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

机译:异构运行条件下的生产率分析数据包络分析方法在美国重轨工业中的应用

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摘要

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.
机译:解决了运输行业中生产率分析和异构操作条件的问题。提出了一种新的方法,顺序数据包络分析(DEA)。该方法通过使用涉及DEA和统计分析的两步过程来说明运输机构的运行状况。顺序DEA在1984-1997年期间应用于美国的14个铁路运输系统,以确定生产率水平。分析的输出为乘客英里,并且选择要包括在此非参数分析中的三个运行条件是人口密度,上班途中的过境份额和车站可用性。连续DEA生产率分析的结果表明,在使用固定投入的情况下,铁路运输行业的平均技术效率为76%。该结果比常规DEA估计的效率水平高8%。此外,还确定了参考机构和每个机构的最佳产出水平。

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