# A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection
## 6 Managerial Implications  
In this study, the resilience element was incorporated in supplier selection to improve the SC ability to deal with unexpected risks and disruptions, consequently reducing the occurrence of financial issues. An effective Grey-MCDM model that integrated GRA with BWM and TOPSIS was proposed to measure the suppliers' performances with respect to the set of 7 resilience criteria. To deal with SC risks and disruptions, GRA was applied due to its strength in coping with uncertainties and incomplete data in supplier selection. Then, BWM was applied to calculate criteria weights due to its simplicity. In addition, BWM was adopted to reduce the inconsistency of judgments with less pairwise comparisons needed. Thus, a more consistent result could be generated. Moreover, TOPSIS as one of the most common MCDM techniques was applied to evaluate the suppliers' performances because it eases the computational work and has a better tolerance to a higher level of criterion weight change. Therefore, GRA-BWM-TOPSIS could be more effectively implemented to select the resilient suppliers. Other than that, the proposed set of resilience criteria was identified based on the review of literature and consideration of current SC needs. The proposed criteria do not only consider the basic traditional elements, but also resilience and financial elements. With this, the company's managers could focus on different aspects by clearly identifying the resilience criteria with their importance to be prioritized in the assessment process. By applying the knowledge, the case company would be able to achieve its objective of building up a resilient SC through resilient supplier selection. The findings are not only useful to provide a clearer image for the decision-makers in selecting the best resilient supplier, but also to benchmark the performances of the suppliers with the consideration of uncertainties and incomplete data. In this case, the new technique was validated by comparing it with another common method to ensure its effectiveness in improving the performance of the SC, raising the satisfaction level of the customers and finally increasing the resiliency of the company. Overall, this study provides a reference for resilient supplier selection so that the company could remain alert towards the unexpected  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Supplier** & **Rank (GRA-BWM-TOPSIS)** & **Rank (AHP-VIKOR)** \\ \hline S1 & 10 & 10 \\ S2 & 5 & 5 \\ S3 & 2 & 2 \\ S4 & 1 & 1 \\ S5 & 3 & 3 \\ S6 & 8 & 8 \\ S7 & 6 & 6 \\ S8 & 9 & 9 \\ S9 & 7 & 7 \\ S10 & 4 & 4 \\ \hline \hline \end{tabular}
\end{table}
Table 20: Comparisons of results on suppliers ranking.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Criteria** & **Weights (GRA-BWM-TOPSIS)** & **Weights (AHP-VIKOR)** \\ \hline C1 & 0.0367 & 0.0254 \\ C2 & 0.0643 & 0.0403 \\ C3 & 0.4225 & 0.3603 \\ C4 & 0.0735 & 0.0754 \\ C5 & 0.1286 & 0.1576 \\ C6 & 0.1029 & 0.1050 \\ C7 & 0.1715 & 0.2360 \\ \hline \hline \end{tabular}
\end{table}
Table 19: Comparisons of results on criteria weights.  
risks by focusing on the prioritized criteria with the consideration of uncertainties and incomplete data, thus, achieving a more robust SC.