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A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps
Open accessAbstract
Over the past three decades, the Technology Acceptance model (TAM) has garnered considerable attention in higher education. COVID-19 boosted the development of TAM as multiple studies were rapidly undertaken during the pandemic. This, however, created a gap in our current understanding of the directions and trends of TAM advancement. The purpose of this study is to obtain insight into the advancement of TAM throughout the pandemic. It would assist researchers in comprehending the advancement and direction of TAM studies in higher education, such as gaining an understanding of the prevalent external variables for TAM, the statistical analysis employed, research methodologies, the technologies studied, and the geographic location of the research conducted. Finally, research gaps and future directions for TAM studies are presented. A systematic review utilizing PRISMA was conducted on 104 sampled publications. It was found that self-efficacy, subjective norms, experience, and enjoyment were the external variables most frequently used in TAM, while internal motivation received minimal attention. The existing studies have focused mainly on student samples, so further investigation is needed into lecturers, higher education personnel, and mixed groups. Further study is also required on qualitative and mixed methods, with the partial least square structural equation model currently dominating statistical analysis. Future technologies such as 5G, AI, cloud computing, augmented reality, virtual reality, and BYOD represent new TAM-related research gaps. The majority of studies have been undertaken in Asian countries, such as China and those in southeast Asia. This new systematic literature review provides insight into the trend of TAM advancement in the sustainability of higher education during the pandemic, the identified research gaps, and recommendations for future research directions. These findings also serve as a reference for future research by enhancing the foundation established by previous reviews and research on TAM, thereby facilitating the model’s ongoing expansion.
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“A recent systematic review by Rosli et al. [30] on the advancements in and adaptations of TAM in the context of higher education highlighted that despite the robust framework of TAM, there are emerging gaps, particularly in understanding how these constructs interact with newer technologies, such as the GenAI in this study.”
From Modeling teachers’ acceptance of generative artificial intelligence use in higher education: the role of AI literacy, intelligent TPACK, and perceived trust (2024) · cites this paper as [30]
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Cao, J., Yang, T., Lai, I. K.-W., & Wu, J. (2023) · International Journal of Electrical Engineering & Education · doi:10.1177/00207209211003270 · Cited by 28
RetractedThe PRISMA 2020 statement: An updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n71 · Cited by 108,283
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.191 · Cited by 43,925
When to Use and How to Report the Results of PLS-SEM
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019) · European Business Review · doi:10.1108/ebr-11-2018-0203 · Cited by 27,541
Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions
Ryan, R. M., & Deci, E. L. (2000) · Contemporary Educational Psychology · doi:10.1006/ceps.1999.1020 · Cited by 18,666 · cited 1×
“Enjoyment has been added to TAM to supplement the lack of intrinsic drive in the original form, which led to criticism [67].”
BackgroundVenkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · Systematic Reviews · doi:10.1186/s13643-021-01626-4 · Cited by 13,874
Technology Acceptance Model 3 and a Research Agenda on Interventions
Venkatesh, V., & Bala, H. (2008) · Decision Sciences · doi:10.1111/j.1540-5915.2008.00192.x · Cited by 8,159 · cited 1×
“When analyzing the development of TAM3 in situations unrelated to pandemics, it is possible that experience would become the most important factor [66].”
Background
Research works printed but not linked: 11
- Hwang, 2016, A review of diffusion for the smart devices based on technology acceptance model, ICIC Express Lett., 7, 11
- Fishbein, M., and Ajzen, I. (2009). Predicting and Changing Behavior: The Reasoned Action Approach, Psychology Press.
- Kamri, K.A., Isa, K., Yahya, A., Ahmad, A.R., and Md Yusoff, R. (2016, January 9–10). Factors influencing alumni donations at Malaysian public universities. Proceedings of the 28th International Business Information Management Association Conference—Vision 2020: Innovation Management, Development Sustainability, and Competitive Economic Growth, Seville, Spain. Available online: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013948484&partnerID=40&md5=bfc11d749aade77d33ae541dce29ab0c.
- Azhar, 2022, Factors affecting the effectiveness of on-line learning in higher education, World Trans. Eng. Technol. Educ., 20, 60
- Lebbe, 2021, M-Learning Systems Usage: A Perspective from Students of Higher Educational Institutions in Sri Lanka, J. Asian Financ., 8, 637
- Akram, 2021, The challenges of online teaching in COVID-19 pandemic: A case study of public universities iN, J. Inf. Technol. Educ. Res., 20, 263
- Masilo, 2021, Students’ behavioural intention and challenges to bring your own device (BYOD) in higher education during COVID-19 and beyond, World Trans. Eng. Technol. Educ., 19, 10
- Mukminin, 2022, Analyzing social media use in tefl via the technology acceptance model in indonesian higher education during the COVID-19 pandemic, Teach. English with Technol., 22, 3
- 2021, Investigating University Students’ Acceptance of Blended Learning during COVID-19 Pandemic, Int. Trans. J. Eng., 12, 1
- Shahin, 2022, Al Learning technologies among academics in the United Arab Emirates: One academic year since COVID-19, Int. J. Inf. Educ. Technol., 12, 141
- Ariza, 2022, RaspyLab: A Low-Cost Remote Laboratory to Learn Programming and Physical Computing Through Python and Raspberry Pi, IEEE Rev. Iberoam. Tecnol. del Aprendiz., 17, 140
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Sorted by citations
Al-Abdullatif, A. M. (2024) · Education Sciences · doi:10.3390/educsci14111209 · Cited by 169
Witkowski, K. G. K., Okhai, R., & Neely, S. R. (2024) · BMC Medical Ethics · doi:10.1186/s12910-024-01066-4 · Cited by 174
The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping
Bunea, O.-I., Corboș, R.-A., Mișu, S. I., Triculescu, M., & Trifu, A. (2024) · Journal of theoretical and applied electronic commerce research · doi:10.3390/jtaer19040125 · Cited by 66
Ursavaş, Ö. F., Yalçın, Y., İslamoğlu, H., Bakır-Yalçın, E., & Cukurova, M. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00535-z · Cited by 69
Rosli, M. S., Saleh, N. S., Ali, A. M., & Bakar, S. A. (2023) · Sustainability · doi:10.3390/su15075752 · Cited by 98
Self-citation
Metadata
- Authors
- Rosli, M. S., Saleh, N. S., Md. Ali, A., Abu Bakar, S., & Mohd Tahir, L.
- Affiliations
- University of Technology Malaysia (MY)
- Tun Hussein Onn University of Malaysia (MY)
- School of Human Resource Development and Psychology, Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
- School of Education, Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
- Corresponding author
- Rosli, Mohd Shafie
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2022-09-10
- Volume
- 14
- Issue
- 18
- Pages
- 11389
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W4295408927
- Cited by
- 126
- References
- 168
- Citations by year
- 2026: 42 · 2025: 32 · 2024: 34 · 2023: 14 · 2022: 4
- FWCI
- 3.37
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Ministry of Higher Education and Universiti Teknologi Malaysia (Q.J130000.2553.21H23)
- Universiti Teknologi Malaysia (Q.J130000.2553.21H23)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Educational Innovations and Technology
- Social Sciences › Education › Education during COVID-19 pandemic
- Keywords
- technology acceptance model, higher education, COVID-19 pandemic, sustainability of higher education, research trends, research gaps, self-efficacy, subjective norms, technology adoption, student technology use, 5G, artificial intelligence in education, cloud computing, augmented reality, virtual reality, Bring Your Own Device, university employees
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