Financial Innovation (Nov 2024)

Information disclosure and funding success of green crowdfunding campaigns: a study on GoFundMe

  • Ziyi Yin,
  • Guowei Huang,
  • Rui Zhao,
  • Sen Wang,
  • Wen-Long Shang,
  • Chunjia Han,
  • Mu Yang

DOI
https://doi.org/10.1186/s40854-024-00666-8
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 23

Abstract

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Abstract Crowdfunding has become important in increasing financial support for the development of green technologies. Self-disclosed information significantly affects supporters’ decisions and is important for the success of green project funding. However, current studies still lack investigations into the impact of information disclosure on green crowdfunding performance. This research aims to fill this knowledge gap by exploring eight information disclosure-relevant factors in green crowdfunding performance. Applying machine learning techniques (e.g., Natural Language Processing and Computer Vision) and logistic regression, this study investigates 720 green crowdfunding campaigns on GoFundMe and empirically finds that the duration, length of campaign introductions, and length of the title influence fundraising outcomes. However, no evidence supports the impact of goal size, emotion of campaign introduction, or image content on funding success. This study clarifies the information disclosure-related data that green crowdfunding campaigns should consider and provides founders with a constructive guide to smoothly raise money for a green crowdfunding campaign. This study also contributes to data processing methods by providing future studies with an approach for transferring unstructured data to structured data.

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