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The dynamic and complex interactions between the urban freight-transportation system and population, economy, traffic flow, fuel consumption, and environmental pollution, make policymaking in this system one of the fundamental challenges of urban management. In this regard, a systemic approach in urban freight-transportation system modelling should be considered to solve the problems of the system. One of the main problems of this system is the mismatch between the freight-transportation capacity and the total freight-transportation demand. Considering the lack of sufficient studies in the field of macro and quantitative modeling of this system, the main goal of this article is to model the urban freight-transportation system in order to identify the factors affecting the urban freight-transportation demand and capacity. The main focus of the research is to develop quantitative scenarios which balance the freight-transportation capacity and freight-transportation demand. The urban freight-transportation system is modelled by the System Dynamics (SD) approach and their basic behaviors; as well as this the results of some policy-making scenarios are simulated. The model is validated by the real data of Shiraz. Five quantitative scenarios are designed with two approaches of managing the freight-transportation demand and freight-transportation-capacity sectors. The scenarios are based on four control variables, including the distribution coefficient, trip numbers, vehicle capacity, and vehicle numbers. The simulation results show that the total gap between freight-transportation capacity and freight-transportation demand will decrease by optimizing each of the control variables. However, the combined scenario is the most applicable policy in order to maintain the balance between freight-transportation capacity and demand. Generally, the proposed model can be used to design different quantitative scenarios in order to optimize the freight-transportation system’s performance. This study can also help policymakers to manage the urban freight-transportation system more efficiently.
Ghaemi et al. (Wed,) studied this question.