(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.