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Do Machine Learning and Business Analytics Approaches Answer the Question of ‘Will Your Kickstarter Project be Successful?

Author

Listed:
  • Murat Kilinc

    (Dokuz Eylul University, Faculty of Economics and Administrative Sciences, Department of Management Information Systems, Izmir, Turkey)

  • Can Aydin

    (Dokuz Eylul University, Faculty of Economics and Administrative Sciences, Department of Management Information Systems, Izmir, Turkey)

  • Cigdem Tarhan

    (Dokuz Eylul University, Faculty of Economics and Administrative Sciences, Department of Management Information Systems, Izmir, Turkey)

Abstract

Kickstarter is one of the popular crowdfunding platforms used to implement business ideas on the web. The success of crowdfunding projects such as Kickstarter is realized with future financial support. However, there is no platform where users can get decision support before presenting their projects to supporters. To solve this problem, a platform where users can test their projects is required. Within this scope, a business intelligence model that works on the web has been developed by combining business analytics and machine learning methods. The data used for business analytics has been brought to a state that can provide inferences through visualization, reporting and query processes. Within the scope of machine learning, various algorithms were applied for success classification and the best results were given by 91% Random Forest, 85% Decision Tree, 84% K-Nearest Neighbors (KNN) algorithms. F1-Score, Recall, Precision, Mean Squared Error (MSE), Kappa and AUC values were analyzed to determine the most successful models. Thus, Kickstarter users will be able to see their shortcomings and have a prediction about success before presenting their projects to their backers.

Suggested Citation

  • Murat Kilinc & Can Aydin & Cigdem Tarhan, 2021. "Do Machine Learning and Business Analytics Approaches Answer the Question of ‘Will Your Kickstarter Project be Successful?," Istanbul Business Research, Istanbul University Business School, vol. 50(2), pages 255-274, November.
    • Handle: RePEc:ist:ibsibr:v:50:y:2021:i:2:p:255-274
    DOI: 10.26650/ibr.2021.50.0117
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Bi, Sheng & Liu, Zhiying & Usman, Khalid, 2017. "The influence of online information on investing decisions of reward-based crowdfunding," Journal of Business Research, Elsevier, vol. 71(C), pages 10-18.
    3. Alex Kindler & Michael Golosovsky & Sorin Solomon, 2019. "Early prediction of the outcome of Kickstarter campaigns: is the success due to virality?," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-6, December.
    Full references (including those not matched with items on IDEAS)

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