Evaluating Online Data Collection Platforms Using A Simple Rule-Following Task

Dominik Suri, Sebastian Kube and Johannes Schultz

Economics Letters, 2025, vol. 255, issue C

Abstract: High-quality experimental data is crucial for human-subject research. The increasing prevalence of online experimental studies has raised concerns regarding the quality and reliability of data collected in such environments. Recent evidence indicates that data quality varies across popular crowdsourcing platforms. We test if this also holds for less complex, easily comprehensible tasks. We find that compliance rates in a simple rule-following task are significantly lower in our Amazon Mechanical Turk sample compared to those from Prolific Academic and a German university lab.

Keywords: Rule-following task; Online experiments; Replication study; Amazon Mechanical Turk; Prolific Academic (search for similar items in EconPapers)
JEL-codes: C91 D91 Z13 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:255:y:2025:i:c:s0165176525003465

DOI: 10.1016/j.econlet.2025.112509

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