Chapter 3. Literature Review
3.2 Technology Acceptance
3.2.2 Defining Technology Acceptance
User acceptance is a critical factor in ICT implementation projects, regardless of whether the ICT is an enabler of change in and of itself or part of an organisational change project. Yet the implementation and acceptance research streams rarely overlap and “...few studies have examined potential linkages between ICT implementation tactics or strategies and ICT acceptance research models” (Barki, et al. 2008, p. 278), although ICT implementation strategies such as user participation, training and support can influence acceptance outcomes (Ali, et al. 2016; Barki et al. 2008; Meier et al. 2013). Both Schaper and Pervan (2005), and De Toni et al. (2015) support this view, arguing that the implementation context and process plays a major role in influencing user acceptance and implementation success. Implementation strategies could also be used as antecedents to acceptance (Barki et al. 2008).
Within the implementation and acceptance research streams the terms adoption, acceptance and use are often used interchangeably, or as proxies for one another, despite their very different meanings (Schwarz and Chin, 2007; Malhotra, 1999). Malhotra (1999) argues that adoption and acceptance are two different things; and that acceptance should not be used as a proxy for usage. This author believes that adoption is a process of sense-making in which psychological acceptance of technology is gained through a personal construction view, (i.e. “the adoption of a specific technology is dependent upon the extent to which the adopter finds it personally relevant or meaningful” (Malhotra, 1999, p. 98)). Schwarz and Chin (2007) note that ICT acceptance is generally viewed as being identical with ICT usage (as is the case with TAM, for example) and that this leads to a failure to consider “alternative notions of acceptance” (Schwarz and Chin, 2007, p. 233). Schwarz et. al., (2014, p.74) offer an alternative approach to TAM “by proposing a process-orientated model of IT acceptance”. They argue that acceptance is a process comprising five psychological modes of acceptance:
1) To receive: the psychological state of taking the technology without question;
2) To grasp the idea: the psychological state of fully comprehending the intentionality (e.g. functionality and design) of the technology;
3) To assess the worth: the psychological state of evaluating the value and desirability of the technology to me;
4) To be given: the psychological state of an individual willing to adapt their routines to what was required by the technology; and
5) To submit: the psychological state of the individual surrendering to the intentionality of the technology (Schwarz et al. 2014, p. 75).
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These authors then identify antecedents to the process of acceptance, consisting of such things as user participation, training and perceptions of the ICT, such as usefulness, which would contribute to how a user progresses through the psychological modes of acceptance (Schwarz and Chin, 2007).According to Lucas et al. (2007) and Schwarz and Chin (2007), acceptance has its own process beginning with initial adoption (initially by the organisation and then by the individual), with the final indicator being usage (to varying degrees). This acceptance then leads to diffusion which “is essentially a social process in which subjectively perceived information about the… (innovation)…is communicated from person to person” (Rogers, 2003, p. xx). As illustrated in Figure 3-4 the term acceptance, encompassing individual adoption and usage, will continue to be used throughout this thesis.
Figure 3-4: Process of Acceptance
The technology acceptance model has been a dominant influence within the acceptance research stream (Anderson, 2016; Lee et al. 2003; Malhotra et al. 2008; Marangunić and Granić, 2015; Wu and Lu; 2013) with implications for researchers investigating the implications of intrinsic motivation on user acceptance (including the present project).
Davis (1989) initially recognised the importance of having users accept and use technology and found very few valid measurement scales for predicting acceptance and how acceptance related to use. In the original Technology Acceptance Model (TAM) Davis proposed that perceived usefulness (PU) and perceived ease of use (PEOU) were fundamental determinants to explain user behaviour (Davis, 1989) and provided the following definitions for each:
PU is “the degree to which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989, p. 320)
PEOU is “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p. 320)
Davis (1989) argued that these determinants could be used by practitioners to predict a system’s acceptability and to diagnose why a system was not being accepted – and could lead to appropriate interventions such as training, education and user involvement being used to improve user acceptance.
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TAM was adapted from the Theory of Reasoned Action (TRA) (Davis et al. 1992), an intention model used to predict and explain consciously-intended behaviours (Ajzen, 2001; Davis et al. 1992) whereby “people act in accordance with their intentions and perceptions of control over the behaviour…intentions…are influenced by attitudes toward the behaviour, subjective norms and perceptions of behavioural control” (Ajzen, 2001, p. 43). TRA and, thus, TAM are consistent with the cognitive (expectancy) theories of motivation (Ajzen, 2001; Venkatesh, 2000), whereas Meier et al. (2013) argue that current acceptance models are based on mechanistic (a stimulus/response association) assumptions which, as Section 3.3 will argue in more detail, do not address either the varying types of motivation or the energisation of motivation. TAM has evolved over the years from the original theory of that name (Davis et al. 1989) to TAM2 (Venkatesh 2000), the Integrated Model of Technology Acceptance (IMTA) (Venkatesh, et al. 2002), the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003) and, more recently, TAM3 (Venkatesh and Bala 2008), UTAUT2 (Venkatesh et al. 2012), EBTAM (Leyton et al. 2015) and finally a framework of technology adoption and use has been developed based on a synthesis and review of UTAUT by Venkatesh et al. (2016) . For a history of the evolution of TAM see Lee et al. (2003); Venkatesh et al. (2003) and a literature review by Marangunić and Granić (2015).Despite its evolution, TAM and all its variations continue to use PU and PEOU as the two principal determinants (each with a number of variables) of a user’s behavioural intention to accept and use technology. Both these variables have been used as examples of extrinsic and intrinsic motivation respectively by a number of researchers (Davis et al. 1992; Hwang 2005). Davis et al. (1992) incorporated motivation by adding the ‘enjoyment’ variable (which is described by Gerow et al. 2013, p.361) as the “Motivational Technology Acceptance Model or MTAM”). Venkatesh et al. (2002) also attempted to incorporate intrinsic motivation as an additional determinant of TAM in their IMTA.
Other recent examples of attempts to incorporate intrinsic motivation into the acceptance research stream include: Fagan et al. (2008) who uses the IMTA and Self Determination Theory to incorporate intrinsic motivation; Luo et al. (2010) who combine constructs from TAM and Innovation Diffusion Theory to create a model to explain user adoption; Park (2010) who integrates TAM with a gratifications framework to explore user motivation; Singh and Holmtrom (2015) who use Maslow’s hierarchy of needs viewpoint to investigate Building Information Modelling adoption and, finally, Torres and Sidoroav, (2015) who integrate the concept of task-technology fit with SDT. Similarly, Venkatesh et al. (2012) have included hedonic motivation “conceptualised as perceived enjoyment” (Venkatesh et al. 2012; p.161) as a determinant in UTAUT2. Motivation in the acceptance research stream continues to be a mis-represented construct as reported in Venkatesh et al. (2016) where researchers have integrated UTAUT with other models: in one study effort expectancy is used as construct of intrinsic motivation, whereas in another study it is viewed as a construct of extrinsic motivation.
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Other studies (Lin and Bhattacherjee, 2010; Gerow et al. 2013; Lowry et al. 2013; Wu and Lu, 2013) have focussed on intrinsic and extrinsic motivation in hedonic application use (pleasure, fun) and utilitarian application use (productivity, practical). Both Gerow et al. (2013) and Wu and Lu (2013) have conducted meta-analyses of existing studies. While Gerow et. al. (2013, p.360) found that “intrinsic motivation is equally relevant for predicting intentions toward using and actual use of both hedonic and utilitarian systems”; Wu and Lu (2013) found that intrinsic motivators are more important than extrinsic motivators in the context of hedonic application use. Lowry et al. (2013) proposed the Hedonic-Motivation System Adoption Model (HMSAM), in preference to extending the TAM, although they used the “more expansive intrinsic motivation construct of CA” (Cognitive Absorption) (Lowry et al. 2013, p.632) in place of joy. Briefly, CA was introduced by Agarwal and Karahanna (2000, p. 666) as a conceptual construct where it is presented as “an intrinsic motivation related variable” consisting of several sub-constructs: Control; Curiosity; Joy; Focused Immersion; and Temporal Dissociation which, the authors say “represent different forms of intrinsic motivation” (Agarwal and Karahanna, 2000, p. 673). While “control”, for example, is an important factor in intrinsic motivation it is not a form of intrinsic motivation in itself, an issue which is discussed more fully in Section 3.4.Almost all these studies, however, base intrinsic motivation on TAM’s definition of motivation, which equates intrinsic motivation with playfulness and/or enjoyment. Playfulness, however, is not the same thing as intrinsic motivation – as already discussed in Section 1.1.3 and further clarified in Section 3.4.
Because of TAM’s dominant influence in the technology acceptance literature, the majority of studies into user motivation continue to misrepresent the motivation concept in this field. The present study offers a different perspective on this important issue. The discussion which follows and, particularly, the analysis in Section 3.3offers a very different approach to user motivation – and this is one of the major contributions to both theory and practice made by this thesis.