JOURNAL ARTICLE

Laissez-Faire vs. Government Intervention: Implications of Regulation Preventing Nonauthorized Remanufacturing.

  • Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2025, v. 27, n. 2. P. 588 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Esenduran, Gökçe; Jin, Minyue; Zhou, Yu 3 of 3

Abstract

This article compares two policy regimes governing third-party remanufacturing: a laissez-faire policy, where independent remanufacturers (IRs) may choose whether to obtain original equipment manufacturer (OEM) authorization, and a mandatory authorization policy, which requires IRs to obtain OEM authorization and pay a per-unit fee. Using a game-theoretic supply chain model involving a supplier, an OEM, and an IR, the study finds that contrary to conventional wisdom, mandatory authorization can benefit all firms—including IRs—when remanufacturing costs are low, by encouraging higher new product manufacturing and remanufacturing volumes. Conversely, for products with moderately high remanufacturing costs, a laissez-faire policy yields higher profits for all firms and greater consumer surplus, though often with increased environmental impact. The analysis also highlights trade-offs between economic and environmental outcomes under each policy and underscores the importance of supply chain structure and strategic firm interactions in shaping policy effectiveness.

Additional Information

  • Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2025/03, Vol. 27, Issue 2, p588
  • Document Type:Article
  • Subject Area:Politics and Government
  • Publication Date:2025
  • ISSN:1523-4614
  • DOI:10.1287/msom.2023.0128
  • Accession Number:184090835
  • 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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