A theory-grounded framework of Open Source Software adoption in SMEs.
ABSTRACT The increasing popularity and use of Open Source Software (OSS) has led to significant interest from research communities and enterprise practitioners, notably in the small business sector where this type of software offers particular benefits given the financial and human capital constraints faced. However, there has been little focus on developing valid frameworks that enable critical evaluation and common understanding of factors influencing OSS adoption. This paper seeks to address this shortcoming by presenting a theory-grounded framework for exploring these factors and explaining their influence on OSS adoption, with the context of study being small- to medium-sized Information Technology (IT) businesses in the U.K. The framework has implications for this type of business – and, we will suggest, more widely – as a frame of reference for understanding, and as tool for evaluating benefits and challenges in, OSS adoption. It also offers researchers a structured way of investigating adoption issues and a base from which to develop models of OSS adoption. The study reported in this paper used the Decomposed Theory of Planned Behaviour (DTPB) as a basis for the research propositions, with the aim of: (i) developing a framework of empirical factors that influence OSS adoption; and (ii) appraising it through case study evaluation with 10 U.K. Small- to medium-sized enterprises in the IT sector. The demonstration of the capabilities of the framework suggests that it is able to provide a reliable explanation of the complex and subjective factors that influence attitudes, subjective norms and control over the use of OSS. The paper further argues that the DTPB proved useful in this research area and that it can provide a variety of situation-specific insights related to factors that influence the adoption of OSS.
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ABSTRACT: The understanding of the viability, competitiveness, and challenges of using open source software has important implications for the understanding of its adoption. However, one important problem is the paucity of contextual, valid and generalizable frameworks for understanding the adoption of open source software. In contributing to address this important issue, this paper presents a theory-grounded framework for understanding factors and their influence in the adoption of open source software. The framework has been developed based on the decomposed theory of planned behavior (DTPB), through the augmentation of the research areas of the adoption of open source software and the adoption of information and communication technology (ICT) in small businesses. We show that the exploratory and explanatory capabilities of the framework provides simple concepts for researchers seeking to develop valid and generalizable research models and analysis instruments, and for practitioners seek common understanding of factors influencing their adoption of open source software. Implications of the framework are discussed within the contexts of direct utilization, as justifications for intervention, and as frame of reference for understanding and communicating issues influencing the adoption of open source software. The paper outlines proposals for future research to extend and validate the analytical capabilities of the framework.British Journal of Applied Science and Technology. 09/2014; 4(34):4817 - 4834.
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ABSTRACT: A multitude of factors influence the adoption of cloud computing. Organizations must systematically evaluate these factors prior to making the decision to adopt cloud-based solutions. To assess the determinants influencing the adoption of cloud computing, we develop a research model based on the innovation characteristics from the diffusion of innovation (DOI) theory, and the technology-organization-environment (TOE) framework. Data collected from 369 firms in Portugal are used to test the related hypotheses. The study also investigates the determinants of cloud computing adoption in the manufacturing and services sector.Information & Management 07/2014; · 1.79 Impact Factor