Current Project
To ensure continued survey participation and data quality, the survey landscape must adapt to the changing social reality, especially with regard to mobility and digitalization. This requires survey researchers to move from one-size-fits-all solutions to a data collection strategy that takes into account people's communication habits, abilities and preferences. For several decades, computer-assisted personal interviewing (CAPI) was the best-practice gold standard in survey research. However, with declining response rates, rising costs, and differing communication preferences, new solutions must be found. Computer-assisted web interviewing (CAWI) has proven to be a useful, self-administered, and cost-effective supplement, but is not a sufficiently suitable replacement for many applications, including more complex household surveys. Given the increasing prevalence of video telephony in many people's lives, computer-assisted live video interviewing (CALVI) can serve as a new alternative survey mode. The advantage of CALVI is that it helps interviewers navigate through long and complex survey instruments to ensure completeness and data quality without the need for an interviewer to be physically present.
In addition, CALVI uses web-based data collection techniques that speed up the fieldwork process, offer respondents more flexibility, and reduces costs. Nevertheless, there is limited evidence to date of the successful usability of CALVI in longitudinal studies. This research project aims to determine under what circumstances, to what extent, and with which specific demographic subgroups video interviews can and should be conducted. This includes investigating potential non-response biases that may occur when CALVI is used for first-time respondents and/or for established panel members.
The project has two aims: First, to test and optimize the feasibility of CALVI in a mixed-mode household panel survey, the SOEP Innovation Panel (SOEP-IS). Second, to develop a targeted multi-mode survey strategy that includes CALVI alongside CAPI and CAWI to maximize response rates and data quality within a fixed financial budget. The objectives will be achieved in three steps: 1) Experimental implementation of CALVI in the SOEP-IS data collection wave 2024; 2) Development of a model-based mode assignment strategy using the collected data; and 3) Experimental implementation of the developed strategy in the SOEP-IS data collection wave 2025.