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An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India

机译:将方向距离函数与事故数量作为不良输出的应用来衡量印度国道运输的技术效率

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By using the directional distance function (DDF) of data envelopment analysis (DEA), this study measures the technical efficiency of 37 Indian state road transport undertakings (SRTUs) for the year 2012-13. We employ the DDF as a tool for analyzing a joint production function with both desirable and undesirable outputs (i.e., the number of accidents). A comparison between the results with and without accidents shows that several SRTUs have experienced significant changes in their efficiency scores as well as in their rankings after accounting for the undesirable output. This indicates the importance of including the number of accidents - a safety standard - as representative of the undesirable output in computing the efficiency scores of SRTUs. The results of the Tobit model indicate that SRTUs with greater vehicle productivity are more efficient under both conventional DEA and DDF approaches. We also employed zero-truncated negative binomial model to assess the factors influencing the number of road accident experienced by the Indian SRTUs and found that the accident count was significantly influenced by fleet utilization and vehicle productivity. (C) 2016 Elsevier Ltd. All rights reserved.
机译:通过使用数据包络分析(DEA)的方向距离函数(DDF),本研究测量了2012-13年度印度37个州道路运输企业(SRTU)的技术效率。我们将DDF用作分析具有期望和不期望输出(即事故数量)的联合生产函数的工具。有事故和无事故的结果之间的比较表明,在考虑了不良输出之后,几个SRTU的效率得分以及排名发生了重大变化。这表明在计算SRTU效率得分时,包括事故数量(安全标准)作为不良输出代表的重要性。 Tobit模型的结果表明,在传统的DEA和DDF方法下,车辆生产率更高的SRTU效率更高。我们还采用了零截断的负二项式模型来评估影响印度SRTU发生的道路交通事故数量的因素,并发现事故计数受车队利用率和车辆生产率的显着影响。 (C)2016 Elsevier Ltd.保留所有权利。

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