A New Model for Evaluation of the Passenger and Freight Transportation Planning Based on the Sustainability and Safety Dimensions: A Case Study

As the population grows and industries develop, it is essential for countries to improve the environmental and safety impacts by evaluating the performance of their transportation systems. In this paper, data envelopment analysis (DEA) has been applied for performance evaluation of decision-making units (DMUs). Then, the network and leader-follower models are developed based on the DEA model for considering different time periods and dependency of the DMUs on each other. A multi-criteria decision-making (MCDM) model is proposed for determining the leader in the leader-follower model in which the uncertainty of data is also considered in the form of normal and chance modes. A multi-objective programming model is proposed for performance evaluation of the models which leads to improvement in the discrimination power of the models. The mathematical programming model has been investigated under interval uncertainty conditions and random variation of the data. Finally, the rank of the countries is aggregated by the proposed model. The proposed models are run with the road transportation data of European countries. Based on the results, Latvia, Slovakia and Bulgaria ranked first to third, where Latvia has the highest degree of randomness, while Slovakia and Bulgaria have the lowest degree of randomness. Then, as a case study, Iran is compared to European countries in terms of road safety, where the models are extended to consider non-homogenous data. The results show that Iran has the lowest ranking and road safety in Iran needs to be addressed with special attention.