## 5 Analysis and Discussion of the Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Hypothesis Test Summary**} \\ \hline  & **Null Hypothesis** & **Test** & **Sig.** & **Decision** \\ \hline \multirow{3}{*}{\(1\)} & The distribution of BlockChain is & \multirow{3}{*}{\(0.023\)} & \multirow{3}{*}{\(0.053\)} & \multirow{3}{*}{\(0.016\)} \\  & the same across categories of & & & \\ \cline{1-1}  & General feeling about & & Kruskal-Wallis Test & \\ \cline{1-1}  & technological disruption. & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results of Kruskal-Wallis test. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multicolumn{1}{c}{**Sample1-Sample2**} & **Test Statistic** & **SDT. Error** & **SDT. Test Statistic** & **Sig.** & **Adj. Sig.** \\ \hline Eventually adapt-Opportunities & –15.721 & 6.236 & –2.521 & **0.012** & 0.070 \\ Eventually adapt-Treat survival & 18.000 & 9.718 & 1.852 & 0.064 & 0.384 \\ Eventually adapt-Helps conquest & –21.423 & 7.131 & –3.004 & **0.003** & 0.016 \\ Opportunities-Threat survival & 2.279 & 8.389 & 0.272 & 0.786 & 1.000 \\ Opportunities-Helps conquest & –5.702 & 5.175 & –1.102 & 0.270 & 1.000 \\ Threat\_survival-Helps\_conquest & –3.423 & 9.074 & –0.377 & 0.706 & 1.000 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of [PERSON]’s test. Regarding the most relevant results associated with question B9--Part 2 of the questionnaire--these were: 58% of respondents indicated that this question does not apply to the \"Retail\" department; the departments that have a greater degree of agility in the adaptation to technological change are \"IT\", followed by \"Marketing\". In order to summarize the information presented in question B9, we use the CATPCA with the Varimax rotation method (the one that produced a more interpretable solution) and Kaiser Normalization [50,51]. For component retention we use the rule of eigenvalue greater than 1 and percentage of explained variance higher than 70%. The internal consistency of the two components/dimensions (Table 4) was measured with [PERSON]'s Alpha [51] (0.813 and 0.743, which shows a good internal consistency). Figure 4: Position of the original departments after CATPCA, in the two retained dimensions. Figure 3: Boxplot and pairwise comparisons of _“Blockchain”_ for _“General feeling...”_ (A4). Table 5 shows that the most agile departments in their ability to adapt to technological change (departments that are strongly related related to Dimension 1) are \"Manufacturing/Logistics\", \"Customer Service\" and \"Human Resources\". Departments of \"Marketing\" and \"Sales/Business\" are very strongly associated with Dimension 2 (second major component). Additionally, despite the lower relevance, we can state that the \"Legal\" and \"IT\" departments are correlated with Dimension 1. Finally, it should be noted that the weights obtained for the \"Product management\" department in both dimensions reflect the fact that the department's ability to adapt to technological changes is explained simultaneously by both. Thus, we can conclude that Dimension 1 is the \"Product/Customer\" component and Dimension 2 is the \"Marketing/Sales\" component. Combining the analysis of Table 5 with observation of Figure 4, we can also distinguish four groups within organizations according to their adaptability (greater or less agility in adaptation) to the technological changes of the various departments of the organization: Business Group (Sales/Business and Marketing), Personal Group (Human resources and Legal department), Customer Group (Manufacturing/Logistics and Customer service) and Technological Group (IT). In order to evaluate the future of the organization in relation to DT (\"Organization future regarding Digital Transformation\"--Part 3), given the accelerated pace of technological change, we began by investigating the organization's adaptability over the next three years (Question C1).