摘要
【目的】无人机是全球战略性新兴科技的热门发展方向和中国具有较强竞争力的高科技产品之一,揭示全球无人机贸易网络及影响因素,可为全球优化贸易格局、中国规避潜在贸易风险提供决策支持。【方法】本文运用复杂网络分析方法、指数随机图模型和网络脆弱性模拟模型,揭示了2022—2024年全球无人机贸易网络拓扑特征,剖析了网络形成的影响因素,模拟了不同冲击情景下的网络脆弱性。【结果】①2022—2024年,全球无人机贸易额从42.32亿美元增长到126.65亿美元,增长了1.99倍。贸易额变化与全球地缘局势、贸易管制政策具有联动性。②参与全球无人机贸易网络的经济体及贸易联系的数量整体上升,“小世界”现象显著。现阶段,乌克兰、美国等欧美经济体的进口地位愈发突出,中国内地、中国香港逐渐主导出口格局,马来西亚对网络的影响力快速扩大。网络由单核结构演化为双核结构,形成以中国内地和中国香港为主要核心的超级组团,覆盖全球75%的经济体、近80%的贸易额。③互惠关系是驱动网络扩张的重要内生结构,开放程度大、制度环境好、科技水平高、经济实力强的经济体以其显著的进出口优势塑造了网络主体结构,地理距离和地缘关系对贸易联系建立的影响有限。④在传递式为主的贸易网络模体结构影响下,不同类型经济体的退出对网络效率的影响表现为媒介型>综合型>出口型>进口型,“出口型”经济体的出口管制对网络效率的影响高于“进口型”经济体的进口管制。【结论】研究期内,全球无人机贸易规模倍增,网络结构的变化与国际局势具有联动性,中国在全球无人机贸易市场具有规模性优势和集中性风险。
[Objective]Unmanned aerial vehicles(UAV)represent a key development direction in global strategic emerging technologies and one of the highly competitive high-tech products in China.Revealing the global UAV trade network and its influencing factors can provide decision-making support for optimizing the global trade pattern and helping China avoid potential trade risks.[Methods]Complex network analysis,exponential random graph model,and network vulnerability simulation model were employed to reveal the topological characteristics of the global UAV trade network from 2022 to 2024,analyze the influencing factors of the network,and simulate the network vulnerability under different impact scenarios.[Results](1)From 2022 to 2024,global UAV trade volume increased from 4.232 billion USD to 12.665 billion USD,an increase of 1.99 times.Changes in trade volume were linked to the global geopolitical situation and trade control policies.(2)Overall,both the number of participating economies and trade connections in the global UAV trade network increased,with a significant small-world phenomenon.At present,western economies such as Ukraine and the United States have played an increasingly prominent role as importers,while the mainland of China and Hong Kong of China gradually dominated the export pattern.Malaysia’s influence on trade networks rapidly expanded.The network evolved from a single-core structure to a dual-core structure,forming a super cluster centered on the mainland of China and Hong Kong of China,covering 75%of the global economies and nearly 80%of the trade volume.(3)Reciprocal relationships served as a critical endogenous structure driving the expansion of the network.Economies with high openness,favorable institutional environment,advanced technological levels,and strong economic strength shaped the core structure of the network through their significant advantages in both imports and exports.The influence of geographical distance and geopolitical relationships on the establishment of trade connections was limited.(4)Under the influence of the transmission-based trade network motif structure,the influence of the withdrawal of different types of economies on network efficiency followed the order:intermediary type>comprehensive type>export-oriented type>import-oriented type.The influence of export restrictions by export-oriented type economies on network efficiency was greater than that of import restrictions by import-oriented type economies.[Conclusion]From 2022 to 2024,the global UAV trade scale has doubled,and changes in the network structure are linked to the international situation.China has a scale advantage and concentrated risks in the global UAV trade market.
作者
张超
陆旻昊
秦奇
吴映梅
ZHANG Chao;LU Minhao;QIN Qi;WU Yingmei(Faculty of Geography,Yunnan Normal University,Kunming 650500,China;The Strategic Assessment and Consultation Institute,Academy of Military Science,Beijing 100091,China;Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China)
出处
《资源科学》
北大核心
2025年第8期1772-1791,共20页
Resources Science
基金
云南省科技厅基础研究专项(202401CF070030)
云南省基础研究重点项目(202401AS070037)
国家自然科学基金重点项目(42130508)。
关键词
无人机
贸易网络
指数随机图模型
影响因素
脆弱性
全球
unmanned aerial vehicles
trade network
exponential random graph model
influencing factors
vulnerability
global
