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2.4.1.1 Technology*Acceptance*Model*

Of all the models that have been proposed for user technology acceptance, the Technology Acceptance Model (TAM) has been the most influential (Altaf and Schuff 2010; Lederer et al. 2000; Hu et al. 1999; Igbaria et al.

1997; Chau 1996; Szajna 1996; Venkatesh and Davis 1996; Taylor and Todd 1995; Subramanian 1994; Szajna 1994; Hendrickson et al. 1993; Adams et al. 1992; Mathieson 1991; Davis 1989; Davis et al. 1989).

Davis (1989) introduced the TAM, a well-known and widely referred model regarding the adoption of technology. He developed and validated a

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measurement scale for predicting user acceptance of technology, based on two variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.

People tend to use or not use an application to the extent they believe it will help them to perform their job better. This first variable is called perceived usefulness. However, even if potential users believe that a given application is useful, they may, at the same time, believe that the system is too hard to use and that the performance benefits of usage are outweighed by the effort of using the application. This second variable is called perceived ease of use. Both variables have an impact on the intention to use (Figure 2.10).

Perceived usefulness is “the degree to which a person believes that using a particular system would enhance his or her job performance”.

Perceived ease of use, in contrast, refers to "the degree to which a person believes that using a particular system would be free of effort”. The intention to use is “the extent to which a person intends to use a particular system”.

Figure 2.10: Technology Acceptance Model (from (Davis et al. 1989))

Davis (1989) refined the measures and streamlined them, which resulted in two six-item scales for perceived usefulness and perceived ease of use.

Perceived usefulness:

1) Work more quickly 2) Improve job performance 3) Increase productivity 4) Enhance effectiveness 5) Make job easier 6) It is useful

For perceived usefulness, notice that the items fall into three main clusters. The first cluster relates to job effectiveness (2,4), the second to productivity and time savings (1,3), and the third to the importance of the system to one's job (5,6).

Perceived ease of use:

1) Easy to learn

2) Controllable (get it to do what I want it to do) 3) Clear and understandable

4) Flexible to interact with 5) Easy to become skillful 6) Easy to use

These items also fall into three main clusters. The first relates to physical effort (2,4), while the second relates to mental effort (3,6). The third cluster is somewhat more difficult to interpret but appears to be tapping perceptions of how easy a system is to learn (1,5).

In both studies performed by Davis, perceived usefulness was significantly more strongly linked to usage than was perceived ease of use.

Users are driven to adopt an application primarily because of the functions it performs for them, and secondarily for how easy or hard it is to get the system to perform those functions. For instance, users are often willing to cope with some difficulty of use in a system that provides critically needed functionality. Although difficulty of use can discourage adoption of an otherwise useful system, no amount of ease of use can compensate for a system that does not perform a useful function. Ease of use may in this way be an antecedent to usefulness, rather than a parallel, direct determinant of usage (Figure 2.10). All else being equal, the easier a system is to interact with, the less effort needed to operate it, and the more effort one can allocate to other activities (Radner and Rothschild 1975), contributing to overall job performance and perceived usefulness.

It should be emphasized that perceived usefulness and perceived ease of use are people's subjective appraisal of performance and effort, respectively, and do not necessarily reflect objective reality.

Practitioners generally evaluate systems not only to predict acceptability but also to diagnose the reasons underlying lack of acceptance and to formulate interventions to improve user acceptance. In this sense, research on how usefulness and ease of use of EA techniques can be influenced by various controllable factors (e.g., design, user interface, functional characteristics, training and education, case study testing and user involvement in design, ...) is important.

2.4.1.2 Method*Evaluation*Model*

Moody (2003) noticed that IS design research emphasized the development of new methods, while the evaluation of methods was only addressed in a limited fashion (Westrup 1993; Fitzgerald 1991; Bubenko 1986; Curtis 1986). Wynekoop and Russo (1997) conducted a review of IS design research published in the leading IS journals and concluded that there was a

“lack of serious empirical research into the efficacy of methods in practice”

and a “need for validation of methods in organizational contexts using real practitioners”. Regardless of the potential benefits of IS design methods published, unless they are used in practice, these benefits cannot be realized.

The issue of practitioner acceptance of methods is something which has been largely ignored in IS design research and could help improving the acceptance of EA techniques in SMEs. However, usage is an important pragmatic measure of the “success” of a method and also of the impact of research on practice (Fitzgerald 1991).

Moody (2003) proposed a theoretical model and associated measurement instrument for evaluating IS design methods, like EA methods.

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The method is based on the previously mentioned TAM (Davis 1989) and Methodological Pragmatism (Rescher 1977).

2.4.1.3 Methodological*Pragmatism*

Methodological Pragmatism (Rescher 1977) assumes that methods have no truth value, only pragmatic value. A method does not describe any external reality, so it cannot be true or false, only effective or ineffective. Unlike theses, methods cannot be established deductively from known facts or inductively from observations. The validity of a method can only be established by applicative success in practice. The objective of validation should not be to demonstrate that the method is “correct”, but that it is rational practice to adopt the method based on its pragmatic success.

Pragmatic success is defined as “the efficiency and effectiveness with which a method achieves its objectives”. All methods are designed to improve performance of a task (Figure 2.11). Task performance can be improved in two ways:

• Efficiency improvement: reducing the effort required to complete the task, i.e. reducing the inputs.

• Effectiveness improvement: improving the quality of the result, i.e.

improving the outputs.

Figure 2.11: Efficiency vs. Effectiveness (from (Moody 2003))

2.4.1.4 Combining*Methodological*Pragmatism*and*

TAM*

Moody (2003) argued that there are clear parallels between user acceptance of information systems and practitioner adoption of methods. Both are subject to individual choice: users make decisions about what systems they will use and practitioners make decisions about what methods they will use.

Both are therefore the result of reasoned action. For this reason, Moody argued that theoretical models used to explain and predict user acceptance of information technology may be adapted to explain and predict the adoption of methods.

Actual efficacy and adoption in practice are two dimensions of success. On their own, neither actual efficacy nor adoption in practice will

lead to improved practices. A method that improves performance but that is not used will have no effect on practices. Similarly, a method that people use but which reduces performance of the task will have a negative effect on practices. Nowadays, as already mentioned, EA is hardly used in SMEs, although it could improve performance.

Both TAM and Methodological Pragmatism are combined in the Method Evaluation Model, a theoretical model for evaluating methods.

Figure 2.12 shows the primary constructs of the model and causal relationships.

Figure 2.12: The Method Evaluation Model (from (Moody 2003))

The definitions of the constructs of the model are:

• Actual efficiency: the effort required to apply a method.

• Actual effectiveness: the degree to which a method achieves its objectives.

• Perceived ease of use: the degree to which a person believes that using a particular method would be free of effort.

• Perceived usefulness: the degree to which a person believes that a particular method will be effective in achieving its intended objectives.

• Intention to use: the extent to which a person intends to use a particular method.

• Actual usage: the extent to which a method is used in practice.

Actual efficiency and actual effectiveness are constructs from Methodological Pragmatism. Perceived ease of use, perceived usefulness and intention to use are the constructs of TAM.

The causal relationships between the constructs of the model are:

• Perceived ease of use is determined by actual efficiency: actual efficiency measures the effort required to apply the method, which should determine perceptions of effort required.

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• Perceived usefulness is determined by actual effectiveness: actual effectiveness measures how well the method achieves its objectives, which should determine perceptions of its effectiveness.

• Perceived usefulness is determined by its perceived ease of use. This follows from TAM.

• Intention to use a method is jointly determined by its perceived ease of use and perceived usefulness. This follows from TAM.

• Actual usage of a method is determined by intention to use. This also follows from TAM and the Theory of Planned Behavior (Ajzen 1991), which establishes that perceptions influence intentions which in turn influence the actual behavior of the individual.

The main difference with TAM is that in the Method Evaluation Model actual efficiency and effectiveness determine intentions to use a method only via perceptions of ease of use and usefulness. This is a subtle difference, but an important one: in human behavior, subjective reality is more important than objective reality. The perceptions will also be influenced by other factors (e.g., prior knowledge, experience with particular methods, normative influences).

Moody also concluded that the relative importance of perceived ease of use in making decisions about method adoption is much higher for technique, it cannot result in improved practices unless people use it.

2.4.1.5 Adoption*Models*of*IT*in*SMEs*

Many studies have attempted to describe the factors influencing IT adoption in SMEs (Altaf and Schuff 2010; Chwelos et al. 2001; Kuan and Chau 2001;

Igbaria et al. 1997; Iacovou et al. 1995). In order to develop an integrated model of IS adoption in SMEs, Thong (1999) specified four contextual variables as primary determinants of IS adoption. He grouped the many variables in four groups: CEO, IS, organizational characteristics, and environmental characteristics. Grandon and Pearson (2004) proposed a model for e-commerce adoption in SMEs based on a fusion of the strategic value of certain information technologies to top managers (Subramanian and Nosek 2001; Chan 2000; Barua et al. 1995) and factors that influence the adoption of IT (TAM (Davis 1989)). The results confirmed TAM in the sense that perceived usefulness and perceived ease of use turned out to be the most influential factors of e-commerce adoption as perceived by top managers of SMEs.

Although these models discuss the adoption of information technology and not methods in SMEs, they confirm the factors of TAM as being the most influential for adoption in SMEs. The Method Evaluation Model of Moody (2003), although not specifically developed for evaluation

of methods in SMEs, is based on the factors of TAM and will be further used as an evaluation model for EA methods in SMEs.