The exploratory and explanatory capability of the conceptual model is derived, respectively, from the 'beliefs' elements and the 'beliefsintentionbehaviour' structure of the model. The exploratory capability comes from the use of the 'beliefs elements' to identify and classify factors that influence the adoption of OSS. The explanatory capability comes from the use of
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the 'beliefsintentionbehaviour' relationships to explain the influence of factors. The conceptual model will now be shown to use this capability in identifying factors and explaining how they influence the adoption of OSS in this study.
The conceptual model in Figure 3.1 represents the 'beliefsintentionbehaviour' structure, with the beliefs element represented as the decomposed belief structures and the belief components, the intention element represented as the construct of the same name, and the behaviour element represented as the usage of OSS. The decomposed belief structures in each belief component are used in identifying factors. Thus, we will discuss the exploratory function of the decomposed belief structures, in turn, for each of the belief components – attitude, subjective norms and perceived behavioural control. In doing so, the influence of the factors identified by each decomposed belief structure will be explained, showing the explanatory capability of each particular decomposed belief structure used in the conceptual model.
Attitude consists of three decomposed belief structures that enable the identification of the perceptions that the use of an OSS is favourable or unfavourable for the SME (section 3.3.1).
The first belief structure – relative advantage – identifies factors such as cost saving (see section 2.2.1), quality characteristics (see section 2.2.4) and trialability (see section 2.2.5), which represent the perceived benefits that using an OSS supersedes those of its precursor.
Relative advantage also explains that such factors have a positive influence on the adoption of OSS. The second belief structure is complexity and identifies factors such as 'lack of support' (see section 2.4.2), which represents the perceptions that an OSS is difficult to use or learn by the SME and it explains that such factors have a negative influence on the adoption of OSS.
The third attitudinal belief structure, compatibility, identifies factors such as functionality (see section 2.2.2), which represents the perceptions that an OSS fits with the SME's existing values, previous experiences or current needs. This belief structure also explains that compatibility factors have a positive influence on the OSS adoption by the SME.
The cumulative influences from the three decomposed belief structures of attitude presented above leads to the formation of attitude towards the use of OSS (see Figure 3.1). Consistent with the 'beliefsintentionbehaviour' relationships, the conceptual model shows that attitude contributes to the formation of intention (see section 3.3.4), which is the evaluations or judgement that using the OSS is good or bad for the SME. Therefore, the attitudinal factors from relative advantage, complexity and compatibility, through the formation of attitude, contribute to the formation of intention to use or not use an OSS. From the formation of
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intention, the direct relationship between intention and behaviour in the conceptual model shows that the attitudinal factors contribute to the actual usage of OSS (see section 3.3.4), which is the implementation of OSS and confirmation of the decision to use it in the organisation. This discussion has shown that the 'beliefsintentionbehaviour' structure can explain the influence of attitudinal factors on the adoption of OSS. Similar explanation will now be developed for the factors in the other belief components and their decomposed belief structures.
The second belief component is subjective norms and includes two belief structures that enable the identification of an SME's perception of social pressure, to use, or not use, an OSS (section 3.3.2). The first belief structure, peer influences, identifies the influences of factors such as friends, families and colleagues (see section 3.3.2), government policies (see section 2.4.1) and vendors and consultants (see section 2.4.3), which represent peers within the social system that influence the decisionmakers to use or not use an OSS in the organisation.
Peer influences explain that, cumulatively, such factors have a subjective influence on the adoption of OSS in the organisation. The second belief structure – superior influences – identifies factors such as information media (see section 3.3.2), which represent information from secondary sources such as TV, the Internet, or printed media, that influence the SME decisionmakers to use or not use an OSS.
Again, the cumulative influences from peer influences and superior influences, as shown in the conceptual model in Figure 3.1, lead to the formation of subjective norms about the use of OSS in the organisation. The conceptual model also shows that subjective norms contribute to the formation of intention (see section 3.3.4) to use or not use an OSS. Therefore, the normative factors through the formation of subjective norms about the use of OSS in the organisation, contribute to the formation of intention. Again, owing to the direct relationship between intention and actual usage (see section 3.3.4), the influences of the normative factors contribute to the implementation and the confirmation of the decision to use OSS by the SME – the actual usage of OSS in the organisation.
The third belief component, perceived behavioural control, consists of three belief structures that enable the identification of an SME's perceived control over the factors that may facilitate or constrain the use of OSS in the organisation (see section 3.3.3). Selfefficacy is the first belief structure and identifies the influence of factors such as innovativeness (see section 2.3.2) and staff IT capacity (see section 2.3.3), which represent the SME's ability and confidence to use the OSS and explains that such factors have a positive influence on the
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SME's control over the adoption of OSS in the organisation. The second belief structure is resource facilitating conditions and identifies factors such as capital investment (see section 2.3.1), which represent the availability or lack of resources, such as time and money, that enable or constrain the use of an OSS. This facilitating condition explains that such factors enable the use of OSS but a lack of them can inhibit its use in the organisation. The third belief structure is technology facilitating conditions, which identifies factors such as adequate IT infrastructure (see section 2.2.3), which represent the access to supporting technological resources that enable or constrain the use of an OSS. This belief structure also explains that while availability of such factors enables the use of OSS, a lack of them can inhibit the SME's use of the OSS.
From the discussion above, the cumulative influences of factors from the control belief structures – selfefficacy, resource facilitating conditions and technology facilitating conditions – leads to the perception of control over the personal/internal and external factors that facilitate and may constrain the use of OSS by the SME (see Figure 3.1). The conceptual model shows that perceived behavioural control contributes to the formation of intention.
Therefore, the influences of the factors from the control beliefs contribute to the evaluations or judgement that using an OSS is good or bad for the SME. Again, owing to the direct relationship between intention and actual usage, the factors from the control beliefs contribute to the actual usage of OSS in the organisation (see section 3.3.4). The conceptual model shows that there can be a direct relationship between perceived behaviour control and actual usage of OSS, which can inhibit the actual use of OSS in the organisation. This inhibiting influence is due to the effects of a lack of facilitating conditions (see section 3.3.3), constraining the perceived control over the external factors that facilitate the use of OSS in the organisation.
The discussion above has shown how factors are identified using decomposed belief structures, leading to the formation of belief components of the related belief structures. The explanation has also shown that all belief components contribute to the formation of intention to use or not use an OSS. Because intention is the immediate determinant of actual usage of OSS, the cumulative influences of factors, through their belief components and intention, contribute to the implementation and the confirmation of the decision to use an OSS. The discussion has also explained why the actual usage of OSS can be inhibited by the constraining influences from the perceived behavioural control components, showing that although intention is the immediate determinant of actual usage, a lack of 'facilitating conditions' can inhibit actual usage of OSS in an organisation.
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3.5 Summary
This chapter has discussed the selection and operationalisation of the Decomposed Theory of Planned Behaviour (DTPB), leading to the development of research propositions for exploring factors that influence the adoption of OSS and explaining their influence. The presentation of the research propositions together led to a research conceptual model of OSS adoption by UK SMEs.
The DTPB was chosen over other theoretical models owing to its enhanced exploratory and explanatory capabilities over other ICT adoption models and theories evaluated in this chapter. The importance of monolithic belief components was discussed, as criteria for the comparison of major ICT adoption models and theories and, were given as a justification for the selection of the DTPB in this study.
The used of the DTPB as an underlying theory led us to develop research propositions, which required the definition of the DTPB constructs and their nomological networks. Factors from the literature analysis in Chapter 2 were used to support the arguments leading to the research propositions. Together with the supporting factors, all the research propositions were presented as a conceptual model for exploring factors that influence the adoption of OSS by SMEs and explaining their influence. The demonstration of the exploratory and explanatory capabilities of research conceptual model has shown that it can be applied in exploring factors explaining their influence on the adoption of OSS.
The conceptual model developed also represent an analysis of the scope of technological, environmental and organisational issues relevant to the adoption of OSS by SMEs and, therefore, has implications for the scope and design of empirical research in the next chapters of this thesis. In this context, the conceptual model provides a theoretical framework which acts as an important empirical research focus, and useful for the scope and design of empirical data collection instruments and analysis methods in Chapter 4 and the reporting format for research findings in Chapters 5 and 6.
4
Research Methods
4.1 Introduction
Chapter 3 presented the development of research propositions which formed the research conceptual model of Open Source Software (OSS) adoption by SMEs. This chapter now focuses on the research methodology, with the three key objectives of establishing (1) the nature and focus of the empirical inquiry, (2) the empirical research instruments, and (3) the procedures, which will be applied in the empirical research. In doing so, this research methodology takes into consideration the research problem, as stated in section 1.4, and uses the research conceptual model (see sections 3.3 and 3.4), as an underlying framework for developing the data collection instrument and the data analysis framework. Thus, the research methodology also guides the design and procedures for the empirical data collection, the data analysis, and the framework for reporting emergent research findings.
In this research methodology, four important issues are considered, including a justification for taking an interpretivism research paradigm, the choice of a qualitative research mode, a justification for case study as the chosen research strategy for this qualitative research, followed by a presentation and implementation of the case study research design. These issues lead to the next four sections of this chapter, which will now be introduced.
Section 4.2 will discuss and justify the research foundations of this study. The discussions encompass three major issues. First, the elements of research paradigms chosen in this study, including the use of an interpretivist stance, are discussed because it establishes the relevance of the empirical research objectives, which aim to explore and explain factors influencing OSS
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adoption by IT SMEs, to the research problem identified in section 1.4. Second, the choice of a qualitative research mode is discussed, explaining the need to apply a naturalist approach in exploring and interpreting factors observed in the empirical research. The choice of qualitative research mode also paves the way towards the selection of relevant research methods and procedures for representing that form of knowledge. The third major issue is a justification for the choice of the multiplecase studies research strategy, and focuses on the need to explore the adoption of OSS across multiple IT SMEs and allowing us to identify generalisable factors that may lead to the formulation of theories.
In section 4.3, the design of case study strategy will be discussed. The discussion encompasses three elements of the design of this multiple case study research: (1) the focus of the case study inquiry; (2) the fit of the research paradigm to the research focus; and (3) the sampling of empirical data and evidence for this study.
Section 4.4 will discuss the data collection methods and procedures applied in the field. The discussion focuses the justification for the selection of interviews as a primary data collection instrument and phases of interviews applied in this study.
In section 4.5, the techniques and procedures applied in the case study data analysis will be discussed. The discussion includes the techniques and procedures applied for data reduction, data displays and conclusions drawing in this multiplecase study research.
Section 4.6 will discuss the measures that will be taken to ensure rigour in this empirical research is presented. Research rigour in this study will focus on measures to enhance the credibility of the data collection and analysis processes, in an aim to ensure that OSS adoption by IT SMEs is properly represented. The research rigour will also consider the reporting format chosen.