Web Survey Bibliography
(a) Relevance & Research Question: The proposed paper builds on findings presented by the authors at the GOR 10. High drop-out rates are considered a major shortcoming of web surveys and considerably threaten data quality. However, despite growing scholarly attention the knowledge on survey drop-out is still fractional. Previous research mainly addresses the impact of survey design, question wording, and characteristics of the respondents on survey drop-out via ex-post statistical methods. The research presented here is innovative in that the respondents are asked directly about the reasons for dropping out, the interview situation, and psychological predispositions in a follow-up survey.
(b) Methods & Data: Based on our previous research regarding survey drop-out, the principal investigators of the GLES granted funding for a series of short follow-up surveys of drops-outs. These surveys will be conducted subsequently to three consecutive online trackings of the GLES, beginning in December 2010. According to experience, a gross sample size of about 400 drop-outs per survey can be expected. Given an estimated response rate of 60 percent a net sample size of 210 to 240 per tracking is anticipated, thus providing a unique database of more than 600 interviews with drop-outs. Since the most essential items are also included in the tracking surveys, the design allows for comparisons between drop-outs and complete responders. Due to the explorative character of the research, the presentation will mainly focus on descriptive statistics as well as multivariate models illustrating our major findings.
(c) Results: First results will be available by mid-January 2011.
(d) Added Value: Follow-up surveys of respondents who dropped-out allow for an enhanced understanding of the complex processes underlying the phenomenon, especially with respect to the subjective reasons of the respondents as well as the situational influences and psychological predispositions, which cannot be studied applying ex-post statistical procedures. In this regard, our research will add to the knowledge on the reasons for drop-out in web surveys and amend both the theoretical explanations of and the prospects for reducing drop-outs.
Conference Homepage (abstract) / (presentation)
Web survey bibliography - 2011 (358)
- Surveying the General Public over the Internet Using Address-Based Sampling and Mail Contact Procedures...; 2011; Messer, B. L., Dillman, D. A.
- Mobile phones as an extension of the participant observer's self: Reflections on the emergent role...; 2011; Hein, W., O'Donohoe, S., Ryan, A.
- Mixed methods designs in marketing research; 2011; Harrison, R. L., Reilly, T. M.
- Introduction to Usability Testing for Survey Research; 2011; Geisen, E., Jarrett, C.
- Utilizing Web Technology in Business Data Collection: Some Norwegian, Dutch and Danish Experiences; 2011; Haraldsen, G., Snijkers, G., Roos, M., Sundvoll, A., Vik, T., Stax, H.-P.
- E-Census 2011 Portugal: implementation and results of the Pilot Survey; 2011; Vicente, P., Rosa, A., Reis, E.
- Facebook sampling methods: some methodological proposals; 2011; Macrì, E., Tessitore, C.
- Reflections on web based data collection in a mixed mode design: the case of the EU Labour Force Survey...; 2011; Kloek, W., van der Valk, J.
- Standardising the web data collection channel at the Basque Statistics Office (EUSTAT); 2011; Prado, C., Guinea , C.
- An Experimental Investigation of Mode Effects in the Hungarian Census Test 2009; 2011; Vereczkei, Z.
- Collaborative systems for enhancing the analysis of social surveys: the Grid Enabled Specialist Data...; 2011; Lambert, P., Warner, G., Doherty, T., McCafferty, S., Watt, J., Comerford, M., Gayle, V., Tan, L., Blum...
- ILS Online Survey; 2011; Weber, C.
- Development of a Web-Based Survey for Monitoring Daily Health and its Application in an Epidemiological...; 2011; Sugiura, H., Ohkusa, Y., Akahane, M., Sano, T., Okabe, N., Imamura, T.
- Sampling v. Scale: An investigation the tension between convenience sampling, response rates, probability...; 2011; Garland, P.
- Effectiveness and consequences of various recruitment methods in psychological research: case study; 2011; Poltorak, M.
- A new approach to the analysis of survey drop-out. Results from Follow-up Surveys in the German Longitudinal...; 2011; Rossmann, J., Blumenstiel, J. E., Steinbrecher, M.
- Tracking the decision-making process – Findings from an Online Rolling Cross-Section Panel Study...; 2011; Faas, T.
- Should we use the progress bar in online surveys? A meta-analysis of experiments manipulating progress...; 2011; Callegaro, M., Yang, Y., Villar, A.
- From "Web Questions" to "Propensity Score Weighting": An Evaluation of Topics and...; 2011; Welker, M., Taddicken, M.
- Rich Profiles – Or: What's the problem with self-disclosure data?; 2011; Tress, F.
- Who are leaving our panel: panel attrition and personality traits; 2011; Marchand, M.
- Mobile Research Apps – Adding New Capabilities to Market Research; 2011; Rieber, D.
- The influence of personality traits and motives for joining on participation behavior in online panels...; 2011; Keusch, F.
- Asking sensitive questions in a recruitment interview for an online panel: the income question; 2011; Schaurer, I., Struminskaya, B., Kaczmirek, L., Bandilla, W.
- Speeders in Online Value Research: Cross-checking results of fast and slow respondents in two separate...; 2011; Beckers, T., Siegers, P., Kuntz, A.
- Effects of survey question clarity on data quality; 2011; Lenzner, T.
- Respondent Characteristics as Explanations for Uninformative Survey Response: Sources of Nondifferentiation...; 2011; Van Meurs, L., Klausch, L. T., Schoenbach, K.
- Snap judgement polling; 2011; Anderson, K., Wright, M., Wheeler, M.
- Individual differences in motivation to participate in online panels; 2011; Bruggen, E., Wetzels, M., de Ruyter, K., Schillewaert, N.
- Data Use: A systematic method for checking online questionnaires; 2011; Arbittier, J.
- Understanding the pros and cons of mixed-mode research; 2011; Mora, M.
- Visiting item non-responses in internet survey data collection; 2011; Albaum, G., Roster, C. A., Smith, S. M., Wiley, J. B.
- Why Web-assisted TDIs are a cost-effective qualitative methodology ; 2011; Donnelly, T.
- Capturing affective experiences using the SMS Experience Sampling (SMS-ES) method.; 2011; Andrews, L., Russell-Bennett, R., Drennan, J.
- Successful Prompting Methods on a Web-Based Survey; 2011; Venkataraman, L.
- Multi-Mode Survey Administration; 2011; Holder, T.
- Do’s and Don’ts of Developing Mixed Mode Surveys; 2011; Sanders, Ti.
- Mobile Survey Development Toolkit/Survey Framework; 2011; Rauch, M.
- Web based CATI on Amazon Elastic Compute Cloud and VirtualBox using queXS; 2011; Zammit, A.
- Survey Suite: Our "LOGIN & GO" Solution to Survey Research Needs; 2011; Lowden, M.
- A Dinosaur That Just Won't Die: A Return to Paper Surveys; 2011; Crandall, S., Crisafulli, T.
- Responses to Mail-Internet Mixed Mode Surveys: When Can we do Away with Paper Questionnaires?; 2011; Krebill-Prather, R.
- Web/Cloud Based CATI Using queXS; 2011; Zammit, A.
- When Referring to Mode, Is Expressed Preference the Same as Reality?; 2011; Denk, K.
- Developing Paradata Tools to Maximize Call Center Conversion Rates; 2011; Heinrich, T., Pittman, J., Abu, K.
- Incentives, Research-based Best Practices; 2011; Dykema, J.
- "But This is My Cell Phone!": A Qualitative Look at Practical Techniques for Gaining the...; 2011; George, J., Balok, T., Frasier, A. M.
- Developing and Implementing Adaptive Total Design (ATD); 2011; Carley-Baxter, L. R., Mitchell, S., Peytchev, A., Day, O.
- Three Era's of Survey Research; 2011; Groves, R. M.
- Creating Effective Designs for Mixed-Mode Surveys; 2011; Dillman, D. A.