## 5 Results and Discussion
Several previous research works were carefully selected and are listed in Table 5 in order to enrich the discussion in terms of how these previous studies contribute differently compared to the current study, and considering the use of DEA and PROMETHEE [29; 30; 31; 32; 33; 34; 35; 36; 37; 38]. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**DC** & **\(\boldsymbol{\varphi}\) (i)** & **Max \(\boldsymbol{\varphi}\) (i)** & **Min \(\boldsymbol{\varphi}\) (i)** & \
\begin{tabular}{c} **DEA Efficiency** \\ \end{tabular} &
\begin{tabular}{c} **DEA-Based** \\ **Score** \\ \end{tabular} \\ \hline MKO & \(0.1197\) & \(0.119747\) & & \(1.0000\) & \(1\) & \(1.0000\) \\ MDR & \(0.1159\) & \(\cdots\) & & \(0.9879\) & \(1\) & \(0.9879\) \\ MKK & \(0.0853\) & & & \(0.8924\) & \(0.727\) & \(0.6488\) \\ RRC & \(0.0639\) & & & \(0.8255\) & \(0.932\) & \(0.7693\) \\ PSC & \(0.0043\) & & & \(0.6395\) & \(0.832\) & \(0.5321\) \\ RBC & \(-0.0012\) & & & \(0.6223\) & \(1\) & \(0.6223\) \\ TFC & \(-0.0718\) & & & \(0.4020\) & \(1\) & \(0.4020\) \\ IJC & \(-0.1156\) & & & \(0.2652\) & \(0.582\) & \(0.1543\) \\ MKR & \(-0.2005\) & \(-0.20051\) & \(0.0000\) & \(0.881\) & \(0.0000\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Normalized PROMETHEE II results and the final DEA-based PROMETHEE II score. Figure 2: DCs ranking comparison with respect to PROMETHEE II, DEA, and DEA-based PROMETHEE II. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Title of Previous Studies** & **Publication Date** & **MCDM Theoretical Base \& Assumptions** & **Methodology** & **Dissimilarities in the Contribution Compared to the Current Study** \\
**Previous Studies** & **Date** & **(Context: Criteria, Alternatives, Decision Making Units (DMDM), etc. )** & **(MCDM Tools and Techniques)** & **Hudding Any Potential Improvements to Be Handled in Further/Future Studies, Gaps/Aspects not Covered, or Motives for Further Investigations)** \\ \hline An integrated benchmarking approach to distribution center performance using DEA modelling [29] & 2002 & Context: Distribution Center Performance; Criteria: 3 inputs (fheet size, experience, and the mean order throughput time in days (MOT)): and outputs (sales volume of 4 different products): Alternatives Distribution Centers. & Use of DEA alone (i.e., efficiency focused model) \\ \hline Freight village design using the multicriteria method PROMETHEE [30] & 2007 & Context: Freight village design; Criteria: freight village layout, the cross-coding options of the modules and direct railway access, and the circulation conditions: Alternatives three alternative designs of the freight village layout are compared by means of multicriteria analysis & PROMETHEE & The content of the “freight village” is more generic and comprehensive compared to the context of the “disturbation centers” based on a single technique (PROMETHEE) \\ \hline Evaluating Efficiency and Effectiveness Based on PCA-DE Approach in China [31] & 2009 & Context: Legislative Infrastructure Criteria: in inputs (number of staff and employed workers in transport, possession of civil motor vehicles, possession of water, railways density, and waterways density), highway density and 2 outputs (freight or/clear) & Principal Component & Logistics infrastructure and location oriented, not performance oriented. \\ \hline \multirow{2}{*}{Facility Location Selection PROMETHEE PROMETEE [32]} & \multirow{2}{*}{2010} & Context: Legislative Infrastructure Criteria: in inputs (number of staff and employed workers in transport, possession of civil motor vehicles, possession of water, railways density, and waterways density), highway density and 2 outputs (freight or/clear) & Principal Component & Logistics infrastructure and location oriented, not performance oriented. \\ \cline{1-1} \cline{3-3}  & & & & \\