JOURNAL ARTICLE
The Varying Returns to Diversification Along the Value Chain.
Published In: Strategy Science (INFORMS), 2023, v. 8, n. 1. P. 44 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Karniouchina, Ekaterina; Carson, Stephen J.; Moore, William L.; Sarangee, Kumar R.; Uslay, Can 3 of 3
Abstract
This study investigates how the benefits of diversification differ across value chain activities, specifically product development and distribution, within the motion picture industry. Using data from 779 movies linked to 57 production studios and 30 distributors, the research finds that greater focus (less diversification) in film production positively impacts profitability, while diversification levels in distribution show no significant effect on profitability. These results align with the resource-based view (RBV) theory, which suggests that product development relies on less fungible, unique resources (e.g., talent and technical expertise), making focus more valuable, whereas distribution involves more fungible resources, allowing for greater diversification without profitability loss. The study also reveals significant heterogeneity among production studios in how focus affects performance, emphasizing the need to consider value chain activities individually when making diversification decisions. These findings hold for both vertically integrated firms and independent organizations, offering implications for strategic management and vertical integration in industries with decomposable value chains.
Additional Information
- Source:Strategy Science (INFORMS). 2023/03, Vol. 8, Issue 1, p44
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2023
- ISSN:2333-2050
- DOI:10.1287/stsc.2022.0171
- Accession Number:182962455
- Copyright Statement:Copyright of Strategy 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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