VIKOR Method for Plithogenic Probabilistic Linguistic MAGDM and Application to Sustainable Supply Chain Financial Risk Evaluation

In the context of the increasingly competitive post-epidemic social marketing era, the sustainable development of supply chain finance is also facing the impact of more complex risk factors. However, the issue concerning how to scientifically and reasonably select the appropriate applicant company for financing cooperation on the basis of risk evaluation remains unresolved. For the smooth operation of banks’ sustainable supply chain finance (SSCF) business, this paper aims to develop a novel multi-attribute group decision-making (MAGDM) method considering the robustness and comprehensiveness among risk attributes and decision-makers (DMs). First, based on the idea that quantitative assessment values and qualitative linguistic sets can more accurately express uncertain risk information and importance degree of indicators, a novel concept is proposed that combines the probabilistic linguistic term set (PLTS) with the plithogenic set to evaluate the risk attributes of each alternative. Additionally, risk decision matrices evaluated by DMs are integrated and transformed through the operation of PLTS scoring function aggregation operators and the plithogenic contradiction degree. For deriving the integrated weight information of attributes, the objective attribute weights are determined on the basis of the subjective weights by adjusting coefficients. Then, the ranking order of alternatives is generated by applying the VIKOR method and constructing a MAGDM model with plithogenic PLTSs. Finally, the solving of a practical example concerning the selection of financing objects for SSCF oriented by risk evaluation verifies the effectiveness of the proposed model, where five risk indicators are developed, and the superiority of our studies is demonstrated by comparing with the existing TOPSIS and ELECTRE methods.