JOURNAL ARTICLE

Corporate Governance and Related Party Transactions in Global Supply Chains.

  • Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2024, v. 26, n. 4. P. 1489 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Lee, Seungrae; Lim, Michael K.; Park, Seung Jae; Seshadri, Sridhar 3 of 3

Abstract

This article investigates how corporate governance affects operational diversion in related party transactions (RPTs) between parent firms and their foreign subsidiaries within multinational firms' global supply chains. Using a unique dataset of Korean multinational firms from 2006 to 2013 and leveraging the 2011 adoption of International Financial Reporting Standards (IFRS) in Korea as a natural experiment, the study finds that operational diversion—where a parent firm's manager prioritizes parent-only performance at the expense of overall supply chain efficiency—is more pronounced in RPTs involving vertical subsidiaries (focused on production efficiency) than horizontal subsidiaries (market-seeking). Strong corporate governance mechanisms, including internal governance, institutional ownership, and large shareholders, significantly mitigate operational diversion in transactions with vertical subsidiaries but have less impact on horizontal subsidiaries. The findings highlight the need for tailored governance and monitoring strategies that consider the subsidiary's role, emphasizing enhanced oversight of vertical subsidiary relationships and the empowerment of local managers, especially in countries with weaker legal protections.

Additional Information

  • Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2024/07, Vol. 26, Issue 4, p1489
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2024
  • ISSN:1523-4614
  • DOI:10.1287/msom.2022.0372
  • Accession Number:178447830
  • 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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