Improving donation distribution for crowdfunding: An agent-based model

Yi Chieh Lee; Chi Hsien Yen; Wai Tat Fu

doi:10.1007/978-3-319-39931-7_1

Improving donation distribution for crowdfunding: An agent-based model

Yi Chieh Lee, Chi Hsien Yen, Wai Tat Fu

Siebel School of Computing and Data Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Donation-based crowdfunding has the potential to democratize capital raising by soliciting donations directly from the public through the Web and social media. These crowdfunding platforms, however, often function as unregulated open markets, in which there is minimal intervention to influence donation distribution across projects. In fact, research on crowdfunding hints that donation distribution in most crowdfunding platforms are suboptimal: while the overall success rates of crowdfunding projects are often low, a significant proportion of projects receive donations way over their targets. In this paper, we propose a new donation distributing system that aim to (a) distribute donations more effectively among the projects, and (b) align the allocation of donations with the preferences of donors. An agent-based model was developed to test the proposed system. Results showed that the proposed system not only increased the overall success rates of projects, but also led to more successes for projects preferred by donors. Implications to future crowdfunding platforms are discussed.

Original language	English (US)
Title of host publication	Social, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings
Editors	Nathaniel Osgood, Kevin S. Xu, David Reitter, Dongwon Lee
Publisher	Springer
Pages	3-12
Number of pages	10
ISBN (Print)	9783319399300
DOIs	https://doi.org/10.1007/978-3-319-39931-7_1
State	Published - 2016
Event	9th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016 - Washington, United States Duration: Jun 28 2016 → Jul 1 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9708 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	9th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016
Country/Territory	United States
City	Washington
Period	6/28/16 → 7/1/16

Keywords

Crowdfunding
Fundraising
Market

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Online availability

10.1007/978-3-319-39931-7_1

Library availability

Discover UIUC Full Text

Cite this

Lee, Y. C., Yen, C. H., & Fu, W. T. (2016). Improving donation distribution for crowdfunding: An agent-based model. In N. Osgood, K. S. Xu, D. Reitter, & D. Lee (Eds.), Social, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings (pp. 3-12). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9708 LNCS). Springer. https://doi.org/10.1007/978-3-319-39931-7_1

Improving donation distribution for crowdfunding: An agent-based model. / Lee, Yi Chieh; Yen, Chi Hsien; Fu, Wai Tat.
Social, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings. ed. / Nathaniel Osgood; Kevin S. Xu; David Reitter; Dongwon Lee. Springer, 2016. p. 3-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9708 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, YC, Yen, CH & Fu, WT 2016, Improving donation distribution for crowdfunding: An agent-based model. in N Osgood, KS Xu, D Reitter & D Lee (eds), Social, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9708 LNCS, Springer, pp. 3-12, 9th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016, Washington, United States, 6/28/16. https://doi.org/10.1007/978-3-319-39931-7_1

Lee YC, Yen CH, Fu WT. Improving donation distribution for crowdfunding: An agent-based model. In Osgood N, Xu KS, Reitter D, Lee D, editors, Social, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings. Springer. 2016. p. 3-12. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-39931-7_1

Lee, Yi Chieh ; Yen, Chi Hsien ; Fu, Wai Tat. / Improving donation distribution for crowdfunding : An agent-based model. Social, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings. editor / Nathaniel Osgood ; Kevin S. Xu ; David Reitter ; Dongwon Lee. Springer, 2016. pp. 3-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - Donation-based crowdfunding has the potential to democratize capital raising by soliciting donations directly from the public through the Web and social media. These crowdfunding platforms, however, often function as unregulated open markets, in which there is minimal intervention to influence donation distribution across projects. In fact, research on crowdfunding hints that donation distribution in most crowdfunding platforms are suboptimal: while the overall success rates of crowdfunding projects are often low, a significant proportion of projects receive donations way over their targets. In this paper, we propose a new donation distributing system that aim to (a) distribute donations more effectively among the projects, and (b) align the allocation of donations with the preferences of donors. An agent-based model was developed to test the proposed system. Results showed that the proposed system not only increased the overall success rates of projects, but also led to more successes for projects preferred by donors. Implications to future crowdfunding platforms are discussed.

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Improving donation distribution for crowdfunding: An agent-based model

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