IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v49y2016icp415-421.html
   My bibliography  Save this article

Understanding international trade network complexity of platinum: The case of Japan

Author

Listed:
  • Tokito, Shohei
  • Kagawa, Shigemi
  • Nansai, Keisuke

Abstract

In recent decades, platinum-group metals have become increasingly important to the development and diffusion of cleaner technologies being developed to achieve a “low carbon” society. Countries engaged in the development and diffusion of new energy technologies are concerned about steadily importing scarce rare metals. Nevertheless, the question of what kind of competitive relationships exist among demand countries is not well addressed. This study focused on platinum primary product used to produce greener products like next-generation vehicles and analyzed the international trade network complexity of the platinum primary product using the clustering method. From the results, we found that (1) there exit well-separated nine trade clusters (i.e., trade networks with higher exchanges) in the international trade network of 2005, (2) the group including South Africa and the group consisting of Western countries together account for approximately half the total international trade flow in platinum primary products, and (3) international coordination of purchases and sales of platinum among relevant trade partners in the identified largest cluster: South Africa, Russia, Japan, China, Hong Kong, and Switzerland is crucial in securing the stable supply and demand for platinum.

Suggested Citation

  • Tokito, Shohei & Kagawa, Shigemi & Nansai, Keisuke, 2016. "Understanding international trade network complexity of platinum: The case of Japan," Resources Policy, Elsevier, vol. 49(C), pages 415-421.
    • Handle: RePEc:eee:jrpoli:v:49:y:2016:i:c:p:415-421
    DOI: 10.1016/j.resourpol.2016.07.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420716301118
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2016.07.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    2. Keisuke Nansai & Shigemi Kagawa & Yasushi Kondo & Sangwon Suh & Rokuta Inaba & Kenichi Nakajima, 2009. "Improving The Completeness Of Product Carbon Footprints Using A Global Link Input-Output Model: The Case Of Japan," Economic Systems Research, Taylor & Francis Journals, vol. 21(3), pages 267-290.
    3. Shunsuke Okamoto, 2015. "Analyzing instability of industrial clustering techniques," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(3), pages 389-406, July.
    4. Shigemi Kagawa & Sangwon Suh & Yasushi Kondo & Keisuke Nansai, 2013. "Identifying environmentally important supply chain clusters in the automobile industry," Economic Systems Research, Taylor & Francis Journals, vol. 25(3), pages 265-286, September.
    5. Shigetomi, Yosuke & Nansai, Keisuke & Kagawa, Shigemi & Tohno, Susumu, 2015. "Trends in Japanese households' critical-metals material footprints," Ecological Economics, Elsevier, vol. 119(C), pages 118-126.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liang, Xuedong & Yang, Xu & Yan, Fuhai & Li, Zhi, 2020. "Exploring global embodied metal flows in international trade based combination of multi-regional input-output analysis and complex network analysis," Resources Policy, Elsevier, vol. 67(C).
    2. Chen, Jinyu & Luo, Qian & Sun, Xin & Zhang, Zitao & Dong, Xuesong, 2023. "The impact of renewable energy consumption on lithium trade patterns: An industrial chain perspective," Resources Policy, Elsevier, vol. 85(PA).
    3. Ren, Shuai & Li, Huajiao & Wang, Yanli & Guo, Chen & Feng, Sida & Wang, Xingxing, 2021. "Comparative study of the China and U.S. import trade structure based on the global chromium ore trade network," Resources Policy, Elsevier, vol. 73(C).
    4. Tang, Qianyong & Li, Huajiao & Qi, Yajie & Li, Yang & Liu, Haiping & Wang, Xingxing, 2023. "The reliability of the trade dependence network in the tungsten industry chain based on percolation," Resources Policy, Elsevier, vol. 82(C).
    5. Hou, Wenyu & Liu, Huifang & Wang, Hui & Wu, Fengyang, 2018. "Structure and patterns of the international rare earths trade: A complex network analysis," Resources Policy, Elsevier, vol. 55(C), pages 133-142.
    6. Zhang, Ling & Wang, Liang & Wang, Miaomiao & Yuan, Zengwei, 2024. "Multilevel analysis of copper resource reallocation in the anthroposphere through international trade," Resources Policy, Elsevier, vol. 88(C).
    7. Zhu, Zhiyun & Dong, Zhiliang & Zhang, Yanxing & Suo, Guibin & Liu, Sen, 2020. "Strategic mineral resource competition: Strategies of the dominator and nondominator," Resources Policy, Elsevier, vol. 69(C).
    8. Yawen Han & Wanli Xing & Hongchang Hao & Xin Du & Chongyang Liu, 2022. "Interprovincial Metal and GHG Transfers Embodied in Electricity Transmission across China: Trends and Driving Factors," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    9. Song, Yi & Bai, Wenbo & Zhang, Yijun, 2024. "Resilience assessment of trade network in copper industry chain and the risk resistance capacity of core countries: Based on complex network," Resources Policy, Elsevier, vol. 92(C).
    10. Cappelli, Federica & Carnazza, Giovanni & Vellucci, Pierluigi, 2023. "Crude oil, international trade and political stability: Do network relations matter?," Energy Policy, Elsevier, vol. 176(C).
    11. Giovanni Carnazza & Pierluigi Vellucci, 2022. "Network analysis and Eurozone trade imbalances," Papers 2209.09837, arXiv.org.
    12. Shigetomi, Yosuke & Nansai, Keisuke & Kagawa, Shigemi & Kondo, Yasushi & Tohno, Susumu, 2017. "Economic and social determinants of global physical flows of critical metals," Resources Policy, Elsevier, vol. 52(C), pages 107-113.
    13. Tokito, Shohei, 2018. "Environmentally-Targeted Sectors and Linkages in the Global Supply-Chain Complexity of Transport Equipment," Ecological Economics, Elsevier, vol. 150(C), pages 177-183.
    14. Kang, Xinyu & Wang, Minxi & Wang, Taixin & Luo, Fanjie & Lin, Jing & Li, Xin, 2022. "Trade trends and competition intensity of international copper flow based on complex network: From the perspective of industry chain," Resources Policy, Elsevier, vol. 79(C).
    15. Chen, Guang & Kong, Rui & Wang, Yixin, 2020. "Research on the evolution of lithium trade communities based on the complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    16. Keisuke Nansai & Kenichi Nakajima & Sangwon Suh & Shigemi Kagawa & Yasushi Kondo & Wataru Takayanagi & Yosuke Shigetomi, 2017. "The role of primary processing in the supply risks of critical metals," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 335-356, July.
    17. Maeno, Keitaro & Tokito, Shohei & Kagawa, Shigemi, 2022. "CO2 mitigation through global supply chain restructuring," Energy Economics, Elsevier, vol. 105(C).
    18. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    19. Li, Yingli & Huang, Jianbai & Zhang, Hongwei, 2022. "The impact of country risks on cobalt trade patterns from the perspective of the industrial chain," Resources Policy, Elsevier, vol. 77(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yosuke Shigetomi & Keisuke Nansai & Shigemi Kagawa & Susumu Tohno, 2016. "Influence of income difference on carbon and material footprints for critical metals: the case of Japanese households," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-19, December.
    2. Hajime Ohno & Kazuyo Matsubae & Kenichi Nakajima & Keisuke Nansai & Yasuhiro Fukushima & Tetsuya Nagasaka, 2016. "Consumption-based accounting of steel alloying elements and greenhouse gas emissions associated with the metal use: the case of Japan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-17, December.
    3. Li, Xi & Zhang, Runsen & Chen, Jundong & Jiang, Yida & Zhang, Qiong & Long, Yin, 2021. "Urban-scale carbon footprint evaluation based on citizen travel demand in Japan," Applied Energy, Elsevier, vol. 286(C).
    4. Tokito, Shohei, 2018. "Environmentally-Targeted Sectors and Linkages in the Global Supply-Chain Complexity of Transport Equipment," Ecological Economics, Elsevier, vol. 150(C), pages 177-183.
    5. Keisuke Nansai & Kenichi Nakajima & Sangwon Suh & Shigemi Kagawa & Yasushi Kondo & Wataru Takayanagi & Yosuke Shigetomi, 2017. "The role of primary processing in the supply risks of critical metals," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 335-356, July.
    6. Rafael Teixeira & Mário Antunes & Diogo Gomes & Rui L. Aguiar, 2024. "Comparison of Semantic Similarity Models on Constrained Scenarios," Information Systems Frontiers, Springer, vol. 26(4), pages 1307-1330, August.
    7. Del Corso, Gianna M. & Romani, Francesco, 2019. "Adaptive nonnegative matrix factorization and measure comparisons for recommender systems," Applied Mathematics and Computation, Elsevier, vol. 354(C), pages 164-179.
    8. P Fogel & C Geissler & P Cotte & G Luta, 2022. "Applying separative non-negative matrix factorization to extra-financial data," Working Papers hal-03689774, HAL.
    9. Xiao-Bai Li & Jialun Qin, 2017. "Anonymizing and Sharing Medical Text Records," Information Systems Research, INFORMS, vol. 28(2), pages 332-352, June.
    10. Huang, Liqiao & Yoshida, Yoshikuni & Li, Yuan & Cheng, Nan & Xue, Jinjun & Long, Yin, 2024. "Sustainable lifestyle: Quantification and determining factors analysis of household carbon footprints in Japan," Energy Policy, Elsevier, vol. 186(C).
    11. Naiyang Guan & Lei Wei & Zhigang Luo & Dacheng Tao, 2013. "Limited-Memory Fast Gradient Descent Method for Graph Regularized Nonnegative Matrix Factorization," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-10, October.
    12. Spelta, A. & Pecora, N. & Rovira Kaltwasser, P., 2019. "Identifying Systemically Important Banks: A temporal approach for macroprudential policies," Journal of Policy Modeling, Elsevier, vol. 41(1), pages 197-218.
    13. M. Moghadam & K. Aminian & M. Asghari & M. Parnianpour, 2013. "How well do the muscular synergies extracted via non-negative matrix factorisation explain the variation of torque at shoulder joint?," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 16(3), pages 291-301.
    14. Markovsky, Ivan & Niranjan, Mahesan, 2010. "Approximate low-rank factorization with structured factors," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3411-3420, December.
    15. Paul Fogel & Yann Gaston-Mathé & Douglas Hawkins & Fajwel Fogel & George Luta & S. Stanley Young, 2016. "Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health," IJERPH, MDPI, vol. 13(5), pages 1-14, May.
    16. Le Thi Khanh Hien & Duy Nhat Phan & Nicolas Gillis, 2022. "Inertial alternating direction method of multipliers for non-convex non-smooth optimization," Computational Optimization and Applications, Springer, vol. 83(1), pages 247-285, September.
    17. Zhaoyu Xing & Yang Wan & Juan Wen & Wei Zhong, 2024. "GOLFS: feature selection via combining both global and local information for high dimensional clustering," Computational Statistics, Springer, vol. 39(5), pages 2651-2675, July.
    18. Chae, Bongsug (Kevin), 2018. "The Internet of Things (IoT): A Survey of Topics and Trends using Twitter Data and Topic Modeling," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society 190376, International Telecommunications Society (ITS).
    19. Md Nazrul Islam & Md Mofazzal Hossain & Md Shafayet Shahed Ornob, 2024. "Business research on Industry 4.0: a systematic review using topic modelling approach," Future Business Journal, Springer, vol. 10(1), pages 1-15, December.
    20. Mi, Zhifu & Zhang, Yunkun & Guan, Dabo & Shan, Yuli & Liu, Zhu & Cong, Ronggang & Yuan, Xiao-Chen & Wei, Yi-Ming, 2016. "Consumption-based emission accounting for Chinese cities," Applied Energy, Elsevier, vol. 184(C), pages 1073-1081.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:49:y:2016:i:c:p:415-421. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.