# Project Management Information Systems (PMISs):
## 4 Results and Discussion
### First Survey  
The first survey was administered to 75 professionals, and a total number of 67 responses was received. As reported in Section 3.2.1, the number of clusters was identified by cutting the dendrogram obtained for every feature/sub-feature at a particular level of similarity. As an example, the dendrogram of \"Resource Planning\" obtained by Minitab(r) is shown in Figure 4. Four clusters were chosen, where the cutting level is the one represented by the orange dashed line and the four clusters are differently colored. Figure 3: Hierarchical structure. Figure 2: Prototype example. Table 2 shows the number of obtained clusters and the number of respondents per cluster. The relative importance of every feature--total and _per_ cluster--are shown in Table 3.  
On the basis of the last column of Table 3, \"Activity Planning\" and \"Access Permits\" were found to have the highest and lowest importance, respectively. On the other hand, different opinions were observed when comparing feature weights related to every cluster. Therefore, the interactions between respondents' profiles (see Appendix B) and PMIS functionality weights were verified using the \(\chi^{2}\) metric. In particular, taking into account all 67 responses, the distribution of respondents in clusters 3 and 4 was observed to be significantly different from the others in respect to the software usage and best software (Figure 5a,b). It means that a lot of respondents that do not use software or for which the best software does not exist are present in these clusters. Figure 5c shows that the frequency \begin{table}
\begin{tabular}{l l} \hline \hline
**Feature/Sub-Feature** & **Number of Respondents per Cluster** \\ \hline Features level & Cluster 1 = 37; Cluster 2 = 21; Cluster 3 = 5; Cluster 4 = 4 \\ \hline Activity Planning sub-feature & Cluster 1 = 17; Cluster 2 = 17; Cluster 3 = 16; Cluster 4 = 17 \\ \hline Resource Planning sub-feature & Cluster 1 = 31; Cluster 2 = 15; Cluster 3 = 12; Cluster 4 = 9 \\ \hline Control sub-feature & Cluster 1 = 48; Cluster 2 = 19 \\ \hline Risk Management sub-feature & Cluster 1 = 27; Cluster 2 = 33; Cluster 3 = 7 \\ \hline Reporting sub-feature & Cluster 1 = 24; Cluster 2 = 36; Cluster 3 = 18 \\ \hline Communication Management sub-feature & Cluster 1 = 37; Cluster 2 = 12; Cluster 3 = 18 \\ \hline Utility sub-feature & Cluster 1 = 46; Cluster 2 = 13; Cluster 3 = 8 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Obtained clusters and respondents. Figure 4: Dendrogram related to “Resource Planning”. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Feature** & **Cluster 1** & **Cluster 2** & **Cluster 3** & **Cluster 4** & **TOT** \\ \hline Activity Planning & 0.229 & 0.189 & 0.235 & 0.141 & 0.221 \\ \hline Resource Planning & 0.171 & 0.163 & 0.206 & 0.051 & 0.167 \\ \hline Control & 0.171 & 0.135 & 0.059 & 0.115 & 0.167 \\ \hline Risk Analysis & 0.143 & 0.135 & 0.088 & 0.090 & 0.139 \\ \hline Reporting & 0.114 & 0.108 & 0.118 & 0.116 & 0.111 \\ \hline Communication Management & 0.086 & 0.189 & 0.088 & 0.167 & 0.111 \\ \hline Utility & 0.057 & 0.054 & 0.029 & 0.141 & 0.056 \\ \hline Access Permits & 0.029 & 0.027 & 0.177 & 0.179 & 0.028 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Total features weights and per cluster. of foreign respondents in clusters 3 and 4 is switched. In detail, cluster 3 was characterized by a higher presence of foreign respondents in proportion to the total. Weights obtained for \"Activity Planning\", \"Resource Planning\", \"Control\", \"Risk Analysis\", \"Reporting\", \"Communication Management\" and \"Utility\" are reported in Table 4.  
Considering the \(\chi^{2}\) metric for the sub-features of \"Activity Planning\", \"Resource Planning\", \"Control\", \"Reporting\", \"Communication Management\" and \"Utility\", no significant interactions between weights and clusters were observed. As a consequence, the corresponding histograms are not reported.