Web Survey Bibliography
This report provides a review of the most recent literature (2005-2010) on how national statistical institutes (NSIs) measure and try to reduce the response burden caused by their business surveys. The objective of this report is to document and discuss NSI experiences and knowledge in this area. This literature review is the first step of Work package 2; the next step will be to conduct a survey amongst NSIs to collect additional information on response burden measurement and reduction that cannot be found in published documents. The relevance of reducing response burden in business surveys lies both in concerns about the costs for businesses and in the quality and costs of the NSI data collection. The importance of response burden measurement and reduction is underlined by the European Statistics Code of Practice, that states “The reporting burden should be proportionate to the needs of the users and should not be excessive for respondents. The statistical authority monitors the response burden and sets targets for its reduction over time.”
From the reviewed literature the following can be concluded:
- Methods for measuring and calculating response burden are not standardized over European NSIs.
- Many NSIs put effort in the reduction of response burden and undertake very similar actions.
- The effects of these efforts on response burden reduction and data quality are hardly ever documented.
- The effects of actions to reduce response burden are hardly ever researched in experiments or in other types of studies that analyse effects with multivariate quantitative methods.
- Literature on measurement and reduction of response burden is hardly ever published in peer-reviewed journals, but is mainly restricted to conference proceedings.
The importance of response burden reduction seems not to have resulted in many methodological research projects on this topic. Within the next steps of the BLUE-ETS project we aim to make some progress in this direction by a) discussing NSIs best practices of response burden measurement and reduction b) defining a research agenda for these issues and c) make a start in implementing this agenda by conducting empirical research into the effectiveness of promising but not well researched actions to reduce response burden and increase the motivation of business survey respondents.
Web survey bibliography - 2011 (358)
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Computer science security research and human subjects: Emerging considerations for research ethics boards...; 2013; Buchanan, E. A., Aycock, J., Dexter, S., Dittrich, D., Hvizdak, E. E.
- Multiple Sources of Nonobservation Error in Telephone Surveys: Coverage and Nonresponse; 2011; Peytchev, A.; Carley-Baxter, L. R.; Black, M. C.
- Online Questionnaires for Outbreak Investigations; 2011; Parry, A. E.; Johnson, D. R.; Byron-Gray, K.; Raupach, J. C. A.; McPherson, M.
- Inventory of published research: Response burden measurement and reduction in official business statistics...; 2011; Giesen, D. & Snijkers, G. (Eds.), Bavdaz, M., Bergstrom, Y., Gravem, D. F., Haraldsen, G., Hedlin, D...
- Effects of speeding on satisficing in Mixed-Mode Surveys; 2011; Bathelt, S., Bauknecht, J.
- Using Research-Based Practices to Increase Response Rates of Web-Based Surveys; 2011; Perkins, R. A.
- Using break-offs in web interviews for predicting web response in mixed mode surveys; 2011; Beukenhorst, D.
- Web panels in Slovenia; 2011; Lenar, J.
- Traditional and non-traditional treatments for autism spectrum disorder with seizures: an on-line survey...; 2011; Frye, R. E., Sreenivasula, S., Adams, J. B.
- Understanding the new digital divide—A typology of Internet users in Europe; 2011; Brandtzæg, P.B.; Heim, J.; Karahasanoviæ, A.
- Patients’ attitudes toward side effects of antidepressants: an Internet survey; 2011; Kikuchi, T., Uchida, H., Suzuki, T., Watanabe, K., Kashima, H.
- Web-based or paper-based surveys: a quandary?; 2011; Bennett, L., Sid Nair, C.
- Refining the Total Survey Error Perspective; 2011; Smith, T. W.
- ELIPSS: Étude Longitudinale par Internet Pour les Sciences Sociales; 2011; Legleye, S., Lesnard, L.
- Less questions, more data: Revitalizing the european currency in single source affluent audience measurement...; 2011; Hartman, H.
- Linking website exposure data to survey data: A single-source solution; 2011; Krahn, J., Landi, J., Melton, E.
- Inference in surveys with sequential mixed-mode data collection; 2011; Buelens, B., van der Brakel, J.
- Using a Probability-based Online Panel to Survey American Jews; 2011; Wright, G., Phillips, B. T., Tobias, J., Peugh, J., Semans, K.
- Choice of Content Presentation Mode in Web-Based Survey Administration; 2011; Osborn, L., Mansfield, W., Ramirez, C. M., Lacey, J. N., etc.
- Seasonal Yield Variation and Related Response Patterns in Address-based Mail Samples; 2011; DiSogra, C., Hendarwan, E.
- Gender-specific on-line shopping preferences; 2011; Ulbrich, F., Christensen, T., Stankus, L.
- Mixing modes in the LFS - Computer-assisted, cost effective and respondent friendly; 2011; Koerner, T., van der Valk, J.
- Peanuts and Monkeys: Incentivisation and engagement in online access panels; 2011; Marks, B.
- Establishing Cross-National Equivalence of Measures of Xenophobia: Evidence from Probing in Web Surveys...; 2011; Braun, M., Behr, D., Kaczmirek, L.
- Methodological challenges in the use of the Internet for scientific research: Ten solutions and recommendations...; 2011; Reips, U.-D., Buchanan, T., Krantz, J. H., McGrawn, K.Reips, U.-D.
- Search and email still top the list of most popular online activities; 2011; Purcell, K.
- Using Internet in Stated Preference Surveys: A Review and Comparison of Survey Modes; 2011; Lindhjem, H., Navrud, S.
- On the experience and evidence about mixing modes of data collection in large-scale surveys where the...; 2011; Dex, S., Gumy, J.
- Survey Gamification: Old Wine in New Bottles?; 2011; Baker, R. P.
- The Game Experiments: Researching how gaming techniques can be used to improve the quality of feedback...; 2011; Sleep, D., Puleston, J.
- Statistical Estimation of Word Acquisition With Application to Readability Prediction; 2011; Kidwell, P., Lebanon, G., Collins-Thompson, K.
- What is Probit; 2011
- Voice-of-the-customer marketing: A revolutionary 5-step process to create customers who care, spend,...; 2011; Roman, E.
- User agent; 2011
- Unpublisihed internal Google report on break off rates by device type; 2011; Callegaro, M.
- Toward wiser public judgment; 2011; Yankelovich, D., Friedman, W.
- The impact of cookie deletion on site-server and ad-server metrics in Australia. An empirical comScore...; 2011
- The changing role of address-based sampling in survey research; 2011; Iannacchione, V. G.
- State of mobile measurement; 2011; Gluck, M.
- Some issues in the application of latent class models for questionnaire design; 2011; Biemer, P. P., Berzofsky, M.
- Self-administered mobile surveys; 2011; Bosnjak, M.
- SDSC Announces scalable, high-performance data storage cloud; 2011
- Ratings and audience measurement; 2011; Napoli, P. M.
- Randomized response models in survey sampling. Randomized response models; 2011; Hussain, Z.
- Online survey research: Findings, best practices, and future research. Report prepared for the Advertising...; 2011; Vannette, D.
- Online survey research: Findings, Best practices, and future research; 2011
- New Esomar survey on use of cookies and tracking technologies; 2011
- Mobile, webmail, desktops: Where are we viewing email now?; 2011
- Measuring americans' issue priorities. A new version of the most important problem question reveals...; 2011; Yeager, D. S., Larson, S. B., Krosnick, J. A., Tompson, T.