• 中国科学学与科技政策研究会
  • 中国科学院科技战略咨询研究院
  • 清华大学科学技术与社会研究中心
ISSN 1003-2053 CN 11-1805/G3

科学学研究 ›› 2026, Vol. 44 ›› Issue (4): 757-769.

• 理论与方法 • 上一篇    下一篇

数字平台生态系统多主体战略交互演化研究

周冬梅1,江月梅2,周阳3,鲁若愚1   

  1. 1. 电子科技大学经济与管理学院
    2. 电子科技大学计算机科学与工程学院
    3. 安徽财经大学
  • 收稿日期:2025-07-22 修回日期:2026-01-07 出版日期:2026-04-15 发布日期:2026-04-15
  • 通讯作者: 周冬梅
  • 基金资助:
    国家自然科学基金面上项目“数字平台生态系统中互补者的创业成长机制研究”;国家自然科学基金重大项目“创新驱动创业的重大理论与实践问题研究”课题三“大型企业创新驱动的创业研究”

Dynamic Evolution of Multi-Agent Strategic Interactions in Digital Platform Ecosystem

  • Received:2025-07-22 Revised:2026-01-07 Online:2026-04-15 Published:2026-04-15

摘要: 本文借助演化博弈理论,建立起数字平台生态系统中平台所有者、互补者和用户三方主体博弈模型,用仿真实验验证了平衡点,探讨了不同平衡点所对应的各主体状态,以此解释多主体战略交互逻辑。同时,通过三维动力系统分析均衡状态的动态演化,在建模过程中证明了动态方程的演化路径及其平衡点的稳定性。结合仿真实验结果,得到如下结论:结合仿真实验结果,得到如下结论:(1)在平台发展不稳定阶段,平台、互补者、用户分别倾向于选择资源均衡分配、多宿主、不购买战略。(2)在平台完善阶段,平台与互补者间战略博弈突出,平台高比例资源倾斜会激励互补者进行资源高反馈,采取定制战略的互补者会促使平台对其资源倾斜。(3)在平台成熟阶段,平台所有者加大资源投入、适当降低产品定价及加强市场监管会提高用户选择购买战略的概率。(4)数字平台生态系统的动态演变对各参数具有高敏感性,具体表现为平衡点会随参数的改变而进行动态演化,这说明各主体间战略交互显著且易受其余主体战略决策的影响。研究将平台治理的研究焦点从单一主体的视角拓展到多主体的战略交互,实现动态模型从内部/均衡模型到外部/平衡模型的转变,揭示了数字平台生态系统的核心治理逻辑,丰富了现有的平台治理理论,具有深刻的实践指导意义。

Abstract: This study utilizes the evolutionary game theory to construct a tripartite game model among platform owners, complementors, and users within the digital platform ecosystem. Through simulation experiments, the equilibrium points were validated, and the states of each party corresponding to different equilibrium points were explored, thereby elucidating the multi-agent strategic interaction logic. Additionally, the dynamic evolution of equilibrium states was analyzed using a three-dimensional dynamical system, and the evolution paths of the dynamic equations and the stability of their equilibrium points were demonstrated during the modeling process. Based on the simulation results, the conclusions are as follows:(1) During the unstable development phase of the platform, the platform, complementors, and users tend to adopt strategies of balanced resource allocation, multi-homing, and non-purchase, respectively. (2) In the platform improvement phase, the strategic game between the platform and complementors becomes prominent. A high proportion of resource allocation by the platform incentivizes complementors to provide high resource feedback, and complementors adopting a customization strategy encourage the platform to allocate more resources to them.(3) During the platform maturity phase, increasing resource investment by platform owners, appropriately reducing product pricing, and strengthening market regulation will increase the probability of users choosing to purchase.(4) The dynamic evolution of the digital platform ecosystem is highly sensitive to various parameters, manifested as the equilibrium point dynamically evolving with changes in parameters. This indicates that strategic interactions among entities are significant and easily influenced by the strategic decisions of other entities. This study expands the research focus of platform governance from a single-agent perspective to the strategic interactions among multiple agents, and achieves a transition of the dynamic model from an internal/equilibrium model to an external/balance model. It reveals the core governance logic of the digital platform ecosystem, enriches the existing platform governance theory, and provides profound practical insights.

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