Urban freight transport is a challenge for Brazilian cities due to the lack of adequate planning for freight flow movement. Public managers also show negligence and a lack of awareness when dealing with urban logistics. Decision-support data on urban freight transport are still scarce, despite being of fundamental value to economic development. With this in mind, this paper presents problems and solutions regarding urban freight transport in Brazilian cities. Data were obtained through a survey conducted in nine cities and analysed by means of descriptive statistics and the successive intervals method. Additionally, a cluster analysis was performed to identify patterns regarding the typical characteristics of each city in order to compare and generalise the perception of retailers regarding problems and solutions at the national level. The results indicate divergent opinions among retailers from different cities, even from cities with similar socioeconomic profiles and urban dynamics. The municipalities which demonstrated the most similarities were (i) Betim and Niteroi, in the Southeast of Brazil; (ii) Palmas and Quixada, in the North and Northeast, respectively; and (iii) Palmas and Caruaru, also in the North and Northeast. The results reinforce the importance of studying the local context and involving stakeholders in the process of planning urban logistics solutions.

Urban freight transport (UFT) is simultaneously responsible for maintaining the urban lifestyle and the negative externalities impacting urban areas, necessitating strategies that promote sustainable urban freight transport (SUFT). In addition, the stakeholders and geographic factors involved in UFT impose specific concerns in the planning and operation stages of SUFT. Therefore, this paper proposes a model addressing sustainable last-mile delivery considering the relationship between the activity system, transportation system, and stakeholders involved in UFT. Based on the literature review, we identified UFT planning procedures to achieve SUFT. In a cyclical process, these procedures were considered on the proposed model, integrating freight transport planning with urban planning to develop SUFT and, consequently, sustainable cities.

The COVID-19 pandemic has changed lifestyles, with consequent impacts on urban freight movements. This paper analyzes the impacts of COVID-19 on urban deliveries in the Belo Horizonte Metropolitan Region, Brazil. The Lee index and the Local Indicator of Spatial Association were calculated using data on urban deliveries (retail and home deliveries) and COVID-19 cases. The results confirmed the negative impacts on retail deliveries and the positive impacts on home deliveries. The spatial analysis demonstrated that the most interconnected cities presented more similar patterns. At the beginning of the pandemic, consumers were considerably concerned about the virus spread, and the changes in consumption behavior were slow. The findings suggest the importance of alternative strategies to traditional retail. In addition, the local infrastructure should adapt to the increased demand for home deliveries during pandemics.

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.

Many negative externalities are associated with home deliveries, the main ecommerce delivery destination. Despite many solutions that address this problem, the lack of understanding of the spatial pattern of urban deliveries makes it challenging to implement these strategies. This paper analyzed the spatial relationship between sociodemographic, retail and e-commerce deliveries in Belo Horizonte (Brazil) by using official data at the neighborhood level (number of retail shops, gender, income, age, race, and household size), and e-commerce deliveries performed by a transportation company. Global Moran's I indicated the spatial dependence of the e-commerce deliveries. Results of a geographically weighted regression model showed a positive spatial effect of retail, women, Asian population, age from 20 to 29 years old, and income. In addition, a negative spatial effect was identified for the size of the household, 18 to 19 years old, and the black population. Furthermore, the estimated coefficients show small spatial variability, indicating homogeneity in the spatial relation. The uniformity of the parameters indicates that alternative strategies can be implemented throughout the territory to reduce e-commerce deliveries.