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Forecasting the Success Rate of Reward Based Crowdfunding Projects

Author

Listed:
  • Ivelin Elenchev
  • Aleksandar Vasilev

    (Centre for Economic Theories and Policies, Sofia University St. Kliment Ohridski)

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 online 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 crowdfinance 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 fundings prove that a number of product and project specific 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.

Suggested Citation

  • Ivelin Elenchev & Aleksandar Vasilev, 2017. "Forecasting the Success Rate of Reward Based Crowdfunding Projects," Bulgarian Economic Papers bep-2017-09, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, revised Nov 2017.
  • Handle: RePEc:sko:wpaper:bep-2017-09
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    References listed on IDEAS

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    Cited by:

    1. Michael J. Ryoba & Shaojian Qu & Yongyi Zhou, 2021. "Feature subset selection for predicting the success of crowdfunding project campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 671-684, September.

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    More about this item

    Keywords

    microfinance; entrepreneur finance; crowdfunding;
    All these keywords.

    JEL classification:

    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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