# Project Management Information Systems (PMISs):
## 4 Results and Discussion
### Second Survey  
The second survey was administered to 15 experts to rank the 16 prototypes reported in Appendix B. Twelve responses were received for a total number of 192 evaluations. As detailed in Section 3.2.2, a regression model was performed. After using a stepwise regression to select the significant factors (i.e., features) with respect to their contribution to the total variability of responses, only significant terms of the regression model are reported in Table 6. The stepwise procedure highlighted the significance of all main factors, while the interactions between them were eliminated. In addition, the significance of some interactions between features and respondents was demonstrated.  
\begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Source** & **DF** & **AdjSS** & **AdjMS** & **F-Value** & \(p\)**-Value** \\ \hline Regression & 63 & 478.624 & 7.5972 & 10.60 & 0.000 \\ \hline Activity Planning & 1 & 2.250 & 2.2500 & 3.14 & 0.079 \\ \hline Resource Planning & 1 & 6.250 & 6.2500 & 8.72 & 0.004 \\ \hline Control & 1 & 12.250 & 12.2500 & 17.09 & 0.000 \\ \hline Risk Analysis & 1 & 71.908 & 71.9076 & 100.32 & 0.000 \\ \hline Reporting & 1 & 5.501 & 5.5013 & 7.67 & 0.006 \\ \hline Communication Management & 1 & 6250 & 6.2500 & 8.72 & 0.004 \\ \hline Utility & 1 & 5.168 & 5.1680 & 7.21 & 0.008 \\ \hline Access Permits & 1 & 3.939 & 3.9388 & 5.50 & 0.021 \\ \hline Interviewed & 11 & 32.715 & 2.9741 & 4.15 & 0.000 \\ \hline Activity Planning Interviewed & 11 & 17.514 & 1.5922 & 2.22 & 0.017 \\ \hline Resource Planning Interviewed & 11 & 15.077 & 1.3706 & 1.91 & 0.043 \\ \hline Control Interviewed & 11 & 18.764 & 1.7058 & 2.38 & 0.010 \\ \hline Communication Management & 11 & 14.566 & 1.3242 & 1.85 & 0.053 \\ Interviewed & & & & & \\ \hline Error & 128 & 91.750 & 0.7168 & & \\ \hline Total & 191 & 570.374 & & & \\ \hline \multirow{2}{*}{Model Summary} & S & R2 & R2 adj & & \\ \cline{2-5}  & 0.846639 & 83.91\% & 76\% & & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Regression model.  
Figure 6: Histograms related to “Risk Analysis” sub-features.  
The residual analysis (Figure 7)--performed on 192 ratings--confirmed the acceptability of the assumption of normality, which the regression model was based on. The goodness of fit was quite high (R2 = 83.91%; R2 adj = 76%).  
Figure 8 only shows those scenarios where significant interactions between features and the interviewed were observed. For instance, respondents 4 and 12 gave higher ratings to prototypes when \"Activity Planning\" was included. In detail, respondents 4 and 12 are both male, use PMISs software and they do not have any certification. With relation to \"Control\", respondent 5 gave an opposite rating in comparison with the others, providing a high increase with relation to \"Resource Planning\". Respondent 5 works in an IT company, uses software and he/she is trained in project management. On \"Communication Management\", respondents 6 and 12--having more than 10,000 h of project management experience--provided an opposite rating in respect to the other respondents.  
Figure 8: Interactions’ plots between features and respondents.  
Figure 7: Residual analysis.  
As suggested by [PERSON] et al. (2017, 2018), the normalized weights of features (Table 7) were calculated from the previously estimated regression model coefficients.  
The input factors being characterized by the same dispersion (for every column of Table 1, eight +1 and eight-1), the regression coefficients can be combined directly, that is, without any standardization. Therefore, weights were calculated by normalizing them to one.  
Differently to the first survey, the second one returned the highest importance of \"Control\", while \"Activity Planning\" took the fifth position. Both methods assigned low weights to \"Utility\" and \"Access Permits\", even if \"Reporting\" also had a low weight in this second analysis.