Right Indicators of Urban Railway System: Combination of BSC and DEA Model

With the expansion of cities and ever-increasing traffic dilemma closely connected to people’s lives, public transportation has become one the essential needs of communities. Subway because of its benefits is an important part of our lives: alleviating urban transit pressure, high safety and reliability, mass transit capacity, low energyconsumption, and low price. Therefore, its performance improvement led to increasing citizenry satisfaction seems essential. The most important point in evaluation and performance improvement is the proper selection of measures. The main purpose of this paper is to introduce a new approach for selection of right indicators. For this purpose, with respect to the cause and effect relationships in balanced scorecard, its measures are applied as input and output variables of three-stage data envelopment analysis model. At first, some indicators are supposed for each BSC’s aspects and the efficiency of all stages in this basic model is computed. Then, individual inputs are considered in each stage and the efficiency of that stage is computed again in order to compare with the efficiency score of the same stage in the basic model. With interpreting of efficiency variations in each stage, appropriate measures are determined. An experimental example which contains 10 stations of Tehran subway is provided to illustrate the implementation of this model. The results indicate that efficiency of train, concurrent consideration of average density per each passenger and waiting at the station, and simultaneous consideration of average density per each passenger and the delay per trip are appropriate measures. The proposed approach in this study helps to managers and decision makers in transportation industry to recognize right indices for performance improvement

Right Indicators of Urban Railway System: Combination of BSC and DEA Model Keywords:

Urban Railway , Appropriate Measures , Balanced Scorecard (BSC) , Three- Stage Data Envelopment Analysis (DEA) , Transportation