# Establishing a Model for the User Acceptance of Cybersecurity Training
## 2 Components and Evolution of the TAM and Its Extensions  
The core components of the TAM provide a foundational framework that helps understand how users accept a technology. The model explains that the user adoption of technology is influenced by Behavioural Intention (BI), which is influenced by PU and PEOU. PEOU also has in influence on PU. PU, PEOU, and BI, as well as the relationships between those, are mediated by external factors, which are the focus of this research. The external factors outlined by [3; 4] and what the TAM constructs or the relationships it mediates are reflected in Figure 1 below. Factors that mediate the same constructs or relationships are grouped together to increase readability. The TAM has undergone a number of changes over the past few decades. For instance, ref. [3] proposed an update known as TAM2, in which they provided more detailed explanations of why technology users can find a given system useful. This update entailed the notion that users' perceptions of the usefulness of a given system are influenced by their mental assessment of how well the system corresponds to essential goals within the workplace [3]. The study results showed that TAM2 performed well both in voluntary and mandatory settings. Later, ref. [2] reviewed the TAM's evolution over time by assessing its impact and relevance in various contexts. The review is segmented into past, present, and future. The past section traces the origins and early developments of the TAM by highlighting how it emerged as a basic model for understanding the user acceptance of technology using the initial constructs, namely PU and PEOU. The present section of the study discusses the numerous extensions and adaptations that have been proposed to enhance the TAM's explanation and applicability. These extensions often integrate additional factors, including facilitating conditions and social influence, reflecting the dynamic of technology acceptance. The authors also evaluated the TAM's performance across different user demographics and technological contexts. In the future section, ref. [2] suggested potential directions for future research, including exploring emerging technologies and considering novel theoretical constructs. In a subsequent development, ref. [3] presented an advanced version, TAM3, and proposed a research agenda focused on interventions to enhance technology acceptance. This was designed to address some of the limitations by incorporating an extensive set of factors influencing technology acceptance. This model integrates elements from TAM2 and the Unified Theory of Acceptance and Use of Technology (UTAUT), along with new constructs. Key additions include the influence of individual differences (e.g., perceptions of external control and computer self-efficacy), system characteristics (e.g., perceived enjoyment and objective usability), and contextual factors (e.g., experience and voluntariness). The external factors presented in the TAM are described in Table 1.  
Figure 1: Technology Acceptance Model (TAM) and its external factors. Based on refs. [2; 3]. The TAM and its extensions have been extensively employed to understand the user acceptance of technologies in a variety of contexts, demonstrating its adaptability and robustness in explaining technology adoption. Based on studies [2; 3; 4], the TAM has been found to be effective at predicting acceptance and usage behaviour. However, the TAM and its extended models have not been thoroughly explored in the context of cybersecurity training acceptance in spite of their widespread application. It is essential to recognise that cybersecurity involves unique challenges and user interaction paradigms fundamentally different from those associated with traditional technology use. As an example, user compliance with security measures may be driven by a variety of factors, including fear of breaches or potential legal implications, which are not considered primarily in the TAM.