Arbeitspapier
Personalized fundraising: A field experiment on threshold matching of donations
We study a form of threshold matching in fundraising where donations above a certain threshold are topped up with a fixed amount. We show theoretically that threshold matching can induce crowding in if appropriately personalized. In a field experiment, we explore how thresholds should be chosen depending on past donations. The optimal choice of thresholds is rather bold, approximately 75% above past donations. Additionally, we explore how thresholds should be set for new donors as a function of their personal characteristics and demonstrate the benefits of personalization as opposed to setting a general threshold that applies to all recipients of a fundraising call.
- Language
-
Englisch
- Bibliographic citation
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Series: Discussion Paper ; No. 328
- Classification
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Wirtschaft
Field Experiments
Altruism; Philanthropy; Intergenerational Transfers
Consumer Economics: Empirical Analysis
- Subject
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Charitable giving
field experiments
matching donations
personalization
- Event
-
Geistige Schöpfung
- (who)
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Adena, Maja
Huck, Steffen
- Event
-
Veröffentlichung
- (who)
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Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition
- (where)
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München und Berlin
- (when)
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2022
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Adena, Maja
- Huck, Steffen
- Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition
Time of origin
- 2022
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