# Resource Capacity Requirement for Multi-Terminal Cooperation in Container Ports
## 4 Managerial Insights
### Analysis on Interaction Effects
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **SS** & **df** & **MS** & **F-Ratio** & \(p\)**-Value** & **Sig.** \\ \hline Trans-shipment & 26.05 & 3.00 & 8.68 & 195.78 & \(4.58\times 10^{-108}\) & yes \\ Transferring & 4.62 & 1.00 & 4.62 & 104.24 & \(9.50\times 10^{-24}\) & yes \\ Interaction & 21.74 & 3.00 & 7.25 & 163.44 & \(2.35\times 10^{-92}\) & yes \\ Error & 70.60 & 1,592.00 & 0.04 & & \\ Total & 123.01 & 1,599.00 & 0.08 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Two-factor ANOVA results for gate congestion in 5% significance level. The interaction terms consider if the effect of one predictor variable, in this case the transferring or trans-shipment rates, on the response variable, i.e., QC intensity, is different at different values of the other predictor variable. Unlike the results in Table 6, Table 7 shows a significant difference QC intensity between a 90% trans-shipment rate and an 85% trans-shipment rate, whereas an insignificance difference is observed between 90% and 75% of trans-shipment rates under a 75% transferring rate. When transferring rates among the terminals are high, the surge in trans-shipment rates smooths out the QC intensity across the terminals and produces a similar effect to the reduction in the trans-shipment rates that attenuates the QC intensity for trans-shipment TEUs. This finding is underpinned by nonexistence of insignificant interactions in the lower levels of transferring rate (for example, at 60%), whereas high transferring rate contributes the nonsignificant relationship between the two extreme trans-shipment rates. Meanwhile, the differences in degree of gate congestions between the 80% and 75% trans-shipment rates with a 75% transferring rate, and between 90% and 85% trans-shipment rates with a 60% transferring rate are found to be insignificant. The estimates in Cohen's d, which indicate the standardized mean differences between the two groups to be about 9% and 15%, provides further support to these observations (Table 8). As effect size is known to be independent of the sample size, the nonsignificances in the two cases concluded through p-value in Table 7 can rightfully be attributed to the close similarity between the two samples in terms of a comparison of percentiles [22]. This similarity can be explained by the fact that truck arrivals are controlled by the traffic conditions using Equation (8) for the high transferring rates. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Higher (75\%): Transferring**} & \multicolumn{3}{c}{**Lower (60\%): Transferring**} \\ \hline  & & **Higher (85\%)** & **Norm (80\%)** & **Lower (75\%)** & **Higher (85\%)** & **Norm (80\%)** & **Lower (75\%)** \\ \hline \multirow{3}{*}{QC intensity} & Upper (90\%) & yes & yes & no & yes & yes & yes \\  & Higher (85\%) & - & yes & yes & - & yes & yes \\  & Norm (80\%) & - & - & yes & - & - & yes \\ \hline \multirow{3}{*}{Storage space requirement} & Upper (90\%) & yes & yes & yes & yes & yes & yes \\  & Higher (85\%) & & yes & yes & - & yes & yes \\  & Norm (80\%) & - & - & yes & - & - & yes \\ \hline \multirow{3}{*}{Gate congestion} & Upper (90\%) & yes & yes & yes & no & yes & yes \\  & Higher (85\%) & - & yes & yes & - & yes & yes \\ \cline{1-1}  & Norm (80\%) & - & - & no & - & - & yes \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Significance test between individual trans-shipment levels under transferring levels for QC intensity, storage space requirement, and gate congestion using contrasts in 5% significance level.