Contingent stimulus in crowdfunding
File(s)dcf1_v5_POM_r1.pdf (851.52 KB)
Accepted version
Author(s)
Du, Longyuan
Hu, Ming
Wu, Jiahua
Type
Journal Article
Abstract
Reward-based crowdfunding is a form of innovative financing that allows project creators to raise funds from
potential backers to start their ventures. A crowdfunding project is successfully funded if and only if the
predetermined funding goal is achieved within a given time. We study the optimal timing of contingently
placing a “fulcrum” in the random pledging process, with the potential of tilting it towards success, which
would be a win-win-win for the creator, backers, and platform. Specifically, we consider a model where
backers arrive sequentially at a crowdfunding project. Upon arrival, a backer makes her pledging decision
by taking into account the expected success of the project. We characterize the dynamics of the project’s
pledging process. We show that there exists a cascade effect on backers’ pledging, which is mainly driven by
the all-or-nothing nature of crowdfunding projects. According to our data collected from the most popular
online crowdfunding platform, Kickstarter, the majority of projects fail to achieve their goals. To address
this issue, we propose three contingent stimulus policies, namely, seeding, feature upgrade, and limited-time
offer. As a result of the cascade effect on backers’ pledging, the optimal timing to apply stimulus policies
has a cutoff-time structure. Lastly, we show that the benefit of contingent policies is greatest in the middle
of crowdfunding campaigns. Testing with the dataset of Kickstarter, we obtain empirical evidence that the
projects’ success rates improve by 14.6% on average with updates in the middle of the campaign and when
the pledging progress is lagging.
potential backers to start their ventures. A crowdfunding project is successfully funded if and only if the
predetermined funding goal is achieved within a given time. We study the optimal timing of contingently
placing a “fulcrum” in the random pledging process, with the potential of tilting it towards success, which
would be a win-win-win for the creator, backers, and platform. Specifically, we consider a model where
backers arrive sequentially at a crowdfunding project. Upon arrival, a backer makes her pledging decision
by taking into account the expected success of the project. We characterize the dynamics of the project’s
pledging process. We show that there exists a cascade effect on backers’ pledging, which is mainly driven by
the all-or-nothing nature of crowdfunding projects. According to our data collected from the most popular
online crowdfunding platform, Kickstarter, the majority of projects fail to achieve their goals. To address
this issue, we propose three contingent stimulus policies, namely, seeding, feature upgrade, and limited-time
offer. As a result of the cascade effect on backers’ pledging, the optimal timing to apply stimulus policies
has a cutoff-time structure. Lastly, we show that the benefit of contingent policies is greatest in the middle
of crowdfunding campaigns. Testing with the dataset of Kickstarter, we obtain empirical evidence that the
projects’ success rates improve by 14.6% on average with updates in the middle of the campaign and when
the pledging progress is lagging.
Date Issued
2022-09-01
Date Acceptance
2022-06-18
Citation
Production and Operations Management, 2022, 31 (9), pp.3543-3558
ISSN
1059-1478
Publisher
Wiley
Start Page
3543
End Page
3558
Journal / Book Title
Production and Operations Management
Volume
31
Issue
9
Copyright Statement
© 2022 Production and Operations Management Society. This is the peer reviewed version of the following article, which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1111/poms.13782. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Subjects
Science & Technology
Technology
Engineering, Manufacturing
Operations Research & Management Science
Engineering
crowdfunding
dynamic
contingent policy
dynamic programming
empirical evidence
REVENUE MANAGEMENT
Operations Research
0102 Applied Mathematics
1503 Business and Management
Publication Status
Published
Date Publish Online
2022-07-04