Crowdsourcing Consumer Research

By J. Goodman, Gabriele Paolacci. 2017

545 citations recorded by the source corpus.

Subfields: Computer Science Applications, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/593ad2286747b6e5fe0390d66b0e6c40963d1dc3

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In Computer Science Applications

In Sociology and Political Science

Citations in the corpus

Re-examining the Experiential Advantage in Consumption: A Meta-Analysis and Review (2020, background): “…has been a particularly popular sample in consumer research in recent years, but it has its critics and there are individual differences (e.g., extraversion, depression in some samples) between Amazon Mechanical Turk and other samples (Goodman, Cryder, and Cheema 2013; Goodman and Paolacci 2017).”
A Tale of Two Sample Sources: Do Results from Online Panel Data and Conventional Data Converge? (2018, background): “Goodman and Paolacci (2017) note that 43% of the behavioral studies published in the Journal of Consumer Research from June 2015–April 2016 were conducted onMTurk.”
Characterizing the Global Crowd Workforce: A Cross-Country Comparison of Crowdworker Demographics (2018, background): “nd predominantly male in India. A small but signiﬁcant percentage of workers relied on MTurk to make basic ends meet. Later studies on the demographics of MTurk workers reported similar results (e.g. Goodman and Paolacci (2017); Berg (2016); Peer et al. (2017); Pavlick et al. (2014); Naderi (2018); ”
Data quality of platforms and panels for online behavioral research (2021, unknown): “In the past decade, there has been a proliferation of online platforms for research (e.g., Buhrmester et al., 2018; Goodman & Paolacci, 2017).”
On making experimental design choices: Discussions on the use and challenges of demand effects, incentives, deception, samples, and vignettes (2020, background): “A thorough exposition of the strengths and weaknesses of crowdsourcing platforms is offered by Goodman and Paolacci (2017).”