Technology Acceptance Model

One of the most successful theories for exploring and examining technology acceptance is the Technology Acceptance Model (Holden & Karsh, 2010; Sun & Zhang, 2006). The theory approaches the examination of technology acceptance by two variables, that is, Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). The popularity and use of Technology Acceptance Model (TAM) is evident through other studies, which have sought to expand its application by introducing new variables and concepts that allow individual behaviour related to technology use and acceptance to be explained accurately. These studies and researches on TAM introduce variables or concepts that behave like the PU or PEUOU or as intermediaries variables between them and the dependent variables (Ha & Stoel, 2009; van der Heijden & Verhagen, 2009; Roca et al., 2006). According to Davis (1989b), there exists another line of research that focuses on the use of ‘previous external variables’ that were popular before the introduction of PU & PEOU. In this paper, the study applies the latter approach that uses previous and earlier theories of behavior and factors related to internet experience. This approach combines previous theories and approaches related to internet experience (Liaw & Huang, 2003; O’Cass & Fenech, 2003), and intrinsic motivation factors such as self-efficacy (Chen et al.’ 2002; Bruner & Kumar, 2005).

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The use of previous technological experience in this study draws heavily from the key tenets of previous theories such as the Task-Technology Fit Model (Goodhue, 1988; Teo et al., 1999). According to the Task-Technology Fit Model, technological experience allows the direct acquisition of information, which allows individuals to gain more knowledge, and changes their existing perceptions (Min & Galle, 2003), and at the same time encourages the acquisition of new perceptions and knowledge related to Information Technology (Teo et al., 1999). Through the use of new technologies, the use gains new skills and experiences, which lead to accumulation of automatic behavior tendencies over time (Liao et al., 2011).

The study also utilizes two additional factors, that is, acceptance of internet and frequency of use, which have been suggested through the Expectation-Confirmation Theory of Oliver (1980) in addition to the self efficacy of measuring internet experience suggested in Liao and Cheung (2001), Goldsmith and Goldsmith, (2002) and Blake et al. (2003). The new two factors are very important, and are both used to measure the same concept related to the usage of internet and technology (Shih, 2004), and are important in identifying important requirements that individuals must fulfill for an information disclosure. Internet experience is very important as it allows an individual to have greater confidence and comfort with online activities and increases the users or consumer decision-making (Montoya-Weiss et al., 2003; Rodgers et al., 2005).

The variable, ‘perceived self-efficacy” is not a recent addition to the discourse as it has been used in previous theories and models of behavior such as the Social Cognitive Theory (SCT) (Bandura, 1997), and the Theory of Planned Behavior (Schifter & Ajzen, 1985). According to Bandura (1997), ‘Perceived Self-Efficacy” (SEF) is defined as the “people’s judgment of their capabilities to organize and execute courses of action required to attain designated types of performances”. Taylor and Todd (1995) also applied the variable in the formulation of the Decomposed Theory of Planned Behavior (DTPB), which is a theory specifically made to analyze technological behavior.

In expounding on the concept of perceived self-efficacy, Bandura (1997), direct experience is the strongest generator of SEF. Through direct experience, a user is able to gain important skills that allow for the development of the perception (Compeau & Higgins, 1995). Individuals who use internet frequently are more confident and hence more inclined to share and disclose information (Yoon. Et al., 2002). In other words, the research concludes that internet users who have more experience and use internet frequently are more satisfied with it and also have a greater perceived self-efficacy (Goldsmith & Goldsmith, 2002; Yoon et al., 2002).

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StudyCorgi. (2021, January 30). Technology Acceptance Model. Retrieved from https://studycorgi.com/technology-acceptance-model/

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"Technology Acceptance Model." StudyCorgi, 30 Jan. 2021, studycorgi.com/technology-acceptance-model/.

1. StudyCorgi. "Technology Acceptance Model." January 30, 2021. https://studycorgi.com/technology-acceptance-model/.


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StudyCorgi. "Technology Acceptance Model." January 30, 2021. https://studycorgi.com/technology-acceptance-model/.

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StudyCorgi. 2021. "Technology Acceptance Model." January 30, 2021. https://studycorgi.com/technology-acceptance-model/.

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StudyCorgi. (2021) 'Technology Acceptance Model'. 30 January.

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