# A Cost-Optimized Model for Dynamic Port Hinterland
## 1 Introduction  
Port systems play a vital role in the global supply chain, serving as critical nodes that connect maritime and inland transportation networks [1]. Recent studies indicate that up to 40% of total maritime logistics costs are generated in hinterland operations, highlighicong the crucial importance of optimizing these connections for overall supply chain performance [2]. This cost distribution has led to increased focus on hinterland efficiency as a key factor in port competitiveness.  
The evolution of global trade patterns and the increasing complexity of supply chains have fundamentally transformed the nature of port competition [3]. While traditional port competition focused primarily on maritime infrastructure and handling capacity, contemporary ports compete largely through their ability to serve extensive inland territories efficiently. This shift has been particularly evident in the development of intermodal transportation networks and inland logistics centers [4].  
The optimization of hinterland connections has become a strategic priority for port authorities and logistics operators, as it directly impacts their competitive position and market share [5]. Recent technological advances and environmental considerations have further complicated this optimization process, requiring ports to balance efficiency with sustainability goals [6]. The increasing digitalization of logistics operations has also introduced new opportunities and challenges in hinterland management.  
In the contemporary port sector, competition dynamics are increasingly shaped by the ability to effectively serve inland territories. The concept of port hinterland, traditionally defined as the geographic area from which a port derives its business, has evolved beyond simple spatial boundaries into a complex, dynamic construct influenced by multiple economic and operational factors.  
The logistics chains linking ports with their hinterlands face mounting pressure to reduce costs while maintaining operational efficiency. From the perspective of inter-port competition, ports continuously strive to expand their geographical sphere of influence and enhance their economic impact. This expansion, however, must operate within the framework of operational efficiency aimed at reducing costs in commercial transactions for transport companies and other supply chain stakeholders.  
Given that the majority of global trade utilizes maritime transport, a port's sphere of influence can be practically defined as the region where it serves as the primary facilitator for goods transportation. This influence area is largely shaped by transport companies' decisions, which are guided by operational policies prioritizing cost reduction. Consequently, transportation costs emerge as a critical factor in determining optimal transport routes and, by extension, in delineating port hinterlands.  
This study addresses three key research gaps in current hinterland analysis: the need for dynamic models that reflect modern supply chain complexity, limited integration of comprehensive logistics costs in hinterland analysis, and insufficient consideration of product-specific characteristics in port choice.  
An analytical method for determining port hinterland through the optimization of a comprehensive supply chain cost formula is proposed. This approach encompasses costs associated with hinterland operations, foreland transportation, and time-related factors, yielding differentiated hinterland delineations based on specific product characteristics and goods origin.  
The research culminates in a numerical experiment examining goods distribution in Spain, focusing on two distinct product categories to understand how product-specific attributes influence hinterland configurations. This targeted approach aligns with recent literature emphasizing the need for goods-oriented analyses in port choice and hinterland studies.