The choice of shipment size is a vital decision in logistics and has a strong indirect influence on freight transport demand, via the choice of mode and truck type choice. Through time, shipment sizes can change as a result of new decisions in the logistics process or due to conditions external to the supply chain. This study investigates the temporal stability of shipment size choices, relating these to the choice of truck types. It uses repeated cross-sectional data for the years 2015, 2017, and 2019 collected from cordon and business establishment surveys in Addis Ababa city, Ethiopia. The integrated choice and latent variables (ICLV) and latent growth (LG) models were used to assess the time-dependent patterns of choosing shipment sizes, both at the level of the entire freight system as well as the specific truck types. The model results reveal that shipment size decisions are temporally unstable where, in our case, shipment sizes exhibited a declining trend.@en

This paper investigates the effect of spatial and locational characteristics of establishments on freight (trip) attraction (FA/FTA) models. The authors estimated econometric models of FA and FTA as a function of the establishment attributes as well as the spatial and locational determinant variables, using establishment-level data collected from Addis Ababa City, Ethiopia. The interconnected issues of spatial dependency and spatial heterogeneity, together with nonlinear specifications, were incorporated with the application of spatial techniques, including spatial error models (SEM), spatial autoregressive model (SAR), geographically weighted regression (GWR), multiscale-GWR (MGWR), and the combination GWR-SAR/MGWR-SAR. Regarding the explanatory variables, the empirical results revealed that firms in the manufacturing, wholesale and retail sectors located on the wider streets tend to receive more FA and FTA. The closeness to the primary road network and the city entry gate influences the FTA of manufacturing and construction firms. Moreover, retail establishments near the major market tend to receive more tonnage. The models also confirm that FA and FTA are the results of two different processes. Overall, the use of spatial regression techniques improves the accuracy of both FA and FTA models. MGWR-SAR exhibits superior performance by jointly addressing spatial dependency and heterogeneity. The MGWR-SAR model also uncovers the local variability of the variables representing the spatial and locational effects on freight attraction. The methodological analysis and empirical findings of the study could provide useful insights to support urban freight modelling, planning, and decision-making.@en

Urban logistics policies have become instrumental in achieving sustainable transport systems. Developing and emerging countries still lag far behind in the implementation of such policies when compared with developed countries. This exposure gap provides an opportunity for policy transfer, but this is a complex process requiring knowledge of many contextual factors and involving multiple steps. A good understanding of those contextual factors of measures by cities may be critical for a successful transfer. Our study aimed to identify the different contexts of urban logistics measures or policies worldwide and to assess their significance for policy transferability. In this study, urban logistics measures discussed in the literature were retrieved with a systematic literature review method and then the contexts were recorded, distinguishing between economic development levels and geographical regions. The analysis revealed that the economic level and geographical location of cities both have a strong association with the type of measure implemented. Barriers and drivers were identified by assessing policy transfer between developed and developing countries. Institutional and physical barriers appeared to be highly pertinent for a range of measures, while drivers or facilitators were identified from specific problems in developing countries and the respective measures in developed countries. Thus, the analysis of contextual factors can provide a first response to the key challenges and opportunities of sustainable urban logistics policies transfer to developing countries.

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