Modelling Freight Trip Generation Based on Deliveries for Brazilian Municipalities

Leise Kelli de Oliveira (), Gracielle Gonçalves Ferreira de Araújo, Bruno Vieira Bertoncini, Carlos David Pedrosa and Francisco Gildemir Ferreira da Silva
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Leise Kelli de Oliveira: Department of Transportation and Geotechnical Engineering, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil
Gracielle Gonçalves Ferreira de Araújo: Postgraduate Program in Civil Engineering, Federal University of Pernambuco, Recife 50670-901, Brazil
Bruno Vieira Bertoncini: Postgraduate Program in Transport Engineering, Federal University of Ceará, Fortaleza 60455-760, Brazil
Carlos David Pedrosa: Postgraduate Program in Transport Engineering, Federal University of Ceará, Fortaleza 60455-760, Brazil
Francisco Gildemir Ferreira da Silva: Economy Graduate Program, Universidade Federal do Ceará, Fortaleza 60020-060, Brazil

Sustainability, 2022, vol. 14, issue 16, 1-18

Abstract: Freight trip generation modelling is important for forecasting freight movements, and understanding freight movements is crucial to enabling sustainable freight transportation planning. The existing literature focuses on model development, and most of the previous models are estimated by ordinary least squares regression. However, few studies have carefully considered the OLS assumptions. The objective of this paper is to estimate freight trip generation models using deliveries to commercial establishments in Brazilian municipalities. A procedure is described to estimate models by ordinary least squares (OLS), and alternative techniques are considered to address the violations of the OLS assumptions. The analysis was conducted with data from 860 commercial establishments in nine Brazilian municipalities, and models were estimated for capital, non-capital, small, medium, and larger municipalities. The findings showed that alternative techniques to OLS regression can provide better-estimated parameters and more accurate results. Not evaluating the OLS assumptions could compromise the quality of the model and, consequently, planning using these models. Moreover, the results showed that the number of employees has a more significant influence in small cities and a lower influence in medium-sized municipalities. Finally, the findings demonstrated the importance of local models that include the municipalities’ characteristics and that can support freight transportation planning. These models can also include sustainable strategies for freight transport.

Keywords: freight trip generation modelling; urban freight transport; ordinary least squares; robust regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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