## 3 Method
### Hypothesis  
In line with the findings of [PERSON] et al. (2018), we stated the hypothesis listed in Table 2. We expected farmers perceptions about the Ease of Use (PEOU) and the quality of the content (CQ) to have a strong positive influence on the Perceived Usefulness (PU) of the e-learning tool FARMER 4.0 (H10; H1a). The constructs experience (EXP), facilitating conditions (FC), individual innovativeness (II), perceived enjoyment (PE), self  
\begin{table}
\begin{tabular}{p{113.8 pt} p{284.5 pt}} \hline \hline
**Variable** & **Definition** \\ \hline Anxiety (ANX) & Negative and stressful feelings that users might experience when using the technology ([PERSON] et al., 2017; [PERSON] et al., 2018). \\ \hline Content quality (CQ) & Pertinence of the information offered by the system concerning user needs ([PERSON] et al., 2017); organization, relevance, and actuality ([PERSON] et al., 2017); and comprehensibility of the language used ([PERSON] et al., 2017). \\ \hline Experience (EXP) & Previous interactions with similar systems and the accumulated knowledge ([PERSON] et al., 2017; [PERSON] et al., 2018; [PERSON] et al., 2018). \\ \hline Facilitating conditions (FC) & Technical assistance and available resources and infrastructure that facilitate the use of technology ([PERSON] et al., 2017). \\ \hline Individual innovativeness (II) & Personal inclination towards early adoption of technology ([PERSON] et al., 2017; [PERSON] et al., 2018). \\ \hline Perceived enjoyment (PE) & Degree to which the use of the system is entertaining and pleasant independently of any other consequence derived from the usage ([PERSON] et al., 2017; [PERSON] et al., 2018; [PERSON] et al., 2018). \\ \hline Self-efficacy (SE) & User’s confidence that he/she has the knowledge and skills needed to accomplish a task using the technology and overcome any potential difficulties ([PERSON] et al., 2017; [PERSON] et al., 2018; [PERSON] et al., 2018). \\ \hline Social norm (SN) & The extent to which significant others may encourage or deter the use of technology ([PERSON] et al., 2017; [PERSON] et al., 2018; [PERSON] et al., 2018). \\ \hline \hline \end{tabular}
\end{table}
Table 1: Definitions of the external variables included in the TAM extension.  
Figure 4: Technology Acceptance Model extension to validate.  
efficacy (SE), and social norm (SN) were expected to have a medium positive impact on PU (H2a; H3a; H4a; H5a; H6a; H7a). A low negative influence of Anxiety (ANX) on PU was also predicted (H8a). Furthermore, the external variables with strong positive impact on Perceived Ease of Use were expected to be content quality (CQ), experience (EXP), perceived enjoyment (PE), and self-efficacy (SE) (H1b; H2b; H5b; H6b). PEOU was also expected to be moderately influenced by facilitating conditions (FC), social norm (SN), and anxiety (ANX) (H3b; H7b; H8b) and only slightly influenced by individual innovativeness (II) (H4b). Additional hypothesis were included to test the predictive power of PU and PEOU on the attitude towards use (ATT) ((H9a; H9b) and to measure the influence of ATT on the ultimate behavioral intention of farmers to use the FARMER 4.0 e-learning tool (H11). The strength of the relationships will be validated on the basis of path coefficients according to the criteria established by [PERSON] (2018). Path coefficients reporting values below or equal to 0.10 denote a low influence. External variables reporting path coefficients ranging from 0.1 to 0.30 included will be considered as having a moderate predictive power. Finally, higher path coefficients entail a strong causal relationship.