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.
Warehouses are a fundamental element for the supply chain and, consequentially, provide resources for people to perform their daily tasks. Their location determines the type of goods movements that will be performed in the city area. Knowing their location is essential to define public policies applied to urban freight transport, city livability and economic development. In the search to make a better diagnosis of its area, the Belo Horizonte City Hall developed the urban quality-of-life index (UQLI) and the local supply index (LSI). This article used linear regression to identify the correlation amongst the UQLI, the LSI and the location of the logistics warehouses in urban areas. The best model obtained from the econometric analysis is the one that correlates warehouses with supermarkets, bookstores and stationery, residential area, quality of the house, bank and gas station. The results obtained were confirmed with spatial analysis. This result allows concluding that the warehouses are influenced by the favourable zoning, low land cost, proximity of regional and main streets of the city and high population and retailer density.
The warehouse location is a critical factor in the efficiency of urban freight transport. However, several factors influence this location. This paper analyses the spatial correlation of characteristics of cities in a metropolitan region and the location of the warehouses through a case study in the Belo Horizonte metropolitan region. The municipalities' socioeconomic and fleet data were analysed using the Local Moran Index and Bivariate Moran Index statistics. The results were presented by clusters using the Local Indicator of Spatial Association. Populational density, land cost, and truck fleet are spatially correlated with the warehouses' location. Furthermore, the characteristics of some municipalities, as Contagem, Ribeirão das Neves, and Ibirité, create high-high clusters, with high spatial correlation in the municipalities of cluster and, also, in the surroundings. Findings suggest the importance of land use, logistics, and real estate sector public policies minimise warehouses' externalities and contribute to economic development.
Este artigo tem por objetivo identificar a relação da taxa de entrega e da remuneração dos entregadores de aplicativos em cidades brasileiras. Os dados referentes à taxa de entrega e à distância percorrida foram obtidos nos principais aplicativos de entrega para oito cidades brasileiras, dentre elas cinco capitais e 3 cidades do interior. Foi utilizado regressão linear para identificar uma relação entre a taxa de entrega e a distância. Os resultados mostraram diferença na taxa fixa e na taxa variável de entrega entre as cidades consideradas na análise. Para obtenção de uma remuneração básica, isto é, o salário-mínimo, o entregador precisa trabalhar mais de 44 horas semanais, realizando pelo menos uma entrega por hora a uma distância de 3km. Contudo, esta jornada de trabalho pode ser extenuante se as entregas forem realizadas por modos não motorizados.
The use of on-demand delivery services increased in Brazil during the COVID-19 pandemic, mainly by requests for ready meals. While consumers appreciate convenience, the delivery fee is a decisive factor in the purchase process. However, the delivery fee pricing strategy of on-demand delivery service platforms has not been discussed in the literature. Thus, this study aims to analyze the factors that influence the delivery fee pricing of on-demand delivery services and explores the impact of delivery fee strategies on the remuneration of couriers. We collected data from three leading on-demand delivery service platforms regarding product type, order price, service fee, delivery fee, order day, order time, waiting time, and distance. As a result, our database comprises 1,440 orders in 12 Brazilian municipalities. A linear regression model was estimated to identify the factors influencing the delivery fee pricing considering different product types. Findings showed that product type has a diverse effect on delivery fee pricing. Moreover, distance, regardless of the product type, positively influences the delivery fee. The delivery fee of the ready meals is affected by the service fee, waiting time, order day, and order time. Furthermore, the waiting time and order day affect the delivery fee of supermarket and bakery products and beverages. Finally, the delivery fee of medical products is influenced by order day and time. Findings can be helpful for the pricing strategy of on-demand delivery services.
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