• Title of article

    Modelling Crowdfunding Ensemble Learning Prediction

  • Author/Authors

    Saeidi Aghdam, Mehran Department of Eentrepreneurship - Qazvin Branch - Islamic Azad University - Qazvin, Iran , Alamtabriz, Akbar Department of Industrial management - Shahid beheshti University - Tehran, Iran , Bahiraie, Alireza Department of Mathematics - Semnan University - Semnan, Iran , Sadeghi, Ahmad Department of Geography - Faculty of Earth Sciences - Shahid Beheshti University - Tehran, Iran

  • Pages
    16
  • From page
    408
  • To page
    423
  • Abstract
    Crowdfunding is a new technology-enabled innovative process that is changing the capital market space. Internet-based applications, particularly those related to Web 2.0, have had a significant impact on sectors of society such as education, business, and medicine. The goal of this research is to fill a gap in the literature on mathematical modelling and prediction of ensemble learning in order to evaluate crowdfunding projects. The Mathematical model determines the cost of funding for the entrepreneur and the return investors will receive per period. A correct financial model is essential in order to keep all three stakeholders involved in the long term. The results show the designed model improved performance in predicting the evaluation of success or failure of Crowdfunding projects.
  • Keywords
    Prediction , Mathematical , Crowdfunding , Entrepreneurship
  • Journal title
    Advances in Mathematical Finance and Applications
  • Serial Year
    2021
  • Record number

    2658930