## 3 Results
The models are both statistically significant (Table 10) but explain a small percentage of the total variance of the dependent variable (<30%). According to the results of the regression models for each company (Table 11), the standard coefficient indicates a common predictor for both companies, the type of process proposed for change (\(p<0.05\)) but also different predictors as shown: (a) for Company A, the number of days from planning to effective implementation of change requests (\(p=0.000\)) and (b) for Company B, the number of days from creation to planning of change requests (\(p=0.001\)). \begin{table}
\begin{tabular}{l c c c c c c} \hline  & & **Sum of** & **df** & **Mean** & **F** & **Sig.** \\ \hline \multirow{3}{*}{The number of days from creation to planning of change request} & Between groups & 112.283 & 1 & 112.283 & 31.493 & 0.000 \\  & Within groups & 759.410 & 213 & 3.565 & & \\  & Total & 871.693 & 214 & & & \\ \hline \multirow{3}{*}{The number of days from planning to effective implementation of change request} & Between groups & 7.720 & 1 & 7.720 & 1.338 & 0.249 \\  & Within groups & 1229.210 & 213 & 5.771 & & \\ \cline{1-1} \cline{2-6}  & Total & 1236.930 & 214 & & & \\ \hline \end{tabular}
\end{table} 
Table 9: Results of the ANOVA test by comparing company A, according to customer involvement in change requests. Figure 9: Results for the effective implementation month of change requests. Based on the results from Table 10, respectively, the values of the standardized beta coefficients and the number of days between the three phases of a change request are the most important predictors followed by the type of process proposed for change. By interpreting the values of unstandardized regression coefficients from Table 11, we can conclude the following:  
* For company A: (1) Increasing the type of process proposed for change by one unit (from 1 (engineering change) to 2 (corrections)), the status of the change request increases 5.880 units, practically approaching the final status, \"closed\"; (2) increasing the number of days from planning to effective implementation of a change request by one unit (practically the interval of these days, from \(<\)10 days to more than 300 days), the status of the change request increases 2.776 units, practically approaching the final status, \"closed\";
* For company B: (1) Increasing the type of process proposed for change by one unit (from 1 (engineering change) to 2 (corrections)), the status of change request increases 1.139 units, practically approaching the final status, \"closed\"; (2) increasing the number of days from planning to effective implementation of a change request by one unit (practically the interval of these days, from \(<\)10 days to more than 300 days), the change request status decreases 0.940 units. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**ANOVA a**} \\ \hline
**Company** & **Model** & **Sum of Squares** & **df** & **Mean Square** & **F** & **Sig.** \\ \hline \multirow{3}{*}{Company A} & \multirow{3}{*}{\(1\)} & Regression & 11,119.494 & 6 & 1853.249 & 19.031 & 0.000 b  \\  & & Residual & 20,254.878 & 208 & 97.379 & & \\  & & Total & 31,374.372 & 214 & & & \\ \hline \multirow{3}{*}{Company B} & \multirow{3}{*}{\(2\)} & Regression & 1084.293 & 6 & 180.715 & 6.496 & 0.000 c  \\  & & Residual & 20,114.919 & 723 & 27.821 & & \\ \hline \multicolumn{6}{c}{\({}^{\text{a}}\) Dependent variable: Change request status. b,c Predictors: (Constant), number of days from planning to effective implementation of change requests, number of days from creation to planning of change requests, effective implementation month of change requests, the month of proposal/ initiation of change requests, the planned month for implementation of change requests, type of process proposed for change.} \\ \end{tabular}
\end{table} 
Table 10: Results of the ANOVA test for the regression models.