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Urban Vans, E- Commerce and Road Freight Transport

Authors: David Bonilla;

Urban Vans, E- Commerce and Road Freight Transport

Abstract

A city will typically depend on at least 150 supply chains and freight is a key part of them. This article aims to explore at the qualitative and qualitative level (1) how e-commerce drives both travel and urban freight transport and (2) to estimate how various manufacturing activities determine the stability of demand for freight transport. The article provides elasticity estimates on (1) the demand for road freight transport for five industry sectors using a time series framework; data on GDP (gross value added) and on fuel costs per t-km (tonne-km). A key finding is that e-commerce induces freight traffic, by vans, but the decline in freight intensity of the economy is only temporary since urban economic activity contributes to growth of freight. Our analysis of five manufacturing sectors confirms that cyclical sectors are more sensitive to energy price gyrations over time than non-cyclical sectors. Price elasticities are high but comparable to other studies. The income elasticity of freight transport is large for the five sectors, but the high heterogeneity of freight sectors means that predicting this activity is challenging. It is observed that truck freight intensity (km of trucks per GVA) declines but not enough to offset the rise in energy needed to fuel the entire freight transport sector; it is likely that the rise in van freight increases the demand for freight energy in urban regions.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Average
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