全球钴产业链网络动态演化内生驱动因素研究

doi:10.13776/j.cnki.resourcesindustries.20241029.003

摘要/Abstract

摘要： 绿色低碳转型背景下战略性、关键性矿产之一钴由于资源储量和产量低，分布不均衡等特点使得全球各国钴的对外依存度极高，国家（地区）间通过钴的进出口贸易形成了复杂的钴国际贸易网络。本研究选取钴产业链不同阶段的多种商品构建了全球钴产业链网络，通过多层网络指数随机图模型和时间指数随机图模型探讨了影响全球钴产业链网络结构形成与动态演化的内生驱动因素。研究发现钴产业链中不同阶段相同网络内生结构特征对全球钴产业链网络结构形成的影响是一致的，但影响程度有较大程度区别，互惠效应、结构依赖效应和时间依赖效应对全球钴产业链网络动态演化具有显著影响。本研究将国际贸易网络动态演化影响机制研究拓展至产业链视角下的多类商品，为产业链视角下钴国际贸易网络构建与恢复、风险传播与应对等研究提供了一定的启示作用。

关键词: 钴产业链, 多层网络, 动态演化, 多层指数随机图模型, 时间指数随机图模型, 内生驱动因素

Abstract: Most countries largely depend upon external cobalt sourcing due to its low reserve and production and uneven distribution as one of strategic and critical minerals during green low-carbon transformation, which makes cobalt global trading a complicated network. This paper selects a variety of cobalt commodities at different stages to establish a global cobalt industrial chain network, and studies the endogenous drivers of structural formation and dynamic evolution of global cobalt industrial chain network by means of multiple-layered network index random graph model and time index random graph model. In cobalt industrial chain, same network endogenous structures equally impact its structural formation at different stages with varying impacting extent. Mutual-beneficial effect, structural dependence effect and time dependence effect notably impact the dynamic evolution of global cobalt industrial chain. This study expands impacting mechanisms of dynamic evolution of global trade network to multiple commodities in industrial chain, offering references for construction and restoration, risks transmission, and measures of global cobalt trading network from perspective of industrial chain.

Key words: cobalt industrial chain, multiple-layered network, dynamic evolution, multiple-layered index random graph model, time index random graph model;endogenous drivers

中图分类号:

F205

王雁莉, 李华姣, 管建和. 全球钴产业链网络动态演化内生驱动因素研究[J]. 资源与产业, 2024, 26(5): 128-144.

WANG Yanli, LI Huajiao, GUAN Jianhe. ENDOGENOUS DRIVERS OF DYNAMIC EVOLUTION OF GLOBAL COBALT INDUSTRIAL CHAIN NETWORK[J]. Resources & Industries, 2024, 26(5): 128-144.

参考文献

安海忠,李华姣, 2022. 战略性矿产资源全产业链理论和研究前沿[J]. 资源与产业, 24(1): 8-14.〔AN H Z, LI H J, 2022. Theory and research advances in whole industrial chain of strategic mineral resources[J]. Resources & Industries, 24(1):8-14.〕

段庆锋,潘小换, 2018. 文献相似性对科学引用偏好的影响实证研究[J]. 图书情报工作, 62(4): 97-106.〔DUAN Q F, PAN X H, 2018. Empirical research on impact of documents similarity upon scientific citation preference[J]. Library and Information Service, 62(4): 97-106.〕

和聪贤, 2022. 世界大豆贸易网络格局演变及影响机制研究[J]. 世界农业 (8): 27-40.〔HE C X, 2022. Research on pattern evolution and influence mechanism of global soybean trade network[J]. World Agriculture (8): 27-40.〕

孔静静,韩传峰, 2013. 应急组织合作的结构逻辑及运行机制: 以2008年汶川地震应对为例[J]. 公共管理学报, 10(4): 88-101, 141-142.〔KONG J J, HAN C F, 2013. Structural logic and operation mechanism of emergency organizations collaboration: a case study of the response to the 2008 Wenchuan earthquake in China[J]. Journal of Public Management, 10(4): 88-101, 141-142.〕

刘林青,闫小斐,杨理斯,等, 2021. 国际贸易依赖网络的演化及内生机制研究[J]. 中国工业经济 (2): 98-116.〔LIU L Q, YAN X F, YANG L S, et al.，2021. Research on the evolution and endogenous mechanism of international trade dependence network[J]. China Industrial Economics (2): 98-116.〕

罗超亮,符正平,刘冰,等, 2022. 战略性新兴产业国际贸易网络的演化及动力机制研究[J]. 国际贸易问题 (3): 121-139.〔LUO C L, FU Z P, LIU B, et al.，2022. Research on the evolution strategic emerging industries’ international trade network and its dynamic mechanism[J]. Journal of International Trade (3): 121-139.〕

马述忠,任婉婉,吴国杰, 2016. 一国农产品贸易网络特征及其对全球价值链分工的影响: 基于社会网络分析视角[J]. 管理世界(3): 60-72.〔MA S Z, REN W W, WU G J, 2016. The characteristics of agricultural trade network and its effects on the global value chain division: a study base on social network analysis[J]. Journal of Management World (3): 60-72.〕

唐晓彬,崔茂生, 2020. “一带一路”货物贸易网络结构动态变化及其影响机制[J]. 财经研究, 46(7): 138-153.〔TANG X B, CUI M S, 2020. Research on the dynamic change of goods trade network structure and its impact mechanism of countries along the Belt and Road[J]. Journal of Finance and Economics, 46(7): 138-153.〕

魏素豪, 2018. 中国与“一带一路”国家农产品贸易:网络结构、关联特征与策略选择[J]. 农业经济问题(11): 101-113.〔WEI S H, 2018. Agricultural products trade between China and “The Belt and Road” countries: network structure, correlation characteristics and strategy selection[J]. Issues in Agricultural Economy (11): 101-113.〕

吴钢, 2014. 人文关系网络对国际贸易网络的影响机制及效应研究[D]. 长沙: 湖南大学.〔WU G, 2014. The mechanism and effect of the influence of international humanistic relation network on international trade network[D]. Changsha: Hunan University.〕

吴红梅,王蕊,殷沐阳, 2022. 基于ERGM模型的全球林产品出口贸易网络格局及影响因素分析[J]. 农林经济管理学报, 21(2): 188-197.〔WU H M, WANG R, YIN M YANG, 2022. Global forest products export trade network pattern and influencing factors based on ERGM[J]. Journal of Agro-Forestry Economics and Management, 21(2): 188-197.〕

许和连,孙天阳,成丽红, 2015. “一带一路”高端制造业贸易格局及影响因素研究: 基于复杂网络的指数随机图分析[J]. 财贸经济 (12): 74-88.〔XU H L, SUN T Y, CHENG L H, 2015. Trade patterns and influence factors of high-end manufacturing on “One Belt and One Road”[J]. Finance & Trade Economics, (12): 74-88.〕

杨文龙,杜德斌,盛垒, 2022. 全球商品贸易网络生长特征及动力机制[J]. 资源科学, 44(3): 508-522.〔YANG W L, DU D B, SHENG L, 2022. Growth characteristics of the global commodity trade network and its dynamic mechanism[J]. Resources Science, 44(3): 508-522.〕

赵晞泉,陈伟, 2024. 全球钴资源贸易网络演化及其启示[J]. 资源科学, 46(1): 100-113.〔ZHAO X Q, CHEN W, 2024. Changes of global cobalt trade network and implications[J]. Resources Science, 46(1): 100-113.〕

DU R J, WANG Y, DONG G G, et al.，2017. A complex network perspective on interrelations and evolution features of international oil trade, 2002-2013 [J]. Applied Energy, 196: 142-151.

GARLASCHELLI D, LOFFREDO M I, 2004. Patterns of link reciprocity in directed networks[J]. Physical Review Letters, 93: 268701.

GUAN Q, AN H Z, GAO X Y, et al.，2016. Estimating potential trade links in the international crude oil trade: a link prediction approach[J]. Energy, 102: 406-415.

HANNEKE S, FU W, XING E P, 2010. Discrete temporal models of social networks[J]. Electronic Journal of Statistics, 4: 585-605.

HILGERDT F, 1943. The case for multilateral trade [J]. The American Economic Review, 33: 393-407.

HOU W Y, LIU H F, WANG H, et al.，2018. Structure and patterns of the international rare earths trade: a complex network analysis[J]. Resources Policy, 55: 133-142.

HU X Q, WANG C, LIM M K, et al.，2020a. Characteristics of the global copper raw materials and scrap trade systems and the policy impacts of China‘s import ban[J]. Ecological Economics, 172: 106626.

HU X Q, WANG C, LIM M K, et al.，2020b. Characteristics and community evolution patterns of the international scrap metal trade[J]. Journal of Cleaner Production, 243: 118576.

KRIVITSKY P N, HANDCOCK M S, 2014. A separable model for dynamic networks[J]. Journal of the Royal Statistical Society Series B: Statistical Methodology, 76: 29-46.

LAN J, WANG K, FA G F, et al.，2019. Global pattern of international uranium trade and its impact on ecological environment and its various aspects [J]. Ekoloji, 28: 3351-3364.

LIU M, LI H J, ZHOU J S, et al.，2022. Analysis of material flow among multiple phases of cobalt industrial chain based on a complex network[J]. Resources Policy, 77: 102691

LUSHER D, KOSKINEN J, ROBINS G, 2013. Exponential random graph models for social networks: theory, methods, and applications [M]. Cambridge: Cambridge University Press.

NANSAI K, NAKAJIMA K, KAGAWA S, et al.，2014. Global flows of critical metals necessary for low-carbon technologies: the case of Neodymium, Cobalt, and Platinum[J]. Environmental Science & Technology, 48: 1391-1400.

SERRANO M A, BOGUNA M, 2003. Topology of the world trade web[J]. Physical Review E, 68: 015101.

SERRANO M A, BOGUNA M, VESPIGNANI A, 2009. Extracting the multiscale backbone of complex weighted networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 106: 6483-6488.

SHI Q, SUN X Q, XU M, et al.，2022. The multiplex network structure of global cobalt industry chain[J]. Resources Policy, 76: 102555.

SUN X Q, SHI Q, HAO X Q, 2022. Supply crisis propagation in the global cobalt trade network[J]. Resources Conservation and Recycling, 179: 106035.

SUN X, HAO H, LIU Z W, et al.，2019. Tracing global cobalt flow: 1995-2015[J]. Resources Conservation and Recycling, 149: 45-55.

WANG W Y, LI Z F, CHENG X, 2019. Evolution of the global coal trade network: a complex network analysis[J]. Resources Policy, 62: 496-506.

ZHONG W Q, AN H Z, FANG W, et al.，2016. Features and evolution of international fossil fuel trade network based on value of emergy[J]. Applied Energy, 165: 868-877.

ZHONG W Q, DAI T, WANG G S, et al.，2018. Structure of international iron flow: based on substance flow analysis and complex network[J]. Resources Conservation and Recycling, 136: 345-354.

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