Gender differences in reapplication: impact on women's presence in talent pipelines
Research combining mathematical modelling with data from executive hiring, crowdfunding, and patent applications challenges the assumption that increasing the number of women in application pools will improve gender diversity.
The challenge: Women are under-represented in top management positions – such as in executive posts, entrepreneurship and science. A common explanation is that they exit talent pipelines at a faster rate than men. We also know that when men and women go after the same opportunity, and are rejected, women are much less likely than men to reapply for a similar position in the future. The challenge here is to understand the implications that this phenomenon will have for diversity in the long run.
Research combining mathematical modelling with data from executive hiring, crowdfunding, and patent applications challenges the assumption that increasing the number of women in application pools will improve gender diversity.
The challenge: Women are under-represented in top management positions – such as in executive posts, entrepreneurship and science. A common explanation is that they exit talent pipelines at a faster rate than men. We also know that when men and women go after the same opportunity, and are rejected, women are much less likely than men to reapply for a similar position in the future. The challenge here is to understand the implications that this phenomenon will have for diversity in the long run.
The research: Using a novel combination of formal mathematical modelling, with data from executive hiring, crowdfunding and patent applications, the researchers investigated long-term diversity outcomes and simulated the results of various scenarios. The model challenged the popular and obvious assumption that because women are not reapplying for opportunities, there will be fewer women in the pipeline in the long run. They found this only to be true in certain settings, and not even relevant in others. The results of the model helped them to scrutinise a popular intervention for lessening the gender gap: increasing the number of women in the application pool.
The impact: The results of the study were surprising. They suggest that convincing more women to reapply can actually backfire, as it can lead to higher rejection rates with fewer women in the application process in the long run. And in a sex bias analysis, they found that even unbiased rejection rates can yield large segregation effects. For a more effective approach to reducing gender disparities, lowering the rejection rate is paramount; and both for men and women. Surprisingly, this type of gender-neutral policy will result in increased diversity. This model plays a crucial role in evaluating diversity policies and opens up new avenues of research on women’s under-representation in the economy.
