Are There Contagion Effects in IT and Business Process Outsourcing?

Publication Type

Journal Article

Publication Date

2011

Abstract

We model the diffusion of IT outsourcing using announcements about IT outsourcing deals. We estimate a lognormal diffusion curve to test whether IT outsourcing follows a pure diffusion process or there are contagion effects involved. The methodology permits us to study the consequences of outsourcing events, especially mega-deals with IT contract amounts that exceed US$1 billion. Mega-deals act, we theorize, as precipitating events that create a strong basis for contagion effects and are likely to affect decision-making by other firms in an industry. Then, we evaluate the role of different communication channels in the diffusion process of IT outsourcing by testing for the fit of the mixed influence model at the industry level. This helps us to evaluate the consistency of evidence at two different levels of analysis. We also evaluate two flexible diffusion models: the Gompertz and Weibull models. Our results show that the diffusion patterns of IT outsourcing do not appear to be lognormal, suggesting that IT outsourcing does not follow a pure diffusion process. Instead, we find the presence of contagion effects in the diffusion of IT outsourcing. During periods of the most rapid outsourcing growth – the contagion periods – the actions of the large and more visible firms may provide exemplars for smaller firms, reducing their inhibitions about committing to IT outsourcing. We also find that the results of the mixed influence and the Weibull models, which provide the best fit for overall IT outsourcing diffusion patterns, are potentially indicative of the existence of spillovers that might drive the observed contagion effects at the industry level.

Keywords

Business processes, Contagion effects, Economic analysis, Influence models, IT services, S-curve flexible models, Outsourcing

Discipline

Business | Computer Sciences

Research Areas

Information Systems and Management

Publication

Decision Support Systems

Volume

51

Issue

4

First Page

864

Last Page

874

ISSN

0167-9236

Identifier

10.1016/j.dss.2011.02.005

Publisher

Elsevier

Additional URL

http://dx.doi.org/10.1016/j.dss.2011.02.005

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