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Carbon neutrality policies are of great importance for the transportation sector. Thus, some issues need to be taken into consideration to increase the effectiveness of carbon neutrality policies in this sector. However, the biggest disadvantage of these improvements is that they increase costs. Instead of improving a large number of factors, it is more financially feasible to take action on the ones that are more important. Nevertheless, there are a limited number of studies in which priority analysis is made for the factors affecting this process. Therefore, the main missing part in the literature is that a new study should be made in which the importance weights of these variables are determined. 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. It would be appropriate for transportation companies to attach importance to the use of electric vehicles. In this context, government incentives for the use of electric vehicles need to be offered. For example, a tax reduction may increase the use of electric vehicles as it will provide a significant cost advantage.

Evaluation of Multidimensional Carbon Neutrality Policies in Transportation Using a Novel Quantum Picture Fuzzy Rough Modelling