Beyond Words: An Experimental Study of Signaling in Crowdfunding

Increasingly, crowdfunding is transforming financing for many people worldwide. Yet we know relatively little about how, why, and when funding outcomes are impacted by signaling between funders. We conduct two studies of \(N=500\) and \(N=750\) participants involved in crowdfunding to investigate the effect of “crowd signals,” i.e., certain characteristics deduced from the amounts and timing of contributions, on the decision to fund. In our first study, we find that, under a variety of conditions, contributions of heterogeneous amounts arriving at varying time intervals are significantly more likely to be selected than homogeneous contribution amounts and times. The impact of signaling is strongest among participants who are susceptible to social influence. The effect is remarkably general across different project types, fundraising goals, participant interest in the projects, and participants’ altruistic attitudes. Our second study using less strict controls indicates that the role of crowd signals in decision-making is typically unrecognized by participants. Our results underscore the fundamental nature of social signaling in crowdfunding. They highlight the importance of designing around these crowd signals and inform user strategies both on the project creator and funder side.

Authors

Institutions

Publication Details

Journal
ACM Transactions on Computer-Human Interaction
Published
2025-02-12
DOI
https://doi.org/10.1145/3716381
Citations
3
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
6.85
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Beyond Words: An Experimental Study of Signaling in Crowdfunding

Emőke-Ágnes Horvát, Henry K. Dambanemuya, Darren Gergle, Eunseo Choi
3 citations
ACM Transactions on Computer-Human Interaction
FinTech, Crowdfunding, Digital Finance
6.85
article

Beyond Words: An Experimental Study of Signaling in Crowdfunding

Emőke-Ágnes Horvát, Henry K. Dambanemuya, Darren Gergle, Eunseo Choi
article en
3 citations

Abstract

Increasingly, crowdfunding is transforming financing for many people worldwide. Yet we know relatively little about how, why, and when funding outcomes are impacted by signaling between funders. We conduct two studies of \(N=500\) and \(N=750\) participants involved in crowdfunding to investigate the effect of “crowd signals,” i.e., certain characteristics deduced from the amounts and timing of contributions, on the decision to fund. In our first study, we find that, under a variety of conditions, contributions of heterogeneous amounts arriving at varying time intervals are significantly more likely to be selected than homogeneous contribution amounts and times. The impact of signaling is strongest among participants who are susceptible to social influence. The effect is remarkably general across different project types, fundraising goals, participant interest in the projects, and participants’ altruistic attitudes. Our second study using less strict controls indicates that the role of crowd signals in decision-making is typically unrecognized by participants. Our results underscore the fundamental nature of social signaling in crowdfunding. They highlight the importance of designing around these crowd signals and inform user strategies both on the project creator and funder side.

ACM Transactions on Computer-Human InteractionVol. 32(3)
Northwestern University (US), University of Chicago (US), IIT@MIT (US)
Openalex Percentile: Top 4%
FinTech, Crowdfunding, Digital Finance
6.85
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.