Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/170681 
Title: 

Forecasting the Success Rate of Reward Based Crowdfunding Projects

The document was removed on behalf of the author(s)/ the editor(s).

Year of Publication: 
2017
Publisher: 
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft, Kiel und Hamburg
Abstract: 
The present paper develops three models that help predict the success rate and attainable investment levels of online crowdfunding ventures. This is done by applying standard economic theory and machine learning techniques from computer science to the novel sector of on-line crowd-based micro- financing. In contrast with previous research in the area, this paper analyzes transaction-level data in addition to information about completed crowdfunding projects. This provides an unique perspective in the ways crowd finance ventures develop. The models reach an average of 83% accuracy in predicting the outcome of a crowdfunding campaign at any point throughout its duration. These ndings prove that a number of product and project specifi c parameters are indicative of the success of the venture. Subsequently, the paper provides guidance to capital seekers and investors on the basis of these criteria, and allows participants in the crowdfunding marketplace to make more rational decisions.
Subjects: 
microfinance
entrepreneurial finance
crowdfunding
JEL: 
C0
Document Type: 
Preprint

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The document was removed on behalf of the author(s)/ the editor(s) on: August 5, 2019


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