# How the Pandemic Changes the Factors Influencing Aircraft Utilization: The Case of Korea
## 4 Results
### Random Forest Analysis  
#### 4.3.1 Total (FSC + LCC)  
According to the findings of the Random Forest analysis of the ratio of the number of seats supplied for international routes for the Total, the consumer price index, exchange rate (KRW/RMB) and lagging index were ranked highly in such order pre-Pandemic. And the exchange rate (KRW/EUR), KOSDAQ index and exchange rate (KRW/100 JYP) were ranked highly **in such order** during the Pandemic. Also, the lagging index, leading index and coincident index were important in such order post-Pandemic.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Classification**} & \multicolumn{2}{c}{**Pre-Pandemic**} & \multicolumn{2}{c}{**During the Pandemic**} & \multicolumn{2}{c}{**Post-Pandemic**} \\ \cline{2-7}  & \begin{tabular}{c} **Feature** \\ **Importance Vals** \\ **(Percentage)** \\ \end{tabular} & **Rank** & \
\begin{tabular}{c} **Feature** \\ **Importance Vals** \\ **(Percentage)** \\ \end{tabular} & **Rank** &
\begin{tabular}{c} **Feature** \\ **Importance Vals** \\ **(Percentage)** \\ \end{tabular} & **Rank** \\ \hline Price\_Index & 6.70\% & 7 & 19.52\% & 3 & 19.19\% & 3 \\ \hline W/JPY100 & 15.98\% & 2 & 6.28\% & 6 & 6.18\% & 6 \\ \hline W/USD & 11.26\% & 5 & 6.93\% & 4 & 8.52\% & 4 \\ \hline W/CNY & 14.98\% & 3 & 4.95\% & 7 & 4.86\% & 7 \\ \hline W/EUR & 11.62\% & 4 & 33.77\% & 1 & 33.19\% & 1 \\ \hline Lagging\_Composite\_Index & 1.82\% & 10 & 0.01\% & 10 & 0.01\% & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{\begin{tabular}{c} **Classification** \\ **Classification** \\ **Importance Vals** \\ **(Percentage)** \\ \end{tabular} } & \multicolumn{2}{c}{**Pre-Pandemic**} & \multicolumn{2}{c}{**During the Pandemic**} & \multicolumn{2}{c}{**Post-Pandemic**} \\ \cline{2-7}  & \begin{tabular}{c} **Feature** \\ **Importance Vals** \\ **(Percentage)** \\ \end{tabular} & **Rank** & \
\begin{tabular}{c} **Feature** \\ **Importance Vals** \\ **(Percentage)** \\ \end{tabular} & **Rank** &
\begin{tabular}{c} **Feature** \\ **Importance Vals** \\ **(Percentage)** \\ \end{tabular} & **Rank** \\ \hline KOSDAQ\_Index & 1.03\% & 8 & 0.80\% & 8 & 19.25\% & 2 \\ \hline KOSPI\_Index & 40.55\% & 1 & 31.43\% & 1 & 6.57\% & 5 \\ \hline Coincident\_Composite\_Index & 0.27\% & 9 & 0.21\% & 9 & 2.09\% & 8 \\ \hline Leading\_Composite\_Index & 10.55\% & 4 & 8.17\% & 5 & 0.14\% & 9 \\ \hline Price\_Index & 16.61\% & 2 & 12.88\% & 3 & 19.19\% & 3 \\ \hline W/JPY100 & 6.06\% & 7 & 4.69\% & 7 & 6.18\% & 6 \\ \hline W/USD & 6.67\% & 6 & 27.66\% & 2 & 8.52\% & 4 \\ \hline W/CNY & 11.48\% & 3 & 8.90\% & 4 & 4.86\% & 7 \\ \hline W/EUR & 6.78\% & 5 & 5.26\% & 6 & 33.19\% & 1 \\ \hline Lagging\_Composite\_Index & 0.00\% & 10 & 0.00\% & 10 & 0.01\% & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Findings of comparative analysis of grouping factors (SHAP, LCC).  
According to the findings of the Random Forest analysis, the leading index was ranked low pre-and during the Pandemic but became highly important post-Pandemic. Consistent with SHAP, Random Forest analyses also highlighted the exchange rate (KRW/EUR) and lagging index as key factors during and post-Pandemic, respectively. Table 4 presents the findings of the comparative analysis of grouping factors (Random Forest, Total).