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Strategic Behavior in Crowdfunding: Insights from a Large-Scale Online Experiment

Din Amir, Bar Hoter, Moran Koren

TL;DR

This study empirically tests purely informational effects in crowdfunding using a large-scale, single-shot online experiment that contrasts crowdfunding with voting across variations in signal accuracy ($p$), group size, and participation thresholds. It confirms that crowdfunding induces systematic deviations from naive signal-following, with higher signal accuracy reducing risk aversion but increasing mutual insurance, while higher thresholds unexpectedly elevate risk aversion, indicating cognitive load effects. Mutual insurance can aid participation yet hinder information aggregation, especially as signals become more accurate, leading to lower correctness relative to voting under strong private information. The findings provide both validation and critique of existing theoretical models, offering practical guidance for platform design (thresholds and information provisioning) and suggesting avenues to incorporate cognitive factors and dynamics in future theory and experiments.

Abstract

This study examines strategic behavior in crowdfunding using a large-scale online experiment. Building on the model of Arieli et. al 2023, we test predictions about risk aversion (i.e., opting out despite seeing a positive private signal) and mutual insurance (i.e., opting in despite seeing a negative private signal) in a static, single-shot crowdfunding game, focusing on informational incentives rather than dynamic effects. Our results validate key theoretical predictions: crowdfunding mechanisms induce distinct strategic behaviors compared to voting, where participants are more likely to follow private signals (odds ratio: 0.139, $p < 0.001$). Additionally, the study demonstrates that higher signal accuracy (85\% vs. 55\%) decreases risk aversion (odds ratio: 0.414, $p = 0.024$) but increases reliance on mutual insurance (odds ratio: 2.532, $p = 0.026$). However, contrary to theory, increasing the required participation threshold (50\% to 80\%) amplifies risk aversion (odds ratio: 3.251, $p = 0.005$), which, pending further investigation, may indicate cognitive constraints. Furthermore, we show that while mutual insurance supports participation, it may hinder information aggregation, particularly as signal accuracy increases. These findings advance crowdfunding theory by confirming the impact of informational incentives and identifying behavioral deviations that challenge standard models, offering insights for platform design and mechanism refinement.

Strategic Behavior in Crowdfunding: Insights from a Large-Scale Online Experiment

TL;DR

This study empirically tests purely informational effects in crowdfunding using a large-scale, single-shot online experiment that contrasts crowdfunding with voting across variations in signal accuracy (), group size, and participation thresholds. It confirms that crowdfunding induces systematic deviations from naive signal-following, with higher signal accuracy reducing risk aversion but increasing mutual insurance, while higher thresholds unexpectedly elevate risk aversion, indicating cognitive load effects. Mutual insurance can aid participation yet hinder information aggregation, especially as signals become more accurate, leading to lower correctness relative to voting under strong private information. The findings provide both validation and critique of existing theoretical models, offering practical guidance for platform design (thresholds and information provisioning) and suggesting avenues to incorporate cognitive factors and dynamics in future theory and experiments.

Abstract

This study examines strategic behavior in crowdfunding using a large-scale online experiment. Building on the model of Arieli et. al 2023, we test predictions about risk aversion (i.e., opting out despite seeing a positive private signal) and mutual insurance (i.e., opting in despite seeing a negative private signal) in a static, single-shot crowdfunding game, focusing on informational incentives rather than dynamic effects. Our results validate key theoretical predictions: crowdfunding mechanisms induce distinct strategic behaviors compared to voting, where participants are more likely to follow private signals (odds ratio: 0.139, ). Additionally, the study demonstrates that higher signal accuracy (85\% vs. 55\%) decreases risk aversion (odds ratio: 0.414, ) but increases reliance on mutual insurance (odds ratio: 2.532, ). However, contrary to theory, increasing the required participation threshold (50\% to 80\%) amplifies risk aversion (odds ratio: 3.251, ), which, pending further investigation, may indicate cognitive constraints. Furthermore, we show that while mutual insurance supports participation, it may hinder information aggregation, particularly as signal accuracy increases. These findings advance crowdfunding theory by confirming the impact of informational incentives and identifying behavioral deviations that challenge standard models, offering insights for platform design and mechanism refinement.
Paper Structure (16 sections, 3 theorems, 6 equations, 5 tables)

This paper contains 16 sections, 3 theorems, 6 equations, 5 tables.

Table of Contents

  1. Introduction
  2. Literature Review
  3. Theoretical Framework
  4. Performance Metrics.
  5. Group Size Considerations.
  6. Hypotheses Development
  7. Experimental Design
  8. Participants
  9. Procedure
  10. Data processing
  11. Results
  12. Key Findings and Interpretations
  13. Information Aggregation
  14. Experimental Observations
  15. Discussion
  16. ...and 1 more sections

Key Result

theorem thmcountertheorem

No crowdfunding game has more than one symmetric non-trivial Bayes-Nash equilibrium. For any threshold ratio $q \in (0,1]$, when the population is sufficiently large, a unique symmetric non-trivial equilibrium exists.

Theorems & Definitions (3)

  • theorem thmcountertheorem: AKS Theorem 1
  • theorem thmcountertheorem: AKS Theorem 4
  • theorem thmcountertheorem: AKS Lemma 1