Supplier classification and ranking of new energy vehicle based on CPT-TODIMSort method

Purpose The paper proposes a new method based on interval-valued intuitionistic fuzzy set, which improves the traditional TODIM method to classify the parts suppliers of new energy vehicle enterprises. Design/methodology/approach The CPT-TODIMSort method is proposed to address the subjective issue of traditional TODIM during the weighting stage. It utilizes the intuitionistic fuzzy entropy weight method based on cumulative prospect theory for weight calculation. Subsequently, this method is applied to a practical case study involving classification of parts suppliers for a new energy vehicle enterprise. Findings When decision-makers have different risk aversion and risk seeking tendency, the classification results will be different, reflecting the role and importance of decision makers’ psychological behavior in the classification process. Originality/value The new method in this paper not only inherits TODIM’s advantages, but also eliminates subjective attribute weighting, visually demonstrates the impact of decision-maker’s psychological behavior on results, and emphasizes the importance of considering such behavior in classification.