JOURNAL ARTICLE

Supply Chain Nearshoring in Response to Regional Value Content Requirements.

  • Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2026, v. 28, n. 3. P. 762 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Hsu, Jonathan; Li, Zhi; Wu, Jing 3 of 3

Abstract

This article examines how the tightening of rules of origin (ROOs), specifically the regional value content (RVC) requirements under the renegotiated U.S.-Mexico-Canada Agreement (USMCA), influences global sourcing decisions of U.S. automotive firms. Empirical analysis using both aggregate national import data and detailed firm-product-level transaction data shows that U.S. automotive manufacturers significantly increase their imports of automotive products from Mexico and Canada, indicating a nearshoring trend in response to stricter RVC rules. This nearshoring is most pronounced for less complex complementary automotive parts rather than core or principal components, suggesting firms adopt a gradual strategy focusing on lower-cost supply chain adjustments. Additionally, firms with higher property, plant, and equipment (PPE) and leverage ratios exhibit stronger nearshoring responses, which is associated with improved inventory performance but also increased costs and reduced gross margins. The findings highlight that while trade policies like USMCA effectively encourage regional sourcing, firms' strategic responses may not fully align with policymakers' intentions to deepen regional production of critical automotive components.

Additional Information

  • Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2026/05, Vol. 28, Issue 3, p762
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2026
  • ISSN:1523-4614
  • DOI:10.1287/msom.2024.1555
  • Accession Number:193691064
  • Copyright Statement:Copyright of Manufacturing & Service Operations Management (M&SOM) (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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