Last Mile Urban Freight Distribution: A Modelling Framework to Estimate E-Cargo Bike Freight Attraction Demand Share
Urban freight transportation is facing significant challenges due to increasing demand, driven by globalization, e-commerce growth, and the adoption of just-in-time logistics. These trends have led to rising vehicle flows in urban areas, negatively impacting sustainability, economic efficiency, and...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Future Transportation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7590/5/1/31 |
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| Summary: | Urban freight transportation is facing significant challenges due to increasing demand, driven by globalization, e-commerce growth, and the adoption of just-in-time logistics. These trends have led to rising vehicle flows in urban areas, negatively impacting sustainability, economic efficiency, and road safety. In response, cities are exploring innovative last-mile delivery strategies that emphasize sustainability, flexibility, and cost efficiency. Among these strategies, cargo bikes—particularly electric cargo bikes (e-cargo bikes)—are emerging as promising low-emission solutions for urban freight distribution. However, despite their potential, a generalized methodology for estimating their demand share in urban contexts remains underdeveloped. This study proposes a comprehensive modelling framework to evaluate the freight demand share that can be addressed by e-cargo bikes, integrating quantity, restocking service, modal, and delivery sub-models, calibrated using data from a case study in Italy. The results demonstrate that e-cargo bikes could fulfil up to 20% of urban freight demand, depending on the category of goods transported, and underscore the feasibility of integrating e-cargo bikes into urban logistics systems. However, critical challenges related to scalability and cost-effectiveness persist, highlighting the need for further research and reliable cost data to support broader implementation. |
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| ISSN: | 2673-7590 |