CoChat
Sign Up
Cited by 835Survey Methodology and NonresponseSurvey Sampling and Estimation TechniquesMobile Crowdsensing and Crowdsourcing

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Response Rate and Response Quality of Internet-Based Surveys: An Experimental Study

Open access
Deutskens, Elisabeth, de Ruyter, Ko, Wetzels, Martin, Oosterveld, Paul·2004·Marketing Letters
DOI 10.1023/b:mark.0000021968.86465.00
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1023/b:mark.0000021968.86465.00

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Due to survey format limitations, the study was unable to ask many follow-up questions or add many options for multiselect questions because it would increase cognitive load and could decrease response rate.

    “Due to the limitations of the survey format, we were unable to ask many follow-up questions or add many options for multiselect questions because it would increase the cognitive load on the participants and could decrease the response rate [12].”

    From My Code Is Less Secure with Gen AI: Surveying Developers' Perceptions of the Impact of Code Generation Tools on Security (2025) · cites this paper as [12]

    The available passages are bibliographic metadata (unpaginated); they do not discuss questionnaire design or survey outcomes. Searches for cognitive load, follow-up and multiselect questions, questionnaire complexity, and response rates found no passage addressing the attributed rationale. The claim cannot be verified from our copy. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 25

  1. Agresti, Allan. (1990). Categorical Data Analysis. New York: Wiley.
  2. Cook, Colleen, Fred Heath, and Russell Thompson. (2000). “A Meta-Analysis of Response Rates in Web-or Internet-Based Surveys,” Educational & Psychological Measurement, 60(6), 821–836. · DOI
  3. Couper, M. P., M. Traugott, and M. Lamias. (2001). “Web Survey Design and Administration,” Public Opinion Quarterly, 65(2), 230–253. · DOI
  4. Dillman, Don A. (2000). Mail and Internet Surveys, The Tailored Design Method. New York: Wiley.
  5. Fox, Richard J., Melvin R. Crask, and Jonghoon Kim. (1988). “Mail Survey Response Rates,” Public Opinion Quarterly, 52(4), 467–491. · DOI
  6. Furse, David H. and David W. Stewart. (1982). “Monetary Incentives versus Promised Contribution to Charity: New Evidence on Mail Survey Response,” Journal of Marketing Research, 19(3), 375–380. · DOI
  7. Goetz, Edward G., Tom R. Tyler, and Fay Lomax Cook. (1984). “Promised Incentives in Media Research: A Look at Data Quality, Sample Representativeness, and Response Rate,” Journal of Marketing Research, 21(2), 148–154. · DOI
  8. Hansen, Robert A. (1980). “A Self-Perception Interpretation of the Effect of Monetary and Nonmonetary Incentives on Mail Survey Respondent Behavior,” Journal of Marketing Research, 17(1), 77–83. · DOI
  9. Hansen, Robert A. and Carol A. Scott. (1978). “Alternative Approaches for Assessing the Quality of Self Report Data.” In Keith Hunt (ed.), Advances in Consumer Research, Vol. 5. Chicago: Association for Consumer Research, 99–102.
  10. Heberlein, Thomas A. and Robert Baumgartner. (1978). “Factors Affecting Response Rates to Mailed Questionnaires: A Quantitative Analysis of the Published Literature,” American Sociology Review, 43(4), 447–462. · DOI
  11. Ilieva, Janet, Steve Baron, and Nigel M. Healey. (2002). “Online Surveys in Marketing Research: Pros and Cons,” International Journal of Market Research, 44(3), 361–382. · DOI
  12. Kanuk, Leslie and Conrad Berenson. (1975). “Mail Survey and Response Rates: A Literature Review,” Journal of Marketing Research, 12(4), 440–453. · DOI
  13. Kiesler, Sara and Lee S. Sproull. (1986). “Response Effects in the Electronic Survey,” Public Opinion Quarterly, 50(3), 402–413. · DOI
  14. Linsky, Arnold S. (1975). “Stimulating Responses to Mailed Questionnaires,” Public Opinion Quarterly, 39(1), 82–101. · DOI
  15. Lozar Manfreda, Katja, Zenel Batagelj, and Vasja Vehovar. (2002). “Design of Web Survey Questionnaires: Three Basic Experiments,” Journal of Computer-Mediated-Communication, 7(3). Retrieved January 20th, 2003, from the World Wide Web: http://www.ascusc.org/jcmc/vol7/issue3/vehovar.html · DOI
  16. McDaniel, Stephen W. and C. P. Rao. (1980). “The Effect of Monetary Inducement on Mailed Questionnaire Response Quality,” Journal of Marketing Research, 17(2), 265–268. · DOI
  17. Rosenblum, Jeff. (2001). “Give and Take,” Quirk's Marketing Research Review. Retrieved June 14th, 2002, from the World Wide Web: http://www.quirks.com/articles/article_print.asp?arg_articleid=705
  18. Schaefer, David R. and Don A. Dillman. (1998). “Development of a Standard E-Mail Methodology,” Public Opinion Quarterly, 62(3), 378–397. · DOI
  19. Sheehan, Kim B. (2001). “E-mail Survey Response Rates: A Review,” Journal of Computer-Mediated-Communication, 6(2). Retrieved January 15th, 2003, from the World Wide Web: http://www.ascusc.org/jcmc/vol6/issue2/sheehan.html
  20. Sheehan, Kim B. and S. J. McMillan. (1999). “Response Variation in E-Mail Surveys: An Exploration,” Journal of Advertising Research, 39(4), 45. · DOI
  21. Shermis, Mark D. and Danielle Lombard. (1999). “A Comparison of Survey Data Collected by Regular Mail and Electronic Mail Questionnaires,” Journal of Business & Psychology, 14(2), 341–354. · DOI
  22. Tourangeau, Roger, Lance J. Rips, and Kenneth Rasinski. (2000). The Psychology of Survey Response. Cambridge University Press. · DOI · Paper page
  23. Warriner, Keith, John Goyder, Heidi Gjertsen, Paula Hohner, and Kathleen McSpurren. (1996). “Charities, No; Lotteries, No; Cash, Yes,” Public Opinion Quarterly, 60(4), 542–562. · DOI
  24. Yammarino, Francis J., Steven J. Skinner, and Terry L. Childers. (1991). “Understanding Mail Survey Response Behavior,” Public Opinion Quarterly, 55(4), 613–639. · DOI
  25. Yu, Julie and Harris Cooper. (1983). “A Quantitative Review of Research Design Effects on Response Rates to Questionnaires,” Journal of Marketing Research, 20(1), 36–44. · DOI

Cited by

Sorted by citations

Metadata

Authors
Deutskens, E., de Ruyter, K., Wetzels, M., & Oosterveld, P.
Affiliations
  • Maastricht University (NL)
  • Eindhoven University of Technology (NL)
Corresponding author
Deutskens, Elisabeth
ORCID
Venue
Marketing Letters
Publisher
Springer Science and Business Media LLC
Published
2004-02
Volume
15
Issue
1
Pages
21-36
ISSN
  • 0923-0645 (ISSN-L)
  • 1573-059X
DOI
10.1023/b:mark.0000021968.86465.00
OpenAlex
W2171382264
Cited by
835
References
4
Citations by year
2026: 14 · 2025: 29 · 2024: 45 · 2023: 44 · 2022: 52 · 2021: 62 · 2020: 45 · 2019: 37 · 2018: 35 · 2017: 45 · 2016: 44 · 2015: 56 · 2014: 54 · 2013: 50 · 2012: 42
FWCI
59.53
Type
journal article
Language
en
Open access
Licence
Locations
  • Marketing Letters (publishedVersion)
  • TU/e Research Portal (publishedVersion, other-oa)
  • TU/e Research Portal (submittedVersion)
  • Research Publications (Maastricht University) (submittedVersion, other-oa)
  • TU/e Research Portal (submittedVersion, other-oa)
Topics
  • Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
  • Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
  • Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
Keywords
online surveys, response rate, response quality, questionnaire length, survey incentives, vouchers, lotteries, follow-up timing, product image

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review