The Technology Acceptance Model

Since its inception, the model has been tested with various applications in tens of studies and has become a most widely applied model of user acceptance and usage. Nevertheless, the reported findings on the model are mixed in terms of statistical significance, direction, and magnitude. In this study, we conducted a meta-analysis based on 26 selected empirical studies in order to synthesize the empirical evidence. The results suggest that both the correlation between usefulness and acceptance and between usefulness and ease of use are somewhat strong. However, the relationship between ease of use and acceptance is weak, and its significance does not pass the fail-safe test. Extended technology acceptance models had other limitations of their own.

In a few studies, participants were nurses , and physio- or occupational therapists. Five studies collected data from a mix of physicians, nurses, pharmacists, and medical technicians [ ]. Efforts to apply TAM to health IT date back to the late 1990’s, beginning with studies by Hong Kong researchers testing the TAM and, subsequently, different versions of TAM and TPB, technology addiction in a sample of 408 surveyed physicians with access to telemedicine IT . Their findings were disappointing, and they asserted that TAM was a poor fit for physician acceptance of health IT, perhaps because of professional differences between physicians and other workers who use IT . In total, 16 datasets have been analyzed, and TAM has fared much better in later tests.

  • Second, here we review a larger set of 16 data sets analyzed in 22 studies, including ones that were missed by the earlier review and ones that have been published since.
  • SN measures were similar to one another in that almost all asked about the degree to which some referents thought the clinician should use the system.
  • The main criticisms are that it’s trivial, has limited predictive power, and no practical value.
  • Findings departed from her hypothesis in terms of predictability or similarity of patterns among firms.
  • This construct derived from the self-efficacy concept, which refers to a situation-specific belief about how well someone can execute actions for the prospective task (Davis, 1989; Bandura, 1982).
  • The goal of TAM was to become the framework for examining a wide range of behaviours of technology users while maintaining a parsimonious approach .

Marketers can use these findings to develop viral marketing campaigns and encourage customers to contribute useful and credible eWom that could improve the customers’ purchase intention. Concerns that online mental health resources might be used as an alternative to traditional clinician care stem from the potential negative impact of Internet resources on the clinicians’ power. Song L, Park B, Oh K M. Analysis of the technology acceptance model in examining hospital nurses’ behavioral intentions toward the use of bar code medication administration.

Indeed, the two studies with relatively strong PEOU effects both had young, mostly non-physician samples in Taiwanese medical centers who had hands-on experience with the IT . It may also be that the measures of PEOU in the reviewed studies were not sensitive to the ease of use dimensions that are important in health care settings, something that is discussed below. A number of limitations have been discussed in TAM and its extensions over the years. The simplicity of TAM and the lack of understanding of the antecedents of technology acceptance were the subject of criticism in prior research (Venkatesh, Davis & Morris, 2007; Lee, Kozar & Larsen, 2003).

This provides an exhaustive set of conditions and scenarios under which the acceptance of technology is most likely to occur. By delineating the relationships between antecedents, perceived ease of use and perceived usefulness, TAM3 offers a comprehensive list of interventions that have direct implications for decision-making regarding IT implementation and management (Venkatesh & Bala, 2008). The explains the acceptance of information systems by individuals. TAM postulates that the acceptance of technology is predicted by the users’ behavioural intention, which is, in turn, determined by the perception of technology usefulness in performing the task and perceived ease of its use. Organizational investment in information systems is often large and risky given the variety of information requirements placed on systems today. To make more informed decisions and to meet the challenge of developing systems that satisfy these demands, system developers need to achieve a better understanding of factors that ultimately lead to system usage.

  • We partner with institutions to extend their core academic skills support online with timely, after-hours help for all their students, at scale – regardless of their background, study mode or location.
  • When an enterprise is implementing new technology as part of its ongoing digital transformation, digital tools are often imposed upon its employees.
  • The extent of the gap in ETLM adaptation and the driving factors that led to observable discrepancies between privileged and non-privileged schools, even in the urban settings of the KEZ, are also discussed in this study.
  • The factors investigated in the most commonly used technological contexts such as health information technology systems in general, telemedicine, EHR, mobile apps, HIS, E-prescription, PDAs, and personal health record are briefly provided.
  • By understanding the degree to which technology is useful and easy to operate by consumers, they can design consumer-oriented IT products .

That is, few studies have investigated why older users would perceive a particular robot as easy to use or useful. Lastly, the role of “costs” such as privacy or ethical concerns is not well understood in relation to technology acceptance. Thus, although it has been established that older adults hold positive attitudes toward robots to support aging in place, much research is technology definition still needed to better understand specific contexts of use and the factors that drive actual long-term adoption. According to TAM, technology acceptance is a three-stage process, whereby external factors trigger cognitive responses , which, in turn, form an affective response (attitude toward using technology/intention), influencing use behaviour (Davis, 1989; Davis, 1993).

A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM. Finally, it is suggested that the common technology jobs investigated factors in the previous studies , for each technological contexts and user groups, should tested empirically in real settings. If these factors confirmed, it is recommended that they will be applied as a basic model for each technological contexts and user groups. The review showed that the TAM initially was applied to task-related ICT systems such as EHRs.

Persuading users to adopt new information technologies persists as an important problem confronting those responsible for implementing new information systems. In order to better understand and manage the process of new technology adoption, several theoretical models have been proposed, of which the has gained considerable support. A parallel research stream suggests that individual difference factors are important in information technology acceptance but does not explicate the process by which acceptance is influenced.

The new system replaces the old and employees must adopt it regardless of whether they perceive it as useful or easy to use. Employees have to adopt new digital tools and technologies all the time as organizations transform and adapt to the digital world. Examples are digital communication and collaboration platforms, CRM, invoicing, and HR software.

The tradition of adding variables is common in research on TAM and on more general theories of human behavior . Theory-based additions to the prediction and explanation of health IT use and acceptance is a welcomed approach , and it appears to be the approach advocated by some researchers for furthering the use of TAM in health care . And what modifications can be proposed for the variables that are already included in TAM?


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