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When Do Vendors Behave Opportunistically?: An Empirical Study of Financial Market Impacts on Firms in IT Outsourcing Relationships

Published:21 June 2017Publication History

ABSTRACT

Firms experience knowledge spillovers when working with outsourcing partners. This problem may be more severe when a firm and its rivals enter into outsourcing relationships with the same vendor. In such a network of outsourcing relationships, the common vendor may become the conduit for knowledge leakage from one firm to the other due to its own opportunistic calculus. Rooted in transaction cost economics (TCE), we propose that a vendor will utilize the knowledge gained from focal or rival firms whenever it is in the interest of the vendor to do so, resulting in losses or gains to rivals of a focal firm when the focal firm announces a new contract with the common vendor. Using a sample of 510 IT outsourcing contract announcements, we observed such losses and gains through cumulative abnormal returns (CARs) that accrue to rival firms around the date of announcement of a new IT outsourcing contract by a focal firm. Results support our hypotheses and show negative CARs for rivals that in the past had a relationship with the focal vendor but do not have a current relationship with the vendor. We also find that the rival firm size relative to the focal firm size plays an important role in vendor calculus and resulting knowledge spillovers. Knowledge leaks from a rival to a focal firm, and the rival experiences a negative CAR, when the rival is relatively larger in size compared to the focal firm and is no longer in a relationship with the vendor. However, in contrast, when the rival is relatively larger in size compared to the focal firm and is currently in a relationship with the vendor, knowledge leaks from the focal firm to the rival who experiences a positive CAR.

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  • Published in

    cover image ACM Conferences
    SIGMIS-CPR '17: Proceedings of the 2017 ACM SIGMIS Conference on Computers and People Research
    June 2017
    220 pages
    ISBN:9781450350372
    DOI:10.1145/3084381

    Copyright © 2017 ACM

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    New York, NY, United States

    Publication History

    • Published: 21 June 2017

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