More Than Double Your Impact: An Empirical Study of Match Offers on Charitable Crowdfunding Platforms

Dr. Xue (Jane) Tan, Assistant Professor, Department of Operations and Decision Technologies, Indiana University
Chaired by
Dr Stanley KOK, Assistant Professor, School of Computing

  18 Jun 2021 Friday, 10:00 AM to 11:30 AM

 Via Zoom

To promote charitable giving, donation-based crowdfunding platforms adopted match offers, whereby leadership donors commit to matching the contribution of other donors at a given rate. While match offers have great potential to improve fundraising performance, a lot remains unknown about how and when match offers work. Leveraging the data from a donation-based crowdfunding platform, our study seeks to understand (1) how the suppliers of funds (donors) evaluate charitable projects with and without match offers differently, (2) how these donors' preferences toward match offers vary with their donation experience, and (3) how the demanders of funds (fundraisers) react to the introduction of match offers. At an individual level, we find that, on average, donors derive a higher utility when contributing to charitable projects with match offers than without them. Specifically, warm-list donors (recently active donors) are three times more likely to contribute to matched projects than unmatched projects, while cold-list donors (dormant donors) are twice more likely to do so. However, new donors, who have no historical donation records on the platform, are more interested in unmatched projects. At a market level, we focus on the ratio of matched projects over all the projects and find that a 1% increase in the matched project ratio leads to a 1.34% increase in funds asked by demanders and a 0.854% increase in the funds supplied by donors. Finally, we demonstrate the robustness of our findings in a transactional analysis with fine-grained controls at the project level. Our work is one of the first studies that connect micro-level data patterns with macro-level market evidence to disentangle the impact of match offers systematically.

Xue (Jane) Tan is an assistant professor in the Department of Operations and Decision Technologies, Kelley School of Business, Indiana University. She received her Ph.D. in business administration from the Foster School of Business, University of Washington. Her research interests include social network analysis, social media fundraising, online volunteerism, and electronic commerce. She has published in Information Systems Research and Management Information Systems Quarterly.