## 4 Results and Discussion on the Survey
### Detailed Analysis of the Survey Using Chi-Square Analysis  
In this section, we report the results of the chi-square analysis conducted to verify whether there was a significant relationship between the geographical location of companies and the sustainable practices adopted. The test was performed on the questions belonging to the second section, from questions 12 to 18. Question 12. For this question the hypothesis is as follows: There is a significant relationship between the geographical location of companies and the possession of sustainability certifications and standards. The contingency and expected frequencies table (Table 17) shows the percentage of companies that have sustainability certifications based on the geographical area (northern, central, and southern Italy) and the expected values for each cell were then calculated, using these general proportions. The chi-square calculated, according to Equation (1), was 5.808. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was smaller than the chi-square critical value at 5.99. Thus, we cannot accept the hypothesis. Therefore, there is no significant relationship between the geographical location of companies (north, center, south Italy) and the possession of sustainability certifications. Question 13. For the chi-square analysis on proportions, the comparison between the proportions of companies that have adopted renewable energy, divided by geographical was considered. The hypothesis is as follows: There is a significant relationship between the geographical location of companies and the use of renewable energy. The analysis focused on the proportions of companies that use renewable energy in the different regions. Figure 11: Answers to Question 18. \begin{table}
\begin{tabular}{l l l l l} \hline \hline \multirow{2}{*}{**Location**} & **With** & **With** & **Without** & **Without** \\  & **Certifications** & **Certifications** & **Certifications** & **Certifications** \\  & & **(Expected)** & **(Expected)** & **(Expected)** \\ \hline Northern Italy & 0.70 & 0.4028 & 0.30 & 0.0972 \\ Central Italy & 0.92 & 0.2256 & 0.08 & 0.0543 \\ Southern Italy & 0.90 & 0.1772 & 0.10 & 0.0427 \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Contingency and expected frequencies table—question 12. The proportions of companies that use renewable energy are classified and the expected frequencies are then calculated and shown in Table 18.  
The chi-square calculated, according to Equation (1), was 5.67. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was smaller than the chi-square critical value at 5.99. This means that there is no significant relationship between the geographical location of companies and the use of renewable energy. Question 14. The same procedure already performed for question 13 was carried out. The hypothesis for question 14 is as follows: There is a significant relationship between the geographical location of companies and the adoption of water reuse or repurposing systems. The proportions of companies using water reuse or reuse systems are as follows:  
* Northern Italy: 18%. * Central Italy: 13%. * Southern Italy: 0%. The proportions of companies that use water reuse systems and the expected frequencies are shown in Table 19.  
The chi-square calculated was 6.226. The hypothesis was tested at 5% level of significance. In this hypothesis, the chi-square calculated was greater than the chi-square critical value at 5.99. Thus, we cannot accept the hypothesis. This implies that there is a significant relationship between the geographical location of companies and the adoption of water reuse or repurposing systems. Question 15. To analyze the relationship between the geographical location of textile companies and sustainable practices to manage and reduce waste during the processing of textile fibers (such as minimization, recycling, use, composting, and disposal), we can apply the chi-square test.