Choice Architecture in Occupational Choices

We study how choice architecture in online platforms shapes high-stakes occupational choices through two behavioral mechanisms: motivated reasoning and cognitive load. Using detailed process data from a large online job board and exploiting a quasi-experimental setting, we leverage two sources of exogenous variation in the presentation of occupation recommendations. First, we use random variation in the rank order of equally well-matched occupations to study the effects of motivated reasoning. Our results show that rank order strongly increases the level of users' engagement on the platform and, consequently, the number of occupations to which they apply. Second, we exploit a redesign that transformed the occupation recommendations from a static, text-heavy list into an interactive and visually enriched presentation. The redesign was neither announced nor anticipated, which allows for causal interpretation. We find that this small redesign significantly increases the number of occupations to which users apply, supporting our hypothesis that it reduces cognitive load, leading to increased use of a watch list that keeps more occupations in jobseekers' memory. Our findings provide large-scale field evidence showing that even small changes in platform design significantly and strongly shape consequential career choices.