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Examining industry vulnerability: A focus on mineral commodities used in the automotive and electronics industries

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  • Manley, Ross L.
  • Alonso, Elisa
  • Nassar, Nedal T.

Abstract

Automotive manufacturing is material-intensive and dependent on a broad range of mineral commodities. Moreover, the automotive manufacturing industries are reliant on complex and sometimes opaque multi-tiered global supply chains. Among the many industries on which automotive supply chains depend are the electronics and semiconductor industries, which are themselves material-intensive and reliant on opaque global supply chains. A linear programming model built on mineral end-use data and input-output tables provides a tool for investigating inter-industry relationships between the two sets of industry sectors and industrial vulnerability to mineral commodity supply disruptions. Supply disruptions in aluminum, magnesium metal, and zinc—metals used in the body-in-white, wheels and other parts—have significant potential to disrupt the automotive industries. On the other hand, supply disruptions in gallium, tellurium, and indium for example—semiconductor elements used in power electronics, screen coatings and other parts—have significant potential to impact the electronics and computer industries. More interestingly, case studies of the automotive and electronics industries show how supply disruptions in mineral commodities that are generally considered semiconductor materials, such as gallium, can significantly impact the automotive sector.

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  • Manley, Ross L. & Alonso, Elisa & Nassar, Nedal T., 2022. "Examining industry vulnerability: A focus on mineral commodities used in the automotive and electronics industries," Resources Policy, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:jrpoli:v:78:y:2022:i:c:s0301420722003397
    DOI: 10.1016/j.resourpol.2022.102894
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    References listed on IDEAS

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    Cited by:

    1. Zhang, Ling & Wen, Shaobo, 2024. "The influence of global gallium trade network dynamics on price: A complex network and panel regression approach," Resources Policy, Elsevier, vol. 93(C).
    2. Grzegorz Koszalka & Paweł Krzaczek, 2022. "Energy Losses Related to Ring Pack Wear in Gasoline Car Engine," Energies, MDPI, vol. 15(24), pages 1-16, December.

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