Crowdfunding success prediction: An emprical study on Indiegogo platform

Seda Tolun (), Cem Gürler () and Mehmet Ça?lar ()
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Seda Tolun: Istanbul University School of Business, Quantitative Methods Department
Cem Gürler: Istanbul University School of Business, Quantitative Methods Department
Mehmet Ça?lar: Y?ld?z Technical University Faculty of Economic and Administrative Sciences Department of Business Administration Numerical Methods

No 5908122, Proceedings of International Academic Conferences from International Institute of Social and Economic Sciences

Abstract: Crowdfunding is an appealing financing method to enterpreneurs with financial difficulties in realizing their project ideas. This practice is an endeavour to raise funds for a project or a business venture from a large population where the enterpreneurs make an open call through the internet and try to persuade individuals to support their innovative ideas. Within four different types of crowdfunding and hundreds of websites emerged, this study focuses on reward and donation based crowdfunding in one of the most prominent platforms, Indiegogo. The study introduces a decision tree model that classifies the submitted projects at Indiegogo as successful or not and underlines the key success features for entrepreneurs who are to make an online call for fundraising.

Keywords: classification; data mining; crowdfunding; binary model; knowledge discovery (search for similar items in EconPapers)
JEL-codes: C38 C80 (search for similar items in EconPapers)
Pages: 1 page
Date: 2017-10
New Economics Papers: this item is included in nep-pay
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Published in Proceedings of the Proceedings of the 34th International Academic Conference, Florence, Oct 2017, pages 303-303

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Persistent link: https://EconPapers.repec.org/RePEc:sek:iacpro:5908122

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