Sustainable technology selection using decomposed spherical fuzzy Z AHP and VIKOR methodology

Purpose Choosing sustainable vehicle engine technology is critical for reducing environmental degradation, ensuring efficient use of natural resources and achieving long-term economic development. The main aim of this paper is to present a novel fuzzy approach to model decision-makers' judgments for vehicle engine technology selection problem under sustainability. Design/methodology/approach In order to represent decision-makers' uncertain judgments for vehicle engine technology selection, this study presents a novel fuzzy decision-making methodology integrating 3D fuzzy sets for a wider definition volume, Decomposed Spherical Fuzzy Sets (DFSs) to control consistency and Z-fuzzy numbers to model reliability. Therefore, analytical hierarchy process (AHP) method for criteria weighting and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for ranking of alternatives are extended to the DSF Z-AHP method and DSF Z-VIKOR method, respectively. Findings The proposed DSF-Z AHP and VIKOR methodology is successfully implemented for a real-world decision problem. The comparative analysis with the DSF AHP and VIKOR methodology reveals the necessity of reliability information in decision-making. Practical implications The results of the study can particularly contribute to the creation of more sustainable and long-term transportation strategies for transportation planners. Furthermore, the study may serve as a strategic decision-making support tool for automotive sector and policy makers like vehicle technologies prioritization, differentiating R&D activities, developing sustainability-focused products and developing regulatory policies aimed at reducing carbon emissions. Originality/value This study proposes Decomposed Spherical Fuzzy Z numbers for the first time. A novel Decomposed Spherical Fuzzy Z AHP and VIKOR methodology is presented. The proposed methodology can process the decision-makers' uncertainty-containing judgments in a holistic manner without using an immediate defuzzification procedure at the early stages in order not to cause any loss of information.