# Commonly Used External TAM Variables in e-Learning, Agriculture and Virtual Reality Applications
## 6 Conclusions  
The present study is developed in the context of an agricultural project in Europe. Our objective was to conduct a literature review to identify the most common external variables used in TAM applications using the QFD to give structure to the research. Our analysis focused on three sectors, namely, e-learning, agriculture, and virtual reality. We found evidence that among those three sectors, the less explored is the VR sector.  
By setting apart the variables included in the models we analyzed, we identified the most commonly used variables: anxiety, content quality, experience, facilitating conditions, individual innovativeness, perceived enjoyment, self-efficacy, system quality, and social norm. Our findings provide evidence that external variables influence in a different manner the two personal beliefs proposed by [PERSON] (2018) in the TAM. In our case study, PU's primary determinant was PEOU, followed by system and content quality and perceived enjoyment. As for PEOU, it was significantly predicted by self-efficacy, followed by perceived enjoyment, and experience.  
The seven research categories and the different impacts of external variables demonstrated the context-dependency of technology use. As an acceptance measurement tool, the TAM provides flexibility and accuracy by leaving the doors open for several extensions and applications.  
The QFD proposed in the present study seems to provide a functional framework for organizing and prioritizing the information.  
Figure 9: Proposed TAM extension for FARMER 4.0.  
Considering the knowledge gap of technology acceptance in VR innovations and task-level TAM applications, more investigations of those types should be developed. We encourage TAM researchers to provide the existence and validity of relationships along with the effect size. By knowing the variables with a more significant influence on technology acceptance, innovators' efforts will be better oriented.  
Further research is required to validate the proposed model in the context of FARMER 4.0 and make the most out of the platform. However, the ultimate benefit extracted from the e-learning tool will also depend on reducing infrastructure and resource limitations. Electricity and internet connectivity should be accessible in rural areas where our target users develop their daily activities. This is especially important as suggested by [PERSON] et al. [141] because lack of the proper electricity supply can affect the quality of life, reduce the incentives to develop agricultural activities, hamper access to education, and needless to say, will directly affect the usage of the designed tool. Education institutions can also become key players in reducing resource barriers. They can design and implement strategies aiming to increase learning courses, develop new technological capabilities, gain learning flexibility [2], and make available laboratories and technological tools to allow access to platforms such as FARMER 4.0.  
Conceptualization, L.C.C.G., I.A.C.J. and M.G.V.; data curation, L.C.C.G. and I.A.C.J.; formal analysis, L.C.C.G., I.A.C.J., and M.G.V.; funding acquisition, M.G.V.; investigation, L.C.C.G. and I.A.C.J.; methodology, M.G.V., I.A.C.J., and L.C.C.G.; supervision, M.G.V., I.A.C.J., F.M., and E.V.; visualization, M.G.V., F.M., E.V., I.A.C.J. and L.C.C.G.; writing--original draft, L.C.C.G. and I.A.C.J.; writing--review and editing, L.C.C.G., I.A.C.J., M.G.V., F.M., E.V. All authors have read and agreed to the published version of the manuscript.  
This work was supported by European Erasmus+ project \"Farmer 4.0\", project number: 2018-1-IT01-KA202-006775.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.