科研管理

科研管理 ›› 2025, Vol. 46 ›› Issue (6): 10-20.DOI: 10.19571/j.cnki.1000-2995.2025.06.002

• 论文 • 上一篇    下一篇

创新驱动下的数据要素流动网络演化机制研究

吕承超1，姜延杰2，何加豪3，郭梦瑶4   

  1. 1.青岛科技大学经济与管理学院，山东 青岛266061；
    2.中国海洋大学管理学院，山东 青岛266100；
    3.中南财经政法大学金融学院，湖北 武汉430073；
    4.华东师范大学经济与管理学院，上海200062

  • 收稿日期:2024-04-17 修回日期:2025-04-10 出版日期:2025-06-20 发布日期:2025-06-06
  • 通讯作者: 姜延杰
  • 基金资助:
    国家社科基金重大项目： “全国统一大市场的发展进程测度和评价研究”（23&ZD124，2024.01—2027.12）。

Research on the evolution mechanism of data element flow network driven by innovation

Lyu Chengchao1, Jiang Yanjie2, He Jiahao3, Guo Mengyao4   

  1. 1. School of Economics & Management, Qingdao University of Science and Technology, Qingdao 266061, Shandong, China;
    2. Management College, Ocean University of China, Qingdao 266100, Shandong, China;
    3. School of Finance, Zhongnan University of Economics and Law, Wuhan 430073, Hubei, China;
    4. School of Economics and Management, East China Normal University, Shanghai 200062, China
  • Received:2024-04-17 Revised:2025-04-10 Online:2025-06-20 Published:2025-06-06

摘要：     数据要素作为新型创新要素，培育经济增长的新动能，其有序流动是激发数据要素潜力的关键。本文基于数据要素流动环境视角，采用劳瑞引力模型构建数据要素流动空间关联网络，借助社会网络分析方法考察数据要素流动循环畅通情况，采用随机行动者模型，探究空间网络结构演化驱动因素的作用机制，度量各驱动因素的相对重要性。结果表明：（1）数据要素流动呈现网络结构特征，各省份之间数据要素流动频繁，空间联动效应明显；（2）在“东数西算”等政策推动下，板块成员来源多元化，地区承担角色动态化，数据要素流动逐渐呈现多中心特征，数据要素流动空间关联网络的拓扑结构更复杂；（3）内生结构因素对网络结构演化发挥主导作用，各省份通过产业链加强分工合作促进数据要素流动。外生属性因素中，减少政府非市场干预，提升区域创新能力等有利于加快数据要素流动。本研究为全国统一大市场建设提供新视角。

关键词: 数据要素, 空间关联网络, 社会网络分析, 驱动机制, 随机行动者模型

Abstract:    The orderly flow of data elements, as a new type of innovation factor to cultivate new dynamics of economic growth, is the key to stimulating the potential of data elements. From the perspective of data element flow environment, this paper adopted the Laurie gravity model to construct the spatial correlation network of data element flow, examined the circulation of data element flow with the help of social network analysis method, and adopted the stochastic actor model to explore the role mechanism of the driving factors of the evolution of spatial network structure, and measured the relative importance of each driving factor. The results showed that: (1) the flow of data elements is characterized by a network structure, with frequent flow of data elements between provincial-level regions and obvious spatial linkage effects; (2) Under the impetus of policies such as "data in the east and handling capacity in the west"; the sources of plate members are diversified; the roles assumed by regions are dynamic; the flow of data elements is gradually showing polycentric characteristics; and the topology of the spatial correlation network of the flow of data elements is more complex; (3) Endogenous structural factors play a dominant role in the evolution of the network structure, and each provincial-level region promotes the flow of data elements by strengthening the division of labor and cooperation through the industrial chain. Among the exogenous attribute factors, reducing the government′s non-market intervention and enhancing regional innovation capability are conducive to accelerating the flow of data elements. This study will provide a new perspective on the construction of a unified national market.

Key words: data element, spatial association network, social network analysis, driving mechanism, stochastic actor-oriented model