Technology can have far-reaching consequences in many areas. Understanding the factors which influence the adoption and use of information technology by individuals is one of the important issues which continue to interest Information Systems researchers. Many factors influence the process of adaptation, these factors are important to take into account when application developers want users to adopt their products and it can get even more complicated when different cultures are involved. Technology adoption involves the use, the technology and the context [76]. There are many models for understanding technology adoption that have been proposed over the recent years. From these various models, Pedersen (2003) lists Rogers’s innovation diffusion model, the domestication model and technology acceptance model (TAM) as the three most commonly applied:
a. Roger’s innovation diffusion model is founded in sociology but has been applied to the world of marketing where users are seen as economic entities, the model provides an approach to understanding how innovations are adopted by a particular population [77].
b. Domestication model where users are seen as social entities and the model aim to provide a framework for understanding how technology innovations change and are changed by their social contexts [78].
c. Technology acceptance model to explain the determinants of computer acceptance and usage behavior [79].
While Roger’s innovation diffusion model focuses on marketing and sales processes, the domestication approach deals with a more global analysis of adoptions ex post facto and the TAM focuses on information technology adoption in organizations [80].
The theoretical foundation for TAM is based on Fishbein and Ajzen’s theory of reasoned action (TRA) model [81]. TRA is widely used as a study model in social psychology. It attempts to explain why people behave as they do in situations of ‘reasoned action’ by identifying causal relations
between beliefs, attitudes, intentions and behavior [82]. Attitude is defines as the individual’s positive or negative feelings about enacting a target behavior. TRA is illustrated in Figure 2.4 below:
Beliefs and Evaluations Attitude towards Behavior (A) Normative Beliefs and Motivation to Comply Subjective Norm (SN) Behavioral Intention (BI) Actual Behavior
Figure 2.4 Diagrammatic representation of the TRA adapted from [83]
TRA is a general model and it does not specify the active beliefs for a specific behavior. Therefore, for researchers to use the TRA, firstly they have to identify the beliefs that are relevant for subjects regarding the behavior under investigation. For example, if TRA is applied to groupware usage, people’s belief regarding the benefits or liabilities of groupware use have to be identified by the researcher.
The TAM is a special case of TRA for modeling technology adoption in organizations [82]. TRA asserted that beliefs influence attitudes, which in turn lead to intentions that result in behavior. Accordingly, Davis (1986) reasoned that an individual’s beliefs with regard to ‘perceived usefulness’ and ‘perceived ease of use’ resulting in an intention to use that in turn resulted in actual use. The TAM developed by Davis (1989) explained about the acceptance of information technology and aims at assessing user beliefs about the usefulness and ease of use of a technology that is expected to support their work. It has become the core template for much technology acceptance theory. A key purpose of TAM is to provide a basis for tracing the impact of external variables on internal beliefs, attitudes, and intentions. Perceived ease of use (PE) and perceived usefulness (PU) are the two most important factors in TAM. These two factors combined will generate an acceptance or rejection disposition for the user towards using a particular technology. The TAM has the following components [84]:
1. External variables (EV): External variable influence perceived usefulness (PU) and perceived ease of use (PE), for example cultural factors in this research.
2. Perceived usefulness (PU): Perceived usefulness is defined as ‘the extent to which a person believes that using the system will enhance his or her job performance’ [84].
3. Perceived ease of use (PE): Perceived ease of use is ‘the extent to which a person believes that using the system will be free of effort’ [82].
4. Attitudes towards use (A): Attitude toward use is defined as ‘the user’s desirability of his or her using the system. Perceived usefulness (PU) and perceived ease of use (PE) are the sole determinants of attitude (A) towards the technology system.
5. Behavioral intention (BI): Attitude (A) combined with perceived usefulness (PU) predict behavioral intention (BI)
6. Actual use: Behavioral intention (BI) in turn predicts actual use. TAM is illustrated in Figure 2.5 below which includes six concepts [82].
External Variables (EV) Perceived Usefulness (PU) Perceived Ease of Use (PE) Attitude toward use (A) Behavioral Intention to Use (BI) Actual system use
Figure 2.5 Technology Acceptance Model (TAM) [85]
Previous research indicated that TAM is one of the most influential models in the adoption of technology and represents an important theoretical contribution towards the usage of information system and information system acceptance behavior [86]. A review of scholarly research on IS acceptance and usage suggests that TAM has emerged as one of the most influential models in the stream of research [87] and has been fully validated to be powerful as a framework to predict user acceptance of new technology and for predicting whether users will adopt new information technologies. TAM has been tested in many empirical researches and the tools used with the model have proven to be of quality and yield statistically reliable results [46].
TAM model is mainly applied to the adoption of technology within organization and the construed of the model are meant to be general and universal to different types of computer systems and user populations. In general, TAM is able to explain up to 40% of the variance in usage intentions and 30% in system usage [84]. However, over the past years it has also been criticized for its shortcomings. Malhotra and Galletta (1999) indicated that the attitude towards adopting a technology is believed to be the result of personal and social influences and the fact that TAM does not account for social influence is a limitation. TAM received criticism as it does not include social factors that affect technology acceptance and usage, therefore, a further model (TAM2) was later introduced by Venkantesh and Davis (2000). The revised model reveals the effect of three interrelated social forces that influence users to accept or reject adopting the technology, consisting of subjective norms, voluntariness, and perceived status [2]. With this in mind, the TAM model that is used in this research has been extended and modified to fit for applying the social influences.