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The urban transportation network has an undeniable role in addressing the economic, social and environmental issues caused by the traffic. Transportation managers seek to use the existing facilities and capacities in an optimal way to increase customer satisfaction. Therefore, it is necessary to develop an approach to evaluate the performance of the urban transportation system to provide service to citizens effectively. This study develops an approach based on the extended version of the data envelopment analysis (DEA) model to measure the nonradial efficiency and super-efficiency of metro-stations considering the sustainability concept. The developed non-radial DEA model considers the hybrid returns to scale the form of technology by combining constant and variable returns to scale assumptions to improve its applicability to identify efficient and inefficient stations. This DEA model also incorporates the non-discretionary inputs and different types of outputs (i.e. undesirable, negative and non-negative) to improve discrimination power and the ability to interpret the results. The findings help decision-makers identify super-efficient stations as a benchmark for future planning and finding the best location to construct metro-stations. Furthermore, this research enables managers to optimally use the resources to increase the transferred passengers, reduce customer dissatisfaction and optimise the annual profit.

A hybrid returns to scale-DEA model for sustainable efficiency evaluation of urban transportation systems