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A heavy goods vehicle fleet forecast for South Africa
Journal of Transport and Supply Chain Management Pub Date : 2018-06-25 , DOI: 10.4102/jtscm.v12i0.342
Jan H. Havenga , Phillippus P.T. Le Roux , Zane P. Simpson

Purpose: To develop and apply a methodology to calculate the heavy goods vehicle fleet required to meet South Africa’s projected road freight transport demand within the context of total surface freight transport demand. Methodology: Total freight flows are projected through the gravity modelling of a geographically disaggregated input–output model. Three modal shift scenarios, defined over a 15-year forecast period, combined with road efficiency improvements, inform the heavy goods vehicle fleet for different vehicle types to serve the estimated future road freight transport demand. Findings: The largest portion of South Africa’s high and growing transport demand will remain on long-distance road corridors. The impact can be moderated through the concurrent introduction of domestic intermodal solutions, performance-based standards in road freight transport and improved vehicle utilisation. This presupposes the prioritisation of collaborative initiatives between government, freight owners and logistics service providers. Research limitations: (1) The impact of short-distance urban movements on fleet numbers is not included yet. (2) Seasonality, which negatively influences bi-directional flows, is not taken into account owing to the annual nature of the macroeconomic data. (3) The methodology can be applied to other countries; the input data are however country-specific and findings can therefore not be generalised. (4) The future possibility of a reduction in absolute transport demand through, for example, reshoring have not been modelled yet. Practical implications: Provides impetus for the implementation of domestic intermodal solutions and road freight performance-based standards to mitigate the impact of growing freight transport demand. Societal implications: More efficient freight transport solutions will reduce national logistics costs and freight-related externalities. Originality: Develops a methodology for forecasting the heavy goods vehicle fleet within the context of total freight transport to inform government policy and industry actions.

中文翻译:

南非的重型货车车队预测

目的:开发和应用一种方法来计算在地面水运总需求范围内满足南非预计的道路货运需求的重型货车车队。方法:通过地理分解的投入产出模型的重力模型来预测总货运量。在15年的预测期内定义了三种模式转换方案,并结合道路效率的提高,通知重型货车车队使用不同类型的车辆,以满足估计的未来公路货运需求。调查结果:南非运输需求高涨的最大部分将仍然留在长途道路走廊上。可以通过同时引入国内联运解决方案来缓解这种影响,公路货运中基于性能的标准,并提高了车辆的利用率。这以政府,货运所有人和物流服务提供商之间的协作计划为优先。研究局限性:(1)尚未包括短途城市运动对车队数量的影响。(2)由于宏观经济数据的年度性,没有考虑对双向流动产生负面影响的季节性。(3)该方法可适用于其他国家;但是,输入数据是针对特定国家/地区的,因此无法概括调查结果。(4)尚未模拟出通过再运输等减少绝对运输需求的未来可能性。实际影响:为实施国内联运解决方案和基于公路货运绩效的标准提供动力,以减轻货运需求增长的影响。社会意义:更加有效的货运解决方案将减少国家的物流成本和与货运相关的外部性。独创性:开发一种在总货运量范围内预测重型货车车队的方法,以为政府政策和行业行动提供依据。
更新日期:2018-06-25
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