Analyzing Performance of Transit Lines and Depots: A Data Envelopment Analysis Approach

Performance evaluation of transit systems inevitably offers critical information to decision makers, allowing them to modify, adjust or even re-structure transit operations. In this paper, the authors employ Data Envelopment Analysis in order to investigate the efficiency of bus depots and bus lines for the Athens (Greece) bus system. Appropriate labor, capital and operations inputs are used, along with tailor- made composite performance measures for outputs. Also, neural network regression is used for revealing the impact of critical variables to the performance of bus lines. Results on depots reveal differences between the depots with respect to their technical efficiency, as well as the variable returns to scale. For bus lines, DEA results indicate variability in the efficiency lines even for those depots that operate on the efficiency line. This has significant implications to a possible transit network restructure, as it reflects the need to assess each line separately. Finally, the neural network based analysis reveals the importance of the several technical characteristics (line category, route structure, bus type) to the efficiency of the lines.