세계의 물류 분야 디지털 트윈 시장 평가 : 기술별, 용도별, 컴포넌트별, 전개 모델별, 최종사용자별, 지역별 - 기회 및 예측(2018-2032년)

Global digital twins in logistics market are projected to witness a CAGR of 12.13% during the forecast period 2025-2032, growing from USD 3.14 billion in 2024 to USD 7.85 billion in 2032F, owing to an increase in need for visibility, automation, and scenario simulation across logistics networks. From route optimization to predictive maintenance, from warehouse digitalization to asset-level traceability, digital twins are embedded across all logistics layers.

In addition, the logistics is no longer about trucks, terminals, or transit points; it is increasingly about virtual replicas. Digital twins have transitioned from an industrial buzzword to a logistics notable change, enabling companies to mirror physical supply chain processes in real time. The result leads to Data-led decisions, predictive precision, and a new level of agility in a traditionally rigid sector.

Governments and port authorities are also stepping in, driving the global market growth in the forecast period. For instance, in November 2023, the Port of Rotterdam Authority launched its second-generation digital twin platform for real-time vessel traffic simulation and cargo management across the terminal, using data from over 40,000 sensors and predictive AI tools developed in partnership with IBM.

Rising Demand for Predictive Intelligence Drives the Global Digital Twin in Logistics Market Demand

Businesses are now shifting from reactive models to predictive systems, and digital twins sit at the center of transformation. Digital twins allow companies to simulate delivery routes, warehouse operations, and inventory buffers, testing scenarios in advance and turning mitigation into an initiative-taking-rather than reactive-process.

For instance, in February 2024, DHL Supply Chain deployed a digital twin model across 20 of its European logistics centers. The system, developed in partnership with Siemens AG and Blue Yonder, used AI simulations to model traffic, labor shifts, and inbound material delays, reducing lead time variability and increasing pick accuracy.

As customer expectations rise and logistics costs tighten, digital twins provide a powerful solution, reducing waste, optimizing resources, and enhancing service levels while proactively anticipating and mitigating risks before they occur.

E-Commerce Expansion and Rising Need for Virtualized Warehousing Lead to Market Growth

E-commerce has transformed logistics, from static supply chains to hyper-responsive ones. With rapid order fulfilment now the norm, logistics providers are investing in virtualized warehouse systems that simulate shelf space, worker routes, SKU locations, and order flows. Digital twins help maximize storage utilization, optimize labor productivity, and increase demand, especially in last-mile-intensive e-commerce zones.

In July 2024, Amazon.com, Inc. unveiled its proprietary "Fulfillment Twin", a real-time virtual twin platform that maps operations across 50+ warehouses in North America. Built on AWS and integrated with Kiva robotics and AI traffic models, the platform helped reduce order processing times by 12% during the Prime Day sale window.

Smaller players are catching up, too. In April 2024, ShipBob Inc., a U.S. based fulfillment provider, introduced digital twin tools for clients to simulate storage configurations and fulfillment scenarios before physically onboarding inventory, improving SLA adherence and reducing inbound errors. With consumer demand surging and warehouse space becoming premium, virtual warehouse simulation is turning into a competitive edge.

Dominance of AI-Integrated Digital Twins in Market Adoption

Among all technology types in the digital twin ecosystem, AI-integrated digital twins are emerging as the dominant force, enabling not just data visualization but also intelligent decision-making. AI-integrated twins combine machine learning, neural networks, and behavioral models to optimize logistics operations in real time. These systems are used to predict equipment failures, analyze delivery delays, and dynamically reconfigure routes based on traffic and demand data.

For example, in March 2025, Microsoft Azure Digital Twins integrated with the Kinaxis Rapid Response platform to offer end-to-end logistics simulation for global freight clients. This allowed operators to predict inventory shortages, truck downtime, and carrier delays - all within a unified, AI-augmented dashboard.

AI-integrated digital twins are particularly popular with freight operators and large-scale 3PLs, where multiple dynamic factors influence operations daily. As data maturity improves, these AI-led systems are expected to drive the next wave of optimization in supply chain orchestration.

North America Dominates the Global Digital Twins in Logistics Market Demand

North America stands out as the most mature and innovation-driven region in the global digital twins in logistics market, not just in terms of adoption but in depth of deployment across the supply chain. The region's dominance is powered by a convergence of three key factors such as high digital infrastructure readiness, early enterprise adoption of cloud and IoT ecosystems, and strategic emphasis on supply chain resiliency post-COVID and post-China sourcing shifts.

U.S.-based logistics giants such as Amazon, FedEx, and UPS are at the forefront, integrating digital twin ecosystems into their warehousing, transportation, and delivery models. These companies not only deploy real-time virtual replicas but also continuously enhance them with AI, 5G, and edge computing to simulate outcomes at scale.

For instance, in August 2024, FedEx Corporation announced the rollout of its proprietary "Network Control Tower", a digital twin platform capable of visualizing and simulating its entire global delivery network. Built in partnership with Microsoft Azure and SAP Logistics Business Network, the system uses predictive analytics to optimize route selection, package prioritization, and carrier utilization, improving service reliability during high-demand peaks such as Black Friday and Cyber Monday.

North America also benefits from strong government and defense-driven innovation. The U.S. Department of Transportation, along with DARPA and NASA, has invested in AI-backed logistics simulation platforms for infrastructure resilience and disaster readiness, many of which are now being commercialized for freight and port logistics.

Impact of the U.S. Tariff on Global Digital Twins in the Logistics Market

Higher hardware costs (IoT sensors, chips, cloud infrastructure) due to tariffs on Chinese electronics could slow digital twin adoption. Logistics firms may face delays in deploying digital twin systems if reliant on tariff-affected hardware (e.g., servers, edge devices). Accelerated "nearshoring" of tech supply chains, pushing companies to source from non-tariff regions (e.g., Vietnam, India, or domestic U.S. suppliers). U.S. and EU collaborations may strengthen as firms avoid Chinese dependencies, reshaping digital twin ecosystems.

Key Players Landscape and Outlook

The global digital twins in logistics market is being shaped by both tech giants and specialized supply chain platforms. Players through platform depth and global reach, offering scalable, cloud-native digital twin ecosystems. At the same time, firms provide vertical-specific logistics twin solutions, focusing on inventory simulation, warehouse robotics, and freight optimization. Competition is increasingly about ecosystem compatibility, data integration, and AI model maturity. Firms offering plug-and-play solutions with legacy ERP systems and real-time IoT sync capabilities are gaining adoption faster. Strategic alliances are also shaping the landscape. For instance, in 2023, ABB Ltd and Bosch Rexroth integrated sensor-rich industrial hardware with twin software models, giving logistics players the ability to monitor physical assets while simulating end-to-end flows virtually.

For instance, in March 2025, Siemens Industry Software Inc. announced that it would ramp up its U.S. investments by more than USD 10 billion, surpassing USD 100 billion in total U.S. investment over the past two decades. The company opened and expanded factories in Texas and California, creating over 900 skilled manufacturing jobs and more than doubled its production capacity for electric equipment critical to powering AI data centers and other infrastructure. In its largest-ever push into industrial software and AI, Siemens is acquiring Altair Engineering for approximately USD 10 billion, aiming to build the world's most complete AI-powered industrial software portfolio and accelerate digital transformation across American manufacturing.

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Impact of U.S. Tariffs

4. Executive Summary

5. Voice of Customers

• 5.1. Data Integration Capabilities
• 5.2. Scalability and Flexibility
• 5.3. Implementation and Support
• 5.4. Cost of ROI

6. Global Digital Twins in Logistics Market Outlook, 2018-2032F

• 6.1. Market Size Analysis & Forecast
  • 6.1.1. By Value
• 6.2. Market Share Analysis & Forecast
  • 6.2.1. By Technology
    • 6.2.1.1. IoT-based Digital Twins
    • 6.2.1.2. Cloud-based Digital Twins
    • 6.2.1.3. On-Premise Digital Twins
    • 6.2.1.4. Artificial Intelligence Integrated Digital Twins
  • 6.2.2. By Application
    • 6.2.2.1. Route Optimization
    • 6.2.2.2. Warehouse and Inventory Management
    • 6.2.2.3. Predictive Maintenance
    • 6.2.2.4. Asset Tracking
  • 6.2.3. By Component
    • 6.2.3.1. Software
    • 6.2.3.2. Service
  • 6.2.4. By Deployment Model
    • 6.2.4.1. Cloud-based
    • 6.2.4.2. On-premises
  • 6.2.5. By End-user
    • 6.2.5.1. Third-Party Logistics Providers
    • 6.2.5.2. Freight Operators
    • 6.2.5.3. Warehousing
    • 6.2.5.4. E-commerce
  • 6.2.6. By Region
    • 6.2.6.1. North America
    • 6.2.6.2. Europe
    • 6.2.6.3. Asia-Pacific
    • 6.2.6.4. South America
    • 6.2.6.5. Middle East and Africa
  • 6.2.7. By Company Market Share Analysis (Top 5 Companies and Others - By Value, 2024)
• 6.3. Market Map Analysis, 2024
  • 6.3.1. By Technology
  • 6.3.2. By Application
  • 6.3.3. By Component
  • 6.3.4. By Deployment Model
  • 6.3.5. By End-user
  • 6.3.6. By Region

7. North America Digital Twins in Logistics Market Outlook, 2018-2032F

• 7.1. Market Size Analysis & Forecast
  • 7.1.1. By Value
• 7.2. Market Share Analysis & Forecast
  • 7.2.1. By Technology
    • 7.2.1.1. IoT-based Digital Twins
    • 7.2.1.2. Cloud-based Digital Twins
    • 7.2.1.3. On-Premise Digital Twins
    • 7.2.1.4. Artificial Intelligence Integrated Digital Twins
  • 7.2.2. By Application
    • 7.2.2.1. Route Optimization
    • 7.2.2.2. Warehouse and Inventory Management
    • 7.2.2.3. Predictive Maintenance
    • 7.2.2.4. Asset Tracking
  • 7.2.3. By Component
    • 7.2.3.1. Software
    • 7.2.3.2. Service
  • 7.2.4. By Deployment Model
    • 7.2.4.1. Cloud-based
    • 7.2.4.2. On-premises
  • 7.2.5. By End-user
    • 7.2.5.1. Third-Party Logistics Providers
    • 7.2.5.2. Freight Operators
    • 7.2.5.3. Warehousing
    • 7.2.5.4. E-commerce
  • 7.2.6. By Country Share
    • 7.2.6.1. United States
    • 7.2.6.2. Canada
    • 7.2.6.3. Mexico
• 7.3. Country Market Assessment
  • 7.3.1. United States Digital Twins in Logistics Market Outlook, 2018-2032F*
    • 7.3.1.1. Market Size Analysis & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share Analysis & Forecast
      • 7.3.1.2.1. By Technology
        • 7.3.1.2.1.1. IoT-based Digital Twins
        • 7.3.1.2.1.2. Cloud-based Digital Twins
        • 7.3.1.2.1.3. On-Premise Digital Twins
        • 7.3.1.2.1.4. Artificial Intelligence Integrated Digital Twins
      • 7.3.1.2.2. By Application
        • 7.3.1.2.2.1. Route Optimization
        • 7.3.1.2.2.2. Warehouse and Inventory Management
        • 7.3.1.2.2.3. Predictive Maintenance
        • 7.3.1.2.2.4. Asset Tracking
      • 7.3.1.2.3. By Component
        • 7.3.1.2.3.1. Software
        • 7.3.1.2.3.2. Service
      • 7.3.1.2.4. By Deployment Model
        • 7.3.1.2.4.1. Cloud-based
        • 7.3.1.2.4.2. On-premises
      • 7.3.1.2.5. By End-user
        • 7.3.1.2.5.1. Third-Party Logistics Providers
        • 7.3.1.2.5.2. Freight Operators
        • 7.3.1.2.5.3. Warehousing
        • 7.3.1.2.5.4. E-commerce
  • 7.3.2. Canada
  • 7.3.3. Mexico

All segments will be provided for all regions and countries covered

8. Europe Digital Twins in Logistics Market Outlook, 2018-2032F

• 8.1. Germany
• 8.2. France
• 8.3. Italy
• 8.4. United Kingdom
• 8.5. Russia
• 8.6. Netherlands
• 8.7. Spain
• 8.8. Turkey
• 8.9. Poland

9. Asia-Pacific Digital Twins in Logistics Market Outlook, 2018-2032F

• 9.1. India
• 9.2. China
• 9.3. Japan
• 9.4. Australia
• 9.5. Vietnam
• 9.6. South Korea
• 9.7. Indonesia
• 9.8. Philippines

10. South America Digital Twins in Logistics Market Outlook, 2018-2032F

• 10.1. Brazil
• 10.2. Argentina

11. Middle East and Africa Digital Twins in Logistics Market Outlook, 2018-2032F

• 11.1. Saudi Arabia
• 11.2. UAE
• 11.3. South Africa

12. Demand Supply Analysis

13. Value Chain Analysis

14. Porter's Five Forces Analysis

15. PESTLE Analysis

16. Market Dynamics

• 16.1. Market Drivers
• 16.2. Market Challenges

17. Consumer Buying Behavior Analysis

18. Market Trends and Developments

19. Policy and Regulatory Landscape

20. Case Studies

21. Competitive Landscape

• 21.1. Competition Matrix of Top 5 Market Leaders
• 21.2. SWOT Analysis for Top 5 Players
• 21.3. Key Players Landscape for Top 10 Market Players
  • 21.3.1. Microsoft Corporation
    • 21.3.1.1. Company Details
    • 21.3.1.2. Key Management Personnel
    • 21.3.1.3. Products and Services
    • 21.3.1.4. Financials (As Reported)
    • 21.3.1.5. Key Market Focus and Geographical Presence
    • 21.3.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
  • 21.3.2. Oracle Corporation
  • 21.3.3. SAP SE
  • 21.3.4. International Business Machines Corporation (IBM)
  • 21.3.5. Siemens Industry Software Inc.
  • 21.3.6. AVEVA Group Limited
  • 21.3.7. Amazon Web Services, Inc.
  • 21.3.8. Blue Yonder Group, Inc.
  • 21.3.9. Bentley Systems Incorporated
  • 21.3.10. Kinaxis Inc.

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

22. Strategic Recommendations

23. About Us and Disclaimer