Procedia - Social and Behavioral Sciences · 2012 · 94 citations · 25 references
PlanningTransportation PlanningUrban PlanningTransportTransport PlanningTransportationTransport ModelingTransport ModellingTransportation ModelsTransportation SystemsUrban TransportUrban TransportationLogisticsMulti-agent SimulationTime WindowsToll Road PricingUrban Distribution SystemsUrban Freight DistributionUrban LogisticsUrban Road Pricing
Urban distribution centres theoretically appear successful, yet only 15 of 200 operate after five years, and policy measures such as tolls, subsidies, and time windows are expected to improve their functioning. The study aims to analyze how tolls, subsidies, and time windows influence stakeholder interactions in city logistics. A multi‑agent model is employed to simulate dynamic behavioural interactions among freight carriers, retailers, urban distribution centres, and municipalities. Policy experiments with the model show that existing modelling approaches poorly predict the feasibility of urban distribution centres, but the model helps understand stakeholder dynamics.
Previous modelling attempts show that theoretically the urban distribution centre appears to be successful in many cases, which is in sharp contrast with the real world showing the fact that only 15 out of 200 urban distribution centres are running after 5 years. It can be concluded that modeling approaches do not seem to predict well with respect to the feasibility of urban distribution centres. The main policy measures that are expected to contribute to the successful functioning of the urban distribution centres are toll (requirements) (road pricing), providing operational subsidies and application of time windows inside the city. The potentially supportive role of these policies will be analysed more detailed by obtaining more insight into the dynamic behavioural interaction between stakeholders in city logistics such as freight carriers, retailers, urban distribution centre and municipality. Policy experiments with a multi-agent model have shown their value for understanding the dynamic behaviour between stakeholders.
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