Shippers/freight forwarders’ acceptance of dedicated rail freight corridors for freight mobility in India

Sowjanya Dhulipala , Gopal R. Patil
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Abstract

This paper investigates the acceptance of a mega rail freight infrastructure as a sustainable alternative to road transport for domestic freight movements in India. The dedicated rail freight corridors (DFCs) are the freight-only rail corridors proposed by the Indian government to improve freight mobility from a sustainable outlook. A shipper/freight forwarder survey was conducted to gather information on mode attributes and their stated preferences toward DFCs. We employ discrete choice (binary logit) and machine learning algorithms (random forest and extreme gradient boosting) to analyse the choice behaviour. The machine learning methods exhibited higher prediction accuracy, while discrete choice models offered better interpretability. On-time performance and transport costs are crucial factors that influence mode choice. Large-scale companies are more willing to shift to DFCs compared to small and medium firms. The policy scenario analysis indicates that providing a better on-time performance can gain a substantial share of DFCs.

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托运人/货运代理对印度货运专用铁路走廊的接受程度
本文研究了在印度国内货运中将超大型铁路货运基础设施作为公路运输可持续替代方案的接受程度。专用铁路货运走廊(DFC)是印度政府提出的货运专用铁路走廊,旨在从可持续发展的角度改善货运流动性。我们对托运人/货运代理进行了调查,以收集有关模式属性及其对 DFCs 偏好的信息。我们采用离散选择(二元 logit)和机器学习算法(随机森林和极端梯度提升)来分析选择行为。机器学习方法的预测准确率更高,而离散选择模型的可解释性更好。准时率和运输成本是影响模式选择的关键因素。与中小型企业相比,大型企业更愿意转向 DFC。政策情景分析表明,提供更好的准点率可以获得大量的双向燃料电池份额。
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CiteScore
7.10
自引率
8.10%
发文量
41
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