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The Use and Effects of Incentives in Surveys

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  • Eleanor Singer
  • Cong Ye

Abstract

This article is intended to supplement rather than replace earlier reviews of research on survey incentives, especially those by Singer (2002); Singer and Kulka (2002); and Cantor, O’Hare, and O’Connor (2008). It is based on a systematic review of articles appearing since 2002 in major journals, supplemented by searches of the Proceedings of the American Statistical Association’s Section on Survey Methodology for unpublished papers. The article begins by drawing on responses to open-ended questions about why people are willing to participate in a hypothetical survey. It then lays out the theoretical justification for using monetary incentives and the conditions under which they are hypothesized to be particularly effective. Finally, it summarizes research on how incentives affect response rates in cross-sectional and longitudinal studies and, to the extent information is available, how they affect response quality, nonresponse error, and cost-effectiveness. A special section on incentives in Web surveys is included.

Suggested Citation

  • Eleanor Singer & Cong Ye, 2013. "The Use and Effects of Incentives in Surveys," The ANNALS of the American Academy of Political and Social Science, , vol. 645(1), pages 112-141, January.
    • Handle: RePEc:sae:anname:v:645:y:2013:i:1:p:112-141
    DOI: 10.1177/0002716212458082
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    References listed on IDEAS

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    1. F. Thomas Juster & Richard Suzman, 1995. "An Overview of the Health and Retirement Study," Journal of Human Resources, University of Wisconsin Press, vol. 30, pages 7-56.
    2. Elisabeth Deutskens & Ko de Ruyter & Martin Wetzels & Paul Oosterveld, 2004. "Response Rate and Response Quality of Internet-Based Surveys: An Experimental Study," Marketing Letters, Springer, vol. 15(1), pages 21-36, February.
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    Cited by:

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    6. Hannah Schwarz & Melanie Revilla & Bella Struminskaya, 2022. "Do previous survey experience and participating due to an incentive affect response quality? Evidence from the CRONOS panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 981-1003, July.
    7. Nadeem, Kashif & Wong, Sut I. & Za, Stefano & Venditti, Michelina, 2024. "Digital transformation and industry 4.0 employees: Empirical evidence from top digital nations," Technology in Society, Elsevier, vol. 76(C).
    8. Haifeng Zhao & Nosherwan Khaliq & Chunling Li & Judit Oláh, 2024. "In quest of perceived transaction cost’s impact on fintech users’ intention: the moderating role of situational factors," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
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    10. Rolf Becker, 2022. "The effects of a special sequential mixed-mode design, and reminders, on panellists’ participation in a probability-based panel study," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 259-284, February.

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