This article examines the evolution of the global strategic emerging industries trade networks (GSEITNs) and employs the temporal exponential random graph model (TERGM) to investigate the principal determinants of the critical trade cooperation in the global strategic emerging industries (SEIs) from 2007 to 2020. The findings indicate that GSEITNs exhibit a sparse, hierarchical, and monopolistic structure. Despite the continual integration of emerging nations into GSEITNs, countries have grown progressively wary of the network. Moreover, the structure properties of the endogenous network proves that SEIs trade links have a substantial signaling effect. More importantly, SEIs trade is more reliant on the economic size and innovation capacity, and countries are more cautious about protecting their intellectual property, especially when trading with countries possessing similar R&D levels. Furthermore, robust bilateral political ties can augment the probability of SEIs trade between two countries, particularly in sectors such as new energy vehicles and new-generation information technology industries. In summary, this article takes into account the influence of network structure, national attributes and external networks, and provides new insights into studying trade network evolution in SEIs.

中文翻译：

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全球战略性新兴产业贸易网络结构特征演变及其决定因素：TERGM分析

本文考察了全球战略新兴产业贸易网络（GSEITN）的演变，并采用时间指数随机图模型（TERGM）研究了2007年至2020年全球战略新兴产业（SEI）关键贸易合作的主要决定因素。研究结果表明，GSEITN 呈现出稀疏、层级和垄断的结构。尽管新兴国家不断融入 GSEITN，但各国对该网络的警惕性却逐渐提高。此外，内生网络的结构特性证明SE​​I贸易链接具有显着的信号效应。更重要的是，SEIs贸易更加依赖经济规模和创新能力，各国对于保护知识产权更加谨慎，尤其是在与研发水平相似的国家进行贸易时。此外，强有力的双边政治关系可以增加两国之间SEIs贸易的可能性，特别是在新能源汽车和新一代信息技术产业等领域。综上所述，本文考虑了网络结构、国家属性和外部网络的影响，为研究SEI贸易网络演化提供了新的见解。