Digital technologies are essential tools that enable traceability in supply chains. In low-income countries, traceability represents a challenge due to the complicated structure of supply chains and the involvement of multiple stakeholders. This research developed a framework for a digital traceability system (TS), using the Ethiopian coffee supply chain as a case study. A literature review was conducted to gain an in-depth understanding of state-of-the-art digital traceability technologies. A logistics audit was conducted to map the coffee supply chain in Ethiopia and evaluate the implementation level of traceability technologies. Although the implementation of traceability technologies in the Ethiopian coffee supply chain is low, the results revealed that the usage of traceability technologies improves downstream of the supply chain. The traceability framework developed in this study ranges from a paper-based TS to a fully digitalised TS. The implementation of a TS in the coffee supply chain of Ethiopia is met with several challenges such as affordability, limited awareness, resistance of certain stakeholders, infrastructure limitations, restricted accessibility of some technologies and insufficient policy frameworks. Stakeholders from low-income countries can use the framework developed in this study to adopt a TS for their supply chains in line with their needs and current digitalisation levels.

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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

The present study assesses the level of digital technology adoption in the inter-modal freight transport system, with the case study of Ethiopia. To achieve the objectives, we utilized questionnaires and conducted site visits to the companies involved. The results show that all the companies have an equally high level of fundamental technology adoption. However, the use of advanced information and communication technologies, such as artificial intelligence and the internet of things, is limited. Ethiopian's railway transport company uses up-to-date technologies (such as real-time tracking and communication with drivers), whereas road transport companies widely use conventional technologies (such as phone calls) in providing transport services. To increase the level of digital technology adoption, and thus the overall efficiency of the intermodal transport systems, the study revealed a need for investment in human resources, encompassing awareness creation and IT skills training, in parallel to investments in the actual technologies.

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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

Performance evaluation in logistics is crucial in identifying improvement opportunities. This study assessed performance indicators (PIs) for import–export logistics chains, including transport, dry ports, transhipment and warehouses, focusing on Ethiopia. PIs were identified by means of a literature review. An expert survey based on the analytical hierarchy process (AHP) was used to obtain weightings for the indicators to allow an evaluation of the overall performance of the country’s import–export chains. Key challenges faced in the sector were also identified. Indicators such as turnaround time and damage frequency were given high weightings by experts for dry port PIs, security was given the highest weighting for transport PIs, and order lead time was given the highest weighting for warehouse PIs. Technological advancements, human resource capacity building and government policies were found to be the main areas that could improve the performance of logistics operations and address the challenges faced by the sector. These findings could provide a new and comprehensive picture of the key performance indicators of Ethiopian import–export logistics chains.@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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