## 5 Results and Discussion  
Table 2 presents the leaving flow \(\varphi^{+}(i)\) and the entering flow \(\varphi^{-}(i)\) for each DC, and accordingly, the final PROMETHEE II-based ranking of the nine DCs can be identified according to the final values for the \(\varphi\) (\(i\)), as shown in the last two columns. Table 2 shows that MKO, MDR, MKK, RRC, PSC, RBC, TFC, LJC, and MKR are ranked from first to nineth, respectively. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**DC** & **NE** & **SE** & **GDI** & **SR** & **SM** & **JCFR** & **VOR** \\ \hline LJC & 7 & 51.7 & 98.1 & 75.17 & 1.1 & 91.9 & 0.03731 \\ MKK & 9 & 48.4 & 98 & 99.10 & 1.1 & 89.5 & 0.02173 \\ PSC & 6 & 62.2 & 94.5 & 92.40 & 1.8 & 79.3 & 0.03021 \\ MKO & 6 & 40.8 & 94.1 & 92.50 & 2.7 & 80.1 & 0.01655 \\ MDR & 11 & 66.9 & 93.6 & 93.30 & 1.5 & 95.2 & 0.01485 \\ RRC & 8 & 59.1 & 93.5 & 96.50 & 1.1 & 91.7 & 0.01934 \\ RBC & 2 & 9.6 & 90.6 & 91.30 & 2.4 & 77 & 0.01165 \\ TFC & 3 & 38.1 & 89.9 & 94.30 & 1.5 & 73 & 0.01552 \\ MKR & 13 & 21.9 & 89 & 96.30 & 1.1 & 87.2 & 0.01508 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Collected data. Table 3 summarizes the results of the DEA model. Four (MKO, MDR, RBC, and TFC) out of nine DCs scored 1 as an efficiency score, which implies that, considering their input measures, there is no evidence of the inefficiency of these DCs. Specifically, each of them is capable of attaining a certain target for each output measure, considering the output measures in a manner that reflects the proportional differences among all DC input and output measures collectively. Put simply, these four DCs are the best at achieving higher SE, SR, SM, JCSR, and GDI, considering a relatively lower NE and VOR. The remaining DCs (RRC, MKR, PSC, MKK, and LJC) were ranked from fifth to nineth, respectively. Table 3 also illustrates potential improvements, computed via the Frontier Analyst software, for each DC to each measure. The tendency is to provide potential improvements corresponding to outputs rather than inputs due to the output orientation setting of the developed DEA model. Such an output orientation model tends to provide feedback on improvements for the inefficient units (inefficient DCs) by recommending certain increases in each output measure while attempting to maintain the same level of inputs. If these increases are not sufficient to achieve 100% efficiency for the unit under assessment, the model then recommends potential improvements to input measures. To illustrate, the efficiency score for LJC is 0.582, which indicates the lowest efficiency recorded among the listed DCs (i.e., it is ranked nineth (Table 3)). Such a score reveals significant potential for improvements. In order to improve the LJC efficiency and record the maximum efficiency score (i.e., 1 or 100% efficiency), SE, GDI, SR, SM, and JCER should increase by 71%, 113%, 192%, 218%, and 85%, respectively. Additionally, VOR should decrease by 2%. All potential improvements for all inefficient DCs are shown in Table 3. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**DC** & \(\mathbf{\varphi^{+}(i)}\) & \(\mathbf{\varphi^{-}(i)}\) & \(\mathbf{\varphi\) (i)}\) & **Rank** \\ \hline LJC & 0.1867 & 0.3023 & \(-0.1156\) & 8 \\ MKK & 0.2192 & 0.1339 & 0.0853 & 3 \\ PSC & 0.1765 & 0.1722 & 0.0043 & 5 \\ MKO & 0.2370 & 0.1173 & 0.1197 & 1 \\ MDR & 0.2333 & 0.1175 & 0.1159 & 2 \\ RRC & 0.1846 & 0.1207 & 0.0639 & 4 \\ RBC & 0.2350 & 0.2362 & \(-0.0012\) & 6 \\ TFC & 0.1501 & 0.2219 & \(-0.0718\) & 7 \\ MKR & 0.0995 & 0.3000 & \(-0.2005\) & 9 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Leaving flow, entering flow, and the final PROMETHEE II-based ranking of the DCs.