Considering satisfaction levels equ

Considering satisfaction levels equal to or higher than 4 in Table 2, it is identi ed that the overall satisfaction percentage shows that 50% of the respondents noticed improvements in the process a er its implementation (answers ≥ 4 in the scale that was used).
The data were analyzed with the aid of multiple lin- ear regressions for each of the studied factors, as well as for general satisfaction. The results are shown as follows.
5.1 Cost Analysis
Regression analysis for the cost sought to understand how much it was in uenced by each of its sub-fac- tors. Regarding factor and sub-factors relationships, corrective painting was not statistically signi cant. The satisfaction in relation to the cost factor was considered as the dependent variable and the rat- ings of each of the other two remaining sub-factors were treated as independent variables. Expression 1 was obtained. The value of R2 = 0.63 indicates that expression 1 is able to explain 63% of the variability in cost assessments.
Cost = 0.36 x electrical shutdowns + 0.31 x mechani- cal shutdowns (1)
The p-values found for the terms were less than 0.19. This should be considered as an exploratory result related to the signi cance of the sub-factors.
5.2 Safety in Service Analysis
Regression analysis for safety in service tried to understand how it was in uenced by each of its sub-factors. For this factor, tooling storage was not statistically signi cant. Then, the satisfaction in re- lation to the safety in service factor was considered the dependent variable and the rating of safety in handling was treated as the independent variable and the expression 2 was obtained. The value of R2 = 0.73 can state that the second expression is able to explain 73% of the variability in safety in service evaluations.
Safety in Service = 0.66 x safety in handling (2)
The p-value found for the term was less than 0.0001, which allows us to assert that it is signi cant with a probability of at least 99.9%.
5.3 Service Reliability Analysis
Regression analysis for service reliability a empted to understand how it was in uenced by each of its sub-factors. For this factor, e cient routing, opera- tor’s performance and availability did not show sig- ni cance, so the only sub-factor that was considered as an independent variable was operator’s autonomy according to expression 3, where we can see service reliability as the dependent variable. The value of R2 = 0.68 can state that expression 3 is able to explain