科研管理

科研管理 ›› 2025, Vol. 46 ›› Issue (10): 21-30.DOI: 10.19571/j.cnki.1000-2995.2025.10.003

• 论文 • 上一篇    下一篇

数据要素价值化赋能数字新质生产力的效果及机制研究

陈晔婷, 何思源   

  1. 云南师范大学经济学院，云南 昆明650500
  • 收稿日期:2024-07-22 修回日期:2025-05-14 接受日期:2025-05-14 出版日期:2025-10-20 发布日期:2025-10-14
  • 通讯作者: 陈晔婷
  • 基金资助:
    国家社会科学基金青年项目：“中国-东盟跨境数据共享机制研究”(22CGJ036）；云南省哲学社会科学规划年度项目重点项目：“云南-东盟跨境数据共享安全风险评估与应对策略研究”（ZD2020519）。

Research on the effect and mechanism of digital new quality productive forces of enterprises empowered by monetization of data elements

Chen Yeting, He Siyuan   

  1. School of Economics, Yunnan Normal University, Kunming 650500, Yunnan, China
  • Received:2024-07-22 Revised:2025-05-14 Accepted:2025-05-14 Online:2025-10-20 Published:2025-10-14

摘要：    数据作为数字时代的新型生产要素，其要素化重构了传统生产力范式，是推动生产力跃迁的重要引擎，在中国式现代化的背景下，研究数据要素价值化如何提升数字新质生产力，对实现数字新质生产力的提高有较好的理论和现实意义。利用大数据交易中心试点城市为准自然实验，采用2012—2022年中国287个地级市数据，结合多期DID模型评估了数据要素价值化赋能数字新质生产力的效果及其作用机制。研究发现：大数据交易中心的设立能够显著提升数字新质生产力；其促进作用主要体现在政府干预程度较高和数字鸿沟较大的样本组。数据价值化能够通过优化生产要素结构和推进数字经济发展对新质生产力产生促进作用，其中传统要素结构优化的传导路径还不明显；进一步研究发现，数据价值化具有显著的空间溢出效应，在邻接空间权重下大数据交易中心的建立对邻近地区产生显著的负向溢出效应，而在经济空间权重下，本地数据价值化水平的提升会对邻近地区产生正向溢出效应。本研究结论即为相关部门布局大数据交易中心建设提供新的经验证据，也为培育数字新质生产力提供了有益的启示。

关键词: 数据价值化, 数字新质生产力, 生产要素结构, 大数据交易中心

Abstract:    As a new type of production factor in the digital era, data factorization reconstructs the traditional productivity paradigm, and is an important engine to promote the transition of productivity. On the new journey of Chinese path to modernization, it is of great theoretical and practical significance to study how the value of data elements can improve the digital new quality productive forces of enterprises. Using the pilot cities of big data trading centers as a quasi-natural experiment, this paper adopted the data from 287 prefecture level cities in China from 2012 to 2022, combined with a multi period DID model, to evaluate the effectiveness and mechanism of digital new quality productive forces empowered by monetization of data elements. The research found that the establishment of big data trading centers can significantly enhance digital productivity, and that the promoting effect is mainly reflected in the sample group with a higher degree of government intervention and a larger digital divide. The monetization of data can promote the development of new quality productive forces by optimizing the structure of production factors and promoting the development of the digital economy, but the transmission path of optimizing the traditional factor structure is not yet clear. Further research found that data monetization has significant spatial spillover effects. The establishment of big data trading centers under adjacent spatial weights has a significant negative spillover effect on neighboring regions, while under economic spatial weights, the improvement of local data monetization level will have a positive spillover effect on neighboring regions. The conclusion of this study will not only provide new empirical evidence for relevant departments to lay out the construction of big data trading centers, but also provide useful insights for cultivating digital new quality productive forces.

Key words: data monetization, digital new quality productive forces, production factor structure, big data exchange center