RESEARCH SYNOPSIS

Purpose - Identify the extent of Open Source Software (OSS) adoption and further investigate the factors that influence the adoption in global Information Technology (IT) outsourcing organizations serviced by Indian IT service providers.

Methodology – The study adopted Technology-Organization-Environment (TOE) framework to leverage the factors that influence OSS adoption. This explanatory research adopted positivism research philosophy and mixed methods approach. This study used self-administered questionnaire to collect data from top and middle management employees of Indian IT service providers covering a sample of 482 IT outsourcing organizations and the data were analyzed using PLS regression. Partial Least Square (PLS) based Structural Equation Modelling (SEM) is chosen considering the application of Covariance-based SEM requires a strong theoretical foundation, while PLS does not require such a strong theoretical foundation. In addition, an in-depth interview was conducted with ten participants and the survey findings were triangulated based on qualitative data.

Findings - 84.2% of IT outsourcing organizations (n=482; 95% CI, 75-90%) adopt OSS (17.8%; 95% CI 13-19% extensive level of adoption). Less than 1% (95% CI, 0-2%) organizations has adopted OSS in greater than 50% of mission critical applications. The proposed conceptual model identified the factors which play a significant role in OSS adoption such as Software reliability, Legal concern, Software costs, Management support, OSS support availability, Software vendor relationship, and Organization Size. In contrast, this study did not find enough evidence that License concern and IT outsourcing were a significant determinant of OSS adoption.

Practical Implications - IT services provider can utilize this research model to increase their understanding of why some IT outsourcing organizations choose to adopt OSS, while seemingly similar ones facing similar market conditions do not. This can help address the gaps in OSS support availability and achieve reduction in total cost of ownership of software.

Tools Used
SPSS, SmartPLS,  NVivo