Intervention(s)
We conducted a series of data collections to study the quality and feasibility of AI-led interviews. Studies 1, 2, 3 and 5 do not include an experimental manipulation. Study 4 is an experiment.
1) Main study (n=381, Aug-Sep 2023): Descriptive survey with an integrated 30-minute text-based interview led by an AI interviewer. Post-interview survey questions about the interview experiences. Additional survey modules on factors associated with stock market non-participation, respondent characteristics, and household finances.
2) Follow-up study (n=266, May 2024): Long-term follow-up with participants from the main study. Descriptive survey that includes incentivized outcomes to study whether selected interview codes predict choices: (i) demand for insurance against nominal losses, (ii) willingness to pay for an investment course, (iii) incentivized belief about the performance of actively managed funds.
3) Validation survey (n=1,000, May 2024): Descriptive survey with an equal share of stockowners and non-owners. Survey questions aimed at measuring whether respondents hold the "active investing" mental model hypothesized based on the qualitative analysis of the interview transcripts from the main study.
4) Selection experiment (n=499, Nov 2023): Respondents are asked to select all studies they would like to participate in if we decide to run it: (i) 40-minute survey, (ii) 40-minute interview with a human interviewer, (iii) 40-minute interview with an AI interviewer. These studies are shown on separate pages in randomized order (between subjects). The main outcome of interest is the revealed demand for study participation from a between-subject comparison of the first vignette (binary). We additionally explore factors predicting selection into AI-led interviews using within-subject variation.
5) Multiple open-ended questions benchmark (n=384, Nov 2024): Respondents are asked to answer six pre-determined open-ended survey questions about their reasons for stock market non-participation. The first question is identical to the opening question of our AI-led interviews; the other open-ended questions mimic the topic guide of our interviews.