信息资源管理学报 ›› 2025, Vol. 15 ›› Issue (3): 76-92.doi: 10.13365/j.jirm.2025.03.076

• 研究论文 • 上一篇    下一篇

数字经济时代的数据要素流通政策:构成要素、理论框架、实践路径

颜赫隆1,2 刘江峰1,2 王子怡1,2 裴雷1,2   

  1. 1.南京大学数据智能与交叉创新实验室,南京,210023; 
    2.南京大学信息管理学院,南京,210023
  • 出版日期:2025-05-26 发布日期:2025-06-16
  • 作者简介:颜赫隆,硕士研究生,研究方向为政策量化、政策网络与创新扩散;刘江峰(通讯作者),博士研究生,研究方向为科技情报与政策分析、人文计算与数据治理,Email:jfliu@smail.nju.edu.cn;王子怡,硕士研究生,研究方向为政策量化、科技战略情报分析;裴雷,博士,教授,研究方向为国家战略情报与政策分析、情报安全与数据治理。
  • 基金资助:
    本文系国家社会科学基金重大项目“复杂信息环境下的数据要素流通政策仿真与评价监测研究”(24&ZD190)、江苏省研究生科研与实践创新计划项目“以生成式人工智能变革文献知识组织与评价研究”(KYCX24_0111)研究成果之一。

Data Factor Circulation Policy in the Digital Economy Era: Constitutive Elements, Theoretical Framework, and Practical Path

Yan Helong1,2 Liu Jiangfeng1,2 Wang Ziyi1,2 Pei Lei1,2   

  1. 1.Laboratory of Data Intelligence and Cross Innovation, Nanjing University, Nanjing, 210023; 
    2. School of Information Management, Nanjing University, Nanjing, 210023
  • Online:2025-05-26 Published:2025-06-16
  • About author:Yan Helong, master candidate, research interests include policy quantification, policy network and innovation diffusion; Liu Jiangfeng (corresponding author), Ph.D. candidate, research interests include scientific and technological information and policy analysis, humanistic computing and data governance, Email: jfliu@smail.nju.edu.cn; Wang Ziyi, master candidate, research interests include policy quantification, science and technology strategic intelligence analysis; Pei Lei, Ph.D., professor, research interests include national strategic intelligence and policy analysis, intelligence security and data governance
  • Supported by:
    This is an outcome of the major project "Research on Simulation and Evaluation Monitoring of Data Element Circulation Policies in Complex Information Environments" (24&ZD190) supported by the National Social Science Foundation of China, and the Postgraduate Research & Practice Innovation Program of Jiangsu Province "Transforming Literature Knowledge Organisation and Evaluation Research with Generative Artificial Intelligence" (KYCX24_0111).

摘要: 数字经济时代,数据成为关键生产要素。深入探讨数据要素流通政策的构成要素与理论体系,可在政策层面为我国数据要素市场化实践路径提供理论支持。本研究融合程序化扎根理论与大语言模型,提出兼具理论严谨性与技术先进性的自动化政策文本编码方法。通过设计“文本切片-模拟编码-迭代整合-人工检验-文本抽取”的编码架构,结合结果自确认、角色提示、思维链等提示技术,有效缓解大模型幻觉问题,在保证编码质量的同时显著提升分析效率。该方法有效应用于数据要素流通政策,识别出数据产权与安全治理、基础设施与技术支撑、数据要素市场及其生态构建等六个主范畴及其关联。进而从供需角度揭示当前市场发展的不足,提出协调数据确权与数据开放,提升数据应用深度和广度,分层次、分区域有序推进数据要素市场建设的政策建议。

关键词: 数据要素流通政策, 人工智能生成内容, 大语言模型, 扎根理论, 质性研究

Abstract: In the era of digital economy, data has become a key factor of production. An in-depth discussion on the constituent elements and theoretical system of data factor circulation policy can provide theoretical support for the market-oriented practice path of data factor in China at the policy level. This study combines proceduralised grounded theory and large language model to propose an automated policy text coding method with both theoretical rigor and technical advancement. By designing the coding architecture of "text slicing-analog coding-iterative integration-manual inspection-text extraction" and combining the prompt techniques such as result self-confirmation, role prompting, and thought chain, the problem of large model illusion is effectively alleviated, and the analysis efficiency is significantly improved while the coding quality is guaranteed. This method is effectively applied to data factor circulation policy, and identifies six main categories and their correlation, such as data property rights and security governance, infrastructure and technical support, data element market and its ecological construction. Then, it reveals the shortcomings of the current market development from the perspective of supply and demand, and puts forward policy suggestions on coordinating data right confirmation and data opening, improving the depth and breadth of data application, and promoting the construction of data factor market in a hierarchical and subregional manner.

Key words: Data factor circulation policy, Artificial intelligence generated content, Large language model, Grounded theory, Qualitative research

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