Technology Acceptance Model (TAM)

measures being used to predict usage but “little attention is paid to the quality of the measures used or how well they correlate with usage behaviour” (Davis, 1989, p.320). TAM contained two variables used to predict the likeliness of a technology being utilised:

1. Perceived ease of use defined as “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p.320).

2. Perceived usefulness defined as “the degree to which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989, p.320).

Scale items were produced to test these two variables to predict whether users would use the new technology. TAM surveys expected users (pre-implementation) or users (post-implementation) of a system and asks them to complete a likert scale rating items from 1-7. The scale is then used to produce a score for perceived usefulness and perceived ease of use which can predict acceptance of the technology. Both variables were found to correlate to current and predicted usage of a technology, although “usefulness had a significantly greater correlation with usage behaviour than did ease of use”.

“Perceived usefulness has consistently been a strong determinant of usage intentions, with standardized regression co-efficient typically around 0.6” (Venkatesh and Davis, 2000, p.187) and perceived ease of use “exhibited a less consistent effect on intention across studies” (Venkatesh and Davis, 2000, p.187). Although TAM exhibited consistent results it was limited by its use of only two variables. Davis and Venkatesh (2000) extended the model to “include additional key determinants of TAM’s perceived usefulness and usage intention constructs, and to understand how the effects of these determinants change with increasing user experience over time with the target system” (Venkatesh and Davis, 2000, p.187). TAM2 expanded on TAM by further investigating the perceived usefulness construct breaking it down to identify factors which increased or decreased perceived usefulness. TAM2 identified seven constructs impacting perceived usefulness spanning social influence processes (subjective norm, voluntariness and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability and perceived ease of use). Figure 2-10 summarises the constructs found in TAM2.

Figure 2-10 TAM 2 (Venkatesh and Davis, 2000, p.188)

• Subjective Norm - defined as a “person’s perception that most people who are important to him think he should or should not perform the behaviour in question” (Fishbein and Ajzen, 1975, p.302). The inclusion of subjective norm came from the observation that although people may not find a technology useful they may still use it if they believe others feel it is. “People may choose to perform a behaviour, even if they are not themselves favourable toward the behaviour or its consequences, if they believe one or more important referents think they should, and they are sufficiently motivated to comply with the referents.” (Venkatesh and Davis, 2000, p.187). The study identified that subjective norm itself was effected by voluntariness and experience:

o Voluntariness - the extent to which potential adopters perceive the adoption decision to be non-mandatory. TAM2 suggests in mandatory settings there is a “compliance-based effect of subjective norm on intention over and above perceived usefulness and ease of use” (Venkatesh and Davis, 2000, p.188).

o Experience –prior to experiencing the technology being implemented subjective norm will have an effect on intention of use and perceived usefulness. This effect will decrease over time as users get direct experience of the technology. Direct experience provides the intention of use as experience levels increase.

• Image - Moore and Benbasat (1991, p.195) define image as “the degree to which use of an innovation is perceived to enhance one’s ... status in one’s social system”. TAM2 theorizes “that subjective norm will positively influence image because, if important members of a person’s social group at work believe that he or she should perform a behaviour, then performing it will tend to elevate his or her standing within the group” (Venkatesh and Davis, 2000, p.189). An

individual may perceive that using a system will lead to improvements in his or her job performance indirectly due to image enhancement, over and above any performance benefits directly attributable to system use.

• Job Relevance – defined as “an individual’s perception regarding the degree to which the target system is applicable to his or her job” (Venkatesh and Davis, 2000, p.191). Perceived usefulness will be affected by the level to which users feel the technology is relevant to their job. Job relevance relates to Beach et als Image Theory (1998) as “systems below a minimum threshold value of perceived job relevance would be screened from further adoption consideration.” (Venkatesh and Davis, 2000, p.191).

• Output Quality – TAM2 brings into the model the relationship between output quality and perceived usefulness. When there are multiple technology options to choose between, the system providing the highest quality output would be expected to be chosen. Therefore output quality affects the perceived usefulness of a technology.

• Result Demonstrability - defined as the “tangibility of the results of using the innovation” (Moore and Benbasat 1991, p.203). In a previous study Agarwal and Prasad (1997) found significant correlation between usage intentions and result demonstrability. A technology which can clearly demonstrate its results will be rated more useful than a system where results are unclear. These additional constructs were used to create a new likert scale which is distributed to users/ potential users to predict usage. The introduction of the new constructs meant that in the four studies carried out during the expansion of TAM to TAM2 “up to 60% of the variance in” perceived usefulness could now be explained (Venkatesh and Davis, 2000, p.196). TAM2 had practical implications; the study identified that over time a compliance based approach was much less effective than the “use of social influence to target positive changes in perceived usefulness” (Venkatesh and Davis, 2000, p.199). TAM2 suggests that whilst designing and implementing a technology it is important to consider job relevance, output quality and result demonstrability, improving a technology on these factors is likely to improve its usage. Whilst TAM2 expanded the construct of perceived usefulness of TAM it did not expand the second construct of perceived ease of use.

TAM3 (Venkatesh and Bala, 2008) expanded the original TAM to include the as yet unexplored construct of perceived ease of use. Four elements were identified these are labelled anchors in figure 2-11 (adapted from Venkatesh and Bala, 2008, p.278):

• Perceptions of external control - the availability of organisational resources and support structures to facilitate an individuals’ use of the system.

• Computer anxiety – the amount of apprehension an individual expects to feel when using the new system.

• Computer playfulness – the intrinsic motivation associated with the new system.

Two system characteristics are used to determine perceived ease of use after experience, labelled adjustments in figure 2-11:

1. Perceived enjoyment – the extent to which using the new system is deemed to be enjoyable in its own right.

2. Objective usability – comparison of the system based on actual level of effort required to achieve goals.

Figure 2-11 TAM 3(Venkatesh and Bala, 2008, P.280)

TAM3 (shown in figure 2-11) represents the most comprehensive model for predicting technology acceptance of a new system among individuals. The model is relatively new having been published in 2008 and early versions of the TAM or UTAUT are still more commonly used in studies.