JOURNAL ARTICLE
Making Lemonade from Lemons: A Transaction Cost Economics Perspective on Third-Party Disruptions in a Multivendor Information Technology Service.
Published In: Information Systems Research (INFORMS), 2025, v. 36, n. 1. P. 41 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Liu, Haoyuan; Wen, Wen; Barua, Anitesh; Whinston, Andrew B. 3 of 3
Abstract
The article examines how third-party service disruptions affect enterprise customers' use of integrated multivendor IT services, focusing on a case where a third-party GPS tracking service disruption impaired a multivendor Customer Relationship Management (CRM) module without directly affecting first-party services. It finds that during the disruption, customers temporarily increased use of first-party IT modules serving similar goals but reduced overall service use in the long run, even after the third-party service was restored. Importantly, high-quality first-party technical support addressing product-related issues during the disruption encouraged customers to explore and continue using first-party services long term, whereas customer-related support did not have this effect. The study highlights the challenges and strategic opportunities for primary IT vendors in managing customer uncertainty in multivendor environments and underscores the role of targeted technical support in mitigating negative impacts of third-party disruptions.
Additional Information
- Source:Information Systems Research (INFORMS). 2025/03, Vol. 36, Issue 1, p41
- Document Type:Article
- Subject Area:Information Technology
- Publication Date:2025
- ISSN:1047-7047
- DOI:10.1287/isre.2022.0033
- Accession Number:184136943
- Copyright Statement:Copyright of Information Systems Research (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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