Gender-Based Preferences for Tech Work: Field Experimental Evidence from an Internet-of-Things platform

We report on a large field experiment in which 112,770 U.S. university-educated individuals from all fields and career stages were given the opportunity to participate in a technologically-intensive area of learning and innovation, the Internet-of-Things (IoT). Subjects were randomized as to whether the opportunity featured competitive or collaborative interactions with other participants. On average, females are less willing than males to participate in this tech program and especially so under the competitive treatment. However, our main finding is that among those in technical fields, such as Engineering, results reverse: females within technical fields are at least as willing to participate and especially so under the competitive treatment. Differences hold across all career stages. Sorting patterns within the experiment are largely explained by differences in proportional gender representation across fields. The findings are consistent with gender-based sorting and separation to different fields that begins early in life and whose effects are largely established prior to university education. We discuss implications for the improvement of the pipeline of skilled workers.