginie Lurkin, 2020. "A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk," Transportation, Springer, vol. 47(1), pages 23-42, February.
    3. Bozeman, Barry & Youtie, Jan & Jung, Jiwon, 2020. "Robotic Bureaucracy and Administrative Burden: What Are the Effects of Universities’ Computer Automated Research Grants Management Systems?," Research Policy, Elsevier, vol. 49(6).
    4. Schmidt, Gordon B. & Jettinghoff, William M., 2016. "Using Amazon Mechanical Turk and other compensated crowdsourcing sites," Business Horizons, Elsevier, vol. 59(4), pages 391-400.
    5. Boden, Joe & Maier, Erik & Wilken, Robert, 2020. "The effect of credit card versus mobile payment on convenience and consumers’ willingness to pay," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).

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