Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs

Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure levels, to meet the new skills needs. However, there is a risk that the new set of lucrative opportunities for employees in these tech-heavy fields will be biased against diverse demographic groups like women. Although much research has examined the experiences of women in science, technology, engineering, and mathematics (STEM) fields and occupations, less understood is the extent to which gender stereotypes influence recruiters’ perceptions and evaluations of individuals who are deciding whether to apply to STEM training programs. These behaviors are typically unobserved because they occur prior to the application interface. We address this question by investigating recruiters’ initial outreach decisions to more than 166,000 prospective students who have expressed interest in applying to a midcareer level online tech training program in business analytics. Using data on the recruiters’ communications, our results indicate that recruiters are less likely to initiate contact with female than male prospects and search for additional signals of quality from female prospects before contacting them. We also find evidence that recruiters are more likely to base initial outreach activities on prospect gender when they have higher workloads and limited attention. We conclude with a discussion of the implications of this research for our understanding of how screening and selection decisions prior to the application interface may undermine organizational efforts to achieve gender equality and diversity as well as the potential for demand-side interventions to mitigate these gender disparities. Funding: We gratefully acknowledge Harvard Business School and MIT Sloan School of Management for generously funding this work. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.16499 .