ORIGINAL PAPER
Evolution analysis of the global lithium industrial chain trade network: based on the event-shock complex network method
,
 
,
 
 
 
More details
Hide details
1
Development and Research Center of China Geological Survey
 
 
Submission date: 2026-05-02
 
 
Final revision date: 2026-06-08
 
 
Acceptance date: 2026-06-14
 
 
Publication date: 2026-09-28
 
 
Corresponding author
Xuezheng Gao   

Development and Research Center of China Geological Survey
 
 
Gospodarka Surowcami Mineralnymi – Mineral Resources Management 2026;42(3):173-194
 
KEYWORDS
TOPICS
ABSTRACT
Lithium has become a driving force of the new energy revolution, a crucial option for the international community to jointly advance ecological civilization construction, and one of the fundamental resources for achieving carbon neutrality. Its industrial chain trade exerts a significant impact on the global economy. To further explore the patterns and characteristics of international trade in products across all stages of the lithium industrial chain, this paper adopts a full-industry-chain perspective. It applies the complex network method with Event Impact Factor to analyze the evolution of trade patterns in the upstream, midstream and downstream sectors, and constructs trade network indicators to examine the overall and individual nodal characteristics of the network. The research findings indicate that: The international trade of the lithium industrial chain presents distinct trends of decentralization, centralization and polarization transfer in the upstream, midstream and downstream respectively. Upstream trade is primarily affected by industrial technological upgrading and geopolitics, while midstream and downstream trade is mainly shaped by national strategic planning, industrial development and geographical advantages. Countries in the lithium trade network maintain close ties. While network connectivity and efficiency keep rising, blocization remains prominent. Finally, targeted policy recommendations are proposed to enhance the resilience of the entire lithium industrial chain, including improving global governance of the lithium trade network, promoting diversified trade strategies for the global lithium industrial chain, and establishing a global trade early warning and emergency response mechanism.
CONFLICT OF INTEREST
The Authors have no conflict of interest to declare.
METADATA IN OTHER LANGUAGES:
Polish
Analiza ewolucji globalnej sieci handlowej łańcucha przemysłowego litowego w oparciu o metodę sieci złożonych opartych na zdarzeniach i wstrząsach
handel produktami litowymi, pełny łańcuch przemysłowy, złożona sieć podlegająca wpływom zdarzeń i wstrząsów, ewolucja sieci
Lit stał się siłą napędową rewolucji w dziedzinie nowych źródeł energii, kluczowym rozwiązaniem dla społeczności międzynarodowej w zakresie wspólnego budowania cywilizacji ekologicznej oraz jednym z podstawowych zasobów niezbędnych do osiągnięcia neutralności węglowej. Handel w ramach łańcucha przemysłowego litu wywiera znaczący wpływ na gospodarkę światową. Aby dokładniej zbadać wzorce i cechy charakterystyczne handlu międzynarodowego produktami na wszystkich etapach łańcucha przemysłowego litu, w niniejszym artykule przyjęto perspektywę obejmującą cały łańcuch przemysłowy. Wykorzystano metodę sieci złożonych z uwzględnieniem wskaźnika wpływu zdarzeń (Event Impact Factor) do analizy ewolucji wzorców handlu w sektorach górnym, środkowym i dolnym łańcucha przemysłowego oraz skonstruowano wskaźniki sieci handlowej w celu zbadania ogólnych i indywidualnych cech węzłów sieci. Wyniki badań wskazują, że: międzynarodowy handel w łańcuchu przemysłowym litu wykazuje wyraźne tendencje do decentralizacji, centralizacji i przenoszenia polaryzacji odpowiednio w sektorach upstream, midstream i downstream. Na handel w sektorze upstream wpływają przede wszystkim modernizacja technologiczna przemysłu oraz uwarunkowania geopolityczne, natomiast handel w sektorach midstream i downstream kształtowany jest głównie przez krajowe planowanie strategiczne, rozwój przemysłowy oraz przewagi geograficzne. Kraje w sieci handlu litem utrzymują bliskie powiązania. Chociaż łączność i efektywność sieci stale rosną, nadal wyraźnie widoczne jest tworzenie się bloków. Na koniec przedstawiono konkretne zalecenia dotyczące polityki, mające na celu zwiększenie odporności całego łańcucha przemysłowego litowego, w tym poprawę globalnego zarządzania siecią handlu litem, promowanie zróżnicowanych strategii handlowych dla globalnego łańcucha przemysłowego litowego oraz ustanowienie globalnego mechanizmu wczesnego ostrzegania i reagowania kryzysowego w handlu.
REFERENCES (49)
1.
Arthur et al. 1997 – Arthur, B.W., Durlauf, S.N. and Lane, D.A. 1997. The Economy as an Evolving Complex System II. [In:] Sfi Economics Program, Sfi Economics Program.
 
2.
Bai et al. 2024 – Bai, G.Y., Liang, M. and Qi, G.J. 2024. Dependency Risk and Countermeasures of China's Clean Energy Critical Mineralsʼ Import. Asia-Pacific Economic Review 3, pp. 141–152, https://doi.org/10.16407/j.cnk....
 
3.
Barabasi, A.L. and Albert, R. 1999. Emergence of scaling in random networks. Science 286, pp. 509–512, https://doi.org/10.1126/scienc....
 
4.
Beck, K. and Jackson, K. 2024. International trade fluctuations: Global versus regional factors. Canadian Journal of Economics 57(1), pp. 331–358, https://doi.org/10.1111/caje.1....
 
5.
Chen et al. 2022 – Chen, C., Jiang, Z., Li, N., Wang, H., Wang, P., Zhang, Z., Chao Zhang, C., Ma, F., Huang, Y., Lu, X., Wei, J., Qi, J. and Chen, W.Q. 2022. Advancing UN Comtrade for Physical Trade Flow Analysis: Review of Data Quality Issues and Solutions. Resources, Conservation and Recycling 186, https://doi.org/10.1016/j.resc... (in Chinese).
 
6.
Chen et al. 2020 – Chen, G., Kong, R. and Wang, Y. 2020. Research on the evolution of lithium trade communities based on the complex network. Physica A: Statistical Mechanics and its Applications 540(C), https://doi.org/10.1016/j.phys....
 
7.
Chen et al. 2022 – Chen, W., Jiang, Y. and Liu, Z. 2025. Evolution and resilience of the global nickel resources trade network. World Regional Studies 34(1), https://doi.org/10.3969/j.issn....
 
8.
Chen, Z.H. and Feng, M. 2017. Spatial-temporal Variation Characteristics and Trade Pattern of the World Cotton Trade Network Based on the Dynamic Complex Network. International Economics and Trade Research, pp. 36–50, https://doi.org/10.13687/j.cnk... (in Chinese).
 
9.
Craig-Scheckman, M. and Moore, S. 2025. Supply chain competitiveness index: Evaluating U.S. and Chinaʼs lithium-ion battery industries. Resources Policy 107, https://doi.org/10.1016/j.reso....
 
10.
Dong et al. 2016 – Dong, D., An, H., Hao, X. and Zhong, W. 2016. International copper ore trade pattern based on complex network. Economic Geography 36(10), pp. 93–101, https://doi.org/10.15957/j.cnk....
 
11.
Fehérvölgyi et al. 2024 – Fehérvölgyi, B., Király, T. and Kosztyán, Z.T. 2024. Dynamic network analysis of trade networks (Világkereskedelmi hálózatok idősoros vizsgálata). Statisztikai Szemle 102, pp. 38–77, https://doi.org/10.20311/stat2... (in Hungarian).
 
12.
Freeman, L.C. 1977. A Set of Measures of Centrality Based on Betweenness. Sociometry 40(1), pp. 35–41, https://doi.org/10.2307/303354....
 
13.
Granovetter, M. 1985. Economic Action and Social Structure: The Problem of Embeddedness. American Journal of Sociology 91(3), pp. 481–510.
 
14.
Hao et al. 2013 – Hao X.Q., An, H.Z., Chen, Y.R. and Gao, X.Y. 2013. Research on Evolution of International Iron Ore Trade Based on Complex Network Theory. Economic Geography 1, pp. 92–97, https://doi.org/10.15957/j.cnk....
 
15.
Hu et al. 2026 – Hu, Q.J., Hu, M.Y. and Li, J.H. 2026. Spatio-temporal evolution and driving mechanisms of the global petroleum trade dependency network. Oil & Gas Storage and Transportation 45(3), https://doi.org/10.6047/j.issn....
 
16.
Hulianskyi, O. 2025. The Evolution of Global Gold and Copper Trade Networks. Northeast Journal of Complex Systems 7(2), https://doi.org/10.63562/2577-....
 
17.
Kong et al. 2024 – Kong, W., Cheng, J. and Xiao, J. 2024. Market Risk of Lithium Industry Chain – Evidence from Listed Companies. Energies 17(23), https://doi.org/10.3390/en1723....
 
18.
Kong, X.Y. and Zhang, Y.S. 2022. Lithium Resources: The Driving Force of the New Energy Revolution. Frontiers, pp. 76–81, https://doi.org/10.16619/j.cnk....
 
19.
Kosztyán, Z.T. and Kosztyánné Mátrai, R. 2025. Dynamic analysis of multilayer trade networks. Statisztikai Szemle 103(9), pp. 811–852, https://doi.org/10.20311/stat2... (in Hungarian).
 
20.
Ling et al. 2024 – Ling, J.Y., Zhou, N., Hu, P.Q., et al. 2024. Evolution of trade network pattern of chromium ore in global and analysis of competitiveness. China Mining Magazine, pp. 48–58 (in Chinese).
 
21.
Liu et al. 2020 – Liu, S., Dong, Z., Ding, C., Wang, T. and Zhang, Y. 2020. Do you need cobalt ore? Estimating potential trade relations through link prediction. Resources Policy 66, https://doi.org/10.1016/j.reso....
 
22.
Man, Y. and Ren, S.T. 2015. Detecting world trade patterns by complex networks. Journal of Beijing Normal University (Natural Science) 51(2), pp. 140–143, https://doi.org/10.16360/j.cnk... (in Chinese).
 
23.
Meng et al. 2025 – Meng, Z., Sun, H., Daigo, I., Guan, J. and Shan, Y. 2025. Technological risks disrupting trade stability in the global lithium supply chain network. iScience 28(7), https://doi.org/10.1016/j.isci....
 
24.
Rincón et al. 2025 – Rincón, J.M., Gómez, P.C. and Vidal, M.M.J. 2025. Lithium Minerals and their Applications in the “Glass Age”. Estudios Geologicos 81(2), https://doi.org/10.3989/egeol.....
 
25.
Serrano, M.Á. and Boguñá, M. 2003. Topology of the world trade web. Physical Review E 68, https://doi.org/10.1103/PhysRe....
 
26.
Shao et al. 2021 – Shao, L., Hu, J. and Zhang, H. 2021. Evolution of global lithium competition network pattern and its influence factors. Resources Policy 74, https://doi.org/10.1016/j.reso....
 
27.
Shao et al. 2022 – Shao, L., Kou, W. and Zhang, H. 2022. The evolution of the global cobalt and lithium trade pattern and the impacts of the low-cobalt technology of lithium batteries based on multiplex network. Resources Policy 76, https://doi.org/10.1016/j.reso....
 
28.
Sun et al. 2018 – Sun, X., Hao, H., Zhao, F. and Liu, Z. 2018. Global Lithium Flow 1994-2015: Implications for Improving Resource Efficiency and Security. Environmental Science and Technology 52(5), pp. 2827–2834, https://doi.org/10.1021/acs.es....
 
29.
Sun et al. 2021 – Sun, H., Chen, L., Cheng, J.H. and Zhou, W. 2025. Simulation of dynamic impact of technological innovation on the sustainable supply of key minerals: A case study of lithium. Journal of Central South University Social Sciences 4, pp. 113–127 (in Chinese).
 
30.
Sun et al. 2022 – Sun, X., Shi, Q. and Hao, X. 2022. Supply crisis propagation in the global cobalt trade network. Resources, Conservation & Recycling 179, https://doi.org/10.1016/j.resc....
 
31.
Tian et al. 2021. – Tian, X., Geng, Y., Sarkis, J., Gao, C., Sun, X., Micic, T., Hao, H. and Wang, X. 2021. Features of critical resource trade networks of lithium-ion batteries. Resources Policy 73, https://doi.org/10.1016/j.reso....
 
32.
Wang et al. 2015 – Wang, J.L., Xu, L.B. and Pang, C.Y. 2015. Evolution model of online social networks based on complex networks. CAAI Transactions on Intelligent Systems 10(6), pp. 949–953, https://doi.org/10.11992/tis.2... (in Chinese).
 
33.
Wang et al. 2023a – Wang, M., Guo, Y., Hu, H. and Ding, S. 2023a. Embodied carbon emission flow network analysis of the global nickel industry chain based on complex network. Sustainable Production and Consumption 42, pp. 380–391, https://doi.org/10.1016/j.spc.....
 
34.
Wang et al. 2023b – Wang, X.Q., Qin, M., Moldovan, N.C. and Su, C.W. 2023b. Bubble behaviors in lithium price and the contagion effect: An industry chain perspective. Resources Policy 83, https://doi.org/10.1016/j.reso....
 
35.
Wang et al. 2025 – Wang, J., Tan, X. and Liu, D. 2025. Critical risks in an industry chain-based global lithium supply networks: Static structure and dynamic propagation. Process Safety and Environmental Protection 198, https://doi.org/10.1016/j.psep....
 
36.
Wang et al. 2026 – Wang, C., Tan, K., Hu, X., Sun, B. and Zhao, X. 2026. The determinants of global lithium-ion battery trade network based on temporal exponential random graph model. Journal of Industrial Ecology 30, https://doi.org/10.1007/s44498....
 
37.
Watts, D.J. and Strogatz, S.H. 1998. Collective dynamics of ‘small-world’ networks. Nature 393, pp. 440–442, https://doi.org/10.1038/30918.
 
38.
Xing et al. 2022 – Xing, J., Chen, Q., Zhang, Y., Yu, W., Long, T., Zheng, G. and Wang, K. 2022. Development of Lithium and Its Downstream Power Battery Industry Chain in China. Strategic Study of CAE 24(3), pp. 10–19, https://www.engineering.org.cn....
 
39.
Yang et al. 2021 – Yang, P., Gao, X., Zhao, Y., Nanfei Jia, N. and Dong, X. 2021. Lithium resource allocation optimization of the lithium trading network based on material flow. Resources Policy 74, https://doi.org/10.1016/j.reso....
 
40.
Ye et al. 2022 – Ye, H., Li, Z., Li, G. and Liu, G. 2022. Topology Analysis of Natural Gas Pipeline Networks Based on Complex Network Theory. Energies 15(11), https://doi.org/10.3390/en1511....
 
41.
Yi et al. 2024 – Yi, L., Li, Y.Y., Xie, L.Y., et al. 2024. Research on the evolution of trade pattern and export competitiveness of global rare earth industry chain. China Mining Magazine, pp. 53–62 (in Chinese).
 
42.
Yu, H. and Ding, Y.H. 2021. Study on the spatial and temporal correlation of global cobalt intermediate products trade network. China Mining Magazine, pp. 40–47 (in Chinese).
 
43.
Yu et al. 2022 – Yu, Y., Ma, D.P. and Wang, X.M. 2022. International trade network resilience for products in the whole industrial chain of iron ore resources. Resources Science 44, pp. 2006–2021, https://doi.org/10.18402/resci... (in Chinese).
 
44.
Zhang et al. 2015 – Zhang, L.J., Zhang, L.L., Hao, X.Q., Fang, W. and Wu Y.Y. 2015. Research into evolution of international copper ore trade based on complex network theory. China Mining Magazine 24(10), pp. 57–62 (in Chinese).
 
45.
Zhang et al. 2025 – Zhang, Y., Wenbo, B., Yi, S. and Wu, C. 2025. Impact of geopolitical risks on resilience of lithium resource trade network: Based on complex network and panel regression analysis. Resources Science 47(7), pp. 1517–1532, https://doi.org/10.18402/resci....
 
46.
Zheng et al. 2025 – Zheng, L.C., Bao, W.Q., Chen, G. and Geng, A. 2025. Multi-scenario dynamic analysis of demand for critical minerals in China’s new energy vehicles under “dual carbon” goals. Resources Science 47(7), pp. 1485–1504, https://doi.org/10.18402/resci....
 
47.
Zhou et al. 2023 – Zhou, R.B., Chen, Y.N. and Qin, Y. 2023. .Evolution and influencing factors of global high-tech products trade network. World Regional Studies 32(6), pp. 1–13, https://doi.org/10.3969/j.issn... (in Chinese).
 
48.
Zhu et al. 2025 – Zhu, X.H., Liu, J.R. and Zeng, A.Q. 2022. Analysis of Chinaʼs embodied cobalt consumption structure characteristics and key paths based on industrial complex networks. Journal of Central South University (Social Science), pp. 68–81 (in Chinese).
 
49.
Zhuang et al. 2022 – Zhuang, D., Li, J., Chen, Z. and Liu, Y. 2022. The Dynamic Change of Global Rare Earth Trade Network and Its Impact Mechanism: From the Perspective of Industrial Chain. Geographical Science 42(11), pp. 1900–1911, https://doi.org/10.13249/j.cnk... (in Chinese).
 
eISSN:2299-2324
ISSN:0860-0953
Journals System - logo
Scroll to top