A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps

Abstract

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.