Explain how cybersecurity researchers could use the TAM model to explore the factors which affect employee acceptance of biometrics used for access to facilities and computing systems
The technology acceptance model (TAM) is an information systems theory that models how users accept and use technology. Understanding and studying the technology acceptance model may be quite effective and useful in the long run. First, it can lead to better analysis and forecasting of new information resources. Secondly, if users have a certain level of confidence, they will be able to increase the level of personal control over the information.
In this context, many organizations are implementing and using various new technologies to improve their cybersecurity. However, the staff must have certain qualifications and knowledge in order to apply these technologies most effectively (Davis, 1989). Biometric technologies are based on measuring the unique characteristics of an individual. In other words, this type of technology is inextricably linked to the person himself. For this reason, high-quality training of personnel becomes critical for companies and organizations (Ajibade, 2018). Thus, when implementing a new technology, all the company’s personnel must undergo retraining in order to start using this technology effectively.
Many employees may be critical of new technologies due to the fact that over many years of practice they have managed to get used to traditional technologies for them. In this context, the implementation of TAM in the company is critical for the effective functioning of the organization (Portz et al., 2019). TAM aims to help staff adopt and use new technologies in the most effective way. A person’s perception of ease of use is thought to play a key role in their acceptance of the new technology (Portz et al., 2019). Thus, one of the goals of TAM is to explain to students the principle of how technologies work as simply as possible.
Moreover, another goal of TAM is to provide tracking of the influence of external factors on receptivity and intentions. In this sense, the introduction of TAM is also positive for companies that want to successfully apply the latest technologies.
What research questions might they ask?
It becomes possible to identify several questions that researchers may have about this topic. First, how does TAM implementation help increase the adoption of new technologies by staff? In this context, it is important to note that at the moment companies are increasingly exposed to the influence of advanced technologies (Mlekus et al., 2020). Biometric technologies are increasingly found in the work of many companies and organizations.
For this reason, TAM must ensure that staff adopt and approve this advanced technology to result in efficiency and success. The second question is the very usefulness of the new technology for the staff. Some studies show that TAM directly affects the level of satisfaction that advanced technology will cause (Hornbæk et al., 2017). In this context, the introduction of TAM leads to the fact that satisfaction directly affects the usefulness of the technology.
What measurements would be needed?
The measurement needed to identify the impact of TAM on the receptivity of new technologies by employees is a variable. In this sense, a variable is any external factor that somehow affects the perceived utility of using a technology (Hornbæk et al., 2017). Thus, the external variable should be measured by a number of factors that have an effect on both the technology itself and the staff. As a result, it becomes possible to identify the extent to which various external factors will lead to the effective use of new technologies.
References
Ajibade, P. (2018). Technology acceptance model limitations and criticisms: Exploring the practical applications and use in technology-related studies, mixed-method, and qualitative researches. Library Philosophy & Practice, 1941.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. Web.
Hornbæk, K., & Hertzum, M. (2017). Technology acceptance and user experience: A review of the experiential component in HCI. ACM Transactions on Computer-Human Interaction (TOCHI), 24(5), 1-30. Web.
Mlekus, L., Bentler, D., Paruzel, A., Kato-Beiderwieden, A. L., & Maier, G. W. (2020). How to raise technology acceptance: user experience characteristics as technology-inherent determinants. Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO), 51(3), 273-283.
Portz, J. D., Bayliss, E. A., Bull, S., Boxer, R. S., Bekelman, D. B., Gleason, K., & Czaja, S. (2019). Using the technology acceptance model to explore user experience, intent to use, and use behavior of a patient portal among older adults with multiple chronic conditions: descriptive qualitative study. Journal of medical Internet research, 21(4), e11604.