Akademik Məlumat İdarəetmə Sistemi
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, vol.71, pp.7681-7700, 2024 (SCI-Expanded)
The purpose of this study is to evaluate carbon neutrality policies in transportation industry with a novel decision-making model. First, selected indicators are evaluated by quantum picture fuzzy row sets-based multi-step wise weight assessment ratio analysis (M-SWARA) technique. Secondly, the alternatives for the carbon neutrality policies in this industry are ranked. For this purpose, multi-objective optimization on the basis of ratio analysis (MOORA) methodology is considered with quantum picture fuzzy row sets. The main motivation of making this study is the need for a novel and comprehensive decision-making model. The main reason behind this situation is that most of the existing models could not consider the causal directions among the indicators. Due to this situation, this proposed model is created by using causality relationships between the indicators of carbon neutrality policies in transportation industry. The main contribution of this study is that a new model is proposed by integrating quantum theory and picture fuzzy rough sets. This situation has a positive contribution to make sensitive evaluations. Additionally, a novel approach (M-SWARA) is proposed to weight the criteria so that causality relationship among the determinants can be considered in this process. The findings demonstrate that infrastructure development is the most important factor of effective carbon neutrality policies for transportation industry. Cost is another critical indicator in this respect. On the other hand, according to the ranking results, it is determined that reducing traditional fuels with zero-carbon alternatives is the most essential alternative for the carbon neutrality policies in transportation.