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Innovative Reward-Based Crowdfunding Decision Model

Author

Listed:
  • Somboon Prasobpiboon

    (Chulalongkorn University, Thailand)

  • Roongkiat Prasobpiboon

    (Chulalongkorn University, Thailand)

  • Achara Chandrachai

    (Chulalongkorn University, Thailand)

  • Sipat Triukose

    (Chulalongkorn University, Thailand)

Abstract

Due to the risky nature of newly creative projects for entrepreneurs, reward-based crowdfunding is currently an alternative fundraising channel for those who need seed funding to finance the creation of their prototype. The objectives of this research are to explore the success factors, including entrepreneurial, project and campaign factors, in project fundraising under a reward-based crowdfunding platform. We propose to develop a model for predicting the success of crowdfunding projects by machine learning. The datasets have been retrospectively gathered from historical records of campaigns in the Kickstarter website. The study's findings show that the logistic regression and decision tree models, respectively, had accuracy rates of 88.2% and 88.8%. The highest accuracy percentage of 94.1% originates from new testing data that has been externally validated for the technology industry. The practical implication of our research is that entrepreneurs can apply the proposed prediction model to identify the most influential topical features embedded in campaigns.

Suggested Citation

  • Somboon Prasobpiboon & Roongkiat Prasobpiboon & Achara Chandrachai & Sipat Triukose, 2024. "Innovative Reward-Based Crowdfunding Decision Model," International Journal of E-Entrepreneurship and Innovation (IJEEI), IGI Global, vol. 14(1), pages 1-25, January.
    • Handle: RePEc:igg:jeei00:v:14:y:2024:i:1:p:1-25
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    References listed on IDEAS

    as
    1. Mollick, Ethan, 2014. "The dynamics of crowdfunding: An exploratory study," Journal of Business Venturing, Elsevier, vol. 29(1), pages 1-16.
    2. Brown, Terrence E. & Boon, Edward & Pitt, Leyland F., 2017. "Seeking funding in order to sell: Crowdfunding as a marketing tool," Business Horizons, Elsevier, vol. 60(2), pages 189-195.
    3. Michael Marcin Kunz & Ulrich Bretschneider & Max Erler & Jan Marco Leimeister, 2017. "An empirical investigation of signaling in reward-based crowdfunding," Electronic Commerce Research, Springer, vol. 17(3), pages 425-461, September.
    4. Sewaid, Ahmed & Garcia-Cestona, Miguel & Silaghi, Florina, 2021. "Resolving information asymmetries in financing new product development: The case of reward-based crowdfunding," Research Policy, Elsevier, vol. 50(10).
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