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<p>Economic growth dependence provides a new perspective for the study of global value chains. Based on the dependence relationship of economic growth, Global Value Chain (GVC) networks had been constructed, and the structural characteristics had been analyzed. Utilizing the Stochastic Actor-Oriented Model (SAOM), this paper explored the evolution and the driving factors of GVC networks. The results showed that: (1) China has established the dominant position of its domestic economic circulation, with the role in GVC networks continuously rising. (2) Exogenous structural effects factors play the biggest role in shaping GVC networks, contributing about 80.58% on average. (3) Multiple endogenous attribute effects factors collectively play a significant role in the evolution of GVC networks, contributing about 19.42% on average.</p>

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Investigating the changes and driving forces of global value chain networks based on the stochastic actor-oriented model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月27日

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  • Renquan Huang,
  • Cunpu Li,
  • Jing Tian,
  • Qinrong He,
  • Xiao Liu,
  • Qingyun Zhang

摘要

Economic growth dependence provides a new perspective for the study of global value chains. Based on the dependence relationship of economic growth, Global Value Chain (GVC) networks had been constructed, and the structural characteristics had been analyzed. Utilizing the Stochastic Actor-Oriented Model (SAOM), this paper explored the evolution and the driving factors of GVC networks. The results showed that: (1) China has established the dominant position of its domestic economic circulation, with the role in GVC networks continuously rising. (2) Exogenous structural effects factors play the biggest role in shaping GVC networks, contributing about 80.58% on average. (3) Multiple endogenous attribute effects factors collectively play a significant role in the evolution of GVC networks, contributing about 19.42% on average.