Technology Acceptance Model (TAM)

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The previous chapter introduced the research area, the research objectives, research question, and problem statement, contribution of the research and the structure of the study. This chapter reviews current literature on existing IT adoption frameworks. The importance of understanding the IT adoption decision making process in organisations has been highlighted by many researchers (Benbasat & Barki, 2007; Lawrence, 2010). Information Technology adoption at individual (for example, a personal mobile device) or organisational level (for example, an ERP system) is a highly researched topic in the IT field. Most literature on IT adoption in organisations is often premised on the assumption that IT investment benefits are always obvious after selecting the particular technology (Bouwman et al., 2005; Mirza, 2010). However, it has become sufficiently clear that the anticipated benefits from IT adoption in organisations are not self-evident as they may be elusive and difficult to achieve.
Despite several studies on IT adoption on factors influencing IT adoption decision making, challenges still persist (Martins, Moura, Cunha & Figueiredo, 2010; Mirza, 2010). This has prompted many researchers to question the suitability of existing models and frameworks for this complex phenomenon in IS research. The existing models and frameworks therefore seem to have limitations in addressing adoption problems faced by many organisations, for example, failing to understand how a framework may facilitate IT adoption decision making (Benbasat & Barki, 2007; Martins et al., 2010).
Bouwman et al. (2005) defined adoption as the decision making process of introducing a new technology in the organisation. IT adoption governance is defined as the process that describes how the decision of accepting or rejecting new technology from an individual or organisational context is made. IT adoption governance in an organisation context helps to reconcile different stakeholder demands during the process of decision making regarding the acceptance of IT. The IT adoption decision making process results in a decision about whether or not to implement the new technology. IT adoption takes places at micro (individual), meso (organisational) and macro (societal) levels (Bouwman et al., 2005).
The challenge of IT adoption in organisations is how to understand its effects at the three different levels. Individual user and organisation effects of technology adoption can never be fully understood because of its complicity and uncertainty. Bouwman et al. (2005) add that technology adoption in an organisation is a two stage process, which involves the organisation and the individual user who decides to use the new technology. The first stage involves the decision by the organisation executives to embrace a new technology (Rogers; 200; Bouwman et al., 2005). The second stage involves the individual users in the organisation accepting and using the new technology. The adoption of new technology in an organisation is therefore a two stage process where the organisation makes the decision on a strategic level before the individual users make their own technology adoption decision on an operational level.
Rogers (2003) highlighted that individual decision depends on the organisational decision to a large extent. Bouwman et al. (2005) assert that it is therefore difficult to separate the organisational decision making from the individual decision whether or not to adopt the new technology. The technology adoption in an organisation can be either authoritative (where decisions are made by a few top executives) or collective (where decisions are supported by the members of the social system (Bouwman et al., 2005; Cordoba, 2009). The two types of adoption decision making, authoritative and collective, are suitable for different organisational contexts. Authoritative decision making has been found more suitable for bureaucratic organisations, and collective decision making is more suitable for professional adhocracy organisations (Bouwman et al., 2005; Cordoba, 2009).
The size, structure and culture of the organisation are important in determining the suitable type of IT adoption decision making process (Bouwman et al., 2005; Baker, 2012). Bouwman et al. (2005) challenge the belief in the existence of a rational decision making process during IT adoption in an organisation. The higher level of subjectivity, uncertainty and complexity of the decision making makes rational decision making difficult in an organisation (Jackson, 2010). This study focuses on technology adoption in organisations, which also involves an individual’s adoption decision.
This chapter is arranged as follows: section 2.2 discusses the Technology Acceptance Model, section 2.3 discusses the Diffusion of Innovation Theory, section 2.4 discusses the Technology-Organisation Environment theory, section 2.5 discusses the Human Environmental Model, section 2.6 discusses the IT Governance framework, section 2.7 discusses the stakeholder approach, section 2.8 discusses the sociological paradigms and finally Section 2.9 discusses the systems approaches and finally section 2.10 the chapter conclusion

Technology Acceptance Model (TAM)

The previous section introduced the literature with regard to IT adoption decision making in organisations. This section presents the Technology Acceptance Model (TAM) which is one of the most popular models for technology adoption from an individual user perspective. The TAM model by Davis (1989) is a popular and widely used model to predict individual user acceptance of new technology. The TAM model’s assumption is that the individual adoption of technology is influenced by the two factors (perceived usefulness and perceived ease of use) of the new technology. The perceived usefulness refers to how the new technology enhances the user performance on the current work (Davis, 1989). The perceived ease of use refers to the effortlessness of the user working with the new technology (Davis, 1989).
The individual decision to adopt and use technology is of paramount importance to the information systems field (Sternad & Bobek, 2012; Aharony, 2013; Al-Hadeiri, 2013; Priyanka & Kumar, 2013; Musarrat, Loch & Williams, 2013). The current Technology Acceptance Model (TAM) by Davis (1989) shown in Figure 2.1 and its variations (e.g. UTAUT) are based on adaptations of the theories of reasoned action and planned behaviour to examine individual adoption of information technologies. The TAM’s perceived usefulness and ease of use have been found important in individual adoption decision making (Benbasat and Barki, 2007; Kurkinen, 2013; Lee, 2013; Jaradat & Smad, 2013). The TAM’s two constructs (perceived usefulness and perceived ease to use) have been found relevant to capture IT usage contexts (Benbasat and Barki, 2007; Abu-Shanab, 2013; Abu-Nahleh, 2013; Fung, 2013).
Several studies (Schepers & Wetzels, 2007; Buenaflor & Kim, 2013) conducted support the model in predicting the individual user acceptance of new technology. Several extended variations of TAM (TAM2, UTAM, and UTAUT) have added other external variables and factors to the original model. The TAM2 extended model includes other factors such as social influence, cognitive instrumental process, voluntariness and experience. The UTAUT (Unified Theory of Acceptance and Use of Technology) by Venkatesh, Morris, Davis and Davis (2003) added variables such as age gender, experience and voluntariness.
Despite the use of the Technology Acceptance Model by Davis (1989) and its extended models (UTAM) which provide insights into individual user behaviour on technology acceptance, TAM lacks a mechanism for considering the perspectives of multiple stakeholders and their involvement in IT adoption decision making in organisations (Lawrence, 2010; Dimitroviski, Ketikidis, Lazuras & Balh, 2013). The inability of TAM to address diverse perceptions of stakeholders and expectations is detrimental to IT adoption success in organisations (Benbasat & Barki, 2007). TAM models are deterministic in nature because they fail to recognize the importance of different stakeholder worldviews, which is part of IT adoption and the use of technology in organisations (Lawrence, 2010; Oliveira & Martins, 2011).
The TAM model is suitable for individual users rather than for an organisational environment with multiple stakeholders (Lawrence, 2010; Oliveira & Martins, 2011). Although TAM has been found, arguably, to be the most influential theory in IT adoption, it has been criticized for diverting the attention of researchers away from other important issues on IT adoption (Benbasat et al., 2007; Oliveira & Martins, 2011). Most TAM studies reiterate the importance of perceived usefulness without investing much effort in trying to investigate what makes a system useful (Benbasat et al., 2007; Oliveira & Martins, 2011). Some researchers have criticized TAM’s dominance as a paradigm for creating a narrow slice of the IT adoption domain (Benbasat et al., 2007). The perceived usefulness of a TAM construct is also subjective from an organisational context, since individuals have different perceptions of the utility of technology.
The application of TAM to new technology is not clear about which features are perceived as being useful or not, in order to improve the design (Benbasat et al., 2007). There is a need for more IT adoption theories suitable for the complex IT contexts to provide researchers with creative tools for IT adoption in organisations (Benbasat et al., 2007; Schepers & Wetzels, 2007; Luthfihadi & Dhewanto, 2013). While TAM is useful, the model needs to be integrated with other variables related to human and social change processes in IT adoption (Kim, Shin & Lee, 2009, Makori, Musoke & Maiga, 2014; Mekic & Ozlen, 2014; Moshki, Teimouri & Ansari, 2013).
Many researchers have investigated other factors, such as the effects of the potential adopter’s gender, age, prior experience with technology, and the degree to which adoption is voluntary, to name a few (Venkatesh et al., 2006; Bagozzi, 2007; Oliveira & Martins, 2011). Although TAM has been found to be the most influential theory in IT adoption it has resulted in the unintended consequence of diversion of attention away from other important adoption issues (Benbasat et al., 2007; Sun, Wang, Guo & Peng, 2013; Yeboah-Boateng & Essandoh, 2014). Most TAM research has been criticized for ignoring IT artifact design and other important IT adoption consequences (Benbasat et al., 2007; Aziz & Jamali, 2013; Buenaflor & Kim, 2013; Adedoja & Morakinyo, 2013; Chakrabortya & Mansorb, 2013).
Benbasat et al. (2007) point out that the shortcomings of TAM are its lack of a systemic way to expand and adapt its core model based on the constant evolution of IT in organisations. The other important shortcoming of TAM has been its simplistic view of a system based on the predictive nature of cause-effect relationships of a deterministic approach (DeLone and McLean, 2003; Hou et al., 2013; Behrenbruch et al., 2013; Hidayanto et al., 2014). The TAM’s over emphasis on usage as the dependent variable prevents researchers from investigating other important user behaviours. The shortcomings of TAM are due to the constantly changing context of IT organisations making it less relevant (Benbasat et al., 2007; Bagozzi, 2007; Phichitchaisopa & Naenna, 2013; Shah, Bhatti et al., 2013).
In summary, the literature has shown that while TAM has been popular and successful from an individual perspective, it has challenges at organisational level where stakeholders have different perspectives in terms of usefulness and ease of use constructs. Its deterministic approach based on a cause and effect relationship makes it less relevant to a socio-complex organisational environment where stakeholder perception is subjective. The shortcoming justifies the need for an integrated framework with many variables to alleviate the TAM’s weaknesses. The next section discusses the Diffusion of Innovation Theory with regard to IT adoption decision making in organisations


Diffusion of Innovation (DOI) Theory

The previous section discussed TAM with regard to IT adoption decision making from an organisation perspective. The Diffusion of Innovation Theory, shown in Figure 2.2, by Rogers, (1995) is one of the most popular models for understanding IT adoption decision making in organisations, based on its five stages (Akabogu, 2013; Makowsky et al., 2013; Mustafa & Mothana, 2013). The Diffusion of Innovation (DOI) Theory is defined as the way in which an innovation is communicated through certain channels over time among members of a social system (Bouwman et al., 2005). DOI theory has been used as a useful lens to understand the uptake of new technologies in different contexts. Rogers (2003) mentions four important components that influence the perception of adopters of the new technologies, which are innovation, communication channels, time and the social system. In addition to the components there are five technology characteristics (compatibility, relative advantage, complexity, trialability and observability) which have an influence in the adoption of new technology.
The DOI theory is important in understanding the spread of new technology in society from individual and organisational perspectives (Oliveira & Martins, 2011). The DOI theory has been credited with explaining how new technology ideas spread through communities based on five attributes of innovation. The DOI theory’s five characteristics of rate of adoption are important for understanding IT adoption in organisations. The basic tenet of the theory is that innovations are communicated through channels over time within a social system like an organisation. Rogers (2003) notes that at the organisational level of innovation the process is complex as it involves a number of individuals in the process. He adds that at the organisational level innovation success depends on the leadership, structure and other external factors. The DOI theory is useful in understanding the individual and organisational context of innovation.
Despite diffusion of innovation theory’s popularity its bias towards the technological component of the adoption process while ignoring other issues has been criticized by many researchers (Bose & Luo, 2011; Thomas, 2013; Alwahaishi & Snasel, 2013). The criticism of diffusion of innovation theory is that IT adoption in organisations goes beyond technical factors but also includes social, economic and political factors. The diffusion of innovation theory needs further expansion to include other important factors.
Du Plooy (1998) criticizes the classic diffusion theory for ignoring the social context of IT adoption in organisations. The deterministic nature of classical diffusion is too simplistic for complex processes based on social interaction (Du Plooy, 1998; Baker, 2012). Du Plooy (1998) criticizes Roger’s model for being too simplistic to address issues of a social nature in which IT adoption decision making takes place. The limitation of mechanistic causal relationships to socially construct IT adoption in organisations is the failure to understand the human environment and organisational context (Du Ploy, 1998; Baker, 2012). In order for IT adoption to be successful there is a need for social and environmental perspectives to complement technical perspectives (Weilbach et al., 2010).
IT adoption processes need to be based on social-technical adoption models instead of a technological linear phenomenon (Weilbach et al., 2010; Baker, 2012). As a conclusion, while DOI is an improvement from an organisation’s perspective, it is still deterministic in nature and is more focused on the technology side ignoring the social context of IT adoption in organisations. There is therefore a need for an expanded framework that goes beyond the technical factors of IT adoption in organisations. The next section discuss the Technology-Organisation-Environment with regard to IT adoption decision making in organisations

Technology-Organisation-Environment (TOE) Theory

The previous section discussed the Diffusion of Innovation (DOI) theory with regard to IT adoption decision making in organisations. The technology, organisation, and environment (TOE) framework (Figure 2.3) by Tornatsky and Fleischer (1990) on IT adoption in 17 organisations is influenced by three elements namely technology context, organisational context and environmental context (Bernroider & Schmollerl, 2013; Farahmand, 2013; Hsin-Pin, 2014; Luna-Reyes & Gil-Garcia, 2013). The TOE framework is more suitable for understanding IT adoption decision making from an organisation context. The framework is based on the fact that innovation decisions in organisations are dependent on factors associated with the three contexts (Oliveira & Martins, 2011)

1.1 Introduction
1.2 Problem Statement
1.3 Main Research Question
1.4 Research Objectives
1.5 Significance of the study
1.6 Research Methodology
1.7 Ethical Considerations
1.8 Structure of the study
1.9 Main Contribution
1.10 Summary
2.1 Introduction
2.2 Technology Acceptance Model (TAM)
2.3 Diffusion of Innovation (DOI) Theory
2.4 Technology-Organisation-Environment (TOE) Theory
2.5 The Human Environmental Model
2.6 IT Governance
2.7 Stakeholder Approach
2.8 Sociological Paradigms
2.9 Systems Approaches
2.10 Discussion
2.11 Conclusion
3.1 Introduction
3.2 Relationship between Sociological Paradigms and Systems Approaches
3.3 Relationship between Systems Approaches and Problem Context
3.4 Preliminary IT Adoption Governance Framework
3.5 Conclusion
4.1 Introduction
4.2 Research Philosophy
4.3 Research Approach
4.4 Research Strategy
4.5 Research Methods
4.6 Quantitative Data Collection Phase
4.7 Qualitative Data Collection Phase
4.8 Integration of Results
4.9 Ethical Consideration
4.10 Scope and Limitations
4.11 Implications of Research
4.12 Conclusion
5.1 Introduction
5.2 Demographic Characteristics
5.3 Framework Constructs Frequencies
5.4 Means and Standard Deviation of Constructs
5.5 T-Test results of demographic variables
5.6 Analysis of variance of demographic variables
5.7 Correlation Results of Framework Constructs
5.8 Regressions Analysis on IT Governance
5.9 Discussion
5.10 Conclusion.
6.1 Introduction
6.2 Link between Phases
6.3 Framework Components Results
6.4 Discussion
6.5 Conclusion
7.1 Introduction
7.2 Integrated Results
7.3 Discussion
7.4 Final validation interviews
7.5 Conclusion
8.1 Introduction
8.2 Discussion
8.3 To what extent did the study answer the main research question?
8.4 To what extent did the study meet its aim and objectives?
8.6 Research Contributions
8.7 Recommendations
8.8 Limitation of the study
8.9 Future Research

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