# The Impact of the 4.0 Paradigm in the Italian Agricultural Sector: A Descriptive Survey
## 4 Results
### RQ2: What Is the Level of Adoption of Agri 4.0 Solutions? For each Agri 4.0 solution, the respondents were asked to specify whether they used the solution or not, allowing for the identification of adopters and nonusers. Comparing the level of awareness versus the level of adoption, as expected, the rate of awareness increases for those using Agri 4.0 solutions compared with those who do not utilize any of the solutions. Figure 6 links the first two research questions, highlighting higher awareness of different Agri 4.0 solutions among the respondents who used at least one solution compared with those who did not use any. Figure 4: Boxplot graph of awareness level depending on the size of the company (land size). Figure 5: Boxplot graph of awareness level depending on company size (revenues). The level of adoption can also be analyzed by comparing it against some control variables relative to the surveyed sample. First, it was examined whether there was a link between the size of companies and rate of utilization of technological solutions. To assess whether the data and analyses had statistical significance or not, a chi-square test was performed, here measuring the \(p\)-value. Typically, its value is a very small number, close to zero. Here, the \(p\)-value is the assigned level of significance (i.e., a measure of evidence against the null hypothesis) and, to be statistically significant, this value must be less than 0.05. A significant association was found between revenue size cluster and utilization level of Agri 4.0 solutions (Table 9), in which the Pearson's \(\chi^{2}\) test \(p\)-value was very low (3.48 \(\times\) 10\({}^{-19}\), ensuring the significance of the analysis. The growing trend in the level of adoption depends on the size (in terms of turnover) of the companies. This trend is further confirmed by the boxplot presented in Figure 7. To calculate the levels of adoption in the boxplot graphs, the sum of the usage responses for each respondent for the various solutions was analyzed and then divided by the total number of proposed solutions. \begin{table}
\begin{tabular}{l l l l} \hline \hline  & **Agri 4.0 Solution Adoption Level** &
\begin{tabular}{l} **At Least One** \\ **Solution Adopted** \\ \end{tabular} & **No Solutions Adopted** \\ \hline Revenue Cluster & A. \textless{}EUR 30,000 & 47 & 100 \\  & B. between EUR 30,000 and & 98 & 96 \\  & C. between EUR 100,000 and & 97 & 36 \\  & 250,000 & & \\  & D. between EUR 250,000 and & 63 & 21 \\  & 500,000 & 91 & 21 \\ \hline Pearson’s \(\chi^{2}\) test: \(p\)-value = 3.48 \(\times\) 10\({}^{-19}\) (significant). & & \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Pearson’s \(\chi^{2}\) test for adoption level and revenue clusters. Figure 6: Boxplot graph of awareness level and utilization of 4.0 solutions. The association is clear in Figure 7, in which, from the lowest to the highest revenue class, all significant adoption-level metrics increase. The sample presents an average of 5% from the smallest class of revenue to an average of 27%, also taking into consideration the fact that the sample shows a maximum percentage of adoption level that goes from 14% to 71% for the most significant turnover class. The analysis represented in Figure 7 indicates that companies with higher turnover not only have more knowledge of the available solutions, but also a higher degree of use, perhaps because of the greater capacity to spend resources on these solutions. The trend shown above is also confirmed when using the size of the cultivated area as a proxy for farm size. This can be prooved by the strong association between these two variables (utilization rate-size in hectares) with a Pearson's \(\chi^{2}\) test \(p\)-value equal to \(4.618\times 10^{-15}\) (significant). Table 10 shows the increase of utilizers as the farm's size increases. At the same time, the number of farms not using 4.0 solutions drops, resulting in a strong relationship between these two variables.