Opt-out choice framing attenuates gender differences in the decision to compete in the laboratory and in the field

Joyce C. He, Sonia K. Kang and Nicola Lacetera
Additional contact information
Joyce C. He: a Anderson School of Management, University of California, Los Angeles, CA 90095;
Sonia K. Kang: b Department of Management, University of Toronto, Mississauga, ON L5L 1C6, Canada

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 42, e2108337118

Abstract: How can we close the gender gap in high-level positions in organizations? Interventions such as unconscious bias training or the “lean in” approach have been largely ineffective. This article suggests, and experimentally tests, a “nudge” intervention, altering the choice architecture around the decision to apply for top positions from an “opt in” to an “opt out” default. Evidence from the laboratory and the field shows that a choice architecture in which applicants must opt out from competition reduces gender differences in competition. Opt-out framing thus seems to remove some of the bias inherent in current promotion systems, which favor those who are overconfident or like to compete. Importantly, we show that such an intervention is feasible and effective in the field.

Keywords: gender; competition; behavioral economics; organizational behavior; choice architecture (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.pnas.org/content/118/42/e2108337118.full (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:118:y:2021:p:e2108337118

Access Statistics for this article

More articles in Proceedings of the National Academy of Sciences from Proceedings of the National Academy of Sciences
Bibliographic data for series maintained by PNAS Product Team ().