Randomized, Multicenter, Parallel-Arm (RMPA) research trial design: a potential solution to survey length, response rate and data quality in social science research

John F. Riggs (), Dena Hale (), Scott Widmier () and Sonya Tidwell-Riggs ()
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John F. Riggs: Centurion Sales Program at Stetson University
Dena Hale: Centurion Sales Program at Stetson University
Scott Widmier: Kennesaw State University
Sonya Tidwell-Riggs: ArkVisum LLC

Journal of Marketing Analytics, 2023, vol. 11, issue 4, No 3, 577-586

Abstract: Abstract Previous research has shown that long surveys negatively impact response rate and can negatively impact the quality of the data collected through respondent fatigue. Several solutions have been tried including survey design, incentivizing respondents, esthetically enhancing surveys, infusing secondary data and shortening the scales; however, these actions create their own problems that further impact the quality of data. The purpose of this paper is to illustrate the use of a modified version of a commonly used method in medical research, Randomized, Multicenter, Parallel-Arm Research Design. This methodology is proposed as a solution to lengthy surveys in social science research for specific types of applications. Using a typology research example, a survey with 1020+ items was divided (into three parallel arms) using this methodology, given to different respondents (randomly across multiple centers), later recombined and analyzed. Exploratory results demonstrate the potential of the methodology for use in social science research. The most critical element to ensure successful use of this methodology is the creation of relevant inclusion criteria for the samples of interest.

Keywords: Survey length; Multi-Arm Research; Recombining survey data (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1057/s41270-023-00233-7

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