Digital Freight Matching Market
Digital Freight Matching Market Forecasts to 2030 - Global Analysis By Technology (Web-based, Mobile-based and Other Technologies), Service (Carrier search, Real-time matching and Other Services), Transportation Mode, Application, End User and By Geography
According to Stratistics MRC, the Global Digital Freight Matching Market is accounted for $37.58 billion in 2023 and is expected to reach $284.01 billion by 2030 growing at a CAGR of 33.50% during the forecast period. Digital freight matching (DFM) is a transformative technology in the logistics and transportation industries. It leverages digital platforms and algorithms to efficiently connect shippers with carriers, matching available freight with trucking capacity in real-time. By utilizing data analytics, machine learning, and automation, DFM streamlines the traditionally manual process of matching shipments with carriers, leading to improved efficiency, reduced costs, and enhanced transparency throughout the supply chain. This technology enables better utilization of resources, reduces empty miles, and minimizes wait times, ultimately optimizing the logistics process for both shippers and carriers.
According to the U.S. Department of Commerce’s Annual Retail Trade Survey (ARTS) in 2020, e-commerce sales in the U.S. rose by 43% in 2020 compared to 2019.
Market Dynamics:
Driver:
Efficiency and cost reduction
By leveraging digital platforms, companies can streamline the process of matching freight with available carriers, reducing idle time, and optimizing routes. This leads to improved efficiency as trucks spend less time empty or underutilized, ultimately reducing overall transportation costs. DFM solutions enable real-time tracking and monitoring, minimizing delays and ensuring timely deliveries. By automating many tasks traditionally done manually, such as paperwork and communication, DFM solutions further cut down operational costs while enhancing productivity across the supply chain. Additionally, the emphasis on efficiency and cost reduction in DFM translates into tangible benefits for both shippers and carriers, making it a crucial aspect of the modern logistics landscape.
Restraint:
Security concerns
Security concerns in this market revolve around data privacy, cyberattacks, and system vulnerabilities. With sensitive information, such as shipment details and financial transactions, being exchanged online, there's a risk of data breaches and unauthorized access. Cyberattacks targeting DFM platforms could disrupt operations, leading to delays and financial losses for the companies involved. Additionally, the integration of various stakeholders in the supply chain increases the attack surface, requiring robust cybersecurity measures to safeguard against potential threats.
Opportunity:
Access to a wider network
Access to a wider network opportunity is the ability for shippers and carriers to connect with a broader range of potential partners and resources through digital platforms. By leveraging technology, DFM platforms can aggregate a vast network of carriers, shippers, brokers, and other stakeholders, transcending geographical limitations. This expanded network offers increased flexibility, efficiency, and scalability in matching freight with available capacity, ultimately driving down costs and enhancing operational agility. Moreover, it enables participants to access real-time data, analytics, and visibility, empowering informed decision-making and optimized logistics strategies.
Threat:
Market fragmentation
Market fragmentation in the Digital Freight Matching (DFM) market poses a significant threat due to the proliferation of numerous platforms offering similar services. This fragmentation leads to inefficiencies as shippers and carriers must navigate multiple platforms to find suitable matches, resulting in increased transaction costs and reduced operational transparency. Moreover, fragmented markets lack standardization, making it challenging for participants to integrate their systems seamlessly. Ultimately, this hampers the scalability and widespread adoption of DFM solutions, potentially stifling innovation and limiting the overall effectiveness of the digital freight industry.
Covid-19 Impact:
Initially, disruptions in global supply chains led to a surge in demand for DFM solutions to efficiently manage logistics amid fluctuating freight volumes and capacity constraints. However, as economies slowed down and transportation demand fluctuated, DFM platforms faced challenges in matching supply with demand effectively. Many DFM companies pivoted to offer additional services, such as real-time tracking and supply chain visibility, to adapt to changing market dynamics. Overall, while the pandemic accelerated the adoption of DFM technology, it also highlighted the need for greater resilience and flexibility in supply chain management.
The web-based segment is expected to be the largest during the forecast period
The growth of web-based segments in the market is fueled by increased internet penetration and advancements in web technologies which facilitated easier access to DFM platforms. The convenience and efficiency offered by web-based solutions for freight matching attract both shippers and carriers, leading to an expanding user base. The scalability and flexibility of web-based DFM platforms make them suitable for businesses of all sizes, contributing to market growth. Additionally, the integration of features like real-time tracking and analytics enhances operational transparency and decision-making, further driving adoption.
The 3rd party logistics segment is expected to have the highest CAGR during the forecast period
The growth of the 3rd Party Logistics (3PL) segment is primarily driven by the increasing demand for efficient and cost-effective freight management solutions. 3PL providers are leveraging digital technologies to streamline operations, optimize routes, and match shipments with available carriers more effectively. This adoption of DFM platforms allows 3PLs to offer enhanced visibility, real-time tracking, and seamless communication between shippers and carriers, thereby improving overall supply chain efficiency. Moreover, as businesses increasingly outsource their logistics functions to focus on core competencies, the demand for 3PL services continues to rise. Furthermore, he scalability and flexibility offered by DFM solutions enable 3PLs to adapt quickly to changing market dynamics and customer demands, further fueling their growth in this segment.
Region with largest share:
The North American region has experienced significant growth in the market due to the region's highly developed transportation infrastructure and logistics networks, providing a robust foundation for the adoption of digital solutions. The increasing demand for efficient freight management and optimization has driven companies to seek out DFM platforms to streamline operations and reduce costs. The presence of tech-savvy businesses and a strong entrepreneurial culture have fostered innovation in the DFM sector, leading to the emergence of numerous startups and new entrants.
Region with highest CAGR:
The Asia-Pacific region has witnessed substantial growth due to the region's burgeoning e-commerce and efficient need for freight management solutions, driving the adoption of digital platforms for matching shippers with carriers. Additionally, the rapid urbanization and industrialization across countries like China, India, and Southeast Asian nations have spurred demand for streamlined logistics operations. Moreover, advancements in technology, such as IoT, AI, and blockchain, have enhanced the efficiency and transparency of freight matching processes in the region. Government initiatives aimed at improving trade facilitation and infrastructure development have also contributed to the expansion of the DFM market in Asia-Pacific.
Key players in the market
Some of the key players in Digital Freight Matching market include 123Loadboard, C.H.Robinson, Cargo Chief, Convoy, DAT Solutions, Delhivery, Flexport , Forto, Loadsmart, Motive Technologies, Samsara, Trucker Path, Uber Freight and uShip.
Key Developments:
In March 2024, Delhivery has transformed its facility in Punjab’s Moga into an all-woman-run hub, the leading integrated logistics service provider. The company plans to establish similar types of all-women-run facilities in other regions of the country, including Uttar Pradesh and Rajasthan.
In January 2024, Trucking industry software platform Trucker Path announced that it has tapped online lending marketplace Lendio to embed small business lending tools within its mobile app. Lendio, will offer Trucker Path’s community of one million users a range of financing services, including asset or revenue-based financing, debt financing, lines of credit, and equipment financing.
Technologies Covered:
• Web-based
• Mobile-based
• Enterprise solutions
• Other Technologies
Services Covered:
• Carrier search
• Real-time matching
• Load posting
• Other Services
Transportation Modes Covered:
• Rail freight
• Ocean Freight
• Road Freight
• Air Freight
• Other Transportation Modes
Applications Covered:
• Carriers
• Freight Brokers
• Shippers
• 3rd Party Logistics
• Other Applications
End Users Covered:
• Retail & E-Commerce
• Manufacturing
• Automotive
• Healthcare
• Oil & Gas
• Food & Beverages
• Other End Users
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Technology Analysis
3.7 Application Analysis
3.8 End User Analysis
3.9 Emerging Markets
3.10 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Digital Freight Matching Market, By Technology
5.1 Introduction
5.2 Web-based
5.3 Mobile-based
5.3.1 iOS
5.3.2 Android
5.4 Enterprise solutions
5.5 Other Technologies
6 Global Digital Freight Matching Market, By Service
6.1 Introduction
6.2 Carrier search
6.3 Real-time matching
6.4 Load posting
6.5 Other Services
7 Global Digital Freight Matching Market, By Transportation Mode
7.1 Introduction
7.2 Rail freight
7.3 Ocean Freight
7.4 Road Freight
7.5 Air Freight
7.6 Other Transportation Modes
8 Global Digital Freight Matching Market, By Application
8.1 Introduction
8.2 Carriers
8.3 Freight Brokers
8.4 Shippers
8.5 3rd Party Logistics
8.6 Other Applications
9 Global Digital Freight Matching Market, By End User
9.1 Introduction
9.2 Retail & E-Commerce
9.3 Manufacturing
9.4 Automotive
9.5 Healthcare
9.6 Oil & Gas
9.7 Food & Beverages
9.8 Other End Users
10 Global Digital Freight Matching Market, By Geography
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 Europe
10.3.1 Germany
10.3.2 UK
10.3.3 Italy
10.3.4 France
10.3.5 Spain
10.3.6 Rest of Europe
10.4 Asia Pacific
10.4.1 Japan
10.4.2 China
10.4.3 India
10.4.4 Australia
10.4.5 New Zealand
10.4.6 South Korea
10.4.7 Rest of Asia Pacific
10.5 South America
10.5.1 Argentina
10.5.2 Brazil
10.5.3 Chile
10.5.4 Rest of South America
10.6 Middle East & Africa
10.6.1 Saudi Arabia
10.6.2 UAE
10.6.3 Qatar
10.6.4 South Africa
10.6.5 Rest of Middle East & Africa
11 Key Developments
11.1 Agreements, Partnerships, Collaborations and Joint Ventures
11.2 Acquisitions & Mergers
11.3 New Product Launch
11.4 Expansions
11.5 Other Key Strategies
12 Company Profiling
12.1 123Loadboard
12.2 C.H.Robinson
12.3 Cargo Chief
12.4 Convoy
12.5 DAT Solutions
12.6 Delhivery
12.7 Flexport
12.8 Forto
12.9 Loadsmart
12.10 Motive Technologies
12.11 Samsara
12.12 Trucker Path
12.13 Uber Freight
12.14 uShip
List of Tables
1 Global Digital Freight Matching Market Outlook, By Region (2021-2030) ($MN)
2 Global Digital Freight Matching Market Outlook, By Technology (2021-2030) ($MN)
3 Global Digital Freight Matching Market Outlook, By Web-based (2021-2030) ($MN)
4 Global Digital Freight Matching Market Outlook, By Mobile-based (2021-2030) ($MN)
5 Global Digital Freight Matching Market Outlook, By iOS (2021-2030) ($MN)
6 Global Digital Freight Matching Market Outlook, By Android (2021-2030) ($MN)
7 Global Digital Freight Matching Market Outlook, By Enterprise solutions (2021-2030) ($MN)
8 Global Digital Freight Matching Market Outlook, By Other Technologies (2021-2030) ($MN)
9 Global Digital Freight Matching Market Outlook, By Service (2021-2030) ($MN)
10 Global Digital Freight Matching Market Outlook, By Carrier search (2021-2030) ($MN)
11 Global Digital Freight Matching Market Outlook, By Real-time matching (2021-2030) ($MN)
12 Global Digital Freight Matching Market Outlook, By Load posting (2021-2030) ($MN)
13 Global Digital Freight Matching Market Outlook, By Other Services (2021-2030) ($MN)
14 Global Digital Freight Matching Market Outlook, By Transportation Mode (2021-2030) ($MN)
15 Global Digital Freight Matching Market Outlook, By Rail freight (2021-2030) ($MN)
16 Global Digital Freight Matching Market Outlook, By Ocean Freight (2021-2030) ($MN)
17 Global Digital Freight Matching Market Outlook, By Road Freight (2021-2030) ($MN)
18 Global Digital Freight Matching Market Outlook, By Air Freight (2021-2030) ($MN)
19 Global Digital Freight Matching Market Outlook, By Other Transportation Modes (2021-2030) ($MN)
20 Global Digital Freight Matching Market Outlook, By Application (2021-2030) ($MN)
21 Global Digital Freight Matching Market Outlook, By Carriers (2021-2030) ($MN)
22 Global Digital Freight Matching Market Outlook, By Freight Brokers (2021-2030) ($MN)
23 Global Digital Freight Matching Market Outlook, By Shippers (2021-2030) ($MN)
24 Global Digital Freight Matching Market Outlook, By 3rd Party Logistics (2021-2030) ($MN)
25 Global Digital Freight Matching Market Outlook, By Other Applications (2021-2030) ($MN)
26 Global Digital Freight Matching Market Outlook, By End User (2021-2030) ($MN)
27 Global Digital Freight Matching Market Outlook, By Retail & E-Commerce (2021-2030) ($MN)
28 Global Digital Freight Matching Market Outlook, By Manufacturing (2021-2030) ($MN)
29 Global Digital Freight Matching Market Outlook, By Automotive (2021-2030) ($MN)
30 Global Digital Freight Matching Market Outlook, By Healthcare (2021-2030) ($MN)
31 Global Digital Freight Matching Market Outlook, By Oil & Gas (2021-2030) ($MN)
32 Global Digital Freight Matching Market Outlook, By Food & Beverages (2021-2030) ($MN)
33 Global Digital Freight Matching Market Outlook, By Other End Users (2021-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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