# The Impact of the 4.0 Paradigm in the Italian Agricultural Sector: A Descriptive Survey
## 3 Methodology
### Variable Definition and Measure  
Table 7 shows the variables used in the survey. The variable \"Agri 4.0 solutions knowledge level\" evaluates the degree of knowledge of the various solutions proposed. Four options are considered: \"I have never used this solution, and I am not familiar with it,\" \"I have never used this solution, but I know it,\" \"I do not currently use this solution but have used it in the past,\" and \"I currently use this solution.\" A variable implicitly connected to the one just described is \"Agri 4.0 solutions adoption,\" in which the answer \"I currently use this solution\" was used to represent the results.  
To identify the enabling solutions, benefits, and obstacles related to the Agri 4.0 paradigm, no systematic analysis was carried out, but a narrative literature review was conducted. This type of analysis, which is widely used in studies related to the medical sci  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Prevalent Cultivation** & \multicolumn{2}{l}{**Sample Pareto Distribution (\%)**} \\ \hline (a) & Cereals & 37.4 \\ (b) & Vineyards & 19.7 \\ (c) & Forage & 8.2 \\ (d) & Olive groves & 7.9 \\ (e) & Vegetables & 5.5 \\ (f) & Pome fruit trees & 4.7 \\ (g) & Stone fruit orchards & 4.6 \\ (h) & Industrial crops & 3.3 \\ (i) & Leguminous & 2.1 \\ (j) & Flowers and ornamental plants & 1.6 \\ (k) & Nursery tree & 1.6 \\ (l) & Other arboreturns & 1.4 \\ (m) & Potatoes & 1.3 \\ (n) & Citrus groves & 0.5 \\ (o) & Other & 0.3 \\ \hline Total & 100 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Pareto distribution of prevalent cultivation.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Variable** & **Type** & **Nr. of Levels/Clusters** & **Levels** \\ \hline \multirow{3}{*}{Company size (revenues)} & \multirow{3}{*}{Ordinal} & \multirow{3}{*}{5} & A. Less than EUR 30,000; B. between EUR 30,000 and \\  & & & 100,000; C. between EUR 100,000 and 250,000; D. between EUR 250,000 and 500,000; E. over EUR 500,000 \\ \hline \multirow{3}{*}{Company size (land)} & \multirow{3}{*}{Ordinal} & \multirow{3}{*}{5} & A. Lower than 10 hectares; B. Between 10 and 20 hectares; C. Between 20 and 50 hectares; D. Over \\  & & & 50 hectares \\ \hline \multirow{3}{*}{Agri 4.0 solutions knowledge level} & \multirow{3}{*}{Ordinal} & \multirow{3}{*}{4} & I am not familiar with the solution; I am a little familiar with the solution at a theoretical level; I am familiar with the solution at a practical level \\ \cline{1-1} \cline{3-3}  & & & 10 use the solution; I do not use the solution \\ \hline \multicolumn{3}{l}{Benefits} & \multirow{3}{*}{Ordinal} & \multirow{3}{*}{5} & Null; Low; Middle; High; Very High \\ \cline{1-1} \cline{3-3}  
ences [45], does not involve following a strict protocol or specific standards but still allows for the identification of the main studies describing a problem of interest [46]. Concerning the identification of the articles to be analyzed, the Scopus and Web of Science databases were surveyed using strings formulated from the keywords related to agriculture and digitalization (\"Smart Agrifood,\" \"Smart Agriculture,\" \"Smart Farming,\" \"Agrifood 4.0,\" \"Agriculture 4.0,\" \"Farming 4.0,\" \"Internet of Farming,\" \"Digital Agrifood,\" \"Digital Agriculture,\" \"Digital Farming,\" \"Precision Agriculture,\" and \"Precision Farming\"). The set of enabling solutions, benefits, and obstacles have already been presented in Section 2.