Impact of government outsourcing contracts on high-tech vendors: An empirical study

Publication Type

Journal Article

Publication Date

4-2024

Abstract

Outsourcing is an important strategic decision of high-tech firms. However, while the research has extensively studied the implications of outsourcing to high-tech clients, its impact on high-tech vendors remains underexplored. This study empirically estimates the impact of government outsourcing contracts on high-tech vendors. Employing the earnings-return analyses framework, we find that, for high-tech vendors engaged in government outsourcing contracts, the stock market places a higher value on each unit of unexpected earnings compared to other firms. Additionally, this impact becomes stronger for contracts with longer terms, for contracts outsourced by the U.S. government or by countries with better political and economical stability. We obtain causal evidence through difference-in-differences (DID) analyses of high-tech firms' initiations of government contracts. Mechanism analyses uncover two primary drivers behind this impact: increased persistence of future earnings and improved alignment between accrual earnings and cash flows. Overall, our research indicates that when valuing high-tech firms, the stock market incorporates information from supply-chain networks, especially that related to government customers. Our results underscore the importance of obtaining government outsourcing contracts for high-tech firms' managers. Becoming a vendor to the government helps a high-tech firm reduce the uncertainty faced by its outside investors, who in turn value the high-tech firm's earnings to a greater extent.

Keywords

High-tech, IT firms, outsourcing, government contracts, firm value, firm earnings, earnings-return framework

Discipline

Databases and Information Systems | Management Information Systems | Technology and Innovation

Research Areas

Data Science and Engineering

Publication

Journal of Management Information Systems

Volume

41

Issue

2

First Page

581

Last Page

609

ISSN

0742-1222

Identifier

10.1080/07421222.2024.2340823

Publisher

Taylor and Francis Group

Additional URL

https://doi.org/10.1080/07421222.2024.2340823

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