Scientific Foundations and Efficiency of Multimodal Transportation in Foreign Automobile Import

02.06.2026 64 baxış

Globalization and the integration of global supply chains require new scientific and practical approaches in the field of automotive logistics, which is one of the crucial branches of international trade. In the modern era, importing cars from abroad from major markets such as the USA, Europe, Dubai, or China is not merely a transport process from one point to another; it is a complex system based on economic, mathematical, and legal optimization models.
Particularly in regional hubs like Azerbaijan, where direct access to the sea is limited, individual and corporate automobile import is, in most cases, impossible with a single mode of transport. It is precisely at this point that multimodal transportation – meaning the combination of two or more modes of transport (road, sea, rail, air) within a single legal contract and a unified tariff policy – emerges as a scientific necessity.
In this article, we will analyze the mathematical-economic foundations, risk management, and logistics cost minimization strategies of multimodal transport models applied during international car ordering from a scientific perspective.
Multimodal Transport Models and Integration Algorithms
Establishing a multimodal chain in international automotive logistics requires the physical and technical alignment of different transport infrastructures. The integration of vehicles from famous US auctions like Copart, IAAI, or Manheim, as well as from Asian markets, into the infrastructure of Azerbaijan is usually carried out according to a three-stage model:
• First Stage (First Mile Logistics): Collection of vehicles from the auction site or manufacturing plant and transporting them to the nearest logistics terminal (port or railway station). At this stage, routing problems are solved via specialized auto-trailers (tow trucks or car haulers).
• Second Stage (Mainhaul Transportation): To cover long distances, car transportation by containers or Ro-Ro shipping (Roll-on/roll-off) using specialized vessels is applied. This stage is the longest and most sensitive part of the transport chain in terms of prime cost.
• Third Stage (Last Mile Logistics): Delivery of vehicles from transit ports (e.g., Poti or Batumi ports on the Black Sea coast) to Baku and other customs-logistics centers via road or railway platforms.
The success of this system depends on reducing the idle time of cars at handling points to zero. In scientific literature, this is achieved by adapting "Just-in-Time" and "Cross-docking" (direct handling without warehousing) principles to automotive logistics.
Minimization of Logistics Costs: Cost-Benefit Analysis
Economic efficiency in the process of importing cars from abroad does not end just with choosing the cheapest mode of transport. A total logistics cost minimization model must be applied here. The total cost is formed by four main components: the net transport tariff, port handling costs, the value of frozen capital while the vehicle is en route (time value), and the financial equivalent of potential damage and delay risks.
During the optimization of logistics routes, the multimodal model combines the economic efficiency of the full sea route with the speed of road transport. Analyses show that a properly structured multimodal chain reduces the prime cost per single vehicle by an average of up to 15-20 percentage points compared to full road or full sea transport, providing an ideal balance.
Conclusion
Modern logistics companies operating in the field of automobile import from abroad must utilize scientifically sound multimodal chains to gain a competitive advantage. The synergy of road, sea, rail, and alternatively air transport not only reduces costs but also ensures transparency, safety, and predictable delivery times for the end consumer making an international car order. Azerbaijan's geostrategic position and developing transport corridors create extensive infrastructure opportunities for the application of these scientific models.