JOURNAL ARTICLE
Vertical Integration and Market Power in Supply Networks.
Published In: Manufacturing & Service Operations Management (M&SOM) (INFORMS), 2025, v. 27, n. 6. P. 1939 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Arora, Kashish; Singh, Amandeep; Sahare, Mamta 3 of 3
Abstract
This article investigates the effects of vertical integration—where firms control multiple stages of production and distribution—on market competition and operational outcomes using a novel dataset of 213 vertical mergers from 2003 to 2022. Employing production function estimations to measure firm-level markups and a staggered difference-in-difference approach with an instrumental variable addressing endogeneity, the study finds that vertical integration increases acquiring firms' markups by 13% and rivals' markups by 6%, indicating heightened market power. While integrating firms achieve cost efficiencies averaging a 2.9% reduction in cost of goods sold, rival firms face a 2% cost increase, consistent with the "raising rivals' costs" theory, which suggests that vertical integration can harm consumer welfare by elevating prices. The analysis further reveals that these effects persist over time and vary with firm size, global sourcing intensity, supply network position, and levels of upstream and downstream competition, highlighting important implications for operations management and antitrust policy.
Additional Information
- Source:Manufacturing & Service Operations Management (M&SOM) (INFORMS). 2025/11, Vol. 27, Issue 6, p1939
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2025
- ISSN:1523-4614
- DOI:10.1287/msom.2024.1454
- Accession Number:190748622
- 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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