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中国管理科学 ›› 2025, Vol. 33 ›› Issue (3): 62-79.doi: 10.16381/j.cnki.issn1003-207x.2024.2040cstr: 32146.14/j.cnki.issn1003-207x.2024.2040

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超联世界中的超链风险及其应对:以经济金融系统为例

田虎1, 郑晓龙2,3()   

  1. 1.北京大学光华管理学院,北京 100871
    2.中国科学院自动化研究所多模态人工智能系统全国重点实验室,北京 100190
    3.中国科学院大学人工智能学院,北京 101408
  • 收稿日期:2024-11-13 修回日期:2024-12-30 出版日期:2025-03-25 发布日期:2025-04-07
  • 通讯作者: 郑晓龙 E-mail:xiaolong.zheng@ia.ac.cn
  • 基金资助:
    国家杰出青年科学基金项目(72225011);国家自然科学基金重点项目(72434005)

Hyper-chain Risks in the Hyper-connected World and Their Mitigation: A Case Study of the Economic and Financial System

Hu Tian1, Xiaolong Zheng2,3()   

  1. 1.Guanghua School of Management Peking University,Beijing 100871,China
    2.National Key Laboratory for Multimodal Artificial Intelligence Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China
    3.School of Artificial Intelligence,University of Chinese Academy of Sciences,Beijing 101408,China
  • Received:2024-11-13 Revised:2024-12-30 Online:2025-03-25 Published:2025-04-07
  • Contact: Xiaolong Zheng E-mail:xiaolong.zheng@ia.ac.cn

摘要:

随着数字化、网络化和智能化技术的快速发展,人类社会进入了由海量数据、数以百亿计的连接设备及复杂交互网络构成的超联世界。在这个背景下,经济金融系统作为社会经济活动的核心环节,其复杂性和不确定性显著增加,超链风险成为影响安全发展格局构建的主要风险类型。超链风险是指在超联世界中,随着各个子系统间联系的加强,局部事件的影响可能迅速扩散并放大,最终演变成全局性危机的不确定性。本文通过剖析超链风险的特征,归纳了超联复杂性与社会-技术-经济的交互演化,结合经济金融系统的网络动力学建模,分析了超链风险在网络中的传播机制。为了应对超链风险,本文从降低经济金融系统复杂性的角度提出了系统构建和结构优化的方法,并围绕经济和金融安全提出了政策建议和应对策略。最后,本文探讨了未来研究的方向,包括研究范式的转变、研究工具的革新、实证研究与模拟实验的结合以及技术驱动的系统设计等。本文不仅在理论层面为理解和管理复杂经济金融系统中的风险提供了新的视角,还在实践层面为政策制定者、金融机构以及监管机构提供了应对超链风险的具体指导原则,从而赋能新形态下国家与社会治理。

关键词: 超联世界, 超链风险, 经济金融系统, 风险形成与传播, 复杂系统理论

Abstract:

In the era of rapid digitalization, networking, and intelligent technologies, human society has transitioned into a "hyper-connected world" characterized by vast data, billions of interconnected devices, and intricate interaction networks. This transformation has led to an unprecedented increase in the complexity and uncertainty of economic and financial systems, with hyper-chain risk emerging as a critical concern. Hyper-chain risk is defined as the uncertainty where local events can rapidly diffuse and amplify across tightly interconnected subsystems, potentially leading to a global crisis. It aims to provide a comprehensive overview of the concept of hyper-chain risk, its underlying mechanisms, and the implications for socio-economic systems in this paper, while also offering insights on how contemporary complex system science, sociology, and economics can be integrated to address these challenges.It begins by tracing the origins of hyper-chain risk, which arise from the intricate interweaving of human and machine systems, as well as the interconnectedness of information. This type of risk is not confined to a single system or sector but spans across multiple domains, forming a complex network of risks. It highlights that traditional approaches to risk management are increasingly inadequate in dealing with the emergent phenomena resulting from this high degree of interconnectedness. It is argued that a deeper understanding of hyper-connectivity and the associated risks requires a multidisciplinary approach, incorporating concepts from complex systems theory, network science, and social-technical-economic interactions. The hyper-chain risk is distinguished from other types of risks, such as component risk, systemic risk, and cascading risk, emphasizing its unique characteristics: the rapid diffusion and amplification of local disturbances, the involvement of multiple interconnected systems, and the resultant global impact.To understand the interactions among elements within economic and financial systems, the network representation of hyper-chain risk is introduced, including single-layer, multilayer, and high-order interaction networks. A dynamic modeling framework is also developed for hyper-chain risk, examining from three perspectives: supply chain networks, institutional coordination networks, and cognitive spillover networks. How shocks propagate through these networks is elaborated on, leading to a sharp decline in system functionality or productivity, and various mechanisms of risk contagion are uncovered, including direct, indirect, and cross-layer contagion in multi-layer networks. Additionally, it discusses the self-fulfilling feedback effects triggered by changes in market participants’beliefs or behaviors.Furthermore, the importance of adopting a guided self-organization principle is discussed and decentralization strategies are appropriated to manage the complexity of hyper-connected systems. Decentralization is highlighted as a method to reduce single points of failure, distribute risk, and enhance the overall resilience of the system. The need for adaptive regulatory frameworks is also emphasized that can respond to the dynamic nature of these systems, as well as the necessity of improving the financial literacy and risk management capabilities of market participants. For the future research directions, it calls for a shift in research paradigms in this paper, embracing a more holistic and interdisciplinary approach that integrates complex system theory, social science, and economics. It advocates for the development of advanced analytical tools, such as agent-based modeling, system dynamics, and artificial intelligence, to better simulate and predict the behavior of economic and financial systems.In conclusion, it offers a novel viewpoint on the challenges posed by hyper-chain risk in the context of the hyper-connected world. It synthesizes insights from existing literature and proposes a new paradigm for understanding and managing risks in the hyper-connected world. By bridging the gap between complex system science, sociology, and economics, it seeks to stimulate discussions and foster a robust and adaptive approach to managing the hyper-connected complexities of modern socio-economic systems. Its contributions are expected to inspire further interdisciplinary research and inform policy-making, ultimately contributing to the stability and sustainability of the global economy.

Key words: hyper-connected world, hyper-chain risks, economic and financial system, risk formation and propagation, complex system theory

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