Title: The Incentive Problems with the All-or-Nothing Crowdfunding Model
Publisher: University of California, Hastings College of Law
Publication Year: 2016
JRC N°: JRC98537
ISSN: 1554-849X
URI: http://journals.uchastings.edu/journals/websites/business/HBLJ_12_3.pdf
Type: Articles in periodicals and books
Abstract: This paper discusses how the all-or-nothing model can dis-incentivize crowd investors to perform due diligence over the fraud or failure risks of crowdfunding campaign. Specifically, the major upside of this model is that a project cannot be funded without a critical mass investing. If enough individual in this critical mass of crowd investors perform its due diligence to check whether projects will become successful then the model function; instead, this paper argues that this model incentivizes the crowd to produce noisy information that cannot be relied. In the all-or-nothing model, sequential investments encourages rational investors not perform due diligence because they relied on the self-interest of prior investors to perform due diligence while non-fully rational investors may rely on the belief that prior investors have better information than they might gather. Allowing campaigns to be overfunded can exacerbate some of the all-or-nothing model characteristics. This paper concludes by discussing ways within this model how the platforms, campaign creators, and crowd investors can be incentivized to better filter projects – in order to assure that crowdfunding fulfils its potential.
JRC Directorate:Growth and Innovation

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