Links between freight trip generation rates, accessibility and socio-demographic variables in urban zones

Gonzalez-Feliu Jesus; Palacios-Argüello Laura; Suarez-Nanez Carlos

doi:10.5604/01.3001.0014.1738

Authors

Gonzalez-Feliu Jesus Department of Supply Chain, Purchasing and Project Management, Center of Research in Managerial Intelligence and Innovation -CERIIM, Excelia Group La Rochelle Business School, La Rochelle, France Author https://orcid.org/0000-0002-0056-7627
Palacios-Argüello Laura Department of Environment and Organization Engineering, Institut Henri Fayol, Ecole des Mines de Saint-Etienne, France Author https://orcid.org/0000-0002-9512-1344
Suarez-Nanez Carlos Institute of Innovation in Productivity and Logistics CATENA-USFQ, Department of Industrial Engineering, Universidad San Francisco de Quito, Ecuador Author https://orcid.org/0000-0001-8375-1843

DOI:

https://doi.org/10.5604/01.3001.0014.1738

Keywords:

urban goods transport, transport modelling, city logistics, land use, accessibility, FTG, decision support

Abstract

This paper proposes an assessment of the links between freight trip generation (FTG) rates and accessibility. First, the paper overviews the background, sets the context and motivates the research. Second, it presents the proposed methodology, which combines an FTG model, two accessibility indicators and a linear regression analysis to assess the relationships between freight trip demand and a set of socio-demographic variables including accessibility. The FTG modelling framework, adapted from previous works, allows estimating the number of freight trips with a small amount of standard data, even when no surveyed data is available. The two gravity accessibility indexes, one potential and one exponential, are defined in the continuity of recent freight accessibility works. To those indicators, a set of socio-demographic variables, including population, area or a zone (or density), are introduced. The relationships between FTG and all those variables are assessed via standard linear regression methods completed by the verification of the corresponding linear relationship hypotheses. Third, the framework is applied to the urban area of Lyon (France), where no urban goods survey data is available. Results show that potential accessibility seems to have a better correlation to FTG and could be a good decision support indicator when combined with the population as an explanatory variable. The population can be added to accessibility as an explanatory variable, the resulting models with two variables have a slightly lower accuracy but remains close to that of models with only accessibility as an explanatory variable. This work remains exploratory and finishes by proposing practical implications and further development lines.

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