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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 8
2448-2454

Crowdfunding performance prediction model based on investor behavior analysis

Wei Ju1
Zhou Zhengming2
1. Bank of Beijing Post-Doctoral Research Station, Bank of Beijing, Beijing 100033, China
2. Post-Doctoral Research Station, Bank of Communications, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2023.11.0590

Abstract

Addressing the issue of information asymmetry in crowdfunding, this paper developed a new model for predicting crowdfunding performance, based on the decision utility rules for processing uncertain information in prospect theory and combining the analysis of crowdfunding project information disclosure with investor utility. To tackle the issue of excessive feature selection in practical applications, it introduced a sparsity-based feature selection method using neural networks, which could help crowdfunding platforms to focus on core features for better understanding and predicting investor behavior. Empirical analysis of over 150 000 projects on the Kickstarter platform shows that models considering investors' perception of risk and prospect utility have better predictive and explanatory power for crowdfunding performance. The research results not only provide a new perspective for the prediction and evaluation of crowdfunding projects, but also offer powerful tools for crowdfunding platforms and fundraisers to establish models for analyzing backers' backing behavior.

Foundation Support

上海金融智能工程技木研究中心资助项目(19DZ2254600)
国家社科重大资助项目(18ZDA088)
国家社科基金重大资助项目(20ZDA060)
国家社科基金青年项目(20CSH037)
教育部人文社会科学研究青年基金资助项目(22YJC630220)
河南省高校人文社会科学研究一般项目(2024-ZZJH-038)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0590
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 8
Section: System Development & Application
Pages: 2448-2454
Serial Number: 1001-3695(2024)08-028-2448-07

Publish History

[2024-02-22] Accepted Paper
[2024-08-05] Printed Article

Cite This Article

魏菊, 周正铭. 基于投资者行为分析的众筹绩效预测模型 [J]. 计算机应用研究, 2024, 41 (8): 2448-2454. (Wei Ju, Zhou Zhengming. Crowdfunding performance prediction model based on investor behavior analysis [J]. Application Research of Computers, 2024, 41 (8): 2448-2454. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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