Framework for Identification of Critical Factors for Open Source Software Adoption Decision in Mission-Critical IT Infrastructure Services

Abstract

Mission-critical IT systems are utilizing closed source software (CSS) mainly due to reasons related to “quality assurance” and “continued support” despite much better benefits of using Open Source Software (OSS). OSS permits users to access source code for assessment, amendment, and redistribution, which offers low dependency on a vendor without license or maintenance cost. This paper investigates and analyzes OSS adoption factors for “critical IT infrastructure” by conducting a comprehensive review of the relevant literature. Furthermore, this paper proposes a framework that can help the critical IT industry to have increased confidence in OSS. The proposed framework utilizes the organizing logic of the Technology, Organization, and Environment (TOE) framework, recommends factors that were recognized by critically scrutinizing the studies found in the available literature. To validate the framework, a questionnaire-based survey was conducted targeting IT experts in critical sectors. The data integrity of survey results was analyzed using Cronbach's alpha. Framework factors were validated statistically using one sample T-test. The outcome indicated that the factors were statistically significant as the p-value was less than 0.05 for all the factors.

KEYWORDS:

• Open-source software
• Proprietary software
• Free and Open Source Software
• Technology Organization and Environment
• Enterprise resource planning
• Systems Applications, and Products in Data Processing
• Free/Libre/Open Source Software

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

F. Umm-e-Laila

Umm-e-Laila is a PhD scholar at NED University of Engineering and Technology. She has obtained her bachelor's and master's degree in computer engineering from Sir Syed University of Engineering & Technology (SSUET). She is currently working as an assistant professor in Computer Engineering SSUET..

S. Najeed Ahmed Khan

Najeed Ahmed Khan has done PhD in computer vision from the University of Leeds, United Kingdom. His main interest is in computer vision. He is the author of more than 30 publications in JCR and ISI indexed journals. Dr Khan has won HEC National Centre for Artificial Intelligence (NCAI) for NED University as CO-PI. Currently, he is serving at University as associate professor of artificial intelligence and as executive officer & care taker MoST Chair Professor endowment. Email: [email protected]

T. Asad Arfeen

Asad Arfeen is an assistant professor at the Department of Computer and Information Systems Engineering of NED University of Engineering & Technology, Karachi Pakistan. He completed his PhD from the University of Canterbury, New Zealand, in 2015. Email: [email protected]