A heavy goods vehicle fleet forecast for South Africa

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 o...

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Main Authors: Jan H. Havenga, Phillippus P.T. le Roux, Zane P. Simpson
Format: Article
Language:English
Published: AOSIS 2018-06-01
Series:Journal of Transport and Supply Chain Management
Subjects:
Online Access:https://jtscm.co.za/index.php/jtscm/article/view/342
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spelling doaj-c9c6ed80010945509d73530317e1e2002020-11-25T00:56:29ZengAOSISJournal of Transport and Supply Chain Management2310-87891995-52352018-06-01120e1e1210.4102/jtscm.v12i0.342194A heavy goods vehicle fleet forecast for South AfricaJan H. Havenga0Phillippus P.T. le Roux1Zane P. Simpson2Department of Logistics, Stellenbosch UniversityDepartment of Logistics, Stellenbosch UniversityDepartment of Industrial Engineering,, Stellenbosch UniversityPurpose: 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.https://jtscm.co.za/index.php/jtscm/article/view/342heavy goods vehicle fleetmodal shiftperformance-based standardscollaborationSouth Africa
collection DOAJ
language English
format Article
sources DOAJ
author Jan H. Havenga
Phillippus P.T. le Roux
Zane P. Simpson
spellingShingle Jan H. Havenga
Phillippus P.T. le Roux
Zane P. Simpson
A heavy goods vehicle fleet forecast for South Africa
Journal of Transport and Supply Chain Management
heavy goods vehicle fleet
modal shift
performance-based standards
collaboration
South Africa
author_facet Jan H. Havenga
Phillippus P.T. le Roux
Zane P. Simpson
author_sort Jan H. Havenga
title A heavy goods vehicle fleet forecast for South Africa
title_short A heavy goods vehicle fleet forecast for South Africa
title_full A heavy goods vehicle fleet forecast for South Africa
title_fullStr A heavy goods vehicle fleet forecast for South Africa
title_full_unstemmed A heavy goods vehicle fleet forecast for South Africa
title_sort heavy goods vehicle fleet forecast for south africa
publisher AOSIS
series Journal of Transport and Supply Chain Management
issn 2310-8789
1995-5235
publishDate 2018-06-01
description 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.
topic heavy goods vehicle fleet
modal shift
performance-based standards
collaboration
South Africa
url https://jtscm.co.za/index.php/jtscm/article/view/342
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