Using quality control checks to overcome pitfalls in the collection of primary data via online platforms

Sam Fullerton () and Tammy McCullough ()
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Sam Fullerton: The North-West University (RSA) and Eastern Michigan University
Tammy McCullough: Eastern Michigan University

Journal of Marketing Analytics, 2023, vol. 11, issue 4, No 5, 602-612

Abstract: Abstract A sample of 1452 adult respondents in the United States was drawn using a highly respected commercial Internet-based service provider. The 85-question survey addressed issues related to anti-consumption behavior among consumers. The instrument incorporated four quality control checks designed to identify inattentive respondents and cleanse the resultant data set. These quality control (QC) checks were a uniform identifier (where one specific response should result), an instructional manipulation check. A common knowledge question, and a time check. A total of 514 (35.4%) respondents failed at least one of the four QC checks with nine respondents failing all four. Comparisons of inattentive respondents to those who passed all four QC checks consistently identified statistically significant differences on each of the metrics used to determine the potential impact of inattentive respondents. These results indicate that inattentiveness does not produce “random noise” as some authors have stated; rather the inattentive respondents “create both random and systematic measurement error which impacts estimates of the reliability and validity” of the metrics used to assess various consumer phenomena. The results of this study are important, not only in projects designed to help marketers, but also for research in other fields where accuracy is of paramount importance.

Keywords: Questionnaires; Online; Inattentive; Quality control checks; Random noise; Systematic error (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1057/s41270-023-00249-z

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