Precomitting Increases Donations

Intervention · Charitable Giving

The results show that donors were more likely to increase their donation amount when they were committing to increasing their donation at a future time.

Background

The commitment bias describes how people and groups are willing to support their past ideas and decisions – even when new evidence or events makes doing so irrational. This bias is also known as escalation of commitment or the sunk cost fallacy. It was initially described by Barry M. Staw in his 1976 paper, “Knee deep in the big muddy: A study of escalating commitment to a chosen course of action”.

The commitment bias explains that we tend towards being consistent with our prior commitments, actions, thoughts and dispositions, even when it is against our own interests.

WANT TO WORK TOGETHER ON A RELATED PROBLEM?

Effective interventions start with a nuanced understanding of how decisions are made. Our mission is to help large organizations be better and do better, using behavioral science.

Learn about what we do

Sources

[1] The Behavioural Insights Team. (2017). The Behavioural Insights Team Update Report 2016-17. Retrieved from: https://38r8om2xjhhl25mw24492dir.wpengine.netdna-cdn.com/wp-content/uploads/2017/10/BIT_Update-16-17_E_.pdf

[2] R. B. Cialdini, A. Levy, C. P. Herman, L. T. Kozlowski & R. E. Petty. (1976). Elastic shifts of opinion: Determinants of direction and durability. Journal of Personality and Social Psychology, 34(4), 663-672. Retrieved from: https://dx.doi.org/10.1037/0022-3514.34.4.663

[3] J. Guszcza. (2015). The last-mile problem: How data science and behavioral science can work together. Deloitte Review, 16. Retrieved from: https://dupress.deloitte.com/dup-us-en/deloitte-review/issue-16/behavioral-economics-predictive-analytics.html

[4] M. Kosinski, D. Stillwel & T. Graepel. (2013). Private traits and attributes are predictable from digital records of human behavior. PNAS, 110(1), 5802-5805. Retrieved from: https://www.pnas.org/content/110/15/5802.full.pdf

[5] Y. Wang & M. Kosinski. (2017). Deep neural networks are more accurate than humans at detecting sexual orientation from facial images. Retrieved from: osf.io/zn79k

Notes illustration

Eager to learn about how behavioral science can help your organization?