JOURNAL ARTICLE

Production Chain Organization in the Digital Age: Information Technology Use and Vertical Integration in U.S. Manufacturing.

  • Published In: Management Science (INFORMS), 2025, v. 71, n. 2. P. 1027 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Forman, Chris; McElheran, Kristina 3 of 3

Abstract

The article investigates how advances in information technology (IT), specifically the rise of the internet, influenced the vertical organization of production chains in U.S. manufacturing during the 1990s and early 2000s. Using detailed U.S. Census Bureau microdata on over 5,600 manufacturing plants, the study applies plural governance theory—which recognizes firms' simultaneous use of multiple governance modes—to analyze shifts in downstream vertical integration, measured by the internal transaction ratio (ITR). The main finding is that increased internet use for external coordination caused a significant decline in downstream vertical integration, with external sales rising at the expense of within-firm transfers. This effect was strongest among plants already engaged in plural selling, those with significant internal vertical linkages, and plants operating near capacity, highlighting the role of organizational flexibility and cross-transaction interdependencies. Additionally, the study finds that internal production IT complemented external internet use in reducing vertical integration, challenging prior assumptions of substitution between internal and external IT. These results underscore the importance of nuanced organizational design and IT complementarities in understanding firm boundary decisions amid digital transformation.

Additional Information

  • Source:Management Science (INFORMS). 2025/02, Vol. 71, Issue 2, p1027
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:0025-1909
  • DOI:10.1287/mnsc.2019.01586
  • Accession Number:182990730
  • Copyright Statement:Copyright of Management Science (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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