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Managing first- and last-mile transport under real-world constraints: leveraging human experience with idiosyncrasies
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DOI：10.1007/s12063-026-00607-x.png)
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Abstract
En 中文
Although transport management research offers powerful optimization techniques, most models overlook the idiosyncrasies that shape real-world operations management in this specific domain, for example, incomplete customer data or heterogeneous driver performance. Drawing on field-tested practice, this Industry and Practice Note reports how human improvisation, when supported by algorithmically defined planning structures, can effectively manage such constraints. Building on this industry practice, we outline four promising directions for human-centric transport research: (1) Algorithmic management balanced with human improvisation, (2) familiarity and fairness in vehicle routing models, (3) process-dependent idiosyncrasies, and (4) improvisation versus standardization. Future research must integrate human experience with idiosyncrasies to provide applicable and agile support models for first- and last-mile transportation in real-world settings.
Keywords:
Last-mile Transport
Algorithmic Management
Human Experience
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5.3
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