Abstract

Crowdfunding platforms are becoming more and more popular for fund-raising of entrepreneurial ventures, but the success rate of crowdfunding campaigns is found to be less than 50%. Recent research has shown that, in addition to the quality and representations of project ideas, dynamics of investment during a crowdfunding campaign also play an important role in determining its success. To further understand the role of investment dynamics, we did an exploratory analysis of the time series of money pledges to campaigns in Kickstarter to investigate the extent to which simple inflows and first-order derivatives can predict the eventual success of campaigns. Using decision tree models, we found that there were discrete stages in money pledges that predicted the success of crowdfunding campaigns. Specifically, we found that, for the majority of projects that had the default campaign duration of one month in Kickstarter, money pledges inflow occurring in the initial 10% and 40-60%, and the first order derivative of inflow at 95-100% of the duration of the campaigns had the strongest impact on the success of campaigns. In addition, merely utilizing the initial 15% money inflows, which could be regarded as “seed money”, to build a predictor can correctly predict 84% of the success of campaigns. Implication of current results to crowdfunding campaigns is also discussed.

Keywords

Crowdfunding predictor decision tree dynamic 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Huaming Rao
    • 1
    • 2
  • Anbang Xu
    • 2
  • Xiao Yang
    • 3
  • Wai-Tat Fu
    • 2
  1. 1.Dept. of Computer Sci & TechUniversity of Sci & TechChina
  2. 2.Dept. of Computer ScienceUniversity of Illinois at Urbana-ChampaignUSA
  3. 3.Dept. of AutomationTsinghua UniversityChina

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