管理评论

管理评论 ›› 2025, Vol. 37 ›› Issue (8): 67-77.

• 经济与金融管理 • 上一篇    

基于数据远程监督的上市企业捐赠意愿预测模型研究

赵硕1, 柳涛2,3, 汪展鹏4, 马克1, 李雪蓉5   

  1. 1. 中国科学院大学教育基金会, 北京 100049;
    2. 中国科学院成都文献情报中心, 成都 610041;
    3. 中国科学院大学经济与管理学院, 北京 100190;
    4. 中国科学院大学数学科学学院, 北京 100049;
    5. 中国科学院数学与系统科学研究院, 北京 100190
  • 收稿日期:2023-03-03 发布日期:2025-09-09
  • 作者简介:赵硕，中国科学院大学教育基金会秘书长，高级工程师，博士；柳涛，中国科学院成都文献情报中心硕士研究生；汪展鹏，中国科学院大学数学科学学院硕士研究生；马克，中国科学院大学教育基金会项目主管；李雪蓉（通讯作者），中国科学院数学与系统科学研究院助理研究员，博士。

Predicting Donation Intention of Listed Companies Based on Distant Supervision

Zhao Shuo1, Liu Tao2,3, Wang Zhanpeng4, Ma Ke1, Li Xuerong5   

  1. 1. University of Chinese Academy of Sciences Education Foundation, Beijing 100049;
    2. Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041;
    3. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
    4. School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049;
    5. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190
  • Received:2023-03-03 Published:2025-09-09

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摘要： 高校教育基金会作为高校吸纳社会资源的重要平台，承担着吸引社会捐赠，扩大社会合作的重要责任。如何拓宽筹资渠道、汇聚社会与校友资源、健全募捐和资金管理的长效机制，是增强高校教育基金会可持续发展能力的关键问题。本文利用大数据挖掘技术与人工智能方法充分挖掘互联网开源数据中现有捐赠企业和潜在捐赠企业的各种相关信息，提出了基于数据远程监督的上市企业捐赠意愿预测模型和校友资源挖掘的方法框架。此模型区别于传统定性研究方法与适合小样本数据的传统文本挖掘方法，可有效支持大数据环境下捐赠信息挖掘，并准确识别未来较有可能发生捐赠的重点潜在捐赠企业，为高校基金会更有效地发挥校友资源的优势提供参考。此外，本文以中国科学院大学为案例，应用所提出的方法框架挖掘了校友资源并预测了校友企业的捐赠意愿，验证了本文方法的有效性和应用价值。

关键词: 大数据技术, 高校基金会, 捐赠意愿预测模型, 远程监督

Abstract: As an important platform for colleges and universities to absorb social resources, university education foundation undertakes the important responsibility of attracting social donations and expanding social cooperation. How to expand the financing channels, gather the resources of society and alumni, and improve the long-term mechanism of fundraising and fund management are the key issues to enhance the sustainable development ability of university education foundations. In this paper, big data mining technology and artificial intelligence method are used to explore various relevant information of existing and potential donor companies from the open-source data of the Internet. We propose the framework of alumni resource mining and the prediction model of donation intention of listed companies based on distant supervision. This model is different from the traditional qualitative research method and the traditional text mining method suitable for small sample data. It can effectively support the donation information mining in the big data environment, and accurately identify the key potential donation enterprises that are more likely to make donations in the future, so as to provide insights for university foundations to take the advantages of alumni resources more effectively. In the case study of the University of Chinese Academy of Sciences, we use the proposed framework to explore alumni resources and predict the willingness of alumni enterprises to donate. Combined with the actual donation cases, the effectiveness and application value of the proposed method are verified.

Key words: big data technology, university foundation, donation intention prediction model, distant supervision