PUBLISHER: Grand View Research | PRODUCT CODE: 1654614
PUBLISHER: Grand View Research | PRODUCT CODE: 1654614
The global automotive logistics market size is estimated to reach USD 365.78 billion by 2030, expanding at a CAGR of 8.0% from 2025 to 2030, according to a new report by Grand View Research, Inc. The growth of the market is directly linked to the demand for automobile and automobile parts, development of comprehensive world-wide trade flow, and existing economic environment. Furthermore, rapid proliferation of trade agreements among various countries is a key factor fueling the growth of the market.
Automotive logistics is a part of the automotive supply chain, which spans across the globe. Automotive logistics ensures seamless transportation of component, system, and finished vehicle in the economy, starting from pre-assembled components to the transport of finished automobiles to a local warehouse. Automotive logistics is crucial for raw material producers, components suppliers, vehicle manufacturing, spare parts suppliers, and automotive sales. It comprises inbound logistics of raw materials and components, garage logistics of the manufacturing process, sales logistics of spare parts, and finished vehicle, which also includes loading/unloading, storage, transportation, information processing, distribution, and delivery. In a broader supply chain, automotive logistics also provides transportation of automotive industry waste for recycling.
Key service providers are adopting advanced technologies, such as Big Data and connected ships, to improve supply-chain management processes for optimizing modes of transport in the industry. The application of technologies such as big data enables cost comparison, reliability, and quality of concerned product components transportation to suggest the perfect and most economical mode of transportation. It also analyzes statistical data for predicting the demand and helps in streamlining the procurement process with minimum inventory cost, making it more cost efficient. Big data analytics also aid in the reduction of labor costs by making use of predictive assessment on routing to eliminate delays in shipments, thereby reducing the operational cost to increase the profit margin of the service providers.