Abstract
Introduction: The competitiveness of a port depends on hinterland characteristics, among other factors. In particular, hinterland accessibility and efficient inland logistics are key factors in ensuring the speed of goods flows. The port systems have to be configured as an efficient and logistically effective interface between oceanic maritime trade and inland trade. The paper has been elaborated starting from research carried out in the European ISTEN project (Integrated and Sustainable Transport in the Efficient Network), aiming to improve the intermodal connections among the ports of the Adriatic-Ionian area and the ports and their hinterlands. Objective: The objective of the work is to propose an original approach for identifying the port hinterland based on the evaluation of transport times and costs in the whole supply chain (from the origin in the foreland zone to a final destination in the hinterland). Methods: The analyses have been carried out by considering separately the transport time and monetary cost components and generalized transport cost. The methodology involves wide research of data and careful analysis of the port hinterland connectivity. An analytical application is proposed in order to identify and compare the potential hinterlands of two Italian ports, Gioia Tauro and Genoa. Results: The results of the proposed analyses show that the geographical distribution of the port hinterlands changes significantly in relation to the reference drivers in terms of monetary cost and time along the intermodal international paths; this has led to further analyses considering the transport generalized cost which has integrated into travel time and monetary cost. Conclusion: The aim of the proposed approach is to overcome the limits of the methodologies of the sector based on geographical characteristics that focus attention only on market aspects considering marginally the transport component. The methodology is transferable to other contexts and other types of freight interchange nodes by adapting the cost functions.
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