A convenient solution: Using MTurk to sample from hard-to-reach populations
Abstract
We agree with Landers and Behrend's (2015) proposition that Amazon's Mechanical Turk (MTurk) may provide great opportunities for organizational research samples. However, some groups are characteristically difficult to recruit because they are stigmatized or socially disenfranchised (Birman, 2005; Miller, Forte, Wilson, & Greene, 2006; Sullivan & Cain, 2004; see Campbell, Adams, & Patterson, 2008, for a review). These groups may include individuals who have not previously been the focus of much organizational research, such as those of low socioeconomic status; individuals with disabilities; lesbian, gay, bisexual, or transgender (LGBT) individuals; or victims of workplace harassment. As Landers and Behrend (2015) point out, there is an overrepresentation of research using “Western, educated, industrialized, rich, and democratic” participants. It is important to extend research beyond these samples to examine workplace phenomena that are specific to special populations. We contribute to this argument by noting the particular usefulness that MTurk can provide for sampling from hard-to-reach populations, which we characterize as groups that are in the numerical minority in terms of nationwide representation. To clarify, we focus our discussion on populations that are traditionally hard to reach in the context of contemporary organizational research within the United States.
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Hughes, H. P. N., Davis, M. C., Robinson, M. A., & McKay, A. (2020) · European Journal of Work and Organizational Psychology · doi:10.1080/1359432x.2020.1722219 · Cited by 13 · see citing works
A Practical Guide for Using Electronic Surveys in Aviation Research: Best Practices Explained
Rice, S. C., & Winter, S. R. (2020) · International Journal of Aviation Aeronautics and Aerospace · doi:10.15394/ijaaa.2020.1457 · Cited by 13 · see citing works
Park, L. S., & Martinez, L. R. (2022) · Journal of Organizational Behavior · doi:10.1002/job.2626 · Cited by 15 · see citing works
Confronting sexism: Identifying dimensions and exploring impact
Dray, K. K., & Sabat, I. E. (2022) · Journal of Applied Social Psychology · doi:10.1111/jasp.12861 · Cited by 12 · see citing works
Bias against Latina and African American women job applicants: a field experiment
Vick, A. D., & Cunningham, G. B. (2018) · Sport Business and Management An International Journal · doi:10.1108/sbm-11-2017-0073 · Cited by 12 · see citing works
“People Nowadays Will Take Everything They Can Get”: American Perceptions of Basic Income Usage
Hamilton, L. K., Yorgun, M., & Wright, A. (2021) · Journal of Policy Practice and Research · doi:10.1007/s42972-021-00035-0 · Cited by 11 · see citing works
- Authors
- Smith, N. A., Sabat, I. E., Martinez, L. R., Weaver, K., & Xu, S.
- Affiliations
- Pennsylvania State University (US)
- George Mason University (US)
- Corresponding author
- Smith, Nicholas A.
- Venue
- Industrial and Organizational Psychology
- Publisher
- Cambridge University Press (CUP)
- Published
- 2015-06
- Volume
- 8
- Issue
- 2
- Pages
- 220-228
- ISSN
- 1754-9426 (ISSN-L)
- 1754-9434
- OpenAlex
- W2424520822
- Cited by
- 190
- References
- 23
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 17 · 2023: 24 · 2022: 24 · 2021: 35 · 2020: 16 · 2019: 23 · 2018: 15 · 2017: 10 · 2016: 4
- FWCI
- 14.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Industrial and Organizational Psychology (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
- Keywords
- Amazon Mechanical Turk, hard-to-reach populations, online recruitment, stigmatized groups, low socioeconomic status, people with disabilities, LGBT people, workplace harassment, underrepresented populations in research
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