A Two-Stage Multi-Criteria Supplier Selection Model for Sustainable Automotive Supply Chain under Uncertainty

Abstract

Sustainable supplier selection (SSS) is gaining popularity as a practical method to supply chain sustainability among academics and practitioners. However, in addition to balancing economic, social, and environmental factors, the emergence of the COVID-19 pandemic has affected the selection of long-term suppliers to ensure sustainable supply chains, recover better from the pandemic and effectively respond to any future unprecedented crises. The purpose of this study is to assess and choose a possible supplier based on their capability to adapt to the COVID-19 epidemic in a sustainable manner. For this assessment, a framework based on multi-criteria decision making (MCDM) is provided that integrates spherical fuzzy Analytical Hierarchical Process (SF-AHP) and grey Complex Proportional Assessment (G-COPRAS), in which spherical fuzzy sets and grey numbers are used to express the ambiguous linguistic evaluation statements of experts. In the first stage, the evaluation criteria system is identified through a literature review and experts’ opinions. The SF-AHP is then used to determine the criteria weights. Finally, the G-COPRAS method is utilized to select sustainable suppliers. A case study in the automotive industry in Vietnam is presented to demonstrate the proposed approach’s effectiveness. From the SF-AHP findings, “quality”, “use of personal protective equipment”, “cost/price”, “safety and health practices and wellbeing of suppliers”, and “economic recovery programs” have been ranked as the five most important criteria. From G-COPRAS analysis, THACO Parts (Supplier 02) is the best supplier. A sensitivity study was also conducted to verify the robustness of the proposed model, in which the priority rankings of the best suppliers are very similar. For long-term development and increased competitiveness, industrial businesses must stress the integration of response mechanisms during SSS implementation in the COVID-19 epidemic, according to the findings. This will result in significant cost and resource savings, as well as reduced environmental consequences and a long-term supply chain, independent of the crisis.

Dental Material Selection for the Additive Manufacturing of Removable Complete Dentures (RCD)

“…The development of the proposed approach correlates with the attraction of the MCDM, which takes the experts’ uncertainty in decision-making (estimation) into account. The methods based on fuzzy logic theory are among them [ 41 , 62 , 63 ].…”

Vendor Partnerships in Sustainable Supply Chain in Indian Electric Two-Wheeler Industry – A Systematic Review of Literature

“…Vendor Partnerships in Indian Automobile Industry Sahu et al (2022) study supplier selection using a decision making model, which employs an integrated MCDM approach with evidence from the Indian automotive sector. Vendor selection in the Indian automotive industry has been studied through a case study by Jain et al (2018); Dang et al (2022), who have created a Two-Stage Multi-Criteria Supplier Selection Model for sustainability in supply chains in automobile industry; and Sytch et al (2022) who have studied the practices for the selection of suppliers to ensure lasting global supply chain networks. Juned & Farooquie (2022) study VMI factors in automotive industries from two different perspectives (from buyers & vendors), comparing the perceptions of professionals and academia.…”

Multiple-Attribute Decision Making Based on the Probabilistic Dominance Relationship with Fuzzy Algebras

“…Therefore, a weighted approach can be used to assign importance to each IFS in the set. Several researchers have proposed different methods to rank IFSs and HIFs based on their importance, such as fuzzy-based symmetrical multi-criteria decision-making procedures [39][40][41] and the synchronization of fractional-order neural networks via pinning control [42]. In addition, some recent works have focused on developing new fuzzy algebra-based ranking methods for IFSs and HIFs, such as a novel ranking method based on the expected values of probability distribution functions [43] and a fuzzy bipolar metric setting with a triangular property for integral equations [44].…”