Descriptive norms -the behavior of other individuals in one's reference group - play a key role in shaping individual decisions in managerial contexts and beyond. Organizations are increasingly using information about descriptive norms to nudge positive behavior change. When characterizing peer decisions, a standard approach in the literature is to focus on average behavior. In this paper, we argue both theoretically and empirically that not only averages but also the shape of the whole distribution of behavior can play a crucial role in how people react to descriptive norms. Using a representative sample of the U.S. population, we experimentally investigate how individuals react to strategic environments that are characterized by different distributions of behavior, focusing on the distinction between tight (i.e., characterized by low behavioral variance), loose (i.e., characterized by high behavioral variance), and polarized (i.e., characterized by u-shaped behavior) environments. We find that individuals indeed strongly respond to differences in the variance and shape of the descriptive norm they are facing: loose norms generate greater behavioral variance and polarization generates polarized responses. In polarized environments, most individuals prefer extreme actions - which expose them to considerable strategic risk - to intermediate actions that minimize such risk. Furthermore, in polarized and loose environments, personal traits and values play a larger role in determining actual behavior. These nuances of how individuals react to different types of descriptive norms have important implications for company culture, productivity, and organizational effectiveness alike.

We study gender gaps in a multi-stage hiring process, focusing on recommendation and recruitment. Across two experiments - one with academic economists and one with a college-educated sample - we show how recommendation letters can cause gender hiring gaps. While recruiters favor female candidates, consistent with efforts to diversify hiring, some groups of recommenders choose less effective letters for women, undermining this advantage. Strategic but erroneous beliefs about letter effectiveness and gender views of recommenders explain these choices. A two-sample prediction exercise using letters from the academic job market supports the experimental finding that gender views drive the language used in recommendations.

In two studies using AI-assisted qualitative interviews, we ask a representative sample of the German electorate (N=1013) to reflect on the most important societal events of the last 15 years. We document that far-right supporters construct systematically different narratives about the recent past. First, they recall different events - with a strong focus on migration-related issues. Second, even when they do consider the same events, they are more likely to blame the establishment and describe events more negatively and with greater emotional intensity. We further document that these narratives are associated with policy preferences, and that far-right supporters are more inclined than supporters of other parties to prioritize cultural over economic issues. Together, our findings reveal that partisan divides extend to how citizens remember and interpret shared national experiences.