Cited by 190Mobile Crowdsensing and CrowdsourcingEmployer Branding and e-HRMSurvey Methodology and Nonresponse

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A Convenient Solution: Using MTurk To Sample From Hard-To-Reach Populations

Smith, Nicholas A., Sabat, Isaac E., Martinez, Larry R., Weaver, Kayla, Xu, Shi·2015·Industrial and Organizational Psychology

DOI 10.1017/iop.2015.29

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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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Mitsouridis, M. A., Genitsaris, E., Gkalimanis, P., Naveau, M., Petrík, V., & Mansard, N. (2026) · Open Research Europe · doi:10.12688/openreseurope.25208.1

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.
ORCID: Smith, Nicholas A.
Sabat, Isaac E.
Martinez, Larry R.
Xu, Shi
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
DOI: 10.1017/iop.2015.29
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
Licence: www.cambridge.org/core/terms (unspecified, 57 d)
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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A Convenient Solution: Using MTurk To Sample From Hard-To-Reach Populations

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