Productivity Analysis in Heterogeneous Operating Conditions: Data Envelopment Analysis Method Applied to the U.S. Heavy Rail Industry

Abstract

The problem of productivity analysis and heterogeneous operating conditions in the transit industry is addressed. A new method, sequential data envelopment analysis (DEA), is presented. This method accounts for the operating conditions of transit agencies by using a two-step procedure involving DEA and statistical analyses. Sequential DEA was applied to 14 rail transit systems in the United States for the years 1984-1997 to determine productivity levels. The output analyzed was passenger miles, and the three operating conditions selected for inclusion in this nonparametric analysis were population density, transit share of the journey to work trips, and station availability. The results of the sequential DEA productivity analysis indicate that the rail transit industry, on average, operates at a technical efficiency of 76% in using its fixed input. This result is 8% higher than the efficiency levels estimated by conventional DEA. In addition, the referent agencies and optimal output levels for each agency were identified.

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