“Making the cut”: Introducing rebate rules in reward-based crowdfunding
Fabian Gerstmeier et al.
Abstract
Reward-based crowdfunding is an important alternative to traditional financing methods. The most prominent funding scheme is the all-or-nothing model, where a project is realized only if it reaches its funding goal. Upon project realization, backers who pledge at least the minimum reservation price receive a reward, while excess pledges go to the project creator. We scrutinize whether redistributing excess pledges back to backers enhances pledging behavior and improves project realization by incorporating rebate rules. We consider two rebate rules: (i) Under the proportional rebate rule, excess pledges are rebated in proportion to the amount backers’ pledges exceed the reservation price; (ii) Under the bid-cap rule, full pledges must only be paid up to a cap, determined ex post to exactly meet the funding goal. Theoretically, both rules improve backer outcomes when pledges exceed the funding goal, with the bid-cap rule inducing lower payment variance compared to the proportional rebate rule. In a laboratory experiment, we find that both rebate rules induce higher pledges and increase project realization rates compared to the all-or-nothing model. Further, we confirm that the payment variance is lower under the bid-cap rule than under the proportional rebate rule. • We introduce rebate rules into reward-based crowdfunding mechanisms. • Rebates redistribute excess pledges among project backers. • The bid-cap rule reduces payment variance between project backers. • Our experiment shows rebate rules outperform the all-or-nothing model. • Both rebate rules raise pledges and increase project realization rates.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.