Journal of Transport and Supply Chain Management (Jun 2018)

A heavy goods vehicle fleet forecast for South Africa

  • Jan H. Havenga,
  • Phillippus P.T. le Roux,
  • Zane P. Simpson

DOI
https://doi.org/10.4102/jtscm.v12i0.342
Journal volume & issue
Vol. 12, no. 0
pp. e1 – e12

Abstract

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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.

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