Innovation Diffusion Theory

Innovation Diffusion Theory: The earliest theory on of consumers’ toward adoption of e-banking services. technology acceptance is based on (Rogers, 1995) theory of diffusion of innovation (IDT). This theory posits that innovation adoption is a process of uncertainty about the young technology; individuals will gather and harmonize information about using the technology. Beliefs then cause individuals to accept or reject the technology. Nor and (Nor & Pearson, 2008) established diffusion as “the process in which an innovation is communicated through certain channels over time among the members of a social system. As expressed in this description: Innovation characteristics, individual user characteristics, adopter distribution over time, diffusion

The TRA hypothesizes that a behavior is predicted by an individual’s intention to engage in a given behavior. Intention, in turn, is predicted by two factors, the individual’s attitude towards the behavior and the subjective norm (Ajzen & Fishbein, 2009). Attitude toward the behavior reflects an individual’s evaluation or general feeling toward a target behavior. It indicates an individual’s positive or negative evaluation about performing the behavior. The theory postulates that the intention to perform a behavior will be higher when the individual has positive evaluation of performing the behavior (Ajzen I. , 1991). Theory of reasoned action (TRA) has been widely applied in variety of research settings, from predicting the intention to seek psychological services for alcohol abuse (Lee, Kwon, & David, 2005), to predicting the consumption of fats and oils. The theory has also been used in the information system field and confirmed the ability of the model to predict behavioral intention to use a certain technology. Thus, it is reasonable to believe that theory of reasoned action will provide a very good foundation for this study to investigate intention to use e-banking services, because this study involve

, 1991) with aspects of innovation diffusion theory (Rogers, 1995). The theory postulate that attitude, subjective norm and perceived behavioral control will influence the intention to use a technology. (Taylor & Todd, 1995) extended the theory by decomposing the attitudinal, normative and perceived control beliefs into multi-dimensional constructs this provided higher explanatory power and a more precise understanding of the antecedents of behavior. Search through established databases returned that several researchers have used the DTPB as their research framework. For instance, the DTPB was compared to TAM and TPB to predict information technology usage. Utilizing 786 business students and using computing resource center as the target technology, (Taylor & Todd, 1995) found that the DTPB provided well predictive behavior when compared to TAM and TPB. In another framework of DTPB, another author employed DTPB to explore which type of treatment chronic pain patients prefer, the traditional or an Internet treatment and which factors contribute to their preference (Yi, Park, & Jae, 2006). Qualitative semi-structured interviews were conducted with 25 patients with chronic pain from a pain rehabilitation centre in the Netherlands. The study shows that participants considered an