SOEP Brown Bag Seminar

Inexpensive and time-efficient web surveys have increasingly replaced survey interviews, especially conducted in person. Even well-known social surveys, such as the European Social Survey, follow this trend. However, web surveys suffer from low response rates and frequently struggle to assure that the data are of high quality. New advances in communication technology and artificial intelligence make it possible to introduce new approaches to web survey data collection. Building on these advances, we investigate web surveys in which questions are read through life-like virtual interviewers and in which respondents answer through selecting options from rating scales, incorporating features of in-person interviews in self-administered web surveys. This has the great potential to improve data quality through the creation of rapport and engagement. We address the following overarching research question: Can we improve data quality in web surveys by programming life-like virtual interviewers reading questions aloud to respondents? For this purpose, we conducted a smartphone survey pilot (N = 1,871) in Germany in which respondents were randomly assigned to virtual interviewers varying in gender (male or female) and clothing (casual or business casual) or a text-based control interface (without a virtual interviewer). We employed three questions on women’s role in the workplace, three questions on family relations, and several questions for evaluating respondents’ experience with the virtual interviewers. We will examine satisficing behavior (e.g., primacy effects, middle tendency, and speeding). In addition, we will compare respondents’ overall survey evaluations (e.g., satisfaction and personal feeling) and evaluations of the different virtual interviewers (e.g., rapport and naturalness). By employing life-like virtual interviewers, researchers may be able to deploy web surveys that include the best of interviewer- and self-administered surveys. Thus, our study provides new impulses for improving data quality in web surveys.

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